From eeda205a0f36f830587c853d9139c88467ea47a7 Mon Sep 17 00:00:00 2001 From: nicksxs Date: Sun, 24 Mar 2024 21:04:18 +0800 Subject: [PATCH] Site updated: 2024-03-24 21:04:17 --- 2019/12/18/1Q84读后感/index.html | 2 +- 2020/07/11/2020年中总结/index.html | 2 +- .../index.html | 2 +- .../index.html | 2 +- .../07/关于读书打卡与分享/index.html | 2 +- 2021/02/14/AQS篇一/index.html | 2 +- .../AQS-之-Condition-浅析笔记/index.html | 2 +- .../聊聊-Linux-下的-top-命令/index.html | 2 +- 2021/07/18/2021-年中总结/index.html | 2 +- .../《长安的荔枝》读后感/index.html | 2 +- .../index.html | 2 +- atom.xml | 4 +- baidusitemap.xml | 24 +- categories/Java/GC/index.html | 2 +- categories/Java/index.html | 2 +- categories/Java/page/2/index.html | 2 +- categories/linked-list/index.html | 2 +- index.html | 2 +- leancloud.memo | 1 + leancloud_counter_security_urls.json | 2 +- page/33/index.html | 2 +- page/35/index.html | 2 +- page/40/index.html | 2 +- page/47/index.html | 2 +- search.xml | 3298 +++++++++-------- sitemap.xml | 478 +-- 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What hurts more, the pain of hard work or the pain of regret?

村上春树《1Q84》读后感

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看完了村上春树的《1Q84》，这应该是第五本看的他的书了，继 跑步，挪威的森林，刺杀骑士团长，海边的卡夫卡之后，不是其中最长的，好像是海边的卡夫卡还是刺杀骑士团长比较长一点，都是在微信读书上看的，比较方便，最开始在上面看的是高晓松的《鱼羊野史》，不知道为啥取这个名字，但是还是满吸引我的，不过由于去年的种种，没有很多心思把它看完，而且本身的组织形式就是比较松散的，看到哪算哪，其实一些野史部分是我比较喜欢，有些谈到人物的就不太有兴趣，而且类似于大祥哥吃的东西，反正都是哇，怎么这么好吃，嗯，太爱（niu）你（bi）了，高晓松就是这个人是我最喜欢的 xxx 家，我也没去细究过他有没有说重复过，反正是不太爱，后来因为这书还一度对战争史有了浓厚的兴趣，然而事实告诉我，大部头的战争史，其实正史我是真的啃不下去，我可能只对其中 10%的内容感兴趣，不过终于也在今年把它看完了，好像高晓松的晓说也最终季了，貌似其中讲朝鲜战争的还被和谐了，看样子是说出了一些故事（truth）。

本来只是想把 《1Q84》的读后感写下，现在觉得还是把这篇当成我今年的读书总结吧，不过先从《1Q84》说起。

严格来讲，这不是很书面化的读后感，可能我想写的也只是像聊天一样的说下我读过的书，包括的技术博客其实也是类似的，以后或许会转变，但是目前水平如此吧，写多了可能会变好，也可能不会。

开始正文吧，这书有点类似于海边的卡夫卡，一开始是通过两条故事线，穿插着叙述，一条是青豆的，不算是个职业杀手的女杀手，要去解决一个经常家暴的斯文败类，穿着描述得比较性感吧，杀人方式是通过比较长的细针，从脖子后面一个精巧的位置插入，可以造成是未知原因死亡的假象，可能会推断成心梗之类的，这里有个前置的细节，就是青豆是乘坐一辆很高级的出租车，内饰什么的都非常有质感，有点不像一辆出租车，然后车里放了一首比较小众的歌，雅纳切克的《小交响曲》，但是青豆知道它，这跟后面的情节也有些许关系，这是女主人公青豆的出场；相应的男主的出场印象不是太深刻，男主叫天吾，是个不知名的作家，跟一个叫小松的编辑有比较好的关系，虽然天吾还没有拿到比较有分量的奖项，但是小松很看好他，也让他帮忙审校一个新作家奖的投稿文章，虽然天吾自身还没获得过这个奖，天吾还有个正式工作，是当数学老师，天吾在学生时代是个数学天才，但后面有对文学产生了兴趣，文学还不足以养活自己，靠着教课还是能保持温饱；

接下来是正式故事的起点了，就是小松收到了一部小说投稿，名叫《空气蛹》，是个叫深绘里的女孩子投的稿，小松对他赋予了很高的评价，这里好像记岔了，好像是天吾对这部小说很有好感，但是小松比较怀疑，然后小松看了之后也有了浓厚的兴趣，这里就是开端了，小松想让天吾来重写润色这部《空气蛹》，因为故事本身很有分量，但是描写手法叙事方式等都很拙劣，而天吾正好擅长这个，小松对天吾的评价是，描写技巧无可挑剔，就是故事主体的火花还没际遇迸发，需要一个导火索，这个就可以类比我们程序员，很多比较初中级的程序员主要擅长在原来的代码上修修改改或者给他分配个小功能，比较高级的程序员就需要能做一些项目的架构设计，核心的技术方案设计，以前我也觉得写文档这个比较无聊，但是当一个项目真的比较庞大，复杂的时候，整体和核心部分的架构设计和方案还是需要有文档沉淀的，不然别人不知道没法接受，自己过段时间也会忘记。

对于小松的这个建议，他的初衷是想搅一搅这个死气沉沉套路颇深的文坛，因为本身《空气蛹》这部小说的内容很吸引人，小松想通过天吾的润色补充让这部小说冲击新人奖，有种恶作剧的意图，天吾对此表示很多担心和顾虑，小松的这个建议其实也是一种文学作假，有两方面的担心，一方面是原作者深绘里是否同意如此操作，一方面是外界如果发现了这个事实会有什么样的后果，但是小松表示不用担心，前一步由小松牵线，让天吾跟原作者深绘里当面沟通这个代写是否被允许，结果当然是被允许了，这里有了对深绘里的初步描写，按我的理解是比较仙的感觉，然后语言沟通有些吃力，或者说有她自己的特色，当面沟通时貌似是让深绘里回去再考虑下，然后后面再由天吾去深绘里寄宿的戎野老师家沟通具体的细节。

2019年12月18日23:37:19 更新
去到戎野老师家之后，天吾知道了关于深绘里的一些事情，深绘里的父亲与戎野老师应该是老友，深绘里的父亲在当初成立了一个叫”先驱”的公社，一个独立运行的社会组织，以运营农场作为物资来源，追求更为松散的共同体，即不过分激进地公有制，进行松散的共同生活，承认私有财产，简而言之就是这样一个能稳定存活下来的独立社会组织，但是随着稳定运行，内部的激进派和稳健派开始出现分歧，不可磨合，后来两派就分裂了，深绘里的父亲，深田保留在了稳健派，但是此时其实深田保内心是矛盾的，以为一开始其实是他倡导的独立革命才组织起了这群人，然而现在他又认清了现实社会已经不太相信能通过革命来独立的可能性，后来激进派便开始越加封闭，而且进行军事训练和思想教育，而后这个先驱的激进派别便有了新的名字”黎明”，深绘里也是在此时从先驱逃离来投靠戎野老师
暂时先写到这，未完待续~

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What hurts more, the pain of hard work or the pain of regret?

村上春树《1Q84》读后感

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看完了村上春树的《1Q84》，这应该是第五本看的他的书了，继 跑步，挪威的森林，刺杀骑士团长，海边的卡夫卡之后，不是其中最长的，好像是海边的卡夫卡还是刺杀骑士团长比较长一点，都是在微信读书上看的，比较方便，最开始在上面看的是高晓松的《鱼羊野史》，不知道为啥取这个名字，但是还是满吸引我的，不过由于去年的种种，没有很多心思把它看完，而且本身的组织形式就是比较松散的，看到哪算哪，其实一些野史部分是我比较喜欢，有些谈到人物的就不太有兴趣，而且类似于大祥哥吃的东西，反正都是哇，怎么这么好吃，嗯，太爱（niu）你（bi）了，高晓松就是这个人是我最喜欢的 xxx 家，我也没去细究过他有没有说重复过，反正是不太爱，后来因为这书还一度对战争史有了浓厚的兴趣，然而事实告诉我，大部头的战争史，其实正史我是真的啃不下去，我可能只对其中 10%的内容感兴趣，不过终于也在今年把它看完了，好像高晓松的晓说也最终季了，貌似其中讲朝鲜战争的还被和谐了，看样子是说出了一些故事（truth）。

本来只是想把 《1Q84》的读后感写下，现在觉得还是把这篇当成我今年的读书总结吧，不过先从《1Q84》说起。

严格来讲，这不是很书面化的读后感，可能我想写的也只是像聊天一样的说下我读过的书，包括的技术博客其实也是类似的，以后或许会转变，但是目前水平如此吧，写多了可能会变好，也可能不会。

开始正文吧，这书有点类似于海边的卡夫卡，一开始是通过两条故事线，穿插着叙述，一条是青豆的，不算是个职业杀手的女杀手，要去解决一个经常家暴的斯文败类，穿着描述得比较性感吧，杀人方式是通过比较长的细针，从脖子后面一个精巧的位置插入，可以造成是未知原因死亡的假象，可能会推断成心梗之类的，这里有个前置的细节，就是青豆是乘坐一辆很高级的出租车，内饰什么的都非常有质感，有点不像一辆出租车，然后车里放了一首比较小众的歌，雅纳切克的《小交响曲》，但是青豆知道它，这跟后面的情节也有些许关系，这是女主人公青豆的出场；相应的男主的出场印象不是太深刻，男主叫天吾，是个不知名的作家，跟一个叫小松的编辑有比较好的关系，虽然天吾还没有拿到比较有分量的奖项，但是小松很看好他，也让他帮忙审校一个新作家奖的投稿文章，虽然天吾自身还没获得过这个奖，天吾还有个正式工作，是当数学老师，天吾在学生时代是个数学天才，但后面有对文学产生了兴趣，文学还不足以养活自己，靠着教课还是能保持温饱；

接下来是正式故事的起点了，就是小松收到了一部小说投稿，名叫《空气蛹》，是个叫深绘里的女孩子投的稿，小松对他赋予了很高的评价，这里好像记岔了，好像是天吾对这部小说很有好感，但是小松比较怀疑，然后小松看了之后也有了浓厚的兴趣，这里就是开端了，小松想让天吾来重写润色这部《空气蛹》，因为故事本身很有分量，但是描写手法叙事方式等都很拙劣，而天吾正好擅长这个，小松对天吾的评价是，描写技巧无可挑剔，就是故事主体的火花还没际遇迸发，需要一个导火索，这个就可以类比我们程序员，很多比较初中级的程序员主要擅长在原来的代码上修修改改或者给他分配个小功能，比较高级的程序员就需要能做一些项目的架构设计，核心的技术方案设计，以前我也觉得写文档这个比较无聊，但是当一个项目真的比较庞大，复杂的时候，整体和核心部分的架构设计和方案还是需要有文档沉淀的，不然别人不知道没法接受，自己过段时间也会忘记。

对于小松的这个建议，他的初衷是想搅一搅这个死气沉沉套路颇深的文坛，因为本身《空气蛹》这部小说的内容很吸引人，小松想通过天吾的润色补充让这部小说冲击新人奖，有种恶作剧的意图，天吾对此表示很多担心和顾虑，小松的这个建议其实也是一种文学作假，有两方面的担心，一方面是原作者深绘里是否同意如此操作，一方面是外界如果发现了这个事实会有什么样的后果，但是小松表示不用担心，前一步由小松牵线，让天吾跟原作者深绘里当面沟通这个代写是否被允许，结果当然是被允许了，这里有了对深绘里的初步描写，按我的理解是比较仙的感觉，然后语言沟通有些吃力，或者说有她自己的特色，当面沟通时貌似是让深绘里回去再考虑下，然后后面再由天吾去深绘里寄宿的戎野老师家沟通具体的细节。

2019年12月18日23:37:19 更新
去到戎野老师家之后，天吾知道了关于深绘里的一些事情，深绘里的父亲与戎野老师应该是老友，深绘里的父亲在当初成立了一个叫”先驱”的公社，一个独立运行的社会组织，以运营农场作为物资来源，追求更为松散的共同体，即不过分激进地公有制，进行松散的共同生活，承认私有财产，简而言之就是这样一个能稳定存活下来的独立社会组织，但是随着稳定运行，内部的激进派和稳健派开始出现分歧，不可磨合，后来两派就分裂了，深绘里的父亲，深田保留在了稳健派，但是此时其实深田保内心是矛盾的，以为一开始其实是他倡导的独立革命才组织起了这群人，然而现在他又认清了现实社会已经不太相信能通过革命来独立的可能性，后来激进派便开始越加封闭，而且进行军事训练和思想教育，而后这个先驱的激进派别便有了新的名字”黎明”，深绘里也是在此时从先驱逃离来投靠戎野老师
暂时先写到这，未完待续~

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}2020年中总结 | Nicksxs's Blog

Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

2020年中总结

发表于 分类于 ， ， 阅读次数： 阅读次数： Disqus：

很快2020 年就过了一半了，而且是今年这么特殊的一年，很多事情都发生的出乎意料，疫情这个绕不过去的话题，之前写了点比较愤青的文字，感觉不太适合发出来就烂在草稿箱里吧，这个目前一大影响估计是今年都没办法完全摘下口罩了，前面几个月来回杭州都开车，因为彭埠大桥不通行了，实在是非常不方便，每条路都灰常堵，心累，吐槽下杭州的交通规划和交警同志，工作实在做的不咋地。

另外一件是就是蜗壳，从前不知道黝黑蜗壳是啥意思，只是经常会在他的视频里看到，大学的时候在缘网下了一个集锦，炒鸡帅气，各种空接扣篮，越来越能明白那句“你永远不知道意外和明天不知道哪个会先来,且行且珍惜”的含义，只是听了很多道理，依然活不好这一生，知易行难，王阳明真的是这方面的大师，有空可以看看这方面的书，一直想写写我跟篮球跟蜗壳的这十几年，争取能早日写好吧，不过得找个静得下来的时候写。

正事方面上半年还是挺让人失望的，没有达成一些目标，应该还是能力不足吧，技术方面分析一下还是停留在看的表面层，有些实操的，或者结合业务场景的能力不太行，算是在坚持写写 blog，主要是被这个每周一篇的目标推着走，有时会比较焦虑，内容产出也还比较差，希望能在后面有些改善，可能会降低频率，只是觉得降低了也不一定能有比较好的提升，无法战胜自己的惰性，所以暂时还是坚持下这个目标吧，还有就是 coding 能力，有时候也应该刷刷题，提升思维敏捷度，大脑用太少可能生锈了，况且本来就不是很有优势，虽然失望也只能继续努力吧，日拱一卒，来日方长，加油吧~😔

还有就是跑步减肥了，截止今天，上半年跑了 136 公里了，因为疫情影响，农历年后是从 4 月 17 号开始跑的，去年跑到了 300 公里，奖励自己了一个手表（真的挺后悔的，还不如 200 块买个手表），今年希望可以能在这个基础上再进一步，一直跟领导说，跑步算是我坚持下来的唯一一个好习惯了，618 买了个跑步机，周末回家了可以不受天气影响的多跑跑，不过如果天气好可能还是会出去跑跑，跑步机跑道多少还是有点拘束，只是感觉可能是我还是吃得太多了🤦‍♂️，效果不是很明显，还在 80 这个坎徘徊，等于浪费了大半年，可能是年初的项目太费心力，压力比较大，吃得更多，是不是可以算工伤😄，这方面也需要好好调整，可以放得开一点，虽然不太可能一下子到位，但是总要去努力下，随着年龄成长总要承担更多，也要看得开一点，没法事事如愿，尽力就好了，减肥这个事情还在结合一些俯卧撑啥的，希望也能坚持下去，加油吧，不知道原话怎么说的，意思是人类最大的勇敢就是看透了人世间的苦难，仍然热爱生活。我当然没可能让内心变得这么强大，试着去努力吧，奥力给！

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}2020年中总结 | Nicksxs's Blog

Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

2020年中总结

发表于 分类于 ， ， 阅读次数： 阅读次数： Disqus：

很快2020 年就过了一半了，而且是今年这么特殊的一年，很多事情都发生的出乎意料，疫情这个绕不过去的话题，之前写了点比较愤青的文字，感觉不太适合发出来就烂在草稿箱里吧，这个目前一大影响估计是今年都没办法完全摘下口罩了，前面几个月来回杭州都开车，因为彭埠大桥不通行了，实在是非常不方便，每条路都灰常堵，心累，吐槽下杭州的交通规划和交警同志，工作实在做的不咋地。

另外一件是就是蜗壳，从前不知道黝黑蜗壳是啥意思，只是经常会在他的视频里看到，大学的时候在缘网下了一个集锦，炒鸡帅气，各种空接扣篮，越来越能明白那句“你永远不知道意外和明天不知道哪个会先来,且行且珍惜”的含义，只是听了很多道理，依然活不好这一生，知易行难，王阳明真的是这方面的大师，有空可以看看这方面的书，一直想写写我跟篮球跟蜗壳的这十几年，争取能早日写好吧，不过得找个静得下来的时候写。

正事方面上半年还是挺让人失望的，没有达成一些目标，应该还是能力不足吧，技术方面分析一下还是停留在看的表面层，有些实操的，或者结合业务场景的能力不太行，算是在坚持写写 blog，主要是被这个每周一篇的目标推着走，有时会比较焦虑，内容产出也还比较差，希望能在后面有些改善，可能会降低频率，只是觉得降低了也不一定能有比较好的提升，无法战胜自己的惰性，所以暂时还是坚持下这个目标吧，还有就是 coding 能力，有时候也应该刷刷题，提升思维敏捷度，大脑用太少可能生锈了，况且本来就不是很有优势，虽然失望也只能继续努力吧，日拱一卒，来日方长，加油吧~😔

还有就是跑步减肥了，截止今天，上半年跑了 136 公里了，因为疫情影响，农历年后是从 4 月 17 号开始跑的，去年跑到了 300 公里，奖励自己了一个手表（真的挺后悔的，还不如 200 块买个手表），今年希望可以能在这个基础上再进一步，一直跟领导说，跑步算是我坚持下来的唯一一个好习惯了，618 买了个跑步机，周末回家了可以不受天气影响的多跑跑，不过如果天气好可能还是会出去跑跑，跑步机跑道多少还是有点拘束，只是感觉可能是我还是吃得太多了🤦‍♂️，效果不是很明显，还在 80 这个坎徘徊，等于浪费了大半年，可能是年初的项目太费心力，压力比较大，吃得更多，是不是可以算工伤😄，这方面也需要好好调整，可以放得开一点，虽然不太可能一下子到位，但是总要去努力下，随着年龄成长总要承担更多，也要看得开一点，没法事事如愿，尽力就好了，减肥这个事情还在结合一些俯卧撑啥的，希望也能坚持下去，加油吧，不知道原话怎么说的，意思是人类最大的勇敢就是看透了人世间的苦难，仍然热爱生活。我当然没可能让内心变得这么强大，试着去努力吧，奥力给！

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}Linux 下 grep 命令的一点小技巧 | Nicksxs's Blog

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What hurts more, the pain of hard work or the pain of regret?

Linux 下 grep 命令的一点小技巧

发表于 更新于 分类于 ， ， ， ， ， 阅读次数： 阅读次数： Disqus：

用了比较久的 grep 命令，其实都只是用了最最基本的功能来查日志，

譬如

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grep 'xxx' xxxx.log

然后有挺多情况比如想要找日志里带一些符号什么的，就需要用到一些特殊的

比如这样\"userId\":\"123456\"，因为比如用户 ID 有时候会跟其他的 id 一样，只用具体的值 123456 来查的话干扰信息太多了，如果直接这样

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grep '\"userId\":\"123456\"' xxxx.log

好像不行，盲猜就是符号的问题，特别是\和"这两个，

之前一直是想试一下，但是没成功，昨天在排查一个问题的时候发现了，只要把这些都转义了就行了

grep '\\\"userId\\\":\\\"123456\\\"' xxxx.log

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}Linux 下 grep 命令的一点小技巧 | Nicksxs's Blog

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What hurts more, the pain of hard work or the pain of regret?

Linux 下 grep 命令的一点小技巧

发表于 更新于 分类于 ， ， ， ， ， 阅读次数： 阅读次数： Disqus：

用了比较久的 grep 命令，其实都只是用了最最基本的功能来查日志，

譬如

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grep 'xxx' xxxx.log

然后有挺多情况比如想要找日志里带一些符号什么的，就需要用到一些特殊的

比如这样\"userId\":\"123456\"，因为比如用户 ID 有时候会跟其他的 id 一样，只用具体的值 123456 来查的话干扰信息太多了，如果直接这样

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grep '\"userId\":\"123456\"' xxxx.log

好像不行，盲猜就是符号的问题，特别是\和"这两个，

之前一直是想试一下，但是没成功，昨天在排查一个问题的时候发现了，只要把这些都转义了就行了

grep '\\\"userId\\\":\\\"123456\\\"' xxxx.log

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}Apollo 的 value 注解是怎么自动更新的 | Nicksxs's Blog

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What hurts more, the pain of hard work or the pain of regret?

Apollo 的 value 注解是怎么自动更新的

发表于 分类于 ， ， 阅读次数： 阅读次数： Disqus：

在前司和目前公司，用的配置中心都是使用的 Apollo，经过了业界验证，比较强大的配置管理系统，特别是在0.10 后开始支持对使用 value 注解的配置值进行自动更新，今天刚好有个同学问到我，就顺便写篇文章记录下，其实也是借助于 spring 强大的 bean 生命周期管理，可以实现BeanPostProcessor接口，使用postProcessBeforeInitialization方法，来对bean 内部的属性和方法进行判断，是否有 value 注解，如果有就是将它注册到一个 map 中，可以看到这个方法com.ctrip.framework.apollo.spring.annotation.SpringValueProcessor#processField

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@Override
  protected void processField(Object bean, String beanName, Field field) {
    // register @Value on field
    Value value = field.getAnnotation(Value.class);
    if (value == null) {
      return;
    }
    Set<String> keys = placeholderHelper.extractPlaceholderKeys(value.value());

    if (keys.isEmpty()) {
      return;
    }

    for (String key : keys) {
      SpringValue springValue = new SpringValue(key, value.value(), bean, beanName, field, false);
      springValueRegistry.register(beanFactory, key, springValue);
      logger.debug("Monitoring {}", springValue);
    }
  }

然后我们看下这个springValueRegistry是啥玩意

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public class SpringValueRegistry {
  private static final long CLEAN_INTERVAL_IN_SECONDS = 5;
  private final Map<BeanFactory, Multimap<String, SpringValue>> registry = Maps.newConcurrentMap();
  private final AtomicBoolean initialized = new AtomicBoolean(false);
  private final Object LOCK = new Object();

  public void register(BeanFactory beanFactory, String key, SpringValue springValue) {
    if (!registry.containsKey(beanFactory)) {
      synchronized (LOCK) {
        if (!registry.containsKey(beanFactory)) {
          registry.put(beanFactory, LinkedListMultimap.<String, SpringValue>create());
        }
      }
    }

    registry.get(beanFactory).put(key, springValue);

    // lazy initialize
    if (initialized.compareAndSet(false, true)) {
      initialize();
    }
  }

这类其实就是个 map 来存放 springvalue，然后有com.ctrip.framework.apollo.spring.property.AutoUpdateConfigChangeListener来监听更新操作，当有变更时

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@Override
 public void onChange(ConfigChangeEvent changeEvent) {
   Set<String> keys = changeEvent.changedKeys();
   if (CollectionUtils.isEmpty(keys)) {
     return;
   }
   for (String key : keys) {
     // 1. check whether the changed key is relevant
     Collection<SpringValue> targetValues = springValueRegistry.get(beanFactory, key);
     if (targetValues == null || targetValues.isEmpty()) {
       continue;
     }

     // 2. check whether the value is really changed or not (since spring property sources have hierarchies)
     // 这里其实有一点比较绕，是因为 Apollo 里的 namespace 划分，会出现 key 相同，但是 namespace 不同的情况，所以会有个优先级存在，所以需要去校验 environment 里面的是否已经更新，如果未更新则表示不需要更新
     if (!shouldTriggerAutoUpdate(changeEvent, key)) {
       continue;
     }

     // 3. update the value
     for (SpringValue val : targetValues) {
       updateSpringValue(val);
     }
   }
 }

其实原理很简单，就是得了解知道下

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}Apollo 的 value 注解是怎么自动更新的 | Nicksxs's Blog

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What hurts more, the pain of hard work or the pain of regret?

Apollo 的 value 注解是怎么自动更新的

发表于 分类于 ， ， 阅读次数： 阅读次数： Disqus：

在前司和目前公司，用的配置中心都是使用的 Apollo，经过了业界验证，比较强大的配置管理系统，特别是在0.10 后开始支持对使用 value 注解的配置值进行自动更新，今天刚好有个同学问到我，就顺便写篇文章记录下，其实也是借助于 spring 强大的 bean 生命周期管理，可以实现BeanPostProcessor接口，使用postProcessBeforeInitialization方法，来对bean 内部的属性和方法进行判断，是否有 value 注解，如果有就是将它注册到一个 map 中，可以看到这个方法com.ctrip.framework.apollo.spring.annotation.SpringValueProcessor#processField

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@Override
  protected void processField(Object bean, String beanName, Field field) {
    // register @Value on field
    Value value = field.getAnnotation(Value.class);
    if (value == null) {
      return;
    }
    Set<String> keys = placeholderHelper.extractPlaceholderKeys(value.value());

    if (keys.isEmpty()) {
      return;
    }

    for (String key : keys) {
      SpringValue springValue = new SpringValue(key, value.value(), bean, beanName, field, false);
      springValueRegistry.register(beanFactory, key, springValue);
      logger.debug("Monitoring {}", springValue);
    }
  }

然后我们看下这个springValueRegistry是啥玩意

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public class SpringValueRegistry {
  private static final long CLEAN_INTERVAL_IN_SECONDS = 5;
  private final Map<BeanFactory, Multimap<String, SpringValue>> registry = Maps.newConcurrentMap();
  private final AtomicBoolean initialized = new AtomicBoolean(false);
  private final Object LOCK = new Object();

  public void register(BeanFactory beanFactory, String key, SpringValue springValue) {
    if (!registry.containsKey(beanFactory)) {
      synchronized (LOCK) {
        if (!registry.containsKey(beanFactory)) {
          registry.put(beanFactory, LinkedListMultimap.<String, SpringValue>create());
        }
      }
    }

    registry.get(beanFactory).put(key, springValue);

    // lazy initialize
    if (initialized.compareAndSet(false, true)) {
      initialize();
    }
  }

这类其实就是个 map 来存放 springvalue，然后有com.ctrip.framework.apollo.spring.property.AutoUpdateConfigChangeListener来监听更新操作，当有变更时

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@Override
 public void onChange(ConfigChangeEvent changeEvent) {
   Set<String> keys = changeEvent.changedKeys();
   if (CollectionUtils.isEmpty(keys)) {
     return;
   }
   for (String key : keys) {
     // 1. check whether the changed key is relevant
     Collection<SpringValue> targetValues = springValueRegistry.get(beanFactory, key);
     if (targetValues == null || targetValues.isEmpty()) {
       continue;
     }

     // 2. check whether the value is really changed or not (since spring property sources have hierarchies)
     // 这里其实有一点比较绕，是因为 Apollo 里的 namespace 划分，会出现 key 相同，但是 namespace 不同的情况，所以会有个优先级存在，所以需要去校验 environment 里面的是否已经更新，如果未更新则表示不需要更新
     if (!shouldTriggerAutoUpdate(changeEvent, key)) {
       continue;
     }

     // 3. update the value
     for (SpringValue val : targetValues) {
       updateSpringValue(val);
     }
   }
 }

其实原理很简单，就是得了解知道下

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关于读书打卡与分享

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最近群里大佬发起了一个读书打卡活动，需要每天读一会书，在群里打卡分享感悟，争取一个月能读完一本书，说实话一天十分钟的读书时间倒是问题不大，不过每天都要打卡，而且一个月要读完一本书，其实难度还是有点大的，不过也想试试看。
之前某某老大给自己立了个 flag，说要读一百本书，这对我来说挺难实现的，一则我也不喜欢书只读一小半，二则感觉对于喜欢看的内容范围还是比较有限制，可能也算是比较矫情，不爱追热门的各类东西，因为往往会有一些跟大众不一致的观点看法，显得格格不入。所以还是这个打卡活动可能会比较适合我，书是人类进步的阶梯。
到现在是打卡了三天了，读的主要是白岩松的《幸福了吗》，对于白岩松，我们这一代人是比较熟悉，并且整体印象比较不错的一个央视主持人，从《焦点访谈》开始，到疫情期间的各类一线节目，可能对我来说是个三观比较正，敢于说一些真话的主持人，这中间其实是有个空档期，没怎么看电视，也不太关注了，只是在疫情期间的节目，还是一如既往地给人一种可靠的感觉，正好有一次偶然微信读书推荐了白岩松的这本书，就看了一部分，正好这次继续往下看，因为相对来讲不会很晦涩，并且从这位知名央视主持人的角度分享他的过往和想法看法，还是比较有意思的。
从对汶川地震，08 年奥运等往事的回忆和一些细节的呈现，也让我了解比较多当时所不知道的，特别是汶川地震，那时的我还在读高中，真的是看着电视，作为“猛男”都忍不住泪目了，共和国之殇，多难兴邦，但是这对于当事人来说，都是一场醒不过来的噩梦。
然后是对于足球的热爱，其实光这个就能掰扯很多，因为我不爱足球，只爱篮球，其中原因有的没的也挺多可以说的，但是看了他的书，才能比较深入的了解一个足球迷，对足球，对中国足球，对世界杯，对阿根廷的感情。
接下去还是想能继续坚持下去，加油！

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关于读书打卡与分享

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最近群里大佬发起了一个读书打卡活动，需要每天读一会书，在群里打卡分享感悟，争取一个月能读完一本书，说实话一天十分钟的读书时间倒是问题不大，不过每天都要打卡，而且一个月要读完一本书，其实难度还是有点大的，不过也想试试看。
之前某某老大给自己立了个 flag，说要读一百本书，这对我来说挺难实现的，一则我也不喜欢书只读一小半，二则感觉对于喜欢看的内容范围还是比较有限制，可能也算是比较矫情，不爱追热门的各类东西，因为往往会有一些跟大众不一致的观点看法，显得格格不入。所以还是这个打卡活动可能会比较适合我，书是人类进步的阶梯。
到现在是打卡了三天了，读的主要是白岩松的《幸福了吗》，对于白岩松，我们这一代人是比较熟悉，并且整体印象比较不错的一个央视主持人，从《焦点访谈》开始，到疫情期间的各类一线节目，可能对我来说是个三观比较正，敢于说一些真话的主持人，这中间其实是有个空档期，没怎么看电视，也不太关注了，只是在疫情期间的节目，还是一如既往地给人一种可靠的感觉，正好有一次偶然微信读书推荐了白岩松的这本书，就看了一部分，正好这次继续往下看，因为相对来讲不会很晦涩，并且从这位知名央视主持人的角度分享他的过往和想法看法，还是比较有意思的。
从对汶川地震，08 年奥运等往事的回忆和一些细节的呈现，也让我了解比较多当时所不知道的，特别是汶川地震，那时的我还在读高中，真的是看着电视，作为“猛男”都忍不住泪目了，共和国之殇，多难兴邦，但是这对于当事人来说，都是一场醒不过来的噩梦。
然后是对于足球的热爱，其实光这个就能掰扯很多，因为我不爱足球，只爱篮球，其中原因有的没的也挺多可以说的，但是看了他的书，才能比较深入的了解一个足球迷，对足球，对中国足球，对世界杯，对阿根廷的感情。
接下去还是想能继续坚持下去，加油！

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What hurts more, the pain of hard work or the pain of regret?

AQS篇一

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很多东西都是时看时新，而且时间长了也会忘，所以再来复习下，也会有一些新的角度看法这次来聊下AQS的内容，主要是这几个点，

第一个线程

第一个线程抢到锁了，此时state跟阻塞队列是怎么样的，其实这里是之前没理解对的地方

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/**
         * Fair version of tryAcquire.  Don't grant access unless
         * recursive call or no waiters or is first.
         */
        protected final boolean tryAcquire(int acquires) {
            final Thread current = Thread.currentThread();
            int c = getState();
            // 这里如果state还是0说明锁还空着
            if (c == 0) {
                // 因为是公平锁版本的，先去看下是否阻塞队列里有排着队的
                if (!hasQueuedPredecessors() &&
                    compareAndSetState(0, acquires)) {
                    // 没有排队的，并且state使用cas设置成功的就标记当前占有锁的线程是我
                    setExclusiveOwnerThread(current);
                    // 然后其实就返回了，包括阻塞队列的head和tail节点和waitStatus都没有设置
                    return true;
                }
            }
            else if (current == getExclusiveOwnerThread()) {
                int nextc = c + acquires;
                if (nextc < 0)
                    throw new Error("Maximum lock count exceeded");
                setState(nextc);
                return true;
            }
            // 这里就是第二个线程会返回false
            return false;
        }
    }

第二个线程

当第二个线程进来的时候应该是怎么样，结合代码来看

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/**
     * Acquires in exclusive mode, ignoring interrupts.  Implemented
     * by invoking at least once {@link #tryAcquire},
     * returning on success.  Otherwise the thread is queued, possibly
     * repeatedly blocking and unblocking, invoking {@link
     * #tryAcquire} until success.  This method can be used
     * to implement method {@link Lock#lock}.
     *
     * @param arg the acquire argument.  This value is conveyed to
     *        {@link #tryAcquire} but is otherwise uninterpreted and
     *        can represent anything you like.
     */
    public final void acquire(int arg) {
        // 前面第一种情况是tryAcquire直接成功了，这个if判断第一个条件就是false，就不往下执行了
        // 如果是第二个线程，第一个条件获取锁不成功，条件判断!tryAcquire(arg) == true，就会走
        // acquireQueued(addWaiter(Node.EXCLUSIVE), arg)
        if (!tryAcquire(arg) &&
            acquireQueued(addWaiter(Node.EXCLUSIVE), arg))
            selfInterrupt();
    }

然后来看下addWaiter的逻辑

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/**
     * Creates and enqueues node for current thread and given mode.
     *
     * @param mode Node.EXCLUSIVE for exclusive, Node.SHARED for shared
     * @return the new node
     */
    private Node addWaiter(Node mode) {
        // 这里是包装成一个node
        Node node = new Node(Thread.currentThread(), mode);
        // Try the fast path of enq; backup to full enq on failure
        // 最快的方式就是把当前线程的节点放在阻塞队列的最后
        Node pred = tail;
        // 只有当tail，也就是pred不为空的时候可以直接接上
        if (pred != null) {
            node.prev = pred;
            // 如果这里cas成功了，就直接接上返回了
            if (compareAndSetTail(pred, node)) {
                pred.next = node;
                return node;
            }
        }
        // 不然就会继续走到这里
        enq(node);
        return node;
    }

然后就是enq的逻辑了

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/**
     * Inserts node into queue, initializing if necessary. See picture above.
     * @param node the node to insert
     * @return node's predecessor
     */
    private Node enq(final Node node) {
        for (;;) {
            // 如果状态没变化的话，tail这时还是null的
            Node t = tail;
            if (t == null) { // Must initialize
                // 这里就会初始化头结点，就是个空节点
                if (compareAndSetHead(new Node()))
                    // tail也赋值成head
                    tail = head;
            } else {
                // 这里就设置tail了
                node.prev = t;
                if (compareAndSetTail(t, node)) {
                    t.next = node;
                    return t;
                }
            }
        }
    }

所以从这里可以看出来，其实head头结点不是个真实的带有线程的节点，并且不是在第一个线程进来的时候设置的

解锁

通过代码来看下

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/**
     * Attempts to release this lock.
     *
     * <p>If the current thread is the holder of this lock then the hold
     * count is decremented.  If the hold count is now zero then the lock
     * is released.  If the current thread is not the holder of this
     * lock then {@link IllegalMonitorStateException} is thrown.
     *
     * @throws IllegalMonitorStateException if the current thread does not
     *         hold this lock
     */
    public void unlock() {
        // 释放锁
        sync.release(1);
    }
/**
     * Releases in exclusive mode.  Implemented by unblocking one or
     * more threads if {@link #tryRelease} returns true.
     * This method can be used to implement method {@link Lock#unlock}.
     *
     * @param arg the release argument.  This value is conveyed to
     *        {@link #tryRelease} but is otherwise uninterpreted and
     *        can represent anything you like.
     * @return the value returned from {@link #tryRelease}
     */
    public final boolean release(int arg) {
        // 尝试去释放
        if (tryRelease(arg)) {
            Node h = head;
            if (h != null && h.waitStatus != 0)
                unparkSuccessor(h);
            return true;
        }
        return false;
    }
protected final boolean tryRelease(int releases) {
            int c = getState() - releases;
            if (Thread.currentThread() != getExclusiveOwnerThread())
                throw new IllegalMonitorStateException();
            boolean free = false;
    		// 判断是否完全释放锁，因为可重入
            if (c == 0) {
                free = true;
                setExclusiveOwnerThread(null);
            }
            setState(c);
            return free;
        }
// 这段代码和上面的一致，只是为了顺序性，又拷下来看下

public final boolean release(int arg) {
        // 尝试去释放，如果是完全释放，返回的就是true，否则是false
        if (tryRelease(arg)) {
            Node h = head;
            // 这里判断头结点是否为空以及waitStatus的状态，前面说了head节点其实是
            // 在第二个线程进来的时候初始化的，如果是空的话说明没后续节点，并且waitStatus
            // 也表示了后续的等待状态
            if (h != null && h.waitStatus != 0)
                unparkSuccessor(h);
            return true;
        }
        return false;
    }

/**
     * Wakes up node's successor, if one exists.
     *
     * @param node the node
     */
// 唤醒后继节点
    private void unparkSuccessor(Node node) {
        /*
         * If status is negative (i.e., possibly needing signal) try
         * to clear in anticipation of signalling.  It is OK if this
         * fails or if status is changed by waiting thread.
         */
        int ws = node.waitStatus;
        if (ws < 0)
            compareAndSetWaitStatus(node, ws, 0);

        /*
         * Thread to unpark is held in successor, which is normally
         * just the next node.  But if cancelled or apparently null,
         * traverse backwards from tail to find the actual
         * non-cancelled successor.
         */
        Node s = node.next;
        // 如果后继节点是空或者当前节点取消等待了
        if (s == null || s.waitStatus > 0) {
            s = null;
            // 从后往前找，找到非取消的节点，注意这里不是找到就退出，而是一直找到头
            // 所以不必担心中间有取消的
            for (Node t = tail; t != null && t != node; t = t.prev)
                if (t.waitStatus <= 0)
                    s = t;
        }
        if (s != null)
            // 将其唤醒
            LockSupport.unpark(s.thread);
    }
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AQS篇一

发表于 更新于 分类于 ， 阅读次数： 阅读次数： Disqus：

很多东西都是时看时新，而且时间长了也会忘，所以再来复习下，也会有一些新的角度看法这次来聊下AQS的内容，主要是这几个点，

第一个线程

第一个线程抢到锁了，此时state跟阻塞队列是怎么样的，其实这里是之前没理解对的地方

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/**
         * Fair version of tryAcquire.  Don't grant access unless
         * recursive call or no waiters or is first.
         */
        protected final boolean tryAcquire(int acquires) {
            final Thread current = Thread.currentThread();
            int c = getState();
            // 这里如果state还是0说明锁还空着
            if (c == 0) {
                // 因为是公平锁版本的，先去看下是否阻塞队列里有排着队的
                if (!hasQueuedPredecessors() &&
                    compareAndSetState(0, acquires)) {
                    // 没有排队的，并且state使用cas设置成功的就标记当前占有锁的线程是我
                    setExclusiveOwnerThread(current);
                    // 然后其实就返回了，包括阻塞队列的head和tail节点和waitStatus都没有设置
                    return true;
                }
            }
            else if (current == getExclusiveOwnerThread()) {
                int nextc = c + acquires;
                if (nextc < 0)
                    throw new Error("Maximum lock count exceeded");
                setState(nextc);
                return true;
            }
            // 这里就是第二个线程会返回false
            return false;
        }
    }

第二个线程

当第二个线程进来的时候应该是怎么样，结合代码来看

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/**
     * Acquires in exclusive mode, ignoring interrupts.  Implemented
     * by invoking at least once {@link #tryAcquire},
     * returning on success.  Otherwise the thread is queued, possibly
     * repeatedly blocking and unblocking, invoking {@link
     * #tryAcquire} until success.  This method can be used
     * to implement method {@link Lock#lock}.
     *
     * @param arg the acquire argument.  This value is conveyed to
     *        {@link #tryAcquire} but is otherwise uninterpreted and
     *        can represent anything you like.
     */
    public final void acquire(int arg) {
        // 前面第一种情况是tryAcquire直接成功了，这个if判断第一个条件就是false，就不往下执行了
        // 如果是第二个线程，第一个条件获取锁不成功，条件判断!tryAcquire(arg) == true，就会走
        // acquireQueued(addWaiter(Node.EXCLUSIVE), arg)
        if (!tryAcquire(arg) &&
            acquireQueued(addWaiter(Node.EXCLUSIVE), arg))
            selfInterrupt();
    }

然后来看下addWaiter的逻辑

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/**
     * Creates and enqueues node for current thread and given mode.
     *
     * @param mode Node.EXCLUSIVE for exclusive, Node.SHARED for shared
     * @return the new node
     */
    private Node addWaiter(Node mode) {
        // 这里是包装成一个node
        Node node = new Node(Thread.currentThread(), mode);
        // Try the fast path of enq; backup to full enq on failure
        // 最快的方式就是把当前线程的节点放在阻塞队列的最后
        Node pred = tail;
        // 只有当tail，也就是pred不为空的时候可以直接接上
        if (pred != null) {
            node.prev = pred;
            // 如果这里cas成功了，就直接接上返回了
            if (compareAndSetTail(pred, node)) {
                pred.next = node;
                return node;
            }
        }
        // 不然就会继续走到这里
        enq(node);
        return node;
    }

然后就是enq的逻辑了

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/**
     * Inserts node into queue, initializing if necessary. See picture above.
     * @param node the node to insert
     * @return node's predecessor
     */
    private Node enq(final Node node) {
        for (;;) {
            // 如果状态没变化的话，tail这时还是null的
            Node t = tail;
            if (t == null) { // Must initialize
                // 这里就会初始化头结点，就是个空节点
                if (compareAndSetHead(new Node()))
                    // tail也赋值成head
                    tail = head;
            } else {
                // 这里就设置tail了
                node.prev = t;
                if (compareAndSetTail(t, node)) {
                    t.next = node;
                    return t;
                }
            }
        }
    }

所以从这里可以看出来，其实head头结点不是个真实的带有线程的节点，并且不是在第一个线程进来的时候设置的

解锁

通过代码来看下

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/**
     * Attempts to release this lock.
     *
     * <p>If the current thread is the holder of this lock then the hold
     * count is decremented.  If the hold count is now zero then the lock
     * is released.  If the current thread is not the holder of this
     * lock then {@link IllegalMonitorStateException} is thrown.
     *
     * @throws IllegalMonitorStateException if the current thread does not
     *         hold this lock
     */
    public void unlock() {
        // 释放锁
        sync.release(1);
    }
/**
     * Releases in exclusive mode.  Implemented by unblocking one or
     * more threads if {@link #tryRelease} returns true.
     * This method can be used to implement method {@link Lock#unlock}.
     *
     * @param arg the release argument.  This value is conveyed to
     *        {@link #tryRelease} but is otherwise uninterpreted and
     *        can represent anything you like.
     * @return the value returned from {@link #tryRelease}
     */
    public final boolean release(int arg) {
        // 尝试去释放
        if (tryRelease(arg)) {
            Node h = head;
            if (h != null && h.waitStatus != 0)
                unparkSuccessor(h);
            return true;
        }
        return false;
    }
protected final boolean tryRelease(int releases) {
            int c = getState() - releases;
            if (Thread.currentThread() != getExclusiveOwnerThread())
                throw new IllegalMonitorStateException();
            boolean free = false;
    		// 判断是否完全释放锁，因为可重入
            if (c == 0) {
                free = true;
                setExclusiveOwnerThread(null);
            }
            setState(c);
            return free;
        }
// 这段代码和上面的一致，只是为了顺序性，又拷下来看下

public final boolean release(int arg) {
        // 尝试去释放，如果是完全释放，返回的就是true，否则是false
        if (tryRelease(arg)) {
            Node h = head;
            // 这里判断头结点是否为空以及waitStatus的状态，前面说了head节点其实是
            // 在第二个线程进来的时候初始化的，如果是空的话说明没后续节点，并且waitStatus
            // 也表示了后续的等待状态
            if (h != null && h.waitStatus != 0)
                unparkSuccessor(h);
            return true;
        }
        return false;
    }

/**
     * Wakes up node's successor, if one exists.
     *
     * @param node the node
     */
// 唤醒后继节点
    private void unparkSuccessor(Node node) {
        /*
         * If status is negative (i.e., possibly needing signal) try
         * to clear in anticipation of signalling.  It is OK if this
         * fails or if status is changed by waiting thread.
         */
        int ws = node.waitStatus;
        if (ws < 0)
            compareAndSetWaitStatus(node, ws, 0);

        /*
         * Thread to unpark is held in successor, which is normally
         * just the next node.  But if cancelled or apparently null,
         * traverse backwards from tail to find the actual
         * non-cancelled successor.
         */
        Node s = node.next;
        // 如果后继节点是空或者当前节点取消等待了
        if (s == null || s.waitStatus > 0) {
            s = null;
            // 从后往前找，找到非取消的节点，注意这里不是找到就退出，而是一直找到头
            // 所以不必担心中间有取消的
            for (Node t = tail; t != null && t != node; t = t.prev)
                if (t.waitStatus <= 0)
                    s = t;
        }
        if (s != null)
            // 将其唤醒
            LockSupport.unpark(s.thread);
    }
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AQS篇二 之 Condition 浅析笔记

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Condition也是 AQS 中很重要的一块内容，可以先看段示例代码，这段代码应该来自于Doug Lea大大，可以在 javadoc 中的 condition 部分找到，其实大大原来写过基于 synchronized 实现的，后面我也贴下代码

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import java.util.concurrent.locks.Condition;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;

class BoundedBuffer {
    final Lock lock = new ReentrantLock();
    // condition 依赖于 lock 来产生
    final Condition notFull = lock.newCondition();
    final Condition notEmpty = lock.newCondition();

    // 对象池子，put 跟 take 的就是这里的
    final Object[] items = new Object[100];
    int putptr, takeptr, count;

    // 生产
    public void put(Object x) throws InterruptedException {
        // 这里也说明了，需要先拥有锁
        lock.lock();
        try {
            while (count == items.length)
                notFull.await();  // 队列已满，等待，直到 not full 才能继续生产
            items[putptr] = x;
            if (++putptr == items.length) putptr = 0;
            ++count;
            notEmpty.signal(); // 生产成功，队列已经 not empty 了，发个通知出去
        } finally {
            lock.unlock();
        }
    }

    // 消费
    public Object take() throws InterruptedException {
        lock.lock();
        try {
            while (count == 0)
                notEmpty.await(); // 队列为空，等待，直到队列 not empty，才能继续消费
            Object x = items[takeptr];
            if (++takeptr == items.length) takeptr = 0;
            --count;
            notFull.signal(); // 被我消费掉一个，队列 not full 了，发个通知出去
            return x;
        } finally {
            lock.unlock();
        }
    }
}

介绍下 Condition 的结构

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public class ConditionObject implements Condition, java.io.Serializable {
        private static final long serialVersionUID = 1173984872572414699L;
        /** First node of condition queue. */
        private transient Node firstWaiter;
        /** Last node of condition queue. */
        private transient Node lastWaiter;

主要的就这么点，而且也复用了 AQS 阻塞队列或者大大叫 lock queue中同样的 Node 节点，只不过它没有使用其中的双向队列，也就是prev 和 next，而是在 Node 中的 nextWaiter，所以只是个单向的队列，没使用 next 其实还有个用处，后面会提到，看下结构的示意图

然后主要是看两个方法，await 和 signal,
先来看下 await

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/**
 * Implements interruptible condition wait.
 * <ol>
 * <li> If current thread is interrupted, throw InterruptedException.
 * <li> Save lock state returned by {@link #getState}.
 * <li> Invoke {@link #release} with saved state as argument,
 *      throwing IllegalMonitorStateException if it fails.
 * <li> Block until signalled or interrupted.
 * <li> Reacquire by invoking specialized version of
 *      {@link #acquire} with saved state as argument.
 * <li> If interrupted while blocked in step 4, throw InterruptedException.
 * </ol>
 */
public final void await() throws InterruptedException {
    if (Thread.interrupted())
        throw new InterruptedException();

    // 将当前节点包装成一个  condition waiter node 节点
    Node node = addConditionWaiter();

    // 完全释放占有的锁，这里需要是占有锁的线程
    int savedState = fullyRelease(node);
    int interruptMode = 0;

    // 判断下是否在阻塞队列中，因为有可能被其他节点从等待队列移动到阻塞队列
    while (!isOnSyncQueue(node)) {
        // park等待，等待被唤醒
        LockSupport.park(this);
        if ((interruptMode = checkInterruptWhileWaiting(node)) != 0)
            break;
    }

    // 被唤醒后进入阻塞队列，等待获取锁，这里继续用了fullyRelease返回的 state
    if (acquireQueued(node, savedState) && interruptMode != THROW_IE)
        interruptMode = REINTERRUPT;
    if (node.nextWaiter != null) // clean up if cancelled
        unlinkCancelledWaiters();
    if (interruptMode != 0)
        reportInterruptAfterWait(interruptMode);
}

添加条件队列节点

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/**
 * Adds a new waiter to wait queue.
 * @return its new wait node
 */
private Node addConditionWaiter() {
    Node t = lastWaiter;
    // If lastWaiter is cancelled, clean out.
    // 如果节点已经不是 CONDITION 状态了，表示已经取消了
    if (t != null && t.waitStatus != Node.CONDITION) {
        // 把等待队列中取消的节点清理出去
        unlinkCancelledWaiters();
        t = lastWaiter;
    }
    // 把当前线程包装成waitStatus=CONDITION 的节点
    Node node = new Node(Thread.currentThread(), Node.CONDITION);
    // 没有 lastWaiter 节点，直接是 firstWaiter
    if (t == null)
        firstWaiter = node;
    else
    // 不然就接在 lastWaiter 后面
        t.nextWaiter = node;
    // 当前节点就会变成新的 lastWaiter
    lastWaiter = node;
    return node;
}

清理取消的节点

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/**
 * Unlinks cancelled waiter nodes from condition queue.
 * Called only while holding lock. This is called when
 * cancellation occurred during condition wait, and upon
 * insertion of a new waiter when lastWaiter is seen to have
 * been cancelled. This method is needed to avoid garbage
 * retention in the absence of signals. So even though it may
 * require a full traversal, it comes into play only when
 * timeouts or cancellations occur in the absence of
 * signals. It traverses all nodes rather than stopping at a
 * particular target to unlink all pointers to garbage nodes
 * without requiring many re-traversals during cancellation
 * storms.
 */
private void unlinkCancelledWaiters() {
    Node t = firstWaiter;
    Node trail = null;
    // 循环遍历单向链表的节点，如果状态不是 CONDITION 就清出去
    while (t != null) {
        Node next = t.nextWaiter;
        // 循环链表操作，清掉取消的节点
        if (t.waitStatus != Node.CONDITION) {
            t.nextWaiter = null;
            if (trail == null)
                firstWaiter = next;
            else
                trail.nextWaiter = next;
            if (next == null)
                lastWaiter = trail;
        }
        else
            trail = t;
        t = next;
    }
}

完全释放锁

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/**
 * Invokes release with current state value; returns saved state.
 * Cancels node and throws exception on failure.
 * @param node the condition node for this wait
 * @return previous sync state
 */
final int fullyRelease(Node node) {
    boolean failed = true;
    try {
        // 获取下当前的 state 值，因为是可重入的，所以这个值要保存下来
        int savedState = getState();
        // 这里还包含比较多操作，不过跟前面分析 AQS 的释放比较类似，不深入了
        if (release(savedState)) {
            failed = false;
            // 返回这个值
            return savedState;
        } else {
            throw new IllegalMonitorStateException();
        }
    } finally {
        if (failed)
            node.waitStatus = Node.CANCELLED;
    }
}

判断是否在阻塞队列中

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/**
 * Returns true if a node, always one that was initially placed on
 * a condition queue, is now waiting to reacquire on sync queue.
 * @param node the node
 * @return true if is reacquiring
 */
final boolean isOnSyncQueue(Node node) {
    // 如果waitStatus 是 CONDITION 或者没有 prev 前置节点肯定就不在
    if (node.waitStatus == Node.CONDITION || node.prev == null)
        return false;
    // 这里就是我前面提到的 next 的作用
    if (node.next != null) // If has successor, it must be on queue
        return true;
    // 从 tail 开始找，是否在阻塞队列中
    /*
     * node.prev can be non-null, but not yet on queue because
     * the CAS to place it on queue can fail. So we have to
     * traverse from tail to make sure it actually made it.  It
     * will always be near the tail in calls to this method, and
     * unless the CAS failed (which is unlikely), it will be
     * there, so we hardly ever traverse much.
     */
    return findNodeFromTail(node);
}
/**
 * Returns true if node is on sync queue by searching backwards from tail.
 * Called only when needed by isOnSyncQueue.
 * @return true if present
 */
private boolean findNodeFromTail(Node node) {
    Node t = tail;
    // 从 tail 开始，从后往前找
    for (;;) {
        if (t == node)
            return true;
        if (t == null)
            return false;
        t = t.prev;
    }
}

await 的逻辑差不多就是这样子，主要的就是把自己包成一个 Node 节点，waitStatus 的状态是 CONDITION，挂在等待队列的最后，然后完全释放锁，park 等待

signal

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/**
 * Moves the longest-waiting thread, if one exists, from the
 * wait queue for this condition to the wait queue for the
 * owning lock.
 *
 * @throws IllegalMonitorStateException if {@link #isHeldExclusively}
 *         returns {@code false}
 */
public final void signal() {
    if (!isHeldExclusively())
        throw new IllegalMonitorStateException();
    // firstWaiter 肯定是最早开始等待的
    Node first = firstWaiter;
    // 如果不为空就唤醒
    if (first != null)
        doSignal(first);
}
/**
 * Removes and transfers nodes until hit non-cancelled one or
 * null. Split out from signal in part to encourage compilers
 * to inline the case of no waiters.
 * @param first (non-null) the first node on condition queue
 */
private void doSignal(Node first) {
    do {
        // 因为要去唤醒 first 节点了，firstWaiter 需要再从后面找一个
        // 并且判断是否为空，如果是空的话就直接可以把 lastWaiter 设置成空了
        if ( (firstWaiter = first.nextWaiter) == null)
            lastWaiter = null;
        //  first 不需要继续保存后面的 waiter 了，因为 firstWaiter 已经是 first 的后置节点了
        first.nextWaiter = null;
    // 如果 first 节点转移不成功，并且 firstWaiter 节点不为空，则继续进入循环
    } while (!transferForSignal(first) &&
             (first = firstWaiter) != null);
}
/**
 * Transfers a node from a condition queue onto sync queue.
 * Returns true if successful.
 * @param node the node
 * @return true if successfully transferred (else the node was
 * cancelled before signal)
 */
final boolean transferForSignal(Node node) {
    /*
     * If cannot change waitStatus, the node has been cancelled.
     */
    // 如果状态已经不是 CONDITION 就不会设置成功，返回 false
    if (!compareAndSetWaitStatus(node, Node.CONDITION, 0))
        return false;
    /*
     * Splice onto queue and try to set waitStatus of predecessor to
     * indicate that thread is (probably) waiting. If cancelled or
     * attempt to set waitStatus fails, wake up to resync (in which
     * case the waitStatus can be transiently and harmlessly wrong).
     */
    // 调用跟aqs 第一篇中一样的 enq 方法进入阻塞队列，返回入队后的前一节点
    Node p = enq(node);
    int ws = p.waitStatus;
    // 将前置节点状态设置成SIGNAL，表示后面有节点在等了
    if (ws > 0 || !compareAndSetWaitStatus(p, ws, Node.SIGNAL))
        LockSupport.unpark(node.thread);
    // 返回 true，上一个方法的循环就退出了
    return true;
}

这里其实就是把 condition 等待队列的第一个未取消的节点入队到阻塞队列去争锁

附录

synchronized 版的 BoundedBuffer

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/*
  File: BoundedBuffer.java

  Originally written by Doug Lea and released into the public domain.
  This may be used for any purposes whatsoever without acknowledgment.
  Thanks for the assistance and support of Sun Microsystems Labs,
  and everyone contributing, testing, and using this code.

  History:
  Date       Who                What
  11Jun1998  dl               Create public version
  17Jul1998  dl               Simplified by eliminating wait counts
  25aug1998  dl               added peek
   5May1999  dl               replace % with conditional (slightly faster)
*/

package EDU.oswego.cs.dl.util.concurrent;

/**
 * Efficient array-based bounded buffer class.
 * Adapted from CPJ, chapter 8, which describes design.
 * <p>[<a href="http://gee.cs.oswego.edu/dl/classes/EDU/oswego/cs/dl/util/concurrent/intro.html"> Introduction to this package. </a>] <p>
 **/

public class BoundedBuffer implements BoundedChannel {

  protected final Object[]  array_;      // the elements

  protected int takePtr_ = 0;            // circular indices
  protected int putPtr_ = 0;       

  protected int usedSlots_ = 0;          // length
  protected int emptySlots_;             // capacity - length

  /**
   * Helper monitor to handle puts. 
   **/
  protected final Object putMonitor_ = new Object();

  /**
   * Create a BoundedBuffer with the given capacity.
   * @exception IllegalArgumentException if capacity less or equal to zero
   **/
  public BoundedBuffer(int capacity) throws IllegalArgumentException {
    if (capacity <= 0) throw new IllegalArgumentException();
    array_ = new Object[capacity];
    emptySlots_ = capacity;
  }

  /**
   * Create a buffer with the current default capacity
   **/

  public BoundedBuffer() { 
    this(DefaultChannelCapacity.get()); 
  }

  /** 
   * Return the number of elements in the buffer.
   * This is only a snapshot value, that may change
   * immediately after returning.
   **/
  public synchronized int size() { return usedSlots_; }

  public int capacity() { return array_.length; }

  protected void incEmptySlots() {
    synchronized(putMonitor_) {
      ++emptySlots_;
      putMonitor_.notify();
    }
  }

  protected synchronized void incUsedSlots() {
    ++usedSlots_;
    notify();
  }

  protected final void insert(Object x) { // mechanics of put
    --emptySlots_;
    array_[putPtr_] = x;
    if (++putPtr_ >= array_.length) putPtr_ = 0;
  }

  protected final Object extract() { // mechanics of take
    --usedSlots_;
    Object old = array_[takePtr_];
    array_[takePtr_] = null;
    if (++takePtr_ >= array_.length) takePtr_ = 0;
    return old;
  }

  public Object peek() {
    synchronized(this) {
      if (usedSlots_ > 0)
        return array_[takePtr_];
      else
        return null;
    }
  }


  public void put(Object x) throws InterruptedException {
    if (x == null) throw new IllegalArgumentException();
    if (Thread.interrupted()) throw new InterruptedException();

    synchronized(putMonitor_) {
      while (emptySlots_ <= 0) {
	try { putMonitor_.wait(); }
        catch (InterruptedException ex) {
          putMonitor_.notify();
          throw ex;
        }
      }
      insert(x);
    }
    incUsedSlots();
  }

  public boolean offer(Object x, long msecs) throws InterruptedException {
    if (x == null) throw new IllegalArgumentException();
    if (Thread.interrupted()) throw new InterruptedException();

    synchronized(putMonitor_) {
      long start = (msecs <= 0)? 0 : System.currentTimeMillis();
      long waitTime = msecs;
      while (emptySlots_ <= 0) {
        if (waitTime <= 0) return false;
	try { putMonitor_.wait(waitTime); }
        catch (InterruptedException ex) {
          putMonitor_.notify();
          throw ex;
        }
        waitTime = msecs - (System.currentTimeMillis() - start);
      }
      insert(x);
    }
    incUsedSlots();
    return true;
  }



  public  Object take() throws InterruptedException { 
    if (Thread.interrupted()) throw new InterruptedException();
    Object old = null; 
    synchronized(this) { 
      while (usedSlots_ <= 0) {
        try { wait(); }
        catch (InterruptedException ex) {
          notify();
          throw ex; 
        }
      }
      old = extract();
    }
    incEmptySlots();
    return old;
  }

  public  Object poll(long msecs) throws InterruptedException { 
    if (Thread.interrupted()) throw new InterruptedException();
    Object old = null; 
    synchronized(this) { 
      long start = (msecs <= 0)? 0 : System.currentTimeMillis();
      long waitTime = msecs;
      
      while (usedSlots_ <= 0) {
        if (waitTime <= 0) return null;
        try { wait(waitTime); }
        catch (InterruptedException ex) {
          notify();
          throw ex; 
        }
        waitTime = msecs - (System.currentTimeMillis() - start);

      }
      old = extract();
    }
    incEmptySlots();
    return old;
  }

}

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AQS篇二 之 Condition 浅析笔记

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Condition也是 AQS 中很重要的一块内容，可以先看段示例代码，这段代码应该来自于Doug Lea大大，可以在 javadoc 中的 condition 部分找到，其实大大原来写过基于 synchronized 实现的，后面我也贴下代码

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import java.util.concurrent.locks.Condition;
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;

class BoundedBuffer {
    final Lock lock = new ReentrantLock();
    // condition 依赖于 lock 来产生
    final Condition notFull = lock.newCondition();
    final Condition notEmpty = lock.newCondition();

    // 对象池子，put 跟 take 的就是这里的
    final Object[] items = new Object[100];
    int putptr, takeptr, count;

    // 生产
    public void put(Object x) throws InterruptedException {
        // 这里也说明了，需要先拥有锁
        lock.lock();
        try {
            while (count == items.length)
                notFull.await();  // 队列已满，等待，直到 not full 才能继续生产
            items[putptr] = x;
            if (++putptr == items.length) putptr = 0;
            ++count;
            notEmpty.signal(); // 生产成功，队列已经 not empty 了，发个通知出去
        } finally {
            lock.unlock();
        }
    }

    // 消费
    public Object take() throws InterruptedException {
        lock.lock();
        try {
            while (count == 0)
                notEmpty.await(); // 队列为空，等待，直到队列 not empty，才能继续消费
            Object x = items[takeptr];
            if (++takeptr == items.length) takeptr = 0;
            --count;
            notFull.signal(); // 被我消费掉一个，队列 not full 了，发个通知出去
            return x;
        } finally {
            lock.unlock();
        }
    }
}

介绍下 Condition 的结构

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public class ConditionObject implements Condition, java.io.Serializable {
        private static final long serialVersionUID = 1173984872572414699L;
        /** First node of condition queue. */
        private transient Node firstWaiter;
        /** Last node of condition queue. */
        private transient Node lastWaiter;

主要的就这么点，而且也复用了 AQS 阻塞队列或者大大叫 lock queue中同样的 Node 节点，只不过它没有使用其中的双向队列，也就是prev 和 next，而是在 Node 中的 nextWaiter，所以只是个单向的队列，没使用 next 其实还有个用处，后面会提到，看下结构的示意图

然后主要是看两个方法，await 和 signal,
先来看下 await

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/**
 * Implements interruptible condition wait.
 * <ol>
 * <li> If current thread is interrupted, throw InterruptedException.
 * <li> Save lock state returned by {@link #getState}.
 * <li> Invoke {@link #release} with saved state as argument,
 *      throwing IllegalMonitorStateException if it fails.
 * <li> Block until signalled or interrupted.
 * <li> Reacquire by invoking specialized version of
 *      {@link #acquire} with saved state as argument.
 * <li> If interrupted while blocked in step 4, throw InterruptedException.
 * </ol>
 */
public final void await() throws InterruptedException {
    if (Thread.interrupted())
        throw new InterruptedException();

    // 将当前节点包装成一个  condition waiter node 节点
    Node node = addConditionWaiter();

    // 完全释放占有的锁，这里需要是占有锁的线程
    int savedState = fullyRelease(node);
    int interruptMode = 0;

    // 判断下是否在阻塞队列中，因为有可能被其他节点从等待队列移动到阻塞队列
    while (!isOnSyncQueue(node)) {
        // park等待，等待被唤醒
        LockSupport.park(this);
        if ((interruptMode = checkInterruptWhileWaiting(node)) != 0)
            break;
    }

    // 被唤醒后进入阻塞队列，等待获取锁，这里继续用了fullyRelease返回的 state
    if (acquireQueued(node, savedState) && interruptMode != THROW_IE)
        interruptMode = REINTERRUPT;
    if (node.nextWaiter != null) // clean up if cancelled
        unlinkCancelledWaiters();
    if (interruptMode != 0)
        reportInterruptAfterWait(interruptMode);
}

添加条件队列节点

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/**
 * Adds a new waiter to wait queue.
 * @return its new wait node
 */
private Node addConditionWaiter() {
    Node t = lastWaiter;
    // If lastWaiter is cancelled, clean out.
    // 如果节点已经不是 CONDITION 状态了，表示已经取消了
    if (t != null && t.waitStatus != Node.CONDITION) {
        // 把等待队列中取消的节点清理出去
        unlinkCancelledWaiters();
        t = lastWaiter;
    }
    // 把当前线程包装成waitStatus=CONDITION 的节点
    Node node = new Node(Thread.currentThread(), Node.CONDITION);
    // 没有 lastWaiter 节点，直接是 firstWaiter
    if (t == null)
        firstWaiter = node;
    else
    // 不然就接在 lastWaiter 后面
        t.nextWaiter = node;
    // 当前节点就会变成新的 lastWaiter
    lastWaiter = node;
    return node;
}

清理取消的节点

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/**
 * Unlinks cancelled waiter nodes from condition queue.
 * Called only while holding lock. This is called when
 * cancellation occurred during condition wait, and upon
 * insertion of a new waiter when lastWaiter is seen to have
 * been cancelled. This method is needed to avoid garbage
 * retention in the absence of signals. So even though it may
 * require a full traversal, it comes into play only when
 * timeouts or cancellations occur in the absence of
 * signals. It traverses all nodes rather than stopping at a
 * particular target to unlink all pointers to garbage nodes
 * without requiring many re-traversals during cancellation
 * storms.
 */
private void unlinkCancelledWaiters() {
    Node t = firstWaiter;
    Node trail = null;
    // 循环遍历单向链表的节点，如果状态不是 CONDITION 就清出去
    while (t != null) {
        Node next = t.nextWaiter;
        // 循环链表操作，清掉取消的节点
        if (t.waitStatus != Node.CONDITION) {
            t.nextWaiter = null;
            if (trail == null)
                firstWaiter = next;
            else
                trail.nextWaiter = next;
            if (next == null)
                lastWaiter = trail;
        }
        else
            trail = t;
        t = next;
    }
}

完全释放锁

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/**
 * Invokes release with current state value; returns saved state.
 * Cancels node and throws exception on failure.
 * @param node the condition node for this wait
 * @return previous sync state
 */
final int fullyRelease(Node node) {
    boolean failed = true;
    try {
        // 获取下当前的 state 值，因为是可重入的，所以这个值要保存下来
        int savedState = getState();
        // 这里还包含比较多操作，不过跟前面分析 AQS 的释放比较类似，不深入了
        if (release(savedState)) {
            failed = false;
            // 返回这个值
            return savedState;
        } else {
            throw new IllegalMonitorStateException();
        }
    } finally {
        if (failed)
            node.waitStatus = Node.CANCELLED;
    }
}

判断是否在阻塞队列中

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/**
 * Returns true if a node, always one that was initially placed on
 * a condition queue, is now waiting to reacquire on sync queue.
 * @param node the node
 * @return true if is reacquiring
 */
final boolean isOnSyncQueue(Node node) {
    // 如果waitStatus 是 CONDITION 或者没有 prev 前置节点肯定就不在
    if (node.waitStatus == Node.CONDITION || node.prev == null)
        return false;
    // 这里就是我前面提到的 next 的作用
    if (node.next != null) // If has successor, it must be on queue
        return true;
    // 从 tail 开始找，是否在阻塞队列中
    /*
     * node.prev can be non-null, but not yet on queue because
     * the CAS to place it on queue can fail. So we have to
     * traverse from tail to make sure it actually made it.  It
     * will always be near the tail in calls to this method, and
     * unless the CAS failed (which is unlikely), it will be
     * there, so we hardly ever traverse much.
     */
    return findNodeFromTail(node);
}
/**
 * Returns true if node is on sync queue by searching backwards from tail.
 * Called only when needed by isOnSyncQueue.
 * @return true if present
 */
private boolean findNodeFromTail(Node node) {
    Node t = tail;
    // 从 tail 开始，从后往前找
    for (;;) {
        if (t == node)
            return true;
        if (t == null)
            return false;
        t = t.prev;
    }
}

await 的逻辑差不多就是这样子，主要的就是把自己包成一个 Node 节点，waitStatus 的状态是 CONDITION，挂在等待队列的最后，然后完全释放锁，park 等待

signal

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/**
 * Moves the longest-waiting thread, if one exists, from the
 * wait queue for this condition to the wait queue for the
 * owning lock.
 *
 * @throws IllegalMonitorStateException if {@link #isHeldExclusively}
 *         returns {@code false}
 */
public final void signal() {
    if (!isHeldExclusively())
        throw new IllegalMonitorStateException();
    // firstWaiter 肯定是最早开始等待的
    Node first = firstWaiter;
    // 如果不为空就唤醒
    if (first != null)
        doSignal(first);
}
/**
 * Removes and transfers nodes until hit non-cancelled one or
 * null. Split out from signal in part to encourage compilers
 * to inline the case of no waiters.
 * @param first (non-null) the first node on condition queue
 */
private void doSignal(Node first) {
    do {
        // 因为要去唤醒 first 节点了，firstWaiter 需要再从后面找一个
        // 并且判断是否为空，如果是空的话就直接可以把 lastWaiter 设置成空了
        if ( (firstWaiter = first.nextWaiter) == null)
            lastWaiter = null;
        //  first 不需要继续保存后面的 waiter 了，因为 firstWaiter 已经是 first 的后置节点了
        first.nextWaiter = null;
    // 如果 first 节点转移不成功，并且 firstWaiter 节点不为空，则继续进入循环
    } while (!transferForSignal(first) &&
             (first = firstWaiter) != null);
}
/**
 * Transfers a node from a condition queue onto sync queue.
 * Returns true if successful.
 * @param node the node
 * @return true if successfully transferred (else the node was
 * cancelled before signal)
 */
final boolean transferForSignal(Node node) {
    /*
     * If cannot change waitStatus, the node has been cancelled.
     */
    // 如果状态已经不是 CONDITION 就不会设置成功，返回 false
    if (!compareAndSetWaitStatus(node, Node.CONDITION, 0))
        return false;
    /*
     * Splice onto queue and try to set waitStatus of predecessor to
     * indicate that thread is (probably) waiting. If cancelled or
     * attempt to set waitStatus fails, wake up to resync (in which
     * case the waitStatus can be transiently and harmlessly wrong).
     */
    // 调用跟aqs 第一篇中一样的 enq 方法进入阻塞队列，返回入队后的前一节点
    Node p = enq(node);
    int ws = p.waitStatus;
    // 将前置节点状态设置成SIGNAL，表示后面有节点在等了
    if (ws > 0 || !compareAndSetWaitStatus(p, ws, Node.SIGNAL))
        LockSupport.unpark(node.thread);
    // 返回 true，上一个方法的循环就退出了
    return true;
}

这里其实就是把 condition 等待队列的第一个未取消的节点入队到阻塞队列去争锁

附录

synchronized 版的 BoundedBuffer

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/*
  File: BoundedBuffer.java

  Originally written by Doug Lea and released into the public domain.
  This may be used for any purposes whatsoever without acknowledgment.
  Thanks for the assistance and support of Sun Microsystems Labs,
  and everyone contributing, testing, and using this code.

  History:
  Date       Who                What
  11Jun1998  dl               Create public version
  17Jul1998  dl               Simplified by eliminating wait counts
  25aug1998  dl               added peek
   5May1999  dl               replace % with conditional (slightly faster)
*/

package EDU.oswego.cs.dl.util.concurrent;

/**
 * Efficient array-based bounded buffer class.
 * Adapted from CPJ, chapter 8, which describes design.
 * <p>[<a href="http://gee.cs.oswego.edu/dl/classes/EDU/oswego/cs/dl/util/concurrent/intro.html"> Introduction to this package. </a>] <p>
 **/

public class BoundedBuffer implements BoundedChannel {

  protected final Object[]  array_;      // the elements

  protected int takePtr_ = 0;            // circular indices
  protected int putPtr_ = 0;       

  protected int usedSlots_ = 0;          // length
  protected int emptySlots_;             // capacity - length

  /**
   * Helper monitor to handle puts. 
   **/
  protected final Object putMonitor_ = new Object();

  /**
   * Create a BoundedBuffer with the given capacity.
   * @exception IllegalArgumentException if capacity less or equal to zero
   **/
  public BoundedBuffer(int capacity) throws IllegalArgumentException {
    if (capacity <= 0) throw new IllegalArgumentException();
    array_ = new Object[capacity];
    emptySlots_ = capacity;
  }

  /**
   * Create a buffer with the current default capacity
   **/

  public BoundedBuffer() { 
    this(DefaultChannelCapacity.get()); 
  }

  /** 
   * Return the number of elements in the buffer.
   * This is only a snapshot value, that may change
   * immediately after returning.
   **/
  public synchronized int size() { return usedSlots_; }

  public int capacity() { return array_.length; }

  protected void incEmptySlots() {
    synchronized(putMonitor_) {
      ++emptySlots_;
      putMonitor_.notify();
    }
  }

  protected synchronized void incUsedSlots() {
    ++usedSlots_;
    notify();
  }

  protected final void insert(Object x) { // mechanics of put
    --emptySlots_;
    array_[putPtr_] = x;
    if (++putPtr_ >= array_.length) putPtr_ = 0;
  }

  protected final Object extract() { // mechanics of take
    --usedSlots_;
    Object old = array_[takePtr_];
    array_[takePtr_] = null;
    if (++takePtr_ >= array_.length) takePtr_ = 0;
    return old;
  }

  public Object peek() {
    synchronized(this) {
      if (usedSlots_ > 0)
        return array_[takePtr_];
      else
        return null;
    }
  }


  public void put(Object x) throws InterruptedException {
    if (x == null) throw new IllegalArgumentException();
    if (Thread.interrupted()) throw new InterruptedException();

    synchronized(putMonitor_) {
      while (emptySlots_ <= 0) {
	try { putMonitor_.wait(); }
        catch (InterruptedException ex) {
          putMonitor_.notify();
          throw ex;
        }
      }
      insert(x);
    }
    incUsedSlots();
  }

  public boolean offer(Object x, long msecs) throws InterruptedException {
    if (x == null) throw new IllegalArgumentException();
    if (Thread.interrupted()) throw new InterruptedException();

    synchronized(putMonitor_) {
      long start = (msecs <= 0)? 0 : System.currentTimeMillis();
      long waitTime = msecs;
      while (emptySlots_ <= 0) {
        if (waitTime <= 0) return false;
	try { putMonitor_.wait(waitTime); }
        catch (InterruptedException ex) {
          putMonitor_.notify();
          throw ex;
        }
        waitTime = msecs - (System.currentTimeMillis() - start);
      }
      insert(x);
    }
    incUsedSlots();
    return true;
  }



  public  Object take() throws InterruptedException { 
    if (Thread.interrupted()) throw new InterruptedException();
    Object old = null; 
    synchronized(this) { 
      while (usedSlots_ <= 0) {
        try { wait(); }
        catch (InterruptedException ex) {
          notify();
          throw ex; 
        }
      }
      old = extract();
    }
    incEmptySlots();
    return old;
  }

  public  Object poll(long msecs) throws InterruptedException { 
    if (Thread.interrupted()) throw new InterruptedException();
    Object old = null; 
    synchronized(this) { 
      long start = (msecs <= 0)? 0 : System.currentTimeMillis();
      long waitTime = msecs;
      
      while (usedSlots_ <= 0) {
        if (waitTime <= 0) return null;
        try { wait(waitTime); }
        catch (InterruptedException ex) {
          notify();
          throw ex; 
        }
        waitTime = msecs - (System.currentTimeMillis() - start);

      }
      old = extract();
    }
    incEmptySlots();
    return old;
  }

}

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}聊聊 Linux 下的 top 命令 | Nicksxs's Blog

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What hurts more, the pain of hard work or the pain of regret?

聊聊 Linux 下的 top 命令

发表于 更新于 分类于 ， ， ， ， ， 阅读次数： 阅读次数： Disqus：

top 命令在日常的 Linux 使用中，特别是做一些服务器的简单状态查看，排查故障都起了比较大的作用，但是由于这个命令看到的东西比较多，一般只会看部分，或者说像我这样就会比较片面地看一些信息，比如默认是进程维度的，可以在启动命令的时候加-H进入线程模式

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-H  :Threads-mode operation
            Instructs top to display individual threads.  Without this command-line option a summation of all threads in each process  is  shown.   Later
            this can be changed with the `H' interactive command.

这样就能用在 Java 中去 jstack 中找到对应的线程
其实还有比较重要的两个操作，
一个是在 top 启动状态下，按c键，这样能把比如说是一个 Java 进程，具体的进程命令显示出来
像这样
执行前是这样

执行后是这样

第二个就是排序了

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SORTING of task window

          For  compatibility,  this top supports most of the former top sort keys.  Since this is primarily a service to former top users, these commands
          do not appear on any help screen.
                command   sorted-field                  supported
                A         start time (non-display)      No
                M         %MEM                          Yes
                N         PID                           Yes
                P         %CPU                          Yes
                T         TIME+                         Yes

          Before using any of the following sort provisions, top suggests that you temporarily turn on column highlighting using the `x' interactive com‐
          mand.  That will help ensure that the actual sort environment matches your intent.

          The following interactive commands will only be honored when the current sort field is visible.  The sort field might not be visible because:
                1) there is insufficient Screen Width
                2) the `f' interactive command turned it Off

             <  :Move-Sort-Field-Left
                 Moves the sort column to the left unless the current sort field is the first field being displayed.

             >  :Move-Sort-Field-Right
                 Moves the sort column to the right unless the current sort field is the last field being displayed.

查看 man page 可以找到这一段，其实一般 man page 都是最细致的，只不过因为太多了，有时候懒得看，这里可以通过大写 M 和大写 P 分别按内存和 CPU 排序，下面还有两个小技巧，通过按 x 可以将当前活跃的排序列用不同颜色标出来，然后可以通过<和>直接左右移动排序列

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}聊聊 Linux 下的 top 命令 | Nicksxs's Blog

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What hurts more, the pain of hard work or the pain of regret?

聊聊 Linux 下的 top 命令

发表于 更新于 分类于 ， ， ， ， ， 阅读次数： 阅读次数： Disqus：

top 命令在日常的 Linux 使用中，特别是做一些服务器的简单状态查看，排查故障都起了比较大的作用，但是由于这个命令看到的东西比较多，一般只会看部分，或者说像我这样就会比较片面地看一些信息，比如默认是进程维度的，可以在启动命令的时候加-H进入线程模式

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-H  :Threads-mode operation
            Instructs top to display individual threads.  Without this command-line option a summation of all threads in each process  is  shown.   Later
            this can be changed with the `H' interactive command.

这样就能用在 Java 中去 jstack 中找到对应的线程
其实还有比较重要的两个操作，
一个是在 top 启动状态下，按c键，这样能把比如说是一个 Java 进程，具体的进程命令显示出来
像这样
执行前是这样

执行后是这样

第二个就是排序了

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SORTING of task window

          For  compatibility,  this top supports most of the former top sort keys.  Since this is primarily a service to former top users, these commands
          do not appear on any help screen.
                command   sorted-field                  supported
                A         start time (non-display)      No
                M         %MEM                          Yes
                N         PID                           Yes
                P         %CPU                          Yes
                T         TIME+                         Yes

          Before using any of the following sort provisions, top suggests that you temporarily turn on column highlighting using the `x' interactive com‐
          mand.  That will help ensure that the actual sort environment matches your intent.

          The following interactive commands will only be honored when the current sort field is visible.  The sort field might not be visible because:
                1) there is insufficient Screen Width
                2) the `f' interactive command turned it Off

             <  :Move-Sort-Field-Left
                 Moves the sort column to the left unless the current sort field is the first field being displayed.

             >  :Move-Sort-Field-Right
                 Moves the sort column to the right unless the current sort field is the last field being displayed.

查看 man page 可以找到这一段，其实一般 man page 都是最细致的，只不过因为太多了，有时候懒得看，这里可以通过大写 M 和大写 P 分别按内存和 CPU 排序，下面还有两个小技巧，通过按 x 可以将当前活跃的排序列用不同颜色标出来，然后可以通过<和>直接左右移动排序列

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Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

2021 年中总结

发表于 分类于 ， ， 阅读次数： 阅读次数： Disqus：

又到半年总结时，第一次写总结类型的文章感觉挺好写的，但是后面总觉得这过去的一段时间所做的事情，能力上的成长低于预期，但是是需要总结下，找找问题，顺便展望下未来。

这一年做的最让自己满意的应该就是看了一些书，由折腾群洋总发起的读书打卡活动，到目前为止已经读完了这几本书，《cUrl 必知必会》，《古董局中局 1》，《古董局中局 2》，《算法图解》，《每天 5 分钟玩转 Kubernetes》《幸福了吗？》《高可用可伸缩微服务架构：基于 Dubbo、Spring Cloud和 Service Mesh》《Rust 权威指南》后面可以写个专题说说看的这些书，虽然每天打卡如果时间安排不好，并且看的书像 rust 这样比较难的话还是会有点小焦虑，不过也是个调整过程，一方面可以在白天就抽空看一会，然后也不必要每次都看很大一章，注重吸收。

技术上的成长的话，有一些比较小的长进吧，对于一些之前忽视的 synchronized，ThreadLocal 和 AQS 等知识点做了下查漏补缺了，然后多了解了一些 Java 垃圾回收的内容，但是在实操上还是比较欠缺，成型的技术方案，架构上所谓的优化也比较少，一些想法也还有考虑不周全的地方，还需要多花时间和心思去学习加强，特别是在目前已经有的基础上如何做系统深层次的优化，既不要是鸡毛蒜皮的，也不能出现一些不可接受的问题和故障，这是个很重要的课题，需要好好学习，后面考虑定一些周期性目标，两个月左右能有一些成果和总结。

另外一部分是自己的服务，因为 ucloud 的机器太贵就没续费了，所以都迁移到腾讯云的小机器上了，顺便折腾了一点点 traefik，但是还很不熟练，不太习惯这一套，一方面是 docker 还不习惯，这也加重了对这套环境的不适应，还是习惯裸机部署，另一方面就是 k8s 了，家里的机器还没虚拟化，没有很好的条件可以做实验，这也是读书打卡的一个没做好的点，整体的学习效果受限于深度和实操，后面是看都是用 traefik，也找到了一篇文章可以 traefik 转发到裸机应用，因为主仓库用的是裸机的 gogs。

还有就是运动减肥上，唉，这又是很大的一个痛点，基本没效果，只是还算稳定，昨天看到一个视频说还需要力量训练来增肌，以此可以提升基础代谢，打算往这个方向尝试下，因为今天没有疫情限制了，在 6 月底完成了 200 公里的跑步小目标，只是有些膝盖跟大腿根外侧不适，抽空得去看下医生，后面打算每天也能做点卷腹跟俯卧撑。

下半年还希望能继续多看看书，比很多网上各种乱七八糟的文章会好很多，结合豆瓣评分，找一些评价高一些的文章，但也不是说分稍低点的就不行，有些也看人是不是适合，一般 6 分以上评价比较多的就可以试试。

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Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

2021 年中总结

发表于 分类于 ， ， 阅读次数： 阅读次数： Disqus：

又到半年总结时，第一次写总结类型的文章感觉挺好写的，但是后面总觉得这过去的一段时间所做的事情，能力上的成长低于预期，但是是需要总结下，找找问题，顺便展望下未来。

这一年做的最让自己满意的应该就是看了一些书，由折腾群洋总发起的读书打卡活动，到目前为止已经读完了这几本书，《cUrl 必知必会》，《古董局中局 1》，《古董局中局 2》，《算法图解》，《每天 5 分钟玩转 Kubernetes》《幸福了吗？》《高可用可伸缩微服务架构：基于 Dubbo、Spring Cloud和 Service Mesh》《Rust 权威指南》后面可以写个专题说说看的这些书，虽然每天打卡如果时间安排不好，并且看的书像 rust 这样比较难的话还是会有点小焦虑，不过也是个调整过程，一方面可以在白天就抽空看一会，然后也不必要每次都看很大一章，注重吸收。

技术上的成长的话，有一些比较小的长进吧，对于一些之前忽视的 synchronized，ThreadLocal 和 AQS 等知识点做了下查漏补缺了，然后多了解了一些 Java 垃圾回收的内容，但是在实操上还是比较欠缺，成型的技术方案，架构上所谓的优化也比较少，一些想法也还有考虑不周全的地方，还需要多花时间和心思去学习加强，特别是在目前已经有的基础上如何做系统深层次的优化，既不要是鸡毛蒜皮的，也不能出现一些不可接受的问题和故障，这是个很重要的课题，需要好好学习，后面考虑定一些周期性目标，两个月左右能有一些成果和总结。

另外一部分是自己的服务，因为 ucloud 的机器太贵就没续费了，所以都迁移到腾讯云的小机器上了，顺便折腾了一点点 traefik，但是还很不熟练，不太习惯这一套，一方面是 docker 还不习惯，这也加重了对这套环境的不适应，还是习惯裸机部署，另一方面就是 k8s 了，家里的机器还没虚拟化，没有很好的条件可以做实验，这也是读书打卡的一个没做好的点，整体的学习效果受限于深度和实操，后面是看都是用 traefik，也找到了一篇文章可以 traefik 转发到裸机应用，因为主仓库用的是裸机的 gogs。

还有就是运动减肥上，唉，这又是很大的一个痛点，基本没效果，只是还算稳定，昨天看到一个视频说还需要力量训练来增肌，以此可以提升基础代谢，打算往这个方向尝试下，因为今天没有疫情限制了，在 6 月底完成了 200 公里的跑步小目标，只是有些膝盖跟大腿根外侧不适，抽空得去看下医生，后面打算每天也能做点卷腹跟俯卧撑。

下半年还希望能继续多看看书，比很多网上各种乱七八糟的文章会好很多，结合豆瓣评分，找一些评价高一些的文章，但也不是说分稍低点的就不行，有些也看人是不是适合，一般 6 分以上评价比较多的就可以试试。

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What hurts more, the pain of hard work or the pain of regret?

《长安的荔枝》读后感

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断断续续地看完了马伯庸老师的《长安的荔枝》，一开始是看这本书在排行榜排得很高，又是马伯庸的，之前看过他的《古董局中局》，还是很有意思的，而且正好是比较短的，不过前后也拖了蛮久才看完，看完后读了下马老师自己写的后记，就特别有感触。
整个故事是围绕一个上林署监事李善德被委任一项给贵妃送荔枝的差事展开，“长安回望绣成堆，山顶千门次第开，一骑红尘妃子笑，无人知是荔枝来”，以前没细究过这个送荔枝的过程，但是以以前的运输速度和保鲜条件，感觉也不是太现实，所以主人公一开始就以为只是像以往一样是送荔枝干这种，能比较方便运输，不容易变质的，结果发现其实是同僚在坑他，这次是要在贵妃生辰的时候给贵妃送来新鲜的岭南荔枝，用比较时兴的词来说，这就是个送命题啊，鲜荔枝一日色变，两日香变，三日味变，同僚的还有杜甫跟韩承，都觉得老李可以直接写休书了，保全家人，不然就是全家送命，李善德也觉得基本算是判刑了，而且其实是这事被转了几次，最后到老李所在的上林署，主管为了骗他接下这个活还特意在文书上把荔枝鲜的“鲜”字贴住，那会叫做“贴黄”，变成了荔枝“煎”，所以说官场险恶，大家都想把这烫手山芋丢出去，结果丢到了我们老实的老李头上，但是从接到这个通知到贵妃的生辰六月初一还有挺长的时间，其实这个活虽然送命，但是在前期这个“荔枝使”也基本就是类似带着尚方宝剑，御赐黄马褂的职位，随便申请经费，不必像常规的部门费用需要定预算，申请后再层层审批，而是特事特批特办的耍赖做法，所以在这段时间是能够潇洒挥霍一下的。其实可以好好地捞一波给妻女，然后写下和离，在自己死后能让她们过的好一些，但最后还是在杜甫的一番劝导下做出了尝试一番的决定，因为也没其他办法，既是退无可退，何不向前拼死一搏，其实说到这，我觉得看这本书感觉有所收获的第一点，有时候总觉得事情没戏了，想躺平放弃了，但是这样其实这个结果是不会变好的，尝试努力，拼尽全力搏一搏，说不定会有所改观，至少不会变更坏了。

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What hurts more, the pain of hard work or the pain of regret?

《长安的荔枝》读后感

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断断续续地看完了马伯庸老师的《长安的荔枝》，一开始是看这本书在排行榜排得很高，又是马伯庸的，之前看过他的《古董局中局》，还是很有意思的，而且正好是比较短的，不过前后也拖了蛮久才看完，看完后读了下马老师自己写的后记，就特别有感触。
整个故事是围绕一个上林署监事李善德被委任一项给贵妃送荔枝的差事展开，“长安回望绣成堆，山顶千门次第开，一骑红尘妃子笑，无人知是荔枝来”，以前没细究过这个送荔枝的过程，但是以以前的运输速度和保鲜条件，感觉也不是太现实，所以主人公一开始就以为只是像以往一样是送荔枝干这种，能比较方便运输，不容易变质的，结果发现其实是同僚在坑他，这次是要在贵妃生辰的时候给贵妃送来新鲜的岭南荔枝，用比较时兴的词来说，这就是个送命题啊，鲜荔枝一日色变，两日香变，三日味变，同僚的还有杜甫跟韩承，都觉得老李可以直接写休书了，保全家人，不然就是全家送命，李善德也觉得基本算是判刑了，而且其实是这事被转了几次，最后到老李所在的上林署，主管为了骗他接下这个活还特意在文书上把荔枝鲜的“鲜”字贴住，那会叫做“贴黄”，变成了荔枝“煎”，所以说官场险恶，大家都想把这烫手山芋丢出去，结果丢到了我们老实的老李头上，但是从接到这个通知到贵妃的生辰六月初一还有挺长的时间，其实这个活虽然送命，但是在前期这个“荔枝使”也基本就是类似带着尚方宝剑，御赐黄马褂的职位，随便申请经费，不必像常规的部门费用需要定预算，申请后再层层审批，而是特事特批特办的耍赖做法，所以在这段时间是能够潇洒挥霍一下的。其实可以好好地捞一波给妻女，然后写下和离，在自己死后能让她们过的好一些，但最后还是在杜甫的一番劝导下做出了尝试一番的决定，因为也没其他办法，既是退无可退，何不向前拼死一搏，其实说到这，我觉得看这本书感觉有所收获的第一点，有时候总觉得事情没戏了，想躺平放弃了，但是这样其实这个结果是不会变好的，尝试努力，拼尽全力搏一搏，说不定会有所改观，至少不会变更坏了。

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Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

用 ollama 本地运行谷歌开源大模型 Gemma

发表于 分类于 阅读次数： 阅读次数： Disqus：

原先在 23 年初的时候调研过一些国产的大模型，包括复旦开源的 MOSS 和清华的 ChatGLM，那时候还是早期版本，需要在 Linux 上，并且有比较好的显卡，而且一般来讲都得是 N 卡，过程中需要安装 pytorch和比较多依赖，并且当时的效果也还比较差，所以后面就没有长期使用。
最近看到谷歌在 2 月份开源了大模型 Gemma ，gemma 的博客在这里，想要在本地运行这个模型在现在这个阶段也变得简单很多，因为我们有了 ollama 工具

可以通过这个工具来运行大模型，并且已经支持了谷歌开源的 Gemma

我这边本地是 MacBook Pro 14 寸的，m3 pro 的处理器，18g 内存，刚好可以用 7b 量化的模型

这里有推荐的模型和内存推荐匹配规则，16g 可以运行 13B 及以下模型
下载安装完后我们可以用以下命令

1
ollama run gemma:7b

这里需要拉取模型，约5.2g 大小，考虑网络原因可能会比较慢

我们可以简单来试试问个问题


看出来回答的还是比较丰富的，谷歌出品还是比较有水平的，不至于像 ChatGLM 最初版本的在不做调优的情况下甚至有点前言不搭后语
对于想使用 chatgpt 但是没条件，这也算是个低配平替了, 并且已经是个比较可用的了，同时也方便进行学习调优等
如果想要类似于 chatgpt 那样的网页版，可以安装 open-webui
可以通过 webui 访问 ollama 运行的大模型，
用 docker 启动的命令也贴一下

1
docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main


这里有一个小区别，Gemma 在多轮会话的时候会在前面的答案基础上再完善。

补充一个在 windows 环境下，cpu 跑模型的也是可行的

现在是大模型可以深入千家万户了，大家都可以尝试下，如果对日常的工作学习有一些效率上的提升也是好的

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Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

用 ollama 本地运行谷歌开源大模型 Gemma

发表于 分类于 阅读次数： 阅读次数： Disqus：

原先在 23 年初的时候调研过一些国产的大模型，包括复旦开源的 MOSS 和清华的 ChatGLM，那时候还是早期版本，需要在 Linux 上，并且有比较好的显卡，而且一般来讲都得是 N 卡，过程中需要安装 pytorch和比较多依赖，并且当时的效果也还比较差，所以后面就没有长期使用。
最近看到谷歌在 2 月份开源了大模型 Gemma ，gemma 的博客在这里，想要在本地运行这个模型在现在这个阶段也变得简单很多，因为我们有了 ollama 工具

可以通过这个工具来运行大模型，并且已经支持了谷歌开源的 Gemma

我这边本地是 MacBook Pro 14 寸的，m3 pro 的处理器，18g 内存，刚好可以用 7b 量化的模型

这里有推荐的模型和内存推荐匹配规则，16g 可以运行 13B 及以下模型
下载安装完后我们可以用以下命令

1
ollama run gemma:7b

这里需要拉取模型，约5.2g 大小，考虑网络原因可能会比较慢

我们可以简单来试试问个问题


看出来回答的还是比较丰富的，谷歌出品还是比较有水平的，不至于像 ChatGLM 最初版本的在不做调优的情况下甚至有点前言不搭后语
对于想使用 chatgpt 但是没条件，这也算是个低配平替了, 并且已经是个比较可用的了，同时也方便进行学习调优等
如果想要类似于 chatgpt 那样的网页版，可以安装 open-webui
可以通过 webui 访问 ollama 运行的大模型，
用 docker 启动的命令也贴一下

1
docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main

不过有个小问题就是 docker 镜像拉取会有点慢，可以添加下国内镜像加速

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{
    "registry-mirrors": [
        "https://dockerproxy.com",
        "https://docker.mirrors.ustc.edu.cn",
        "https://docker.nju.edu.cn"
    ]
}


这里有一个小区别，Gemma 在多轮会话的时候会在前面的答案基础上再完善。

补充一个在 windows 环境下，cpu 跑模型的也是可行的

现在是大模型可以深入千家万户了，大家都可以尝试下，如果对日常的工作学习有一些效率上的提升也是好的

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}分类: gc | Nicksxs's Blog

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What hurts more, the pain of hard work or the pain of regret?

gc 分类

2021
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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}分类: GC | Nicksxs's Blog

Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

GC 分类

2020
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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}分类: java | Nicksxs's Blog

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}分类: Java | Nicksxs's Blog

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}分类: java | Nicksxs's Blog

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}分类: Linked List | Nicksxs's Blog

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What hurts more, the pain of hard work or the pain of regret?

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}分类: linked list | Nicksxs's Blog

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Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

发表于 分类于 阅读次数： Disqus：

原先在 23 年初的时候调研过一些国产的大模型，包括复旦开源的 MOSS 和清华的 ChatGLM，那时候还是早期版本，需要在 Linux 上，并且有比较好的显卡，而且一般来讲都得是 N 卡，过程中需要安装 pytorch和比较多依赖，并且当时的效果也还比较差，所以后面就没有长期使用。
最近看到谷歌在 2 月份开源了大模型 Gemma ，gemma 的博客在这里，想要在本地运行这个模型在现在这个阶段也变得简单很多，因为我们有了 ollama 工具

可以通过这个工具来运行大模型，并且已经支持了谷歌开源的 Gemma

我这边本地是 MacBook Pro 14 寸的，m3 pro 的处理器，18g 内存，刚好可以用 7b 量化的模型

这里有推荐的模型和内存推荐匹配规则，16g 可以运行 13B 及以下模型
下载安装完后我们可以用以下命令

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ollama run gemma:7b

这里需要拉取模型，约5.2g 大小，考虑网络原因可能会比较慢

我们可以简单来试试问个问题


看出来回答的还是比较丰富的，谷歌出品还是比较有水平的，不至于像 ChatGLM 最初版本的在不做调优的情况下甚至有点前言不搭后语
对于想使用 chatgpt 但是没条件，这也算是个低配平替了, 并且已经是个比较可用的了，同时也方便进行学习调优等
如果想要类似于 chatgpt 那样的网页版，可以安装 open-webui
可以通过 webui 访问 ollama 运行的大模型，
用 docker 启动的命令也贴一下

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docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main


这里有一个小区别，Gemma 在多轮会话的时候会在前面的答案基础上再完善。

补充一个在 windows 环境下，cpu 跑模型的也是可行的

现在是大模型可以深入千家万户了，大家都可以尝试下，如果对日常的工作学习有一些效率上的提升也是好的

发表于 分类于 阅读次数： Disqus：

线程池在实际使用过程中，有时候在理解比较偏理论的时候会出现一些判断错误，这里我们就来看一个实际的案例

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private static final ThreadPoolExecutor threadPoolExecutor =
            new ThreadPoolExecutor(1, 1,
                    0, TimeUnit.MINUTES,
                    new MyArrayBlockingQueue<>(2));
    public static void main(String[] args) throws InterruptedException {
        for (int i = 0; i < 100; i++) {
            Thread.sleep(100);
            for (int j = 0; j < 3; j++) {
                threadPoolExecutor.execute(() -> {
                    int a = 0;
                });
            }
            System.out.println("===============>  详情任务 - 任务处理完成");
        }
        System.out.println("都执行完成了");
    }

MyArrayBlockingQueue 是我复制的 ArrayBlockingQueue 加了点日志，可以认为就是一样的，这种情况下
执行过程是怎么样的呢， 队列长度是 2，核心线程数和最大线程数都是 1，提交任务是采用了两层循环，内层是循环三次，往线程池里提交任务，然后内层循环完了以后会重新睡眠 100 毫秒
在进入下一次外层循环，如果能一眼看出来问题的说明对线程池了解得很深入了，如果没有的话我们就一起来看下
先说下结论，这个代码会出现拒绝异常

考虑下是什么原因呢，是不是我线程数太少了，放大一些，感觉符合直觉一点
修改成

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private static final ThreadPoolExecutor threadPoolExecutor =
            new ThreadPoolExecutor(100, 100,
                    0, TimeUnit.MINUTES,
                    new MyArrayBlockingQueue<>(2));

然而还是一样

只不过晚了点出现，那么问题出在哪呢
为什么我要去重写这个 MyArrayBlockingQueue，就是为了找到原因，其实很多讲解线程池的都是讲了线程池的参数，什么队列是链表的，数组的
但是没有讲到我是怎么往队列塞任务，怎么从队列取任务的呢

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public boolean offer(E e) {
           checkNotNull(e);
           final ReentrantLock lock = this.lock;
           lock.lock();
           try {
               if (count == items.length) {
                   return false;
               }
               else {
                   enqueue(e);
                   return true;
               }
           } finally {
               lock.unlock();
           }
       }

这里是往队列里塞任务，注意这里需要获得锁，
而对于获取任务呢

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public E take() throws InterruptedException {
    final ReentrantLock lock = this.lock;
    lock.lockInterruptibly();
    try {
        while (count == 0)
            notEmpty.await();
        return dequeue();
    } finally {
        lock.unlock();
    }
}

注意这里也需要获得锁，当我一个线程池的线程数进入稳定状态，也就是保持一定数量的线程不变的情况下
上面是一种比较可能的情况，即核心线程数等于最大线程数，那么我在提交任务的时候是非常快的

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if (command == null)
           throw new NullPointerException();
       /*
        * Proceed in 3 steps:
        *
        * 1. If fewer than corePoolSize threads are running, try to
        * start a new thread with the given command as its first
        * task.  The call to addWorker atomically checks runState and
        * workerCount, and so prevents false alarms that would add
        * threads when it shouldn't, by returning false.
        *
        * 2. If a task can be successfully queued, then we still need
        * to double-check whether we should have added a thread
        * (because existing ones died since last checking) or that
        * the pool shut down since entry into this method. So we
        * recheck state and if necessary roll back the enqueuing if
        * stopped, or start a new thread if there are none.
        *
        * 3. If we cannot queue task, then we try to add a new
        * thread.  If it fails, we know we are shut down or saturated
        * and so reject the task.
        */
       int c = ctl.get();
       if (workerCountOf(c) < corePoolSize) {
           if (addWorker(command, true))
               return;
           c = ctl.get();
       }
       if (isRunning(c) && workQueue.offer(command)) {
           int recheck = ctl.get();
           if (! isRunning(recheck) && remove(command))
               reject(command);
           else if (workerCountOf(recheck) == 0)
               addWorker(null, false);
       }
       else if (!addWorker(command, false))
           reject(command);
   }

再来看下这段代码，第一步只需要判断是否为空，第二步就是判断核心线程数量，明显我说的情况，前面两步就直接过去了
然后就是判断线程池运行状态和往队列里塞任务了，但是线程运行完一个任务主动从队列里获取则需要更多的逻辑
这样就造成了我往队列里塞任务会比获取任务快很多，队列一满，就会抛出拒绝异常
即使我把线程数量放大到 100 还是一样，只不过会出现的慢一点，那么口说无凭，我们来验证下，提交任务过快，那么我在提交
方法里做个延迟

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public boolean offer(E e) {
    checkNotNull(e);
    final ReentrantLock lock = this.lock;
    lock.lock();
    try {
        if (count == items.length) {
            return false;
        }
        else {
            enqueue(e);
            return true;
        }
    } finally {
        lock.unlock();
        try {
            Thread.sleep(1000);
        } catch (InterruptedException ex) {
            throw new RuntimeException(ex);
        }
    }
}

这样就没啥问题了

除了最后这个加延时，其他的直接用 ArrayBlockingQueue 就可以实验，实操一下会对这个逻辑有更深的理解

发表于 分类于 阅读次数： Disqus：

https 和 tls

https 我原本的理解来自于几个概念

第一个是非对称加密

也就是公钥可以公开在网上，然后用公钥加密，由私有的私钥进行解密，然后就对 https 有了初步的偏颇的概念，就是浏览器用公钥进行加密，服务器端用私钥进行解密，这里再仔细想想会延伸出来几个问题，也是逐步完善我的后续理解

第二个就是非对称加密以后的对称加密

因为对加密的理解是超大的质数（这个还来源于大学的数据结构老师）相乘后会很难做质因数分解，比如最大的质数2^82,589,933 − 1，用十进制表示有24,862,048位，用现在计算机来算也是非常难的，那如果一直采用非对称加密，这个效率也会比较低，所以在网上查了一番之后知道了是先采用非对称加密，然后再用对称加密，因为非对称加密先有了安全保证，后续的消息就可以用对称加密的方式来进行传输安全了

第三个是最近一次看到的

也是一直缺乏思考的问题，因为 https 我们在使用的时候都会购买证书或者使用免费的证书，那这个证书和前面说的公私钥是什么关系，好像一直是悬空的，没想过这中间的相关性，证书究竟是怎么起作用的

下面是摘自 cloudflare 的 tls 握手流程，把证书的使用方式说的比较明白了

TLS 握手是由客户端和服务器交换的一系列数据报或消息。TLS 握手涉及多个步骤，因为客户端和服务器要交换完成握手和进行进一步对话所需的信息。

TLS 握手中的确切步骤将根据所使用的密钥交换算法的种类和双方支持的密码套件而有所不同。RSA 密钥交换算法虽然现在被认为不安全，但曾在 1.3 之前的 TLS 版本中使用。大致如下：

  1. “客户端问候（client hello）” 消息： 客户端通过向服务器发送“问候”消息来开始握手。该消息将包含客户端支持的 TLS 版本，支持的密码套件，以及称为一串称为“客户端随机数（client random）”的随机字节。
  2. “服务器问候（server hello）”消息： 作为对 client hello 消息的回复，服务器发送一条消息，内含服务器的 SSL 证书、服务器选择的密码套件，以及“服务器随机数（server random）”，即由服务器生成的另一串随机字节。
  3. 身份验证： 客户端使用颁发该证书的证书颁发机构验证服务器的 SSL 证书。此举确认服务器是其声称的身份，且客户端正在与该域的实际所有者进行交互。
  4. 预主密钥： 客户端再发送一串随机字节，即“预主密钥（premaster secret）”。预主密钥是使用公钥加密的，只能使用服务器的私钥解密。（客户端从服务器的 SSL 证书中获得公钥。）
  5. 私钥被使用：服务器对预主密钥进行解密。
  6. 生成会话密钥：客户端和服务器均使用客户端随机数、服务器随机数和预主密钥生成会话密钥。双方应得到相同的结果。
  7. 客户端就绪：客户端发送一条“已完成”消息，该消息用会话密钥加密。
  8. 服务器就绪：服务器发送一条“已完成”消息，该消息用会话密钥加密。
  9. 实现安全对称加密：已完成握手，并使用会话密钥继续进行通信。

为了学习这个过程，我们尝试用 Chrome 的自带抓包工具，以往这是可以通过在 Chrome 地址栏中输入 chrome://net-internals/#events 来打开，现在变成了两部分，chrome://net-export/ 这里可以开始抓包，然后会记录下一个抓包日志文件里，

然后再打开

https://netlog-viewer.appspot.com/#events 来查看具体的日志

这里我们以打开百度为例，即在打开 chrome://net-export/ 并启动抓包后，再在一个新 tab 打开 baidu.com，然后关闭

将日志文件在 https://netlog-viewer.appspot.com/#events 打开

这里可以看到

--> type 1 表示现在 tls 握手进行到哪一步了, 对应的值表示不同的阶段
代码(type)释义
0HelloRequest
1ClientHello
2ServerHello
11Certificate
12ServerKeyExchange
13CertificateRequest
14ServerHelloDone
15CertificateVerify
16ClientKeyExchange
20Finished

具体的对应关系是在这边

比如 11 之后表示我们从服务端收到了证书

然后就要去验证证书的可靠性

后面是验证后的结果

最后就是交换对称会话秘钥然后完成握手

发表于 分类于 阅读次数： Disqus：

这一篇主要补充两个内容，第一部分就是获取任务的逻辑
首先是状态判断，如果是停止了，SHUTDOWN或更大的了，就需要减小工作线程数量
并返回 null，使得工作线程 worker 退出，然后再判断线程数量和超时，同样如果超过了就会返回 null
然后就是去阻塞队列里获取任务，这里是阻塞着获取的

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private Runnable getTask() {
        boolean timedOut = false; // Did the last poll() time out?

        for (;;) {
            int c = ctl.get();
            int rs = runStateOf(c);

            // Check if queue empty only if necessary.
            // 状态异常，如果是大于等于 SHUTDOWN 的，则协助关闭线程池
            if (rs >= SHUTDOWN && (rs >= STOP || workQueue.isEmpty())) {
                decrementWorkerCount();
                return null;
            }

            int wc = workerCountOf(c);

            // Are workers subject to culling?
            boolean timed = allowCoreThreadTimeOut || wc > corePoolSize;

            // 如果线程数量超过核心线程数，则帮助减少线程
            if ((wc > maximumPoolSize || (timed && timedOut))
                && (wc > 1 || workQueue.isEmpty())) {
                if (compareAndDecrementWorkerCount(c))
                    return null;
                continue;
            }

            // 如果前面的不符合，则从阻塞队列获取任务
            try {
                Runnable r = timed ?
                    workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
                    workQueue.take();
                if (r != null)
                    return r;
                timedOut = true;
            } catch (InterruptedException retry) {
                timedOut = false;
            }
        }
    }

阻塞队列的 poll 主要是通过锁，和notEmpty这个 condition 来等待制定的时间
指定时间后开始 dequeue 出队

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public E poll(long timeout, TimeUnit unit) throws InterruptedException {
    long nanos = unit.toNanos(timeout);
    final ReentrantLock lock = this.lock;
    lock.lockInterruptibly();
    try {
        while (count == 0) {
            if (nanos <= 0)
                return null;
            nanos = notEmpty.awaitNanos(nanos);
        }
        return dequeue();
    } finally {
        lock.unlock();
    }
}

第二部分比较重要，有的同学的问题是为什么不一开始开到最大线程，而是达到核心线程数后就进队列了，
其实池化技术最简单的原因就是希望能够复用这些线程，因为创建销毁他们的成本太大了，如果直接最大线程数的话
其实都不用用到线程池技术了，直接有多少任务就开多少线程，用完就丢了，阐述下我认为比较重要的概念点

发表于 分类于 阅读次数： Disqus：

第三篇我们要来讲下 Worker 这个“打工人”，线程池里实际在干活的同学
Worker 实现了 Runnable 接口，所以在前面介绍的 addWorker 中
线程启动其实就调用了下面的 run 方法，而 run 方法则调用了内部的
runWorker 方法

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private final class Worker
    extends AbstractQueuedSynchronizer
    implements Runnable
{
    /**
     * This class will never be serialized, but we provide a
     * serialVersionUID to suppress a javac warning.
     */
    private static final long serialVersionUID = 6138294804551838833L;

    /** Thread this worker is running in.  Null if factory fails. */
    final Thread thread;
    /** Initial task to run.  Possibly null. */
    Runnable firstTask;
    /** Per-thread task counter */
    volatile long completedTasks;

    /**
     * Creates with given first task and thread from ThreadFactory.
     * @param firstTask the first task (null if none)
     */
    Worker(Runnable firstTask) {
        setState(-1); // inhibit interrupts until runWorker
        this.firstTask = firstTask;
        this.thread = getThreadFactory().newThread(this);
    }

    /** Delegates main run loop to outer runWorker  */
    // 启动线程 Worker
    public void run() {
        runWorker(this);
    }

介绍下这个 runWorker 方法
这里就会先处理 firstTask，如果 firstTask 是 null 则会去队列里取
里面会有两个钩子，一个是执行前，一个是执行后，注意这个循环是没有常规
退出逻辑的，说明是一直在往队列里获取，除非获取队列里的任务超时失败了
这样就到最后会去执行 processWorkerExit

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final void runWorker(Worker w) {
        Thread wt = Thread.currentThread();
        Runnable task = w.firstTask;
        w.firstTask = null;
        w.unlock(); // allow interrupts
        boolean completedAbruptly = true;
        try {
            // firstTask 不为空或者从队列里获取到任务
            while (task != null || (task = getTask()) != null) {
                w.lock();
                // If pool is stopping, ensure thread is interrupted;
                // if not, ensure thread is not interrupted.  This
                // requires a recheck in second case to deal with
                // shutdownNow race while clearing interrupt
                if ((runStateAtLeast(ctl.get(), STOP) ||
                     (Thread.interrupted() &&
                      runStateAtLeast(ctl.get(), STOP))) &&
                    !wt.isInterrupted())
                    wt.interrupt();
                try {
                    // 前置执行钩子
                    beforeExecute(wt, task);
                    Throwable thrown = null;
                    try {
                        // 任务执行
                        task.run();
                    } catch (RuntimeException x) {
                        thrown = x; throw x;
                    } catch (Error x) {
                        thrown = x; throw x;
                    } catch (Throwable x) {
                        thrown = x; throw new Error(x);
                    } finally {
                        // 执行完后的钩子
                        afterExecute(task, thrown);
                    }
                } finally {
                    // 最后会执行到这，清空任务
                    task = null;
                    w.completedTasks++;
                    w.unlock();
                }
            }
            completedAbruptly = false;
        } finally {
            // 循环的最后就会去退出Worker
            processWorkerExit(w, completedAbruptly);
        }
    }

而这个 processWorkerExit 也有个比较特殊的逻辑
照理我们会想到这里可能就是线程在处理完队列里的任务
以后，就会判断下是否要退出，如果是核心线程的话就不用
如果是非核心线程就会退出了，但是这里其实有个替换逻辑
就是最后有个 addWorker 调用

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private void processWorkerExit(Worker w, boolean completedAbruptly) {
    if (completedAbruptly) // If abrupt, then workerCount wasn't adjusted
        decrementWorkerCount();

    final ReentrantLock mainLock = this.mainLock;
    mainLock.lock();
    try {
        completedTaskCount += w.completedTasks;
        workers.remove(w);
    } finally {
        mainLock.unlock();
    }

    tryTerminate();

    int c = ctl.get();
    // 判断状态
    if (runStateLessThan(c, STOP)) {
        if (!completedAbruptly) {
            // 核心线程是否也需要退出
            int min = allowCoreThreadTimeOut ? 0 : corePoolSize;
            if (min == 0 && ! workQueue.isEmpty())
                min = 1;
            // 这里代表非核心线程就可以不用替换，也就是回收线程了
            if (workerCountOf(c) >= min)
                return; // replacement not needed
        }
        // 否则是替换线程
        addWorker(null, false);
    }
}

这里主要讲了线程 Worker 运行的逻辑

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Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

发表于 分类于 阅读次数： Disqus：

原先在 23 年初的时候调研过一些国产的大模型，包括复旦开源的 MOSS 和清华的 ChatGLM，那时候还是早期版本，需要在 Linux 上，并且有比较好的显卡，而且一般来讲都得是 N 卡，过程中需要安装 pytorch和比较多依赖，并且当时的效果也还比较差，所以后面就没有长期使用。
最近看到谷歌在 2 月份开源了大模型 Gemma ，gemma 的博客在这里，想要在本地运行这个模型在现在这个阶段也变得简单很多，因为我们有了 ollama 工具

可以通过这个工具来运行大模型，并且已经支持了谷歌开源的 Gemma

我这边本地是 MacBook Pro 14 寸的，m3 pro 的处理器，18g 内存，刚好可以用 7b 量化的模型

这里有推荐的模型和内存推荐匹配规则，16g 可以运行 13B 及以下模型
下载安装完后我们可以用以下命令

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ollama run gemma:7b

这里需要拉取模型，约5.2g 大小，考虑网络原因可能会比较慢

我们可以简单来试试问个问题


看出来回答的还是比较丰富的，谷歌出品还是比较有水平的，不至于像 ChatGLM 最初版本的在不做调优的情况下甚至有点前言不搭后语
对于想使用 chatgpt 但是没条件，这也算是个低配平替了, 并且已经是个比较可用的了，同时也方便进行学习调优等
如果想要类似于 chatgpt 那样的网页版，可以安装 open-webui
可以通过 webui 访问 ollama 运行的大模型，
用 docker 启动的命令也贴一下

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docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main

不过有个小问题就是 docker 镜像拉取会有点慢，可以添加下国内镜像加速

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{
    "registry-mirrors": [
        "https://dockerproxy.com",
        "https://docker.mirrors.ustc.edu.cn",
        "https://docker.nju.edu.cn"
    ]
}


这里有一个小区别，Gemma 在多轮会话的时候会在前面的答案基础上再完善。

补充一个在 windows 环境下，cpu 跑模型的也是可行的

现在是大模型可以深入千家万户了，大家都可以尝试下，如果对日常的工作学习有一些效率上的提升也是好的

发表于 分类于 阅读次数： Disqus：

线程池在实际使用过程中，有时候在理解比较偏理论的时候会出现一些判断错误，这里我们就来看一个实际的案例

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private static final ThreadPoolExecutor threadPoolExecutor =
            new ThreadPoolExecutor(1, 1,
                    0, TimeUnit.MINUTES,
                    new MyArrayBlockingQueue<>(2));
    public static void main(String[] args) throws InterruptedException {
        for (int i = 0; i < 100; i++) {
            Thread.sleep(100);
            for (int j = 0; j < 3; j++) {
                threadPoolExecutor.execute(() -> {
                    int a = 0;
                });
            }
            System.out.println("===============>  详情任务 - 任务处理完成");
        }
        System.out.println("都执行完成了");
    }

MyArrayBlockingQueue 是我复制的 ArrayBlockingQueue 加了点日志，可以认为就是一样的，这种情况下
执行过程是怎么样的呢， 队列长度是 2，核心线程数和最大线程数都是 1，提交任务是采用了两层循环，内层是循环三次，往线程池里提交任务，然后内层循环完了以后会重新睡眠 100 毫秒
在进入下一次外层循环，如果能一眼看出来问题的说明对线程池了解得很深入了，如果没有的话我们就一起来看下
先说下结论，这个代码会出现拒绝异常

考虑下是什么原因呢，是不是我线程数太少了，放大一些，感觉符合直觉一点
修改成

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private static final ThreadPoolExecutor threadPoolExecutor =
            new ThreadPoolExecutor(100, 100,
                    0, TimeUnit.MINUTES,
                    new MyArrayBlockingQueue<>(2));

然而还是一样

只不过晚了点出现，那么问题出在哪呢
为什么我要去重写这个 MyArrayBlockingQueue，就是为了找到原因，其实很多讲解线程池的都是讲了线程池的参数，什么队列是链表的，数组的
但是没有讲到我是怎么往队列塞任务，怎么从队列取任务的呢

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public boolean offer(E e) {
           checkNotNull(e);
           final ReentrantLock lock = this.lock;
           lock.lock();
           try {
               if (count == items.length) {
                   return false;
               }
               else {
                   enqueue(e);
                   return true;
               }
           } finally {
               lock.unlock();
           }
       }

这里是往队列里塞任务，注意这里需要获得锁，
而对于获取任务呢

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public E take() throws InterruptedException {
    final ReentrantLock lock = this.lock;
    lock.lockInterruptibly();
    try {
        while (count == 0)
            notEmpty.await();
        return dequeue();
    } finally {
        lock.unlock();
    }
}

注意这里也需要获得锁，当我一个线程池的线程数进入稳定状态，也就是保持一定数量的线程不变的情况下
上面是一种比较可能的情况，即核心线程数等于最大线程数，那么我在提交任务的时候是非常快的

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if (command == null)
           throw new NullPointerException();
       /*
        * Proceed in 3 steps:
        *
        * 1. If fewer than corePoolSize threads are running, try to
        * start a new thread with the given command as its first
        * task.  The call to addWorker atomically checks runState and
        * workerCount, and so prevents false alarms that would add
        * threads when it shouldn't, by returning false.
        *
        * 2. If a task can be successfully queued, then we still need
        * to double-check whether we should have added a thread
        * (because existing ones died since last checking) or that
        * the pool shut down since entry into this method. So we
        * recheck state and if necessary roll back the enqueuing if
        * stopped, or start a new thread if there are none.
        *
        * 3. If we cannot queue task, then we try to add a new
        * thread.  If it fails, we know we are shut down or saturated
        * and so reject the task.
        */
       int c = ctl.get();
       if (workerCountOf(c) < corePoolSize) {
           if (addWorker(command, true))
               return;
           c = ctl.get();
       }
       if (isRunning(c) && workQueue.offer(command)) {
           int recheck = ctl.get();
           if (! isRunning(recheck) && remove(command))
               reject(command);
           else if (workerCountOf(recheck) == 0)
               addWorker(null, false);
       }
       else if (!addWorker(command, false))
           reject(command);
   }

再来看下这段代码，第一步只需要判断是否为空，第二步就是判断核心线程数量，明显我说的情况，前面两步就直接过去了
然后就是判断线程池运行状态和往队列里塞任务了，但是线程运行完一个任务主动从队列里获取则需要更多的逻辑
这样就造成了我往队列里塞任务会比获取任务快很多，队列一满，就会抛出拒绝异常
即使我把线程数量放大到 100 还是一样，只不过会出现的慢一点，那么口说无凭，我们来验证下，提交任务过快，那么我在提交
方法里做个延迟

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public boolean offer(E e) {
    checkNotNull(e);
    final ReentrantLock lock = this.lock;
    lock.lock();
    try {
        if (count == items.length) {
            return false;
        }
        else {
            enqueue(e);
            return true;
        }
    } finally {
        lock.unlock();
        try {
            Thread.sleep(1000);
        } catch (InterruptedException ex) {
            throw new RuntimeException(ex);
        }
    }
}

这样就没啥问题了

除了最后这个加延时，其他的直接用 ArrayBlockingQueue 就可以实验，实操一下会对这个逻辑有更深的理解

发表于 分类于 阅读次数： Disqus：

https 和 tls

https 我原本的理解来自于几个概念

第一个是非对称加密

也就是公钥可以公开在网上，然后用公钥加密，由私有的私钥进行解密，然后就对 https 有了初步的偏颇的概念，就是浏览器用公钥进行加密，服务器端用私钥进行解密，这里再仔细想想会延伸出来几个问题，也是逐步完善我的后续理解

第二个就是非对称加密以后的对称加密

因为对加密的理解是超大的质数（这个还来源于大学的数据结构老师）相乘后会很难做质因数分解，比如最大的质数2^82,589,933 − 1，用十进制表示有24,862,048位，用现在计算机来算也是非常难的，那如果一直采用非对称加密，这个效率也会比较低，所以在网上查了一番之后知道了是先采用非对称加密，然后再用对称加密，因为非对称加密先有了安全保证，后续的消息就可以用对称加密的方式来进行传输安全了

第三个是最近一次看到的

也是一直缺乏思考的问题，因为 https 我们在使用的时候都会购买证书或者使用免费的证书，那这个证书和前面说的公私钥是什么关系，好像一直是悬空的，没想过这中间的相关性，证书究竟是怎么起作用的

下面是摘自 cloudflare 的 tls 握手流程，把证书的使用方式说的比较明白了

TLS 握手是由客户端和服务器交换的一系列数据报或消息。TLS 握手涉及多个步骤，因为客户端和服务器要交换完成握手和进行进一步对话所需的信息。

TLS 握手中的确切步骤将根据所使用的密钥交换算法的种类和双方支持的密码套件而有所不同。RSA 密钥交换算法虽然现在被认为不安全，但曾在 1.3 之前的 TLS 版本中使用。大致如下：

  1. “客户端问候（client hello）” 消息： 客户端通过向服务器发送“问候”消息来开始握手。该消息将包含客户端支持的 TLS 版本，支持的密码套件，以及称为一串称为“客户端随机数（client random）”的随机字节。
  2. “服务器问候（server hello）”消息： 作为对 client hello 消息的回复，服务器发送一条消息，内含服务器的 SSL 证书、服务器选择的密码套件，以及“服务器随机数（server random）”，即由服务器生成的另一串随机字节。
  3. 身份验证： 客户端使用颁发该证书的证书颁发机构验证服务器的 SSL 证书。此举确认服务器是其声称的身份，且客户端正在与该域的实际所有者进行交互。
  4. 预主密钥： 客户端再发送一串随机字节，即“预主密钥（premaster secret）”。预主密钥是使用公钥加密的，只能使用服务器的私钥解密。（客户端从服务器的 SSL 证书中获得公钥。）
  5. 私钥被使用：服务器对预主密钥进行解密。
  6. 生成会话密钥：客户端和服务器均使用客户端随机数、服务器随机数和预主密钥生成会话密钥。双方应得到相同的结果。
  7. 客户端就绪：客户端发送一条“已完成”消息，该消息用会话密钥加密。
  8. 服务器就绪：服务器发送一条“已完成”消息，该消息用会话密钥加密。
  9. 实现安全对称加密：已完成握手，并使用会话密钥继续进行通信。

为了学习这个过程，我们尝试用 Chrome 的自带抓包工具，以往这是可以通过在 Chrome 地址栏中输入 chrome://net-internals/#events 来打开，现在变成了两部分，chrome://net-export/ 这里可以开始抓包，然后会记录下一个抓包日志文件里，

然后再打开

https://netlog-viewer.appspot.com/#events 来查看具体的日志

这里我们以打开百度为例，即在打开 chrome://net-export/ 并启动抓包后，再在一个新 tab 打开 baidu.com，然后关闭

将日志文件在 https://netlog-viewer.appspot.com/#events 打开

这里可以看到

--> type 1 表示现在 tls 握手进行到哪一步了, 对应的值表示不同的阶段
代码(type)释义
0HelloRequest
1ClientHello
2ServerHello
11Certificate
12ServerKeyExchange
13CertificateRequest
14ServerHelloDone
15CertificateVerify
16ClientKeyExchange
20Finished

具体的对应关系是在这边

比如 11 之后表示我们从服务端收到了证书

然后就要去验证证书的可靠性

后面是验证后的结果

最后就是交换对称会话秘钥然后完成握手

发表于 分类于 阅读次数： Disqus：

这一篇主要补充两个内容，第一部分就是获取任务的逻辑
首先是状态判断，如果是停止了，SHUTDOWN或更大的了，就需要减小工作线程数量
并返回 null，使得工作线程 worker 退出，然后再判断线程数量和超时，同样如果超过了就会返回 null
然后就是去阻塞队列里获取任务，这里是阻塞着获取的

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private Runnable getTask() {
        boolean timedOut = false; // Did the last poll() time out?

        for (;;) {
            int c = ctl.get();
            int rs = runStateOf(c);

            // Check if queue empty only if necessary.
            // 状态异常，如果是大于等于 SHUTDOWN 的，则协助关闭线程池
            if (rs >= SHUTDOWN && (rs >= STOP || workQueue.isEmpty())) {
                decrementWorkerCount();
                return null;
            }

            int wc = workerCountOf(c);

            // Are workers subject to culling?
            boolean timed = allowCoreThreadTimeOut || wc > corePoolSize;

            // 如果线程数量超过核心线程数，则帮助减少线程
            if ((wc > maximumPoolSize || (timed && timedOut))
                && (wc > 1 || workQueue.isEmpty())) {
                if (compareAndDecrementWorkerCount(c))
                    return null;
                continue;
            }

            // 如果前面的不符合，则从阻塞队列获取任务
            try {
                Runnable r = timed ?
                    workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
                    workQueue.take();
                if (r != null)
                    return r;
                timedOut = true;
            } catch (InterruptedException retry) {
                timedOut = false;
            }
        }
    }

阻塞队列的 poll 主要是通过锁，和notEmpty这个 condition 来等待制定的时间
指定时间后开始 dequeue 出队

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public E poll(long timeout, TimeUnit unit) throws InterruptedException {
    long nanos = unit.toNanos(timeout);
    final ReentrantLock lock = this.lock;
    lock.lockInterruptibly();
    try {
        while (count == 0) {
            if (nanos <= 0)
                return null;
            nanos = notEmpty.awaitNanos(nanos);
        }
        return dequeue();
    } finally {
        lock.unlock();
    }
}

第二部分比较重要，有的同学的问题是为什么不一开始开到最大线程，而是达到核心线程数后就进队列了，
其实池化技术最简单的原因就是希望能够复用这些线程，因为创建销毁他们的成本太大了，如果直接最大线程数的话
其实都不用用到线程池技术了，直接有多少任务就开多少线程，用完就丢了，阐述下我认为比较重要的概念点

发表于 分类于 阅读次数： Disqus：

第三篇我们要来讲下 Worker 这个“打工人”，线程池里实际在干活的同学
Worker 实现了 Runnable 接口，所以在前面介绍的 addWorker 中
线程启动其实就调用了下面的 run 方法，而 run 方法则调用了内部的
runWorker 方法

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private final class Worker
    extends AbstractQueuedSynchronizer
    implements Runnable
{
    /**
     * This class will never be serialized, but we provide a
     * serialVersionUID to suppress a javac warning.
     */
    private static final long serialVersionUID = 6138294804551838833L;

    /** Thread this worker is running in.  Null if factory fails. */
    final Thread thread;
    /** Initial task to run.  Possibly null. */
    Runnable firstTask;
    /** Per-thread task counter */
    volatile long completedTasks;

    /**
     * Creates with given first task and thread from ThreadFactory.
     * @param firstTask the first task (null if none)
     */
    Worker(Runnable firstTask) {
        setState(-1); // inhibit interrupts until runWorker
        this.firstTask = firstTask;
        this.thread = getThreadFactory().newThread(this);
    }

    /** Delegates main run loop to outer runWorker  */
    // 启动线程 Worker
    public void run() {
        runWorker(this);
    }

介绍下这个 runWorker 方法
这里就会先处理 firstTask，如果 firstTask 是 null 则会去队列里取
里面会有两个钩子，一个是执行前，一个是执行后，注意这个循环是没有常规
退出逻辑的，说明是一直在往队列里获取，除非获取队列里的任务超时失败了
这样就到最后会去执行 processWorkerExit

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final void runWorker(Worker w) {
        Thread wt = Thread.currentThread();
        Runnable task = w.firstTask;
        w.firstTask = null;
        w.unlock(); // allow interrupts
        boolean completedAbruptly = true;
        try {
            // firstTask 不为空或者从队列里获取到任务
            while (task != null || (task = getTask()) != null) {
                w.lock();
                // If pool is stopping, ensure thread is interrupted;
                // if not, ensure thread is not interrupted.  This
                // requires a recheck in second case to deal with
                // shutdownNow race while clearing interrupt
                if ((runStateAtLeast(ctl.get(), STOP) ||
                     (Thread.interrupted() &&
                      runStateAtLeast(ctl.get(), STOP))) &&
                    !wt.isInterrupted())
                    wt.interrupt();
                try {
                    // 前置执行钩子
                    beforeExecute(wt, task);
                    Throwable thrown = null;
                    try {
                        // 任务执行
                        task.run();
                    } catch (RuntimeException x) {
                        thrown = x; throw x;
                    } catch (Error x) {
                        thrown = x; throw x;
                    } catch (Throwable x) {
                        thrown = x; throw new Error(x);
                    } finally {
                        // 执行完后的钩子
                        afterExecute(task, thrown);
                    }
                } finally {
                    // 最后会执行到这，清空任务
                    task = null;
                    w.completedTasks++;
                    w.unlock();
                }
            }
            completedAbruptly = false;
        } finally {
            // 循环的最后就会去退出Worker
            processWorkerExit(w, completedAbruptly);
        }
    }

而这个 processWorkerExit 也有个比较特殊的逻辑
照理我们会想到这里可能就是线程在处理完队列里的任务
以后，就会判断下是否要退出，如果是核心线程的话就不用
如果是非核心线程就会退出了，但是这里其实有个替换逻辑
就是最后有个 addWorker 调用

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private void processWorkerExit(Worker w, boolean completedAbruptly) {
    if (completedAbruptly) // If abrupt, then workerCount wasn't adjusted
        decrementWorkerCount();

    final ReentrantLock mainLock = this.mainLock;
    mainLock.lock();
    try {
        completedTaskCount += w.completedTasks;
        workers.remove(w);
    } finally {
        mainLock.unlock();
    }

    tryTerminate();

    int c = ctl.get();
    // 判断状态
    if (runStateLessThan(c, STOP)) {
        if (!completedAbruptly) {
            // 核心线程是否也需要退出
            int min = allowCoreThreadTimeOut ? 0 : corePoolSize;
            if (min == 0 && ! workQueue.isEmpty())
                min = 1;
            // 这里代表非核心线程就可以不用替换，也就是回收线程了
            if (workerCountOf(c) >= min)
                return; // replacement not needed
        }
        // 否则是替换线程
        addWorker(null, false);
    }
}

这里主要讲了线程 Worker 运行的逻辑

0%
\ No newline at end of file diff --git a/leancloud.memo b/leancloud.memo index d876b23aa5..0c93a7bf81 100644 --- a/leancloud.memo +++ b/leancloud.memo @@ -262,4 +262,5 @@ {"title":"Java 线程池系列-第四篇","url":"/2024/03/03/Java-线程池系列-第四篇/"}, {"title":"聊一聊 https 的逻辑","url":"/2024/03/10/聊一聊-https-的逻辑/"}, {"title":"Java 线程池系列-实战篇","url":"/2024/03/17/Java-线程池系列-实战篇/"}, +{"title":"用 ollama 本地运行谷歌开源大模型 Gemma","url":"/2024/03/24/用-ollama-本地运行大模型/"}, ] \ No newline at end of file diff --git a/leancloud_counter_security_urls.json b/leancloud_counter_security_urls.json index 5c778f725d..6721dbb3f6 100644 --- a/leancloud_counter_security_urls.json +++ b/leancloud_counter_security_urls.json @@ -1 +1 @@ -[{"title":"2019年终总结","url":"/2020/02/01/2019年终总结/"},{"title":"村上春树《1Q84》读后感","url":"/2019/12/18/1Q84读后感/"},{"title":"2020年中总结","url":"/2020/07/11/2020年中总结/"},{"title":"2020 年终总结","url":"/2021/03/31/2020-年终总结/"},{"title":"2021 年中总结","url":"/2021/07/18/2021-年中总结/"},{"title":"2021 年终总结","url":"/2022/01/22/2021-年终总结/"},{"title":"34_Search_for_a_Range","url":"/2016/08/14/34-Search-for-a-Range/"},{"title":"AbstractQueuedSynchronizer","url":"/2019/09/23/AbstractQueuedSynchronizer/"},{"title":"AQS篇二 之 Condition 浅析笔记","url":"/2021/02/21/AQS-之-Condition-浅析笔记/"},{"title":"add-two-number","url":"/2015/04/14/Add-Two-Number/"},{"title":"Apollo 客户端启动过程分析","url":"/2022/09/18/Apollo-客户端启动过程分析/"},{"title":"2022 年终总结","url":"/2023/01/15/2022-年终总结/"},{"title":"Clone Graph Part I","url":"/2014/12/30/Clone-Graph-Part-I/"},{"title":"Comparator使用小记","url":"/2020/04/05/Comparator使用小记/"},{"title":"Apollo 的 value 注解是怎么自动更新的","url":"/2020/11/01/Apollo-的-value-注解是怎么自动更新的/"},{"title":"Disruptor 系列二","url":"/2022/02/27/Disruptor-系列二/"},{"title":"Apollo 如何获取当前环境","url":"/2022/09/04/Apollo-如何获取当前环境/"},{"title":"Dubbo 使用的几个记忆点","url":"/2022/04/02/Dubbo-使用的几个记忆点/"},{"title":"Filter, Interceptor, Aop, 啥, 啥, 啥? 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Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

发表于 分类于 ， 阅读次数： Disqus：

这几天去了趟厦门，原来几年前就想去了，本来都请好假了，后面因为一些事情没去成，这次刚好公司组织，就跟 LD 一起去了厦门，也不洋洋洒洒地写游记了，后面可能会有，今天先来总结下好的地方和比较坑的地方。
这次主要去了中山路、鼓浪屿、曾厝(cuo)垵、植物园、灵玲马戏团，因为住的离环岛路比较近，还有幸现场看了下厦门马拉松，其中

中山路

这里看上去是有点民国时期的建筑风格，部分像那种电视里的租界啥的，不过这次去的时候都在翻修，路一大半拦起来了，听导游说这里往里面走有个局口街，然后上次听前同事说厦门比较有名的就是沙茶面和海蛎煎，不出意料的不太爱吃，沙茶面比较普通，可能是没吃到正宗的，海蛎煎吃不惯，倒是有个大叔的沙茶里脊还不错，在局口街那，还有小哥在那拍，应该也算是个网红打卡点了，然后吃了个油条麻糍也还不错，总体如果是看建筑的话可能最近不是个好时间，个人也没这方面爱好，吃的话最好多打听打听沙茶面跟海蛎煎哪里正宗。如果不知道哪家好吃，也不爱看这类建筑的可以排个坑。

鼓浪屿

鼓浪屿也是完全没啥概念，需要乘船过去，但是只要二十分钟，岛上没有机动车，基本都靠走，有几个比较有名的地方，菽庄花园，里面有钢琴博物馆，对这个感兴趣的可以去看看，旁边是沙滩还可以逛逛，然后有各种博物馆，风琴啥的，岛上最大的特色是巷子多，道听途说有三百多条小巷，还有几个网红打卡点，周杰伦晴天墙，还有个最美转角，都是挤满了人排队打卡拍照，不过如果不着急，慢慢悠悠逛逛还是不错的，比较推荐，推荐值☆☆

曾厝垵

一直读不对这个字，都是叫：那个曾什么垵，愧对语文老师，这里到算是意外之喜，鼓浪屿回来已经挺累了，不过由于比较饿（什么原因后面说），并且离住的地方不远，就过去逛了逛，东西还蛮好吃的，芒果挺便宜，一大杯才十块，无骨鸡爪很贵，不是特别爱，臭豆腐不错的，也不算很贵，这里想起来，那边八婆婆的豆乳烧仙草还不错的，去中山路那会喝了，来曾厝垵也买了，奶茶爱好者可以试试，含糖量应该很高，不爱甜食或者减肥的同学慎重考虑好了再尝试，晚上那边从牌坊出来，沿着环岛路挺多夜宵店什么的，非常推荐，推荐值☆☆☆☆

植物园

植物园还是挺名副其实的，有热带植物，沙漠多肉，因为赶时间逛得不多，热带雨林植物那太多人了，都是在那拍照，而且我指的拍照都是拍人照，本身就很小的路，各种十八线网红，或者普通游客在那摆 pose 拍照，挺无语的；沙漠多肉比较惊喜，好多比人高的仙人掌，一大片的仙人球，很可恶的是好多大仙人掌上都有人刻字，越来越体会到，我们社会人多了，什么样的都有，而且不少；还看了下百花厅，但没什么特别的，可能赶时间比较着急，没仔细看，比较推荐，推荐值☆☆☆

灵玲马戏团

对这个其实比较排斥，主要是比较晚了，跑的有点远（我太懒了），一开始真的挺拉低体验感受的，上来个什么书法家，现场画马，卖画；不过后面的还算值回票价，主题是花木兰，空中动作应该很考验基本功，然后那些老外的飞轮还跳绳（不知道学名叫啥），动物那块不太忍心看，应该是吃了不少苦头，不过人都这样就往后点再心疼动物吧。

总结

厦门是个非常适合干饭人的地方，吃饭的地方大部分是差不多一桌菜十个左右就完了，而且上来就一大碗饭，一瓶雪碧一瓶可乐，对于经常是家里跟亲戚吃饭都得十几二十个菜的乡下人来说，不太吃得惯这样的🤦‍♂️，当然很有可能是我们预算不足，点的差。但是有一点是我回杭州深有感触的，感觉杭州司机的素质真的是跟厦门的司机差了比较多，杭州除非公交车停了，否则人行道很难看到主动让人的，当然这里拿厦门这个旅游城市来对比也不是很公平，不过这也是体现城市现代化文明水平的一个维度吧。

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之前没注意到这一块，只是比较模糊的印象 dubbo 自己基于 ThreadPoolExecutor 定义了几个线程池，但是没具体看过，主要是觉得就是为了避免使用 jdk 自带的那几个(java.util.concurrent.Executors)，防止出现那些问题
看下代码目录主要是这几个

  • FixedThreadPool：创建一个复用固定个数线程的线程池。
    简单看下代码
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    public Executor getExecutor(URL url) {
            String name = url.getParameter("threadname", "Dubbo");
            int threads = url.getParameter("threads", 200);
            int queues = url.getParameter("queues", 0);
            return new ThreadPoolExecutor(threads, threads, 0L, TimeUnit.MILLISECONDS, (BlockingQueue)(queues == 0 ? new SynchronousQueue() : (queues < 0 ? new LinkedBlockingQueue() : new LinkedBlockingQueue(queues))), new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
        }
    可以看到核心线程数跟最大线程数一致，也就是说就不会在核心线程数和最大线程数之间动态变化了
  • LimitedThreadPool：创建一个线程池，这个线程池中线程个数随着需要量动态增加，但是数量不超过配置的阈值的个数，另外空闲线程不会被回收，会一直存在。
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    public Executor getExecutor(URL url) {
            String name = url.getParameter("threadname", "Dubbo");
            int cores = url.getParameter("corethreads", 0);
            int threads = url.getParameter("threads", 200);
            int queues = url.getParameter("queues", 0);
            return new ThreadPoolExecutor(cores, threads, 9223372036854775807L, TimeUnit.MILLISECONDS, (BlockingQueue)(queues == 0 ? new SynchronousQueue() : (queues < 0 ? new LinkedBlockingQueue() : new LinkedBlockingQueue(queues))), new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
        }
    这个特点主要是创建了保活时间特别长，即可以认为不会被回收了
  • EagerThreadPool ：创建一个线程池，这个线程池当所有核心线程都处于忙碌状态时候，创建新的线程来执行新任务，而不是把任务放入线程池阻塞队列。
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    public Executor getExecutor(URL url) {
            String name = url.getParameter("threadname", "Dubbo");
            int cores = url.getParameter("corethreads", 0);
            int threads = url.getParameter("threads", 2147483647);
            int queues = url.getParameter("queues", 0);
            int alive = url.getParameter("alive", 60000);
            TaskQueue<Runnable> taskQueue = new TaskQueue(queues <= 0 ? 1 : queues);
            EagerThreadPoolExecutor executor = new EagerThreadPoolExecutor(cores, threads, (long)alive, TimeUnit.MILLISECONDS, taskQueue, new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
            taskQueue.setExecutor(executor);
            return executor;
        }
    这个是改动最多的一个了，因为需要实现这个机制，有兴趣的可以详细看下
  • CachedThreadPool： 创建一个自适应线程池，当线程处于空闲1分钟时候，线程会被回收，当有新请求到来时候会创建新线程
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    public Executor getExecutor(URL url) {
            String name = url.getParameter("threadname", "Dubbo");
            int cores = url.getParameter("corethreads", 0);
            int threads = url.getParameter("threads", 2147483647);
            int queues = url.getParameter("queues", 0);
            int alive = url.getParameter("alive", 60000);
            return new ThreadPoolExecutor(cores, threads, (long)alive, TimeUnit.MILLISECONDS, (BlockingQueue)(queues == 0 ? new SynchronousQueue() : (queues < 0 ? new LinkedBlockingQueue() : new LinkedBlockingQueue(queues))), new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
        }
    这里可以看到线程池的配置，核心是 0，最大线程数是 2147483647，保活时间是一分钟
    只是非常简略的介绍下，有兴趣可以自行阅读代码。

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拖更原因

这篇年终总结本来应该在农历过完年就出来的，结果是对没有受疫情影响的春节放假时间空闲情况预估太良好，虽然公司调了几天假，但是因为春节期间疫情状况比较好，本来酒店都不让接待聚餐什么的，后来统统放开，结果就是从初一到初六每天要不就是去亲戚家，要不就是去酒店饭店吃饭，计划很丰满，现实很骨感，时间感觉一下就没了，然后年后感觉有点犯懒了，所以才拖到现在。

生活-健身跑步

去年（19 年）的时候跑步突破了 300 公里，然后20 年给自己定了个 400 公里的目标，结果意料之中的没成功，原因可能疫情算一点吧，后面买了跑步机之后，基本周末回家都能跑一下，但是最后还是只跑了300 多公里，总的keep 记录跑量也没超过 1000 公里，所以跑步这个目标还是没成功的，不过还算是比去年多跑一点，这样也算后面好突破点，后面的目标就不定的太高了，每年能比前一年多一点就好，其实跑步已经从一种减肥方式变成一种习惯了，一周一次的跑步已经比较难有效减重了，但是对于保持精力和身体状态还是很有效和重要的，只是对于目前的体重还是要多减下去一些跑步才好，太重了对膝盖负担太大了，可惜还是时间呐，游泳骑车什么的都需要更苛刻的条件和时间，饮食呢控制起来比较难（贪吃
终于在 3 月底之前跑到了 1000 公里，迟了三个月，不过也总算达到了，只是体重控制还是不行，有试着走走楼梯，但是感觉对膝盖负担比较大，得再想想用什么方式

技术成长

一直提不起笔来写这篇年终总结还有个比较大的原因是觉得20 年的成长不如预期，大小目标都没怎么完成，比如深入了解 jvm，是想能有些深入的见解，而不再是某些点的比较片面的理解，系统性的归纳总结也比较少，每个方向或多或少有些看法和理解，但是不全面，一些东西看过了也会忘记，需要温故而知新，比如 AQS 的内容，第一次读其实理解比较浅，后面就强迫自己去读，去写，才有了一些比之前更深入的理解，因为很多文章都是带有作者思路的引导，适不适合自己都要看是否能从他的思路把它看懂，有些就差别很大，这个跟看书也一样，有些书大众一致推荐，一般情况下大多是经典的好的，但是也有可能是不太适合自己的，可能有时候机缘巧合看到的反而让人茅塞顿开，在 todo 里已经积攒了好多的点和面需要去学习实践，一方面是自己懒，一方面是时间也相对偏少，看看 21 年能不能有所提升，加强“时间管理”，哈哈

技术上主要是看了 mysql 的 mvcc 相关内容，rocketmq 的，redis 的代码，还有 mybatis 等，其实每一个都能写很多，也有很多值得学习的，需要全面系统学习，之前想好好画一个思维导图，将整个技术体系都梳理下，还只做了一点点，方式也有点问题，应该从大到小，而不是深度优先，细节有很多，每一个方面都有自己比较熟悉擅长的，也有不太了解的，可以做一个评分，这个也是亟待改善的，希望今年能完成。

博客

博客方面 20 年一年整是写了 53 篇，差不多是一周一篇的节奏，这个还是不错的，虽然博客质量参差不齐，但是这个更新频率还是比较好的，并且也定了个潜规则，可以一周技术一周生活，这样能缓解水文的频率，提高些技术文章的质量，虽然结果并没有好多少，不过感觉还是可以这么坚持的，能提高一些技术文章的质量那就更好了

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top 命令在日常的 Linux 使用中，特别是做一些服务器的简单状态查看，排查故障都起了比较大的作用，但是由于这个命令看到的东西比较多，一般只会看部分，或者说像我这样就会比较片面地看一些信息，比如默认是进程维度的，可以在启动命令的时候加-H进入线程模式

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-H  :Threads-mode operation
            Instructs top to display individual threads.  Without this command-line option a summation of all threads in each process  is  shown.   Later
            this can be changed with the `H' interactive command.

这样就能用在 Java 中去 jstack 中找到对应的线程
其实还有比较重要的两个操作，
一个是在 top 启动状态下，按c键，这样能把比如说是一个 Java 进程，具体的进程命令显示出来
像这样
执行前是这样

执行后是这样

第二个就是排序了

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SORTING of task window

          For  compatibility,  this top supports most of the former top sort keys.  Since this is primarily a service to former top users, these commands
          do not appear on any help screen.
                command   sorted-field                  supported
                A         start time (non-display)      No
                M         %MEM                          Yes
                N         PID                           Yes
                P         %CPU                          Yes
                T         TIME+                         Yes

          Before using any of the following sort provisions, top suggests that you temporarily turn on column highlighting using the `x' interactive com‐
          mand.  That will help ensure that the actual sort environment matches your intent.

          The following interactive commands will only be honored when the current sort field is visible.  The sort field might not be visible because:
                1) there is insufficient Screen Width
                2) the `f' interactive command turned it Off

             <  :Move-Sort-Field-Left
                 Moves the sort column to the left unless the current sort field is the first field being displayed.

             >  :Move-Sort-Field-Right
                 Moves the sort column to the right unless the current sort field is the last field being displayed.

查看 man page 可以找到这一段，其实一般 man page 都是最细致的，只不过因为太多了，有时候懒得看，这里可以通过大写 M 和大写 P 分别按内存和 CPU 排序，下面还有两个小技巧，通过按 x 可以将当前活跃的排序列用不同颜色标出来，然后可以通过<和>直接左右移动排序列

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事情源于周末来回家发生的两件事情，先是回去的时候从高铁下车要坐公交，现在算是有个比较好的临时候车点了，但是可能由于疫情好转，晚上都不用检查健康码就可以进候车点，但是上公交的时候还是需要看健康码，一般情况下从高铁下来的，各个地方的人都有，而且也不太清楚这边上公交车需要查验健康码，我的一个看法是候车的时候就应该放个横幅告示，或者再配合喇叭循环播放，请提前准备好健康码，上车前需要查验，因为像这周的情况，我乘坐的那辆车是间隔时间比较长，而且终点是工业开发区，可能是比较多外来务工人员的目的地，正好这部分人可能对于操作手机检验健康码这个事情不太熟悉，所以结果就是头上几个不知道怎么搞出来健康码，然后让几乎有满满一整车的人在后面堵着，司机又非常厌烦那些没有提前出示健康码的，有位乘客搞得久了点，还被误以为没刷卡买票，差点吵起来，其实公共交通或者高铁站负责的在公交指引路线上多写一句上车前需要查验健康码，可能就能改善比较多，还有就是那个积水的路，这个吐槽起来就一大坨了，整个绍兴像 dayuejin 一样到处都是破路。
第二个就是来杭州的时候，经过人行横道，远处车道的公交车停下来等我们了，为了少添麻烦总想快点穿过去，但是这时靠近我们的车道（晚上光线较暗，可见度不佳）有一辆从远处来的奥迪 A4 还是 A5 这种的车反而想加速冲过去，如果少看一下可能我已经残了，交规考的靠近人行道要减速好像基本都是个摆设了，杭州也只有公交车因为一些考核指标原因会主动礼让，人其实需要有同理心，虽然可能有些人是开车多于骑车走路的，但是总也不可能永远不穿人行道吧，甚至这些人可能还会在人行道红灯的时候走过去。这个事情不是吐槽公共交通的，只是也有些许关系，想起来还有一件事也是刚才来杭州的时候看到的，等公交的时候看到有辆路虎要加塞，而目标车道刚好是辆大货车，大货车看到按了喇叭，路虎犹豫了下还是挤进去了，可能是对路虎的扛撞性能非常自信吧，反正我是挺后怕的，这种级别的车，被撞了的话估计还是鸡蛋撞石头，吨位惯性在那，这里再延伸下，挺多开豪车的人好像都觉得这路上路权更大一些，谁谁都得让着他，可能实际吃亏的不多，所以越加巩固了这种思维，当真的碰到不管的可能就会明白了，路权这个事情在天朝也基本没啥人重视，也没想说个结论，就到这吧

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Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

发表于 分类于 ， 阅读次数： Disqus：

这几天去了趟厦门，原来几年前就想去了，本来都请好假了，后面因为一些事情没去成，这次刚好公司组织，就跟 LD 一起去了厦门，也不洋洋洒洒地写游记了，后面可能会有，今天先来总结下好的地方和比较坑的地方。
这次主要去了中山路、鼓浪屿、曾厝(cuo)垵、植物园、灵玲马戏团，因为住的离环岛路比较近，还有幸现场看了下厦门马拉松，其中

中山路

这里看上去是有点民国时期的建筑风格，部分像那种电视里的租界啥的，不过这次去的时候都在翻修，路一大半拦起来了，听导游说这里往里面走有个局口街，然后上次听前同事说厦门比较有名的就是沙茶面和海蛎煎，不出意料的不太爱吃，沙茶面比较普通，可能是没吃到正宗的，海蛎煎吃不惯，倒是有个大叔的沙茶里脊还不错，在局口街那，还有小哥在那拍，应该也算是个网红打卡点了，然后吃了个油条麻糍也还不错，总体如果是看建筑的话可能最近不是个好时间，个人也没这方面爱好，吃的话最好多打听打听沙茶面跟海蛎煎哪里正宗。如果不知道哪家好吃，也不爱看这类建筑的可以排个坑。

鼓浪屿

鼓浪屿也是完全没啥概念，需要乘船过去，但是只要二十分钟，岛上没有机动车，基本都靠走，有几个比较有名的地方，菽庄花园，里面有钢琴博物馆，对这个感兴趣的可以去看看，旁边是沙滩还可以逛逛，然后有各种博物馆，风琴啥的，岛上最大的特色是巷子多，道听途说有三百多条小巷，还有几个网红打卡点，周杰伦晴天墙，还有个最美转角，都是挤满了人排队打卡拍照，不过如果不着急，慢慢悠悠逛逛还是不错的，比较推荐，推荐值☆☆

曾厝垵

一直读不对这个字，都是叫：那个曾什么垵，愧对语文老师，这里到算是意外之喜，鼓浪屿回来已经挺累了，不过由于比较饿（什么原因后面说），并且离住的地方不远，就过去逛了逛，东西还蛮好吃的，芒果挺便宜，一大杯才十块，无骨鸡爪很贵，不是特别爱，臭豆腐不错的，也不算很贵，这里想起来，那边八婆婆的豆乳烧仙草还不错的，去中山路那会喝了，来曾厝垵也买了，奶茶爱好者可以试试，含糖量应该很高，不爱甜食或者减肥的同学慎重考虑好了再尝试，晚上那边从牌坊出来，沿着环岛路挺多夜宵店什么的，非常推荐，推荐值☆☆☆☆

植物园

植物园还是挺名副其实的，有热带植物，沙漠多肉，因为赶时间逛得不多，热带雨林植物那太多人了，都是在那拍照，而且我指的拍照都是拍人照，本身就很小的路，各种十八线网红，或者普通游客在那摆 pose 拍照，挺无语的；沙漠多肉比较惊喜，好多比人高的仙人掌，一大片的仙人球，很可恶的是好多大仙人掌上都有人刻字，越来越体会到，我们社会人多了，什么样的都有，而且不少；还看了下百花厅，但没什么特别的，可能赶时间比较着急，没仔细看，比较推荐，推荐值☆☆☆

灵玲马戏团

对这个其实比较排斥，主要是比较晚了，跑的有点远（我太懒了），一开始真的挺拉低体验感受的，上来个什么书法家，现场画马，卖画；不过后面的还算值回票价，主题是花木兰，空中动作应该很考验基本功，然后那些老外的飞轮还跳绳（不知道学名叫啥），动物那块不太忍心看，应该是吃了不少苦头，不过人都这样就往后点再心疼动物吧。

总结

厦门是个非常适合干饭人的地方，吃饭的地方大部分是差不多一桌菜十个左右就完了，而且上来就一大碗饭，一瓶雪碧一瓶可乐，对于经常是家里跟亲戚吃饭都得十几二十个菜的乡下人来说，不太吃得惯这样的🤦‍♂️，当然很有可能是我们预算不足，点的差。但是有一点是我回杭州深有感触的，感觉杭州司机的素质真的是跟厦门的司机差了比较多，杭州除非公交车停了，否则人行道很难看到主动让人的，当然这里拿厦门这个旅游城市来对比也不是很公平，不过这也是体现城市现代化文明水平的一个维度吧。

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之前没注意到这一块，只是比较模糊的印象 dubbo 自己基于 ThreadPoolExecutor 定义了几个线程池，但是没具体看过，主要是觉得就是为了避免使用 jdk 自带的那几个(java.util.concurrent.Executors)，防止出现那些问题
看下代码目录主要是这几个

  • FixedThreadPool：创建一个复用固定个数线程的线程池。
    简单看下代码
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    public Executor getExecutor(URL url) {
            String name = url.getParameter("threadname", "Dubbo");
            int threads = url.getParameter("threads", 200);
            int queues = url.getParameter("queues", 0);
            return new ThreadPoolExecutor(threads, threads, 0L, TimeUnit.MILLISECONDS, (BlockingQueue)(queues == 0 ? new SynchronousQueue() : (queues < 0 ? new LinkedBlockingQueue() : new LinkedBlockingQueue(queues))), new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
        }
    可以看到核心线程数跟最大线程数一致，也就是说就不会在核心线程数和最大线程数之间动态变化了
  • LimitedThreadPool：创建一个线程池，这个线程池中线程个数随着需要量动态增加，但是数量不超过配置的阈值的个数，另外空闲线程不会被回收，会一直存在。
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    public Executor getExecutor(URL url) {
            String name = url.getParameter("threadname", "Dubbo");
            int cores = url.getParameter("corethreads", 0);
            int threads = url.getParameter("threads", 200);
            int queues = url.getParameter("queues", 0);
            return new ThreadPoolExecutor(cores, threads, 9223372036854775807L, TimeUnit.MILLISECONDS, (BlockingQueue)(queues == 0 ? new SynchronousQueue() : (queues < 0 ? new LinkedBlockingQueue() : new LinkedBlockingQueue(queues))), new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
        }
    这个特点主要是创建了保活时间特别长，即可以认为不会被回收了
  • EagerThreadPool ：创建一个线程池，这个线程池当所有核心线程都处于忙碌状态时候，创建新的线程来执行新任务，而不是把任务放入线程池阻塞队列。
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    public Executor getExecutor(URL url) {
            String name = url.getParameter("threadname", "Dubbo");
            int cores = url.getParameter("corethreads", 0);
            int threads = url.getParameter("threads", 2147483647);
            int queues = url.getParameter("queues", 0);
            int alive = url.getParameter("alive", 60000);
            TaskQueue<Runnable> taskQueue = new TaskQueue(queues <= 0 ? 1 : queues);
            EagerThreadPoolExecutor executor = new EagerThreadPoolExecutor(cores, threads, (long)alive, TimeUnit.MILLISECONDS, taskQueue, new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
            taskQueue.setExecutor(executor);
            return executor;
        }
    这个是改动最多的一个了，因为需要实现这个机制，有兴趣的可以详细看下
  • CachedThreadPool： 创建一个自适应线程池，当线程处于空闲1分钟时候，线程会被回收，当有新请求到来时候会创建新线程
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    public Executor getExecutor(URL url) {
            String name = url.getParameter("threadname", "Dubbo");
            int cores = url.getParameter("corethreads", 0);
            int threads = url.getParameter("threads", 2147483647);
            int queues = url.getParameter("queues", 0);
            int alive = url.getParameter("alive", 60000);
            return new ThreadPoolExecutor(cores, threads, (long)alive, TimeUnit.MILLISECONDS, (BlockingQueue)(queues == 0 ? new SynchronousQueue() : (queues < 0 ? new LinkedBlockingQueue() : new LinkedBlockingQueue(queues))), new NamedThreadFactory(name, true), new AbortPolicyWithReport(name, url));
        }
    这里可以看到线程池的配置，核心是 0，最大线程数是 2147483647，保活时间是一分钟
    只是非常简略的介绍下，有兴趣可以自行阅读代码。

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拖更原因

这篇年终总结本来应该在农历过完年就出来的，结果是对没有受疫情影响的春节放假时间空闲情况预估太良好，虽然公司调了几天假，但是因为春节期间疫情状况比较好，本来酒店都不让接待聚餐什么的，后来统统放开，结果就是从初一到初六每天要不就是去亲戚家，要不就是去酒店饭店吃饭，计划很丰满，现实很骨感，时间感觉一下就没了，然后年后感觉有点犯懒了，所以才拖到现在。

生活-健身跑步

去年（19 年）的时候跑步突破了 300 公里，然后20 年给自己定了个 400 公里的目标，结果意料之中的没成功，原因可能疫情算一点吧，后面买了跑步机之后，基本周末回家都能跑一下，但是最后还是只跑了300 多公里，总的keep 记录跑量也没超过 1000 公里，所以跑步这个目标还是没成功的，不过还算是比去年多跑一点，这样也算后面好突破点，后面的目标就不定的太高了，每年能比前一年多一点就好，其实跑步已经从一种减肥方式变成一种习惯了，一周一次的跑步已经比较难有效减重了，但是对于保持精力和身体状态还是很有效和重要的，只是对于目前的体重还是要多减下去一些跑步才好，太重了对膝盖负担太大了，可惜还是时间呐，游泳骑车什么的都需要更苛刻的条件和时间，饮食呢控制起来比较难（贪吃
终于在 3 月底之前跑到了 1000 公里，迟了三个月，不过也总算达到了，只是体重控制还是不行，有试着走走楼梯，但是感觉对膝盖负担比较大，得再想想用什么方式

技术成长

一直提不起笔来写这篇年终总结还有个比较大的原因是觉得20 年的成长不如预期，大小目标都没怎么完成，比如深入了解 jvm，是想能有些深入的见解，而不再是某些点的比较片面的理解，系统性的归纳总结也比较少，每个方向或多或少有些看法和理解，但是不全面，一些东西看过了也会忘记，需要温故而知新，比如 AQS 的内容，第一次读其实理解比较浅，后面就强迫自己去读，去写，才有了一些比之前更深入的理解，因为很多文章都是带有作者思路的引导，适不适合自己都要看是否能从他的思路把它看懂，有些就差别很大，这个跟看书也一样，有些书大众一致推荐，一般情况下大多是经典的好的，但是也有可能是不太适合自己的，可能有时候机缘巧合看到的反而让人茅塞顿开，在 todo 里已经积攒了好多的点和面需要去学习实践，一方面是自己懒，一方面是时间也相对偏少，看看 21 年能不能有所提升，加强“时间管理”，哈哈

技术上主要是看了 mysql 的 mvcc 相关内容，rocketmq 的，redis 的代码，还有 mybatis 等，其实每一个都能写很多，也有很多值得学习的，需要全面系统学习，之前想好好画一个思维导图，将整个技术体系都梳理下，还只做了一点点，方式也有点问题，应该从大到小，而不是深度优先，细节有很多，每一个方面都有自己比较熟悉擅长的，也有不太了解的，可以做一个评分，这个也是亟待改善的，希望今年能完成。

博客

博客方面 20 年一年整是写了 53 篇，差不多是一周一篇的节奏，这个还是不错的，虽然博客质量参差不齐，但是这个更新频率还是比较好的，并且也定了个潜规则，可以一周技术一周生活，这样能缓解水文的频率，提高些技术文章的质量，虽然结果并没有好多少，不过感觉还是可以这么坚持的，能提高一些技术文章的质量那就更好了

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top 命令在日常的 Linux 使用中，特别是做一些服务器的简单状态查看，排查故障都起了比较大的作用，但是由于这个命令看到的东西比较多，一般只会看部分，或者说像我这样就会比较片面地看一些信息，比如默认是进程维度的，可以在启动命令的时候加-H进入线程模式

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-H  :Threads-mode operation
            Instructs top to display individual threads.  Without this command-line option a summation of all threads in each process  is  shown.   Later
            this can be changed with the `H' interactive command.

这样就能用在 Java 中去 jstack 中找到对应的线程
其实还有比较重要的两个操作，
一个是在 top 启动状态下，按c键，这样能把比如说是一个 Java 进程，具体的进程命令显示出来
像这样
执行前是这样

执行后是这样

第二个就是排序了

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SORTING of task window

          For  compatibility,  this top supports most of the former top sort keys.  Since this is primarily a service to former top users, these commands
          do not appear on any help screen.
                command   sorted-field                  supported
                A         start time (non-display)      No
                M         %MEM                          Yes
                N         PID                           Yes
                P         %CPU                          Yes
                T         TIME+                         Yes

          Before using any of the following sort provisions, top suggests that you temporarily turn on column highlighting using the `x' interactive com‐
          mand.  That will help ensure that the actual sort environment matches your intent.

          The following interactive commands will only be honored when the current sort field is visible.  The sort field might not be visible because:
                1) there is insufficient Screen Width
                2) the `f' interactive command turned it Off

             <  :Move-Sort-Field-Left
                 Moves the sort column to the left unless the current sort field is the first field being displayed.

             >  :Move-Sort-Field-Right
                 Moves the sort column to the right unless the current sort field is the last field being displayed.

查看 man page 可以找到这一段，其实一般 man page 都是最细致的，只不过因为太多了，有时候懒得看，这里可以通过大写 M 和大写 P 分别按内存和 CPU 排序，下面还有两个小技巧，通过按 x 可以将当前活跃的排序列用不同颜色标出来，然后可以通过<和>直接左右移动排序列

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事情源于周末来回家发生的两件事情，先是回去的时候从高铁下车要坐公交，现在算是有个比较好的临时候车点了，但是可能由于疫情好转，晚上都不用检查健康码就可以进候车点，但是上公交的时候还是需要看健康码，一般情况下从高铁下来的，各个地方的人都有，而且也不太清楚这边上公交车需要查验健康码，我的一个看法是候车的时候就应该放个横幅告示，或者再配合喇叭循环播放，请提前准备好健康码，上车前需要查验，因为像这周的情况，我乘坐的那辆车是间隔时间比较长，而且终点是工业开发区，可能是比较多外来务工人员的目的地，正好这部分人可能对于操作手机检验健康码这个事情不太熟悉，所以结果就是头上几个不知道怎么搞出来健康码，然后让几乎有满满一整车的人在后面堵着，司机又非常厌烦那些没有提前出示健康码的，有位乘客搞得久了点，还被误以为没刷卡买票，差点吵起来，其实公共交通或者高铁站负责的在公交指引路线上多写一句上车前需要查验健康码，可能就能改善比较多，还有就是那个积水的路，这个吐槽起来就一大坨了，整个绍兴像 dayuejin 一样到处都是破路。
第二个就是来杭州的时候，经过人行横道，远处车道的公交车停下来等我们了，为了少添麻烦总想快点穿过去，但是这时靠近我们的车道（晚上光线较暗，可见度不佳）有一辆从远处来的奥迪 A4 还是 A5 这种的车反而想加速冲过去，如果少看一下可能我已经残了，交规考的靠近人行道要减速好像基本都是个摆设了，杭州也只有公交车因为一些考核指标原因会主动礼让，人其实需要有同理心，虽然可能有些人是开车多于骑车走路的，但是总也不可能永远不穿人行道吧，甚至这些人可能还会在人行道红灯的时候走过去。这个事情不是吐槽公共交通的，只是也有些许关系，想起来还有一件事也是刚才来杭州的时候看到的，等公交的时候看到有辆路虎要加塞，而目标车道刚好是辆大货车，大货车看到按了喇叭，路虎犹豫了下还是挤进去了，可能是对路虎的扛撞性能非常自信吧，反正我是挺后怕的，这种级别的车，被撞了的话估计还是鸡蛋撞石头，吨位惯性在那，这里再延伸下，挺多开豪车的人好像都觉得这路上路权更大一些，谁谁都得让着他，可能实际吃亏的不多，所以越加巩固了这种思维，当真的碰到不管的可能就会明白了，路权这个事情在天朝也基本没啥人重视，也没想说个结论，就到这吧

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Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

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最近群里大佬发起了一个读书打卡活动，需要每天读一会书，在群里打卡分享感悟，争取一个月能读完一本书，说实话一天十分钟的读书时间倒是问题不大，不过每天都要打卡，而且一个月要读完一本书，其实难度还是有点大的，不过也想试试看。
之前某某老大给自己立了个 flag，说要读一百本书，这对我来说挺难实现的，一则我也不喜欢书只读一小半，二则感觉对于喜欢看的内容范围还是比较有限制，可能也算是比较矫情，不爱追热门的各类东西，因为往往会有一些跟大众不一致的观点看法，显得格格不入。所以还是这个打卡活动可能会比较适合我，书是人类进步的阶梯。
到现在是打卡了三天了，读的主要是白岩松的《幸福了吗》，对于白岩松，我们这一代人是比较熟悉，并且整体印象比较不错的一个央视主持人，从《焦点访谈》开始，到疫情期间的各类一线节目，可能对我来说是个三观比较正，敢于说一些真话的主持人，这中间其实是有个空档期，没怎么看电视，也不太关注了，只是在疫情期间的节目，还是一如既往地给人一种可靠的感觉，正好有一次偶然微信读书推荐了白岩松的这本书，就看了一部分，正好这次继续往下看，因为相对来讲不会很晦涩，并且从这位知名央视主持人的角度分享他的过往和想法看法，还是比较有意思的。
从对汶川地震，08 年奥运等往事的回忆和一些细节的呈现，也让我了解比较多当时所不知道的，特别是汶川地震，那时的我还在读高中，真的是看着电视，作为“猛男”都忍不住泪目了，共和国之殇，多难兴邦，但是这对于当事人来说，都是一场醒不过来的噩梦。
然后是对于足球的热爱，其实光这个就能掰扯很多，因为我不爱足球，只爱篮球，其中原因有的没的也挺多可以说的，但是看了他的书，才能比较深入的了解一个足球迷，对足球，对中国足球，对世界杯，对阿根廷的感情。
接下去还是想能继续坚持下去，加油！

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前面写过一系列的 redis 源码分析的，但是实际上很多的问题还是需要结合实际的使用，然后其实就避不开缓存使用的三个著名问题，穿透，击穿和雪崩，这三个概念也是有着千丝万缕的关系，

缓存穿透

缓存穿透是指当数据库中本身就不存在这个数据的时候，使用一般的缓存策略时访问不到缓存后就访问数据库，但是因为数据库也没数据，所以如果不做任何策略优化的话，这类数据就每次都会访问一次数据库，对数据库压力也会比较大。

缓存击穿

缓存击穿跟穿透比较类似的，都是访问缓存不在，然后去访问数据库，与穿透不一样的是击穿是在数据库中存在数据，但是可能由于第一次访问，或者缓存过期了，需要访问到数据库，这对于访问量小的情况其实算是个正常情况，但是随着请求量变高就会引发一些性能隐患。

缓存雪崩

缓存雪崩就是击穿的大规模集群效应，当大量的缓存过期失效的时候，这些请求都是直接访问到数据库了，会对数据库造成很大的压力。

对于以上三种场景也有一些比较常见的解决方案，但也不能说是万无一失的，需要随着业务去寻找合适的方案

解决缓存穿透

对于数据库中就没这个数据的时候，一种是可以对这个 key 设置下空值，即以一个特定的表示是数据库不存在的，这种情况需要合理地调整过期时间，当这个 key 在数据库中有数据了的话，也需要有策略去更新这个值，并且如果这类 key 非常多，这个方法就会不太合适，就可以使用第二种方法，就是布隆过滤器，bloom filter，前置一个布隆过滤器，当这个 key 在数据库不存在的话，先用布隆过滤器挡一道，如果不在的话就直接返回了，当然布隆过滤器不是绝对的准确的

解决缓存击穿

当一个 key 的缓存过期了，如果大量请求过来访问这个 key，请求都会落在数据库里，这个时候就可以使用一些类似于互斥锁的方式去让一个线程去访问数据库，更新缓存，但是这里其实也有个问题，就是如果是热点 key 其实这种方式也比较危险，万一更新失败，或者更新操作的时候耗时比较久，就会有一大堆请求卡在那，这种情况可能需要有一些异步提前刷新缓存，可以结合具体场景选择方式

解决缓存雪崩

雪崩的情况是指大批量的 key 都一起过期了，击穿的放大版，大批量的请求都打到数据库上了，一方面有可能直接缓存不可用了，就需要用集群化高可用的缓存服务，然后对于实际使用中也可以使用本地缓存结合 redis 缓存，去提高可用性，再配合一些限流措施，然后就是缓存使用过程总的过期时间最好能加一些随机值，防止在同一时间过期而导致雪崩，结合互斥锁防止大量请求打到数据库。

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题目介绍

A path in a binary tree is a sequence of nodes where each pair of adjacent nodes in the sequence has an edge connecting them. A node can only appear in the sequence at most once. Note that the path does not need to pass through the root.

The path sum of a path is the sum of the node’s values in the path.

Given the root of a binary tree, return the maximum path sum of any path.

路径 被定义为一条从树中任意节点出发，沿父节点-子节点连接，达到任意节点的序列。该路径 至少包含一个 节点，且不一定经过根节点。

路径和 是路径中各节点值的总和。

给你一个二叉树的根节点 root ，返回其 最大路径和

简要分析

其实这个题目会被误解成比较简单，左子树最大的，或者右子树最大的，或者两边加一下，仔细想想都不对，其实有可能是产生于左子树中，或者右子树中，这两个都是指跟左子树根还有右子树根没关系的，这么说感觉不太容易理解，画个图

可以看到图里，其实最长路径和是左边这个子树组成的，跟根节点还有右子树完全没关系，然后再想一种情况，如果是整棵树就是图中的左子树，那么这个最长路径和就是左子树加右子树加根节点了，所以不是我一开始想得那么简单，在代码实现中也需要一些技巧

代码

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int ansNew = Integer.MIN_VALUE;
public int maxPathSum(TreeNode root) {
        maxSumNew(root);
        return ansNew;
    }
    
public int maxSumNew(TreeNode root) {
    if (root == null) {
        return 0;
    }
    // 这里是个简单的递归，就是去递归左右子树，但是这里其实有个概念，当这样处理时，其实相当于把子树的内部的最大路径和已经算出来了
    int left = maxSumNew(root.left);
    int right = maxSumNew(root.right);
    // 这里前面我有点没想明白，但是看到 ansNew 的比较，其实相当于，返回的是三种情况里的最大值，一个是左子树+根，一个是右子树+根，一个是单独根节点，
    // 这样这个递归的返回才会有意义，不然像原来的方法，它可能是跳着的，但是这种情况其实是借助于 ansNew 这个全局的最大值，因为原来我觉得要比较的是
    // left, right, left + root , right + root, root, left + right + root 这些的最大值，这里是分成了两个阶段，left 跟 right 的最大值已经在上面的
    // 调用过程中赋值给 ansNew 了    
    int currentSum = Math.max(Math.max(root.val + left , root.val + right), root.val);
    // 这边返回的是 currentSum，然后再用它跟 left + right + root 进行对比，然后再去更新 ans
    // PS: 有个小点也是这边的破局点，就是这个 ansNew
    int res = Math.max(left + right + root.val, currentSum);
    ans = Math.max(res, ans);
    return currentSum;
}

这里非常重要的就是 ansNew 是最后的一个结果，而对于 maxSumNew 这个函数的返回值其实是需要包含了一个连续结果，因为要返回继续去算路径和，所以返回的是 currentSum，最终结果是 ansNew

结果图

难得有个 100%，贴个图哈哈

发表于 分类于 ， 阅读次数： Disqus：

今天真的是被气得不轻，情况是碰到一个有 70 多秒的直行红灯，然后直行就排了很长的队，但是左转车道没车，就有好几辆车占着左转车道，准备往直行车道插队加塞，一般这种加塞的，会挑个不太计较的，如果前面一辆不让的话就再等等，我因为赶着回家，就不想让，结果那辆车几次车头直接往里冲，当时怒气值基本已经蓄满了，我真的是分毫都不想让，如果路上都是让着这种人的，那么这种情况只会越来越严重，我理解的这种心态，就赌你怕麻烦，多一事不如少一事，结果就是每次都能顺利插队加塞，其实延伸到我们社会中的种种实质性的排队或者等同于排队的情况，都已经有这种惯有思维，一方面这种不符合规则，可能在严重程度上容易被很多人所忽视，基本上已经被很多人当成是“合理”行为，另一方面，对于这些“微小”的违规行为，本身管理层面也基本没有想要管的意思，就更多的成为了纵容这些行为的导火索，并且大多数人都是想着如果不让，发生点小剐小蹭的要浪费很多时间精力来处理，甚至会觉得会被别人觉得自己太小气等等，诸多内外成本结合起来，会真的去硬刚的可能少之又少了，这样也就让更多的人觉得这种行为是被默许的，再举个非常小的例子，以我们公司疫情期间的盒饭发放为例，有两个比较“有意思”的事情，第一个就是因为疫情，本来是让排队要间隔一米，但是可能除了我比较怕死会跟前面的人保持点距离基本没别人会不挨着前面的人，甚至我跟我前面的人保持点距离，后面的同学会推着我让我上去；第二个是关于拿饭，这么多人排着队拿饭，然后有部分同学，一个人拿好几份，帮组里其他人的都拿了，有些甚至一个人拿十份，假如这个盒饭发放是说明了可以按部门直接全领了那就没啥问题，但是当时的状况是个人排队领自己的那一份，如果一个同学直接帮着组里十几个人都拿了，后面排队的人是什么感受呢，甚至有些是看到队伍排长了，就找队伍里自己认识的比较靠前的人说你帮我也拿一份，其实作为我这个比较按规矩办事的“愣头青”来说，我是比较不能接受这两件小事里的行为的，再往下说可能就有点偏激了，先说到这~

发表于 更新于 分类于 ， ， ， ， 阅读次数： Disqus：

题目介绍

写一个程序找出两个单向链表的交叉起始点，可能是我英语不好，图里画的其实还有一点是交叉以后所有节点都是相同的
Write a program to find the node at which the intersection of two singly linked lists begins.

For example, the following two linked lists:

begin to intersect at node c1.

Example 1:

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Input: intersectVal = 8, listA = [4,1,8,4,5], listB = [5,6,1,8,4,5], skipA = 2, skipB = 3
Output: Reference of the node with value = 8
Input Explanation: The intersected node's value is 8 (note that this must not be 0 if the two lists intersect). From the head of A, it reads as [4,1,8,4,5]. From the head of B, it reads as [5,6,1,8,4,5]. There are 2 nodes before the intersected node in A; There are 3 nodes before the intersected node in B.

分析题解

一开始没什么头绪，感觉只能最原始的遍历，后来看了一些文章，发现比较简单的方式就是先找两个链表的长度差，因为从相交点开始肯定是长度一致的，这是个很好的解题突破口，找到长度差以后就是先跳过长链表的较长部分，然后开始同步遍历比较 A，B 链表；

代码

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public ListNode getIntersectionNode(ListNode headA, ListNode headB) {
        if (headA == null || headB == null) {
            return null;
        }
        // 算 A 的长度
        int countA = 0;
        ListNode tailA = headA;
        while (tailA != null) {
            tailA = tailA.next;
            countA++;
        }
        // 算 B 的长度
        int countB = 0;
        ListNode tailB = headB;
        while (tailB != null) {
            tailB = tailB.next;
            countB++;
        }
        tailA = headA;
        tailB = headB;
        // 依据长度差，先让长的链表 tail 指针往后移
        if (countA > countB) {
            while (countA > countB) {
                tailA = tailA.next;
                countA--;
            }
        } else if (countA < countB) {
            while (countA < countB) {
                tailB = tailB.next;
                countB--;
            }
        }
        // 然后以相同速度遍历两个链表比较
        while (tailA != null) {
            if (tailA == tailB) {
                return tailA;
            } else {
                tailA = tailA.next;
                tailB = tailB.next;
            }
        }
        return null;
    }

总结

可能缺少这种思维，做的还是比较少，所以没法一下子反应过来，需要锻炼，我的第一反应是两重遍历，不过那样复杂度就高了，这里应该是只有 O(N) 的复杂度。

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Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

发表于 分类于 ， ， ， 阅读次数： Disqus：

最近群里大佬发起了一个读书打卡活动，需要每天读一会书，在群里打卡分享感悟，争取一个月能读完一本书，说实话一天十分钟的读书时间倒是问题不大，不过每天都要打卡，而且一个月要读完一本书，其实难度还是有点大的，不过也想试试看。
之前某某老大给自己立了个 flag，说要读一百本书，这对我来说挺难实现的，一则我也不喜欢书只读一小半，二则感觉对于喜欢看的内容范围还是比较有限制，可能也算是比较矫情，不爱追热门的各类东西，因为往往会有一些跟大众不一致的观点看法，显得格格不入。所以还是这个打卡活动可能会比较适合我，书是人类进步的阶梯。
到现在是打卡了三天了，读的主要是白岩松的《幸福了吗》，对于白岩松，我们这一代人是比较熟悉，并且整体印象比较不错的一个央视主持人，从《焦点访谈》开始，到疫情期间的各类一线节目，可能对我来说是个三观比较正，敢于说一些真话的主持人，这中间其实是有个空档期，没怎么看电视，也不太关注了，只是在疫情期间的节目，还是一如既往地给人一种可靠的感觉，正好有一次偶然微信读书推荐了白岩松的这本书，就看了一部分，正好这次继续往下看，因为相对来讲不会很晦涩，并且从这位知名央视主持人的角度分享他的过往和想法看法，还是比较有意思的。
从对汶川地震，08 年奥运等往事的回忆和一些细节的呈现，也让我了解比较多当时所不知道的，特别是汶川地震，那时的我还在读高中，真的是看着电视，作为“猛男”都忍不住泪目了，共和国之殇，多难兴邦，但是这对于当事人来说，都是一场醒不过来的噩梦。
然后是对于足球的热爱，其实光这个就能掰扯很多，因为我不爱足球，只爱篮球，其中原因有的没的也挺多可以说的，但是看了他的书，才能比较深入的了解一个足球迷，对足球，对中国足球，对世界杯，对阿根廷的感情。
接下去还是想能继续坚持下去，加油！

发表于 分类于 ， ， ， ， ， ， 阅读次数： Disqus：

前面写过一系列的 redis 源码分析的，但是实际上很多的问题还是需要结合实际的使用，然后其实就避不开缓存使用的三个著名问题，穿透，击穿和雪崩，这三个概念也是有着千丝万缕的关系，

缓存穿透

缓存穿透是指当数据库中本身就不存在这个数据的时候，使用一般的缓存策略时访问不到缓存后就访问数据库，但是因为数据库也没数据，所以如果不做任何策略优化的话，这类数据就每次都会访问一次数据库，对数据库压力也会比较大。

缓存击穿

缓存击穿跟穿透比较类似的，都是访问缓存不在，然后去访问数据库，与穿透不一样的是击穿是在数据库中存在数据，但是可能由于第一次访问，或者缓存过期了，需要访问到数据库，这对于访问量小的情况其实算是个正常情况，但是随着请求量变高就会引发一些性能隐患。

缓存雪崩

缓存雪崩就是击穿的大规模集群效应，当大量的缓存过期失效的时候，这些请求都是直接访问到数据库了，会对数据库造成很大的压力。

对于以上三种场景也有一些比较常见的解决方案，但也不能说是万无一失的，需要随着业务去寻找合适的方案

解决缓存穿透

对于数据库中就没这个数据的时候，一种是可以对这个 key 设置下空值，即以一个特定的表示是数据库不存在的，这种情况需要合理地调整过期时间，当这个 key 在数据库中有数据了的话，也需要有策略去更新这个值，并且如果这类 key 非常多，这个方法就会不太合适，就可以使用第二种方法，就是布隆过滤器，bloom filter，前置一个布隆过滤器，当这个 key 在数据库不存在的话，先用布隆过滤器挡一道，如果不在的话就直接返回了，当然布隆过滤器不是绝对的准确的

解决缓存击穿

当一个 key 的缓存过期了，如果大量请求过来访问这个 key，请求都会落在数据库里，这个时候就可以使用一些类似于互斥锁的方式去让一个线程去访问数据库，更新缓存，但是这里其实也有个问题，就是如果是热点 key 其实这种方式也比较危险，万一更新失败，或者更新操作的时候耗时比较久，就会有一大堆请求卡在那，这种情况可能需要有一些异步提前刷新缓存，可以结合具体场景选择方式

解决缓存雪崩

雪崩的情况是指大批量的 key 都一起过期了，击穿的放大版，大批量的请求都打到数据库上了，一方面有可能直接缓存不可用了，就需要用集群化高可用的缓存服务，然后对于实际使用中也可以使用本地缓存结合 redis 缓存，去提高可用性，再配合一些限流措施，然后就是缓存使用过程总的过期时间最好能加一些随机值，防止在同一时间过期而导致雪崩，结合互斥锁防止大量请求打到数据库。

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题目介绍

A path in a binary tree is a sequence of nodes where each pair of adjacent nodes in the sequence has an edge connecting them. A node can only appear in the sequence at most once. Note that the path does not need to pass through the root.

The path sum of a path is the sum of the node’s values in the path.

Given the root of a binary tree, return the maximum path sum of any path.

路径 被定义为一条从树中任意节点出发，沿父节点-子节点连接，达到任意节点的序列。该路径 至少包含一个 节点，且不一定经过根节点。

路径和 是路径中各节点值的总和。

给你一个二叉树的根节点 root ，返回其 最大路径和

简要分析

其实这个题目会被误解成比较简单，左子树最大的，或者右子树最大的，或者两边加一下，仔细想想都不对，其实有可能是产生于左子树中，或者右子树中，这两个都是指跟左子树根还有右子树根没关系的，这么说感觉不太容易理解，画个图

可以看到图里，其实最长路径和是左边这个子树组成的，跟根节点还有右子树完全没关系，然后再想一种情况，如果是整棵树就是图中的左子树，那么这个最长路径和就是左子树加右子树加根节点了，所以不是我一开始想得那么简单，在代码实现中也需要一些技巧

代码

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int ansNew = Integer.MIN_VALUE;
public int maxPathSum(TreeNode root) {
        maxSumNew(root);
        return ansNew;
    }
    
public int maxSumNew(TreeNode root) {
    if (root == null) {
        return 0;
    }
    // 这里是个简单的递归，就是去递归左右子树，但是这里其实有个概念，当这样处理时，其实相当于把子树的内部的最大路径和已经算出来了
    int left = maxSumNew(root.left);
    int right = maxSumNew(root.right);
    // 这里前面我有点没想明白，但是看到 ansNew 的比较，其实相当于，返回的是三种情况里的最大值，一个是左子树+根，一个是右子树+根，一个是单独根节点，
    // 这样这个递归的返回才会有意义，不然像原来的方法，它可能是跳着的，但是这种情况其实是借助于 ansNew 这个全局的最大值，因为原来我觉得要比较的是
    // left, right, left + root , right + root, root, left + right + root 这些的最大值，这里是分成了两个阶段，left 跟 right 的最大值已经在上面的
    // 调用过程中赋值给 ansNew 了    
    int currentSum = Math.max(Math.max(root.val + left , root.val + right), root.val);
    // 这边返回的是 currentSum，然后再用它跟 left + right + root 进行对比，然后再去更新 ans
    // PS: 有个小点也是这边的破局点，就是这个 ansNew
    int res = Math.max(left + right + root.val, currentSum);
    ans = Math.max(res, ans);
    return currentSum;
}

这里非常重要的就是 ansNew 是最后的一个结果，而对于 maxSumNew 这个函数的返回值其实是需要包含了一个连续结果，因为要返回继续去算路径和，所以返回的是 currentSum，最终结果是 ansNew

结果图

难得有个 100%，贴个图哈哈

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今天真的是被气得不轻，情况是碰到一个有 70 多秒的直行红灯，然后直行就排了很长的队，但是左转车道没车，就有好几辆车占着左转车道，准备往直行车道插队加塞，一般这种加塞的，会挑个不太计较的，如果前面一辆不让的话就再等等，我因为赶着回家，就不想让，结果那辆车几次车头直接往里冲，当时怒气值基本已经蓄满了，我真的是分毫都不想让，如果路上都是让着这种人的，那么这种情况只会越来越严重，我理解的这种心态，就赌你怕麻烦，多一事不如少一事，结果就是每次都能顺利插队加塞，其实延伸到我们社会中的种种实质性的排队或者等同于排队的情况，都已经有这种惯有思维，一方面这种不符合规则，可能在严重程度上容易被很多人所忽视，基本上已经被很多人当成是“合理”行为，另一方面，对于这些“微小”的违规行为，本身管理层面也基本没有想要管的意思，就更多的成为了纵容这些行为的导火索，并且大多数人都是想着如果不让，发生点小剐小蹭的要浪费很多时间精力来处理，甚至会觉得会被别人觉得自己太小气等等，诸多内外成本结合起来，会真的去硬刚的可能少之又少了，这样也就让更多的人觉得这种行为是被默许的，再举个非常小的例子，以我们公司疫情期间的盒饭发放为例，有两个比较“有意思”的事情，第一个就是因为疫情，本来是让排队要间隔一米，但是可能除了我比较怕死会跟前面的人保持点距离基本没别人会不挨着前面的人，甚至我跟我前面的人保持点距离，后面的同学会推着我让我上去；第二个是关于拿饭，这么多人排着队拿饭，然后有部分同学，一个人拿好几份，帮组里其他人的都拿了，有些甚至一个人拿十份，假如这个盒饭发放是说明了可以按部门直接全领了那就没啥问题，但是当时的状况是个人排队领自己的那一份，如果一个同学直接帮着组里十几个人都拿了，后面排队的人是什么感受呢，甚至有些是看到队伍排长了，就找队伍里自己认识的比较靠前的人说你帮我也拿一份，其实作为我这个比较按规矩办事的“愣头青”来说，我是比较不能接受这两件小事里的行为的，再往下说可能就有点偏激了，先说到这~

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题目介绍

写一个程序找出两个单向链表的交叉起始点，可能是我英语不好，图里画的其实还有一点是交叉以后所有节点都是相同的
Write a program to find the node at which the intersection of two singly linked lists begins.

For example, the following two linked lists:

begin to intersect at node c1.

Example 1:

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Input: intersectVal = 8, listA = [4,1,8,4,5], listB = [5,6,1,8,4,5], skipA = 2, skipB = 3
Output: Reference of the node with value = 8
Input Explanation: The intersected node's value is 8 (note that this must not be 0 if the two lists intersect). From the head of A, it reads as [4,1,8,4,5]. From the head of B, it reads as [5,6,1,8,4,5]. There are 2 nodes before the intersected node in A; There are 3 nodes before the intersected node in B.

分析题解

一开始没什么头绪，感觉只能最原始的遍历，后来看了一些文章，发现比较简单的方式就是先找两个链表的长度差，因为从相交点开始肯定是长度一致的，这是个很好的解题突破口，找到长度差以后就是先跳过长链表的较长部分，然后开始同步遍历比较 A，B 链表；

代码

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public ListNode getIntersectionNode(ListNode headA, ListNode headB) {
        if (headA == null || headB == null) {
            return null;
        }
        // 算 A 的长度
        int countA = 0;
        ListNode tailA = headA;
        while (tailA != null) {
            tailA = tailA.next;
            countA++;
        }
        // 算 B 的长度
        int countB = 0;
        ListNode tailB = headB;
        while (tailB != null) {
            tailB = tailB.next;
            countB++;
        }
        tailA = headA;
        tailB = headB;
        // 依据长度差，先让长的链表 tail 指针往后移
        if (countA > countB) {
            while (countA > countB) {
                tailA = tailA.next;
                countA--;
            }
        } else if (countA < countB) {
            while (countA < countB) {
                tailB = tailB.next;
                countB--;
            }
        }
        // 然后以相同速度遍历两个链表比较
        while (tailA != null) {
            if (tailA == tailB) {
                return tailA;
            } else {
                tailA = tailA.next;
                tailB = tailB.next;
            }
        }
        return null;
    }

总结

可能缺少这种思维，做的还是比较少，所以没法一下子反应过来，需要锻炼，我的第一反应是两重遍历，不过那样复杂度就高了，这里应该是只有 O(N) 的复杂度。

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}Nicksxs's Blog - What hurts more, the pain of hard work or the pain of regret?

Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

发表于 分类于 ， ， ， 阅读次数： Disqus：

这周回家提前约好了要去老丈人家帮下忙，因为在翻修下老房子，活不是特别整的那种，所以大部分都是自己干，或者找个大工临时干几天（我们这那种比较专业的泥工匠叫做大工），像我这样去帮忙的，就是干点小工（把给大工帮忙的，干些偏体力活的叫做小工）的活。从大学毕业以后真的蛮少帮家里干活了，以前上学的时候放假还是帮家里淘个米，简单的扫地拖地啥的，当然刚高考完的时候，还去我爸厂里帮忙干了几天的活，实在是比较累，不过现在想着是觉得自己那时候比较牛，而不是特别排斥这个活，相对于现在的工作来说，导致了一系列的职业病，颈椎腰背都很僵硬，眼镜也不好，还有反流，像我爸那种活反而是脑力加体力的比较好的结合。
这一天的活前半部分主要是在清理厨房，瓷砖上的油污和墙上天花板上即将脱落的石灰或者白色涂料层，这种活特别是瓷砖上的油污，之前在自己家里也干活，还是比较熟悉的，不过前面主要是LD 在干，我主要是先搞墙上和天花板上的，干活还是很需要技巧的，如果直接去铲，那基本我会变成一个灰人，而且吸一鼻子灰，老丈人比较专业，先接上软管用水冲，一冲效果特别好，有些石灰涂料层直接就冲掉了，冲完之后先用带加长杆的刀片铲铲了一圈墙面，说实话因为老房子之前租出去了，所以墙面什么的被糟蹋的比较难看，一层一层的，不过这还算还好，后面主要是天花板上的，这可难倒我了，从小我爸妈是比较把我当小孩管着，爬上爬下的基本都是我爸搞定，但是到了老丈人家也只得硬着头皮上了，爬到跳（一种建筑工地用的架子）上，还有点晃，小心脏扑通扑通跳，而且带加长杆的铲子还是比较重的，铲一会手也有点累，不过坚持着铲完了，上面还是比较平整的，不过下来的时候又把我难住了🤦‍♂️，往下爬的时候有根杆子要跨过去，由于裤子比较紧，强行一把跨过去怕抽筋，所以以一个非常尴尬的姿势停留休息了一会，再跨了过去，幸好事后问 LD，他们都没看到，哈哈哈，然后就是帮忙一起搞瓷砖上的油污，这个太有经验了，不过老丈人更有意思，一会试试啤酒，一会用用沙子，后面在午饭前基本就弄的比较干净了，就坐着等吃饭了，下午午休了会，就继续干活了。
下午是我这次体验的重点了，因为要清理以前贴的墙纸，真的是个很麻烦的活，只能说贴墙纸的师傅活干得太好了，基本不可能整个撕下来，想用铲子一点点铲下来也不行，太轻了就只铲掉表面一层，太重了就把墙纸跟墙面的石灰啥的整个铲下来了，而且手又累又酸，后来想着是不是继续用水冲一下，对着一小面墙试验了下，效果还不错，但是又发现了个问题，那一面墙又有一块是后面糊上去的，铲掉外层的石灰后不平，然后就是最最重头的，也是让我后遗症持续到第二天的，要把那一块糊上去的水泥敲下来，毛估下大概是敲了80%左右，剩下的我的手已经不会用力了，因为那一块应该是要糊上去的始作俑者，就一块里面凹进去的，我拿着榔头敲到我手已经没法使劲了，而且大下午，感觉没五分钟，我的汗已经糊满脸，眼睛也睁不开，不然就流到眼睛里了，此处获得成就一：用榔头敲墙壁，也是个技术加体力的活，而且需要非常好的技巧，否则手马上就废了，敲下去的反作用力，没一会就不行了，然后是看着老丈人兄弟帮忙拆一个柜子，在我看来是个几天都搞不定的活，他轻轻松松在我敲墙的那会就搞定了，以前总觉得我干的活非常有技术含量，可是这个事情真的也是很有技巧啊，它是个把一间房间分隔开的柜子，从底到顶上，还带着门，我还在旁边帮忙撬一下脚踢，一根木条撬半天，唉，成就二：专业的人就是不一样。
最后就是成就三了：我之前沾沾自喜的跑了多少步，做了什么锻炼，其实都是渣渣，像这样干一天活，没经历过的，基本大半天就废了，反过来说，如果能经常去这么干一天活，跑步啥的都是渣渣，消耗的能量远远超过跑个十公里啥的。

发表于 更新于 分类于 ， 阅读次数： Disqus：

Given a linked list, reverse the nodes of a linked list k at a time and return its modified list.

k is a positive integer and is less than or equal to the length of the linked list. If the number of nodes is not a multiple of k then left-out nodes in the end should remain as it is.

Example:

Given this linked list: 1->2->3->4->5

For k = 2, you should return: 2->1->4->3->5

For k = 3, you should return: 3->2->1->4->5

Note:

  • Only constant extra memory is allowed.
  • You may not alter the values in the list’s nodes, only nodes itself may be changed.

这个题也算是经典中的经典了，各种算法题中的保留曲目，可能不全一样，不过反正都是逆转，这个算是比较难度大的，普通的应该就是整个链表反转，或者只对一个链表中的 m 到 n 位做翻转，这里是 k 个一组做翻转，其实这道题比较难的点是两个，一个是想清楚怎么处理，一个是代码的处理
简单来看下

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public ListNode reverseKGroup(ListNode head, int k) {
    if (k <= 1) {
        return head;
    }
    if (head == null) {
        return null;
    }
    ListNode tempEnd = head;
    ListNode tempHead = head;
    ListNode lastHead = null;
    boolean isHeadSet = false;
    while (true) {
        // k 个一组获取头尾
        for (int i = 0; i < k - 1; i++) {
            System.out.println(tempEnd.val);
            if (tempEnd.next != null) {
                tempEnd  = tempEnd.next;
            } else {
                tempEnd = null;
                break;
            }
        }
        if (tempEnd != null) {
            if (!isHeadSet) {
                // 只有在第一组返回的时候需要赋值给 head
                head = reverse(null, tempHead, tempEnd);
                isHeadSet = !isHeadSet;
            } else {
                // 后面的需要将前一组的尾巴传进去，作为后一组头
                reverse(lastHead, tempHead, tempEnd);
            }
            if (tempHead.next != null) {
                // 如果后续节点还有
                lastHead = tempHead;
                tempEnd = tempHead.next;
                tempHead = tempHead.next;
            } else {
                break;
            }
        } else {
            break;
        }
    }

    return head;
}
public ListNode reverse(ListNode lastHead, ListNode tempHead, ListNode tempEnd) {
    // k 个一组的头尾传进来
    ListNode tail = null;
    while (tail != tempEnd) {
        // tail 表示是将头往后换时，把后面那个先拿着
        tail = tempHead.next;
        // 然后就是交换
        tempHead.next = tempEnd.next;
        tempEnd.next = tempHead;
        tempHead = tail;
    }
    if (lastHead !=null) {
        // 如果不是第一组，则需要接上前一组的尾巴
        lastHead.next = tail;
    }
    return tail;
}

发表于 更新于 分类于 ， ， ， ， ， 阅读次数： Disqus：

用了比较久的 grep 命令，其实都只是用了最最基本的功能来查日志，

譬如

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grep 'xxx' xxxx.log

然后有挺多情况比如想要找日志里带一些符号什么的，就需要用到一些特殊的

比如这样\"userId\":\"123456\"，因为比如用户 ID 有时候会跟其他的 id 一样，只用具体的值 123456 来查的话干扰信息太多了，如果直接这样

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grep '\"userId\":\"123456\"' xxxx.log

好像不行，盲猜就是符号的问题，特别是\和"这两个，

之前一直是想试一下，但是没成功，昨天在排查一个问题的时候发现了，只要把这些都转义了就行了

grep '\\\"userId\\\":\\\"123456\\\"' xxxx.log

发表于 更新于 分类于 ， ， ， 阅读次数： Disqus：

原谅我的标题党，其实这些工具的确很厉害，之前其实介绍过一点相关的，是从我一次问题排查的过程中用到的，但是最近又有碰到一次排查问题，发现其实用 idea 直接 dump thread 是不现实的，毕竟服务器环境的没法这么操作，那就得用 Java 的那些工具了

jstack & jps

譬如 jstack，这个命令其实不能更简单了
看看 help 信息

用-l参数可以打出锁的额外信息，然后后面的 pid 就是进程 id 咯，机智的小伙伴会问了（就你这个小白才问这么蠢的问题🤦‍♂️），怎么看 Java 应用的进程呢
那就是 jps 了，命令也很简单，一般直接用 jps命令就好了，不过也可以 help 看一下

稍微解释下，-q是只显示进程 id，-m是输出给main 方法的参数，比如我在配置中加给参数

然后用 jps -m查看

-v加上小 v 的话就是打印 jvm 参数

还是有点东西，然后就继续介绍 jstack 了，然后我们看看 jstack 出来是啥，为了加点内容我加了个死锁

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public static void main(String[] args) throws InterruptedException {
        SpringApplication.run(ThreadDumpDemoApplication.class, args);
        ReentrantLock lock1 = new ReentrantLock();
        ReentrantLock lock2 = new ReentrantLock();
        Thread t1 = new Thread() {
            @Override
            public void run() {
                try {
                    lock1.lock();
                    TimeUnit.SECONDS.sleep(1);
                    lock2.lock();
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            }
        };
        Thread t2 = new Thread() {
            @Override
            public void run() {
                try {
                    lock2.lock();
                    TimeUnit.SECONDS.sleep(1);
                    lock1.lock();
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            }
        };
        t1.setName("mythread1");
        t2.setName("mythread2");
        t1.start();
        t2.start();
        Thread.sleep(10000);
    }

然后看看出来时怎么样的

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2020-08-02 21:50:32
Full thread dump Java HotSpot(TM) 64-Bit Server VM (25.201-b09 mixed mode):

"DestroyJavaVM" #147 prio=5 os_prio=31 tid=0x00007fc9dd807000 nid=0x2603 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"mythread2" #140 prio=5 os_prio=31 tid=0x00007fc9dd877000 nid=0x9903 waiting on condition [0x0000700006fb9000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$2.run(ThreadDumpDemoApplication.java:34)

   Locked ownable synchronizers:
        - <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)

"mythread1" #139 prio=5 os_prio=31 tid=0x00007fc9de873800 nid=0x9a03 waiting on condition [0x0000700006eb6000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$1.run(ThreadDumpDemoApplication.java:22)

   Locked ownable synchronizers:
        - <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)

"http-nio-8080-Acceptor" #137 daemon prio=5 os_prio=31 tid=0x00007fc9de1ac000 nid=0x9b03 runnable [0x0000700006db3000]
   java.lang.Thread.State: RUNNABLE
        at sun.nio.ch.ServerSocketChannelImpl.accept0(Native Method)
        at sun.nio.ch.ServerSocketChannelImpl.accept(ServerSocketChannelImpl.java:422)
        at sun.nio.ch.ServerSocketChannelImpl.accept(ServerSocketChannelImpl.java:250)
        - locked <0x000000076f1e4820> (a java.lang.Object)
        at org.apache.tomcat.util.net.NioEndpoint.serverSocketAccept(NioEndpoint.java:469)
        at org.apache.tomcat.util.net.NioEndpoint.serverSocketAccept(NioEndpoint.java:71)
        at org.apache.tomcat.util.net.Acceptor.run(Acceptor.java:95)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-ClientPoller" #136 daemon prio=5 os_prio=31 tid=0x00007fc9dd876800 nid=0x6503 runnable [0x0000700006cb0000]
   java.lang.Thread.State: RUNNABLE
        at sun.nio.ch.KQueueArrayWrapper.kevent0(Native Method)
        at sun.nio.ch.KQueueArrayWrapper.poll(KQueueArrayWrapper.java:198)
        at sun.nio.ch.KQueueSelectorImpl.doSelect(KQueueSelectorImpl.java:117)
        at sun.nio.ch.SelectorImpl.lockAndDoSelect(SelectorImpl.java:86)
        - locked <0x000000076f2978c8> (a sun.nio.ch.Util$3)
        - locked <0x000000076f2978b8> (a java.util.Collections$UnmodifiableSet)
        - locked <0x000000076f297798> (a sun.nio.ch.KQueueSelectorImpl)
        at sun.nio.ch.SelectorImpl.select(SelectorImpl.java:97)
        at org.apache.tomcat.util.net.NioEndpoint$Poller.run(NioEndpoint.java:709)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-10" #135 daemon prio=5 os_prio=31 tid=0x00007fc9de1af000 nid=0x9d03 waiting on condition [0x0000700006bad000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-9" #134 daemon prio=5 os_prio=31 tid=0x00007fc9de1ab800 nid=0x6403 waiting on condition [0x0000700006aaa000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-8" #133 daemon prio=5 os_prio=31 tid=0x00007fc9de873000 nid=0x9f03 waiting on condition [0x00007000069a7000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-7" #132 daemon prio=5 os_prio=31 tid=0x00007fc9df0a1800 nid=0xa103 waiting on condition [0x00007000068a4000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-6" #131 daemon prio=5 os_prio=31 tid=0x00007fc9df242800 nid=0x6103 waiting on condition [0x00007000067a1000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-5" #130 daemon prio=5 os_prio=31 tid=0x00007fc9de872000 nid=0x5f03 waiting on condition [0x000070000669e000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-4" #129 daemon prio=5 os_prio=31 tid=0x00007fc9de1a6000 nid=0x5e03 waiting on condition [0x000070000659b000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-3" #128 daemon prio=5 os_prio=31 tid=0x00007fc9de871800 nid=0x5c03 waiting on condition [0x0000700006498000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-2" #127 daemon prio=5 os_prio=31 tid=0x00007fc9dead9000 nid=0x5b03 waiting on condition [0x0000700006395000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-1" #126 daemon prio=5 os_prio=31 tid=0x00007fc9ddb00000 nid=0x5a03 waiting on condition [0x0000700006292000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-BlockPoller" #125 daemon prio=5 os_prio=31 tid=0x00007fc9df242000 nid=0xa503 runnable [0x000070000618f000]
   java.lang.Thread.State: RUNNABLE
        at sun.nio.ch.KQueueArrayWrapper.kevent0(Native Method)
        at sun.nio.ch.KQueueArrayWrapper.poll(KQueueArrayWrapper.java:198)
        at sun.nio.ch.KQueueSelectorImpl.doSelect(KQueueSelectorImpl.java:117)
        at sun.nio.ch.SelectorImpl.lockAndDoSelect(SelectorImpl.java:86)
        - locked <0x000000076f1eea30> (a sun.nio.ch.Util$3)
        - locked <0x000000076f1ee198> (a java.util.Collections$UnmodifiableSet)
        - locked <0x000000076f1ee010> (a sun.nio.ch.KQueueSelectorImpl)
        at sun.nio.ch.SelectorImpl.select(SelectorImpl.java:97)
        at org.apache.tomcat.util.net.NioBlockingSelector$BlockPoller.run(NioBlockingSelector.java:313)

   Locked ownable synchronizers:
        - None

"container-0" #124 prio=5 os_prio=31 tid=0x00007fc9df06a000 nid=0x5803 waiting on condition [0x000070000608c000]
   java.lang.Thread.State: TIMED_WAITING (sleeping)
        at java.lang.Thread.sleep(Native Method)
        at org.apache.catalina.core.StandardServer.await(StandardServer.java:570)
        at org.springframework.boot.web.embedded.tomcat.TomcatWebServer$1.run(TomcatWebServer.java:197)

   Locked ownable synchronizers:
        - None

"Catalina-utility-2" #123 prio=1 os_prio=31 tid=0x00007fc9de886000 nid=0xa80f waiting on condition [0x0000700005f89000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076c88ab58> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1088)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"Catalina-utility-1" #122 prio=1 os_prio=31 tid=0x00007fc9de884000 nid=0x5667 waiting on condition [0x0000700005e86000]
   java.lang.Thread.State: TIMED_WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076c88ab58> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:215)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:2078)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1093)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"RMI Scheduler(0)" #15 daemon prio=5 os_prio=31 tid=0x00007fc9de9ee000 nid=0x5503 waiting on condition [0x0000700005d83000]
   java.lang.Thread.State: TIMED_WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x00000006c0015410> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:215)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:2078)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1093)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"Attach Listener" #13 daemon prio=9 os_prio=31 tid=0x00007fc9df149800 nid=0x3c07 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"RMI TCP Accept-0" #11 daemon prio=5 os_prio=31 tid=0x00007fc9df100000 nid=0x4003 runnable [0x0000700005977000]
   java.lang.Thread.State: RUNNABLE
        at java.net.PlainSocketImpl.socketAccept(Native Method)
        at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:409)
        at java.net.ServerSocket.implAccept(ServerSocket.java:545)
        at java.net.ServerSocket.accept(ServerSocket.java:513)
        at sun.management.jmxremote.LocalRMIServerSocketFactory$1.accept(LocalRMIServerSocketFactory.java:52)
        at sun.rmi.transport.tcp.TCPTransport$AcceptLoop.executeAcceptLoop(TCPTransport.java:405)
        at sun.rmi.transport.tcp.TCPTransport$AcceptLoop.run(TCPTransport.java:377)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"Service Thread" #9 daemon prio=9 os_prio=31 tid=0x00007fc9df0ce800 nid=0x4103 runnable [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"C1 CompilerThread2" #8 daemon prio=9 os_prio=31 tid=0x00007fc9df0ce000 nid=0x4203 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"C2 CompilerThread1" #7 daemon prio=9 os_prio=31 tid=0x00007fc9de0a3800 nid=0x3503 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"C2 CompilerThread0" #6 daemon prio=9 os_prio=31 tid=0x00007fc9de89b000 nid=0x3403 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"Monitor Ctrl-Break" #5 daemon prio=5 os_prio=31 tid=0x00007fc9df0ca000 nid=0x3303 runnable [0x0000700005468000]
   java.lang.Thread.State: RUNNABLE
        at java.net.SocketInputStream.socketRead0(Native Method)
        at java.net.SocketInputStream.socketRead(SocketInputStream.java:116)
        at java.net.SocketInputStream.read(SocketInputStream.java:171)
        at java.net.SocketInputStream.read(SocketInputStream.java:141)
        at sun.nio.cs.StreamDecoder.readBytes(StreamDecoder.java:284)
        at sun.nio.cs.StreamDecoder.implRead(StreamDecoder.java:326)
        at sun.nio.cs.StreamDecoder.read(StreamDecoder.java:178)
        - locked <0x00000006c001b760> (a java.io.InputStreamReader)
        at java.io.InputStreamReader.read(InputStreamReader.java:184)
        at java.io.BufferedReader.fill(BufferedReader.java:161)
        at java.io.BufferedReader.readLine(BufferedReader.java:324)
        - locked <0x00000006c001b760> (a java.io.InputStreamReader)
        at java.io.BufferedReader.readLine(BufferedReader.java:389)
        at com.intellij.rt.execution.application.AppMainV2$1.run(AppMainV2.java:64)

   Locked ownable synchronizers:
        - None

"Signal Dispatcher" #4 daemon prio=9 os_prio=31 tid=0x00007fc9de824000 nid=0x4503 runnable [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"Finalizer" #3 daemon prio=8 os_prio=31 tid=0x00007fc9dd811800 nid=0x4f03 in Object.wait() [0x0000700005262000]
   java.lang.Thread.State: WAITING (on object monitor)
        at java.lang.Object.wait(Native Method)
        - waiting on <0x00000006c0008348> (a java.lang.ref.ReferenceQueue$Lock)
        at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:144)
        - locked <0x00000006c0008348> (a java.lang.ref.ReferenceQueue$Lock)
        at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:165)
        at java.lang.ref.Finalizer$FinalizerThread.run(Finalizer.java:216)

   Locked ownable synchronizers:
        - None

"Reference Handler" #2 daemon prio=10 os_prio=31 tid=0x00007fc9de02a000 nid=0x5003 in Object.wait() [0x000070000515f000]
   java.lang.Thread.State: WAITING (on object monitor)
        at java.lang.Object.wait(Native Method)
        - waiting on <0x00000006c001b940> (a java.lang.ref.Reference$Lock)
        at java.lang.Object.wait(Object.java:502)
        at java.lang.ref.Reference.tryHandlePending(Reference.java:191)
        - locked <0x00000006c001b940> (a java.lang.ref.Reference$Lock)
        at java.lang.ref.Reference$ReferenceHandler.run(Reference.java:153)

   Locked ownable synchronizers:
        - None

"VM Thread" os_prio=31 tid=0x00007fc9df00b800 nid=0x2c03 runnable 

"GC task thread#0 (ParallelGC)" os_prio=31 tid=0x00007fc9de805000 nid=0x1e07 runnable 

"GC task thread#1 (ParallelGC)" os_prio=31 tid=0x00007fc9de003800 nid=0x2a03 runnable 

"GC task thread#2 (ParallelGC)" os_prio=31 tid=0x00007fc9df002000 nid=0x5403 runnable 

"GC task thread#3 (ParallelGC)" os_prio=31 tid=0x00007fc9df002800 nid=0x5203 runnable 

"VM Periodic Task Thread" os_prio=31 tid=0x00007fc9df11a800 nid=0x3a03 waiting on condition 

JNI global references: 1087


Found one Java-level deadlock:
=============================
"mythread2":
  waiting for ownable synchronizer 0x000000076f5d4330, (a java.util.concurrent.locks.ReentrantLock$NonfairSync),
  which is held by "mythread1"
"mythread1":
  waiting for ownable synchronizer 0x000000076f5d4360, (a java.util.concurrent.locks.ReentrantLock$NonfairSync),
  which is held by "mythread2"

Java stack information for the threads listed above:
===================================================
"mythread2":
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$2.run(ThreadDumpDemoApplication.java:34)
"mythread1":
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$1.run(ThreadDumpDemoApplication.java:22)

Found 1 deadlock.

前面的信息其实上次就看过了，后面就可以发现有个死锁了，

上面比较长，把主要的截出来，就是这边的，这点就很强大了。

jmap

惯例还是看一下帮助信息

这个相对命令比较多，不过因为现在 dump 下来我们可能会用文件模式，然后将文件下载下来使用 mat 进行分析，所以可以使用
jmap -dump:live,format=b,file=heap.bin <pid>
命令照着上面看的就是打印活着的对象，然后以二进制格式，文件名叫 heap.bin 然后最后就是进程 id，打印出来以后可以用 mat 打开

这样就可以很清晰的看到应用里的各种信息，jmap 直接在命令中还可以看很多信息，比如使用jmap -histo <pid>打印对象的实例数和对象占用的内存

jmap -finalizerinfo <pid> 打印正在等候回收的对象

小tips

对于一些应用内存已经占满了，jstack 和 jmap 可能会连不上的情况，可以使用-F参数强制打印线程或者 dump 文件，但是要注意这两者使用的用户必须与 java 进程启动用户一致，并且使用的 jdk 也要一致

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这周因为没有准备技术方面的内容加之之前有想分享下我和跑步的一些事情，我从小学开始就是个体育渣，因为体重大非常胖，小学的时候要做仰卧起坐，基本是一个都起不来，然后那时候跑步也是要我命那种，跟另外一个比较胖的同学在跑步队尾苟延残喘，只有立定跳远还行。

时光飞逝，我在初中高中的时候因为爱打篮球，以为自己体质已经有了质的变化，所以在体育课跑步的时候妄图跟一位体育非常好的同学一起跑，结果跟的快断气了，最终还是确认了自己是个体育渣，特别是到了大学的第一次体测跑一千米，跑完直接吐了，一则是大学太宅不运动，二则的确是底子不好。那么怎么会去跑步了呢，其实也没什么特殊的原因，就是工作以后因为运动得更少，体质差，而且越来越胖，所以就想运动下，加之跑步也是我觉得成本最低的运动了，刚好那时候17 年租的地方附近小区周围的路车不太多，一圈刚好一公里多，就觉得开始跑跑看，其实想想以前觉得一千米是非常远的，学校塑胶跑道才 400 米，一千米要两圈半，太难了，但是后来在这个小区周围跑的时候好像跑了一圈以后还能再跑一点，最后跑了两圈，可把自己牛坏了，我都能跑两千米了，哈哈，这是个什么概念呢，大学里最让我绝望的两项体育相关的内容就是一千米和十二分钟跑，一千米把我跑吐了，十二分钟跑及格五圈半也能让我跑完花一周时间恢复以及提前一周心理压力爆炸，虽然我那时候跑的不快，但是已经能跑两千米了，瞬间让自己自信心爆炸，并且跑完步出完汗的感觉是非常棒的，毕竟吃奶茶鸡排都能心安理得了，谁叫我跑步了呢😄，其实现在回去看，那时候跑得还算快的，因为还比较瘦，现在要跑得那么快心跳就太快了，关于心跳什么的后面说，开始建立起自信心之后，对跑步这件事就开始不那么排斥跟害怕了，毕竟我能跑两千米了，然后试试三公里，哇，也可以了呢，三公里是什么概念呢，我大学里跑过最多的一次是十二分钟跑五圈半还是六圈，也就是两公里多，不到三公里，几乎是生涯最长了，一时间产生了一些我可能是个被埋没的运动天才的错觉，其实细想下也能明白，只是速度足够慢了就能跑多一点，毕竟提测一千米是要跑进四分钟才及格，自己跑的时候一千米跑六分多钟已经算不慢了（对我自己来说），但是即使是这样还是对把跑步坚持下去这件事有了很大的正面激励作用，并且由于那时候上下班骑车，整个体重控制的比较理想，导致一时间误会跑步就能非常快的减肥（其实这是我跑步历程中比较大的误区之一），因为会在跑步前后称下体重，如果跑个五公里（后面可以跑五公里了），可能体重就能降 0.5 千克，但实际上这只是这五公里跑步身体流失的水分，喝杯水就回来了，那时候能控制体重主要是骑车跟跑步一起的作用，并且工作压力相对来讲比较小，没有过劳肥。

后面其实跑步慢慢变得一个比较习惯的运动了，从三公里，到五公里，到七公里，再到十公里，十公里差不多对我来说是个坎，一直还不能比较轻松的跑十公里，可能近一两年好了一些（原谅我只是跟自己比较，跟那些大神比差得不知道多远），其实对我来说每次都是个突破，因为其实与他人比较没有特别大意义，比较顶尖的差得太远，比较普通的也不行，都会打击自信心，比较比我差的就更没意义了，所以其实能挑战自己，能把自己的上限提高才是最有意义的，这也是我看着朋友圈里的一些大神的速度除了佩服赞叹之外没什么其他的惭愧或者说嫌弃自己的感觉（阿 Q 精神😄）。

一直感性地觉得，跑步能解压，跑完浑身汗，有种把身体的负能量都排出去的感觉，也把吃太多的罪恶感排解掉了🤦‍♂️，之前朋友有看一本书，书名差不多叫越跑越接近自己，这个也是我觉得挺准确的一句话，当跑到接近极限了，还想再继续再跑一点，再跑一点就能突破自己上一次的最远记录了，再跑一点就能又一次突破自己了，成人以后，毕业以后，进入社会以后，世事总是难以件件顺遂，磕磕绊绊的往前走，总觉得要崩溃了，但是还是得坚持，再熬一下，再拼一下，可能还是失败，但人生呢，运气好的人和事总是小概率的，唯有面对挫折，还是日拱一卒，来日方长，我们再坚持下，没准下一次，没准再跑一会，就能突破自己，达到新的境界。

另外个人后期对跑步的一些知识和理解也变得深入一些，比如伤膝盖，其实跑步的确伤膝盖，需要做一些准备和防护，最好的是适合自己的跑鞋和比较好的路（最好的是塑胶跑道了），也要注意热身跟跑后的拉伸（虽然我做的很差），还有就是注意心率，每个人有自己的适宜心率，我这就不冒充科普达人了，可以自行搜索关键字，先说到这吧~

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Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

发表于 分类于 ， ， ， 阅读次数： Disqus：

这周回家提前约好了要去老丈人家帮下忙，因为在翻修下老房子，活不是特别整的那种，所以大部分都是自己干，或者找个大工临时干几天（我们这那种比较专业的泥工匠叫做大工），像我这样去帮忙的，就是干点小工（把给大工帮忙的，干些偏体力活的叫做小工）的活。从大学毕业以后真的蛮少帮家里干活了，以前上学的时候放假还是帮家里淘个米，简单的扫地拖地啥的，当然刚高考完的时候，还去我爸厂里帮忙干了几天的活，实在是比较累，不过现在想着是觉得自己那时候比较牛，而不是特别排斥这个活，相对于现在的工作来说，导致了一系列的职业病，颈椎腰背都很僵硬，眼镜也不好，还有反流，像我爸那种活反而是脑力加体力的比较好的结合。
这一天的活前半部分主要是在清理厨房，瓷砖上的油污和墙上天花板上即将脱落的石灰或者白色涂料层，这种活特别是瓷砖上的油污，之前在自己家里也干活，还是比较熟悉的，不过前面主要是LD 在干，我主要是先搞墙上和天花板上的，干活还是很需要技巧的，如果直接去铲，那基本我会变成一个灰人，而且吸一鼻子灰，老丈人比较专业，先接上软管用水冲，一冲效果特别好，有些石灰涂料层直接就冲掉了，冲完之后先用带加长杆的刀片铲铲了一圈墙面，说实话因为老房子之前租出去了，所以墙面什么的被糟蹋的比较难看，一层一层的，不过这还算还好，后面主要是天花板上的，这可难倒我了，从小我爸妈是比较把我当小孩管着，爬上爬下的基本都是我爸搞定，但是到了老丈人家也只得硬着头皮上了，爬到跳（一种建筑工地用的架子）上，还有点晃，小心脏扑通扑通跳，而且带加长杆的铲子还是比较重的，铲一会手也有点累，不过坚持着铲完了，上面还是比较平整的，不过下来的时候又把我难住了🤦‍♂️，往下爬的时候有根杆子要跨过去，由于裤子比较紧，强行一把跨过去怕抽筋，所以以一个非常尴尬的姿势停留休息了一会，再跨了过去，幸好事后问 LD，他们都没看到，哈哈哈，然后就是帮忙一起搞瓷砖上的油污，这个太有经验了，不过老丈人更有意思，一会试试啤酒，一会用用沙子，后面在午饭前基本就弄的比较干净了，就坐着等吃饭了，下午午休了会，就继续干活了。
下午是我这次体验的重点了，因为要清理以前贴的墙纸，真的是个很麻烦的活，只能说贴墙纸的师傅活干得太好了，基本不可能整个撕下来，想用铲子一点点铲下来也不行，太轻了就只铲掉表面一层，太重了就把墙纸跟墙面的石灰啥的整个铲下来了，而且手又累又酸，后来想着是不是继续用水冲一下，对着一小面墙试验了下，效果还不错，但是又发现了个问题，那一面墙又有一块是后面糊上去的，铲掉外层的石灰后不平，然后就是最最重头的，也是让我后遗症持续到第二天的，要把那一块糊上去的水泥敲下来，毛估下大概是敲了80%左右，剩下的我的手已经不会用力了，因为那一块应该是要糊上去的始作俑者，就一块里面凹进去的，我拿着榔头敲到我手已经没法使劲了，而且大下午，感觉没五分钟，我的汗已经糊满脸，眼睛也睁不开，不然就流到眼睛里了，此处获得成就一：用榔头敲墙壁，也是个技术加体力的活，而且需要非常好的技巧，否则手马上就废了，敲下去的反作用力，没一会就不行了，然后是看着老丈人兄弟帮忙拆一个柜子，在我看来是个几天都搞不定的活，他轻轻松松在我敲墙的那会就搞定了，以前总觉得我干的活非常有技术含量，可是这个事情真的也是很有技巧啊，它是个把一间房间分隔开的柜子，从底到顶上，还带着门，我还在旁边帮忙撬一下脚踢，一根木条撬半天，唉，成就二：专业的人就是不一样。
最后就是成就三了：我之前沾沾自喜的跑了多少步，做了什么锻炼，其实都是渣渣，像这样干一天活，没经历过的，基本大半天就废了，反过来说，如果能经常去这么干一天活，跑步啥的都是渣渣，消耗的能量远远超过跑个十公里啥的。

发表于 更新于 分类于 ， 阅读次数： Disqus：

Given a linked list, reverse the nodes of a linked list k at a time and return its modified list.

k is a positive integer and is less than or equal to the length of the linked list. If the number of nodes is not a multiple of k then left-out nodes in the end should remain as it is.

Example:

Given this linked list: 1->2->3->4->5

For k = 2, you should return: 2->1->4->3->5

For k = 3, you should return: 3->2->1->4->5

Note:

  • Only constant extra memory is allowed.
  • You may not alter the values in the list’s nodes, only nodes itself may be changed.

这个题也算是经典中的经典了，各种算法题中的保留曲目，可能不全一样，不过反正都是逆转，这个算是比较难度大的，普通的应该就是整个链表反转，或者只对一个链表中的 m 到 n 位做翻转，这里是 k 个一组做翻转，其实这道题比较难的点是两个，一个是想清楚怎么处理，一个是代码的处理
简单来看下

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public ListNode reverseKGroup(ListNode head, int k) {
    if (k <= 1) {
        return head;
    }
    if (head == null) {
        return null;
    }
    ListNode tempEnd = head;
    ListNode tempHead = head;
    ListNode lastHead = null;
    boolean isHeadSet = false;
    while (true) {
        // k 个一组获取头尾
        for (int i = 0; i < k - 1; i++) {
            System.out.println(tempEnd.val);
            if (tempEnd.next != null) {
                tempEnd  = tempEnd.next;
            } else {
                tempEnd = null;
                break;
            }
        }
        if (tempEnd != null) {
            if (!isHeadSet) {
                // 只有在第一组返回的时候需要赋值给 head
                head = reverse(null, tempHead, tempEnd);
                isHeadSet = !isHeadSet;
            } else {
                // 后面的需要将前一组的尾巴传进去，作为后一组头
                reverse(lastHead, tempHead, tempEnd);
            }
            if (tempHead.next != null) {
                // 如果后续节点还有
                lastHead = tempHead;
                tempEnd = tempHead.next;
                tempHead = tempHead.next;
            } else {
                break;
            }
        } else {
            break;
        }
    }

    return head;
}
public ListNode reverse(ListNode lastHead, ListNode tempHead, ListNode tempEnd) {
    // k 个一组的头尾传进来
    ListNode tail = null;
    while (tail != tempEnd) {
        // tail 表示是将头往后换时，把后面那个先拿着
        tail = tempHead.next;
        // 然后就是交换
        tempHead.next = tempEnd.next;
        tempEnd.next = tempHead;
        tempHead = tail;
    }
    if (lastHead !=null) {
        // 如果不是第一组，则需要接上前一组的尾巴
        lastHead.next = tail;
    }
    return tail;
}

发表于 更新于 分类于 ， ， ， ， ， 阅读次数： Disqus：

用了比较久的 grep 命令，其实都只是用了最最基本的功能来查日志，

譬如

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grep 'xxx' xxxx.log

然后有挺多情况比如想要找日志里带一些符号什么的，就需要用到一些特殊的

比如这样\"userId\":\"123456\"，因为比如用户 ID 有时候会跟其他的 id 一样，只用具体的值 123456 来查的话干扰信息太多了，如果直接这样

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grep '\"userId\":\"123456\"' xxxx.log

好像不行，盲猜就是符号的问题，特别是\和"这两个，

之前一直是想试一下，但是没成功，昨天在排查一个问题的时候发现了，只要把这些都转义了就行了

grep '\\\"userId\\\":\\\"123456\\\"' xxxx.log

发表于 更新于 分类于 ， ， ， 阅读次数： Disqus：

原谅我的标题党，其实这些工具的确很厉害，之前其实介绍过一点相关的，是从我一次问题排查的过程中用到的，但是最近又有碰到一次排查问题，发现其实用 idea 直接 dump thread 是不现实的，毕竟服务器环境的没法这么操作，那就得用 Java 的那些工具了

jstack & jps

譬如 jstack，这个命令其实不能更简单了
看看 help 信息

用-l参数可以打出锁的额外信息，然后后面的 pid 就是进程 id 咯，机智的小伙伴会问了（就你这个小白才问这么蠢的问题🤦‍♂️），怎么看 Java 应用的进程呢
那就是 jps 了，命令也很简单，一般直接用 jps命令就好了，不过也可以 help 看一下

稍微解释下，-q是只显示进程 id，-m是输出给main 方法的参数，比如我在配置中加给参数

然后用 jps -m查看

-v加上小 v 的话就是打印 jvm 参数

还是有点东西，然后就继续介绍 jstack 了，然后我们看看 jstack 出来是啥，为了加点内容我加了个死锁

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public static void main(String[] args) throws InterruptedException {
        SpringApplication.run(ThreadDumpDemoApplication.class, args);
        ReentrantLock lock1 = new ReentrantLock();
        ReentrantLock lock2 = new ReentrantLock();
        Thread t1 = new Thread() {
            @Override
            public void run() {
                try {
                    lock1.lock();
                    TimeUnit.SECONDS.sleep(1);
                    lock2.lock();
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            }
        };
        Thread t2 = new Thread() {
            @Override
            public void run() {
                try {
                    lock2.lock();
                    TimeUnit.SECONDS.sleep(1);
                    lock1.lock();
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            }
        };
        t1.setName("mythread1");
        t2.setName("mythread2");
        t1.start();
        t2.start();
        Thread.sleep(10000);
    }

然后看看出来时怎么样的

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2020-08-02 21:50:32
Full thread dump Java HotSpot(TM) 64-Bit Server VM (25.201-b09 mixed mode):

"DestroyJavaVM" #147 prio=5 os_prio=31 tid=0x00007fc9dd807000 nid=0x2603 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"mythread2" #140 prio=5 os_prio=31 tid=0x00007fc9dd877000 nid=0x9903 waiting on condition [0x0000700006fb9000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$2.run(ThreadDumpDemoApplication.java:34)

   Locked ownable synchronizers:
        - <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)

"mythread1" #139 prio=5 os_prio=31 tid=0x00007fc9de873800 nid=0x9a03 waiting on condition [0x0000700006eb6000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$1.run(ThreadDumpDemoApplication.java:22)

   Locked ownable synchronizers:
        - <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)

"http-nio-8080-Acceptor" #137 daemon prio=5 os_prio=31 tid=0x00007fc9de1ac000 nid=0x9b03 runnable [0x0000700006db3000]
   java.lang.Thread.State: RUNNABLE
        at sun.nio.ch.ServerSocketChannelImpl.accept0(Native Method)
        at sun.nio.ch.ServerSocketChannelImpl.accept(ServerSocketChannelImpl.java:422)
        at sun.nio.ch.ServerSocketChannelImpl.accept(ServerSocketChannelImpl.java:250)
        - locked <0x000000076f1e4820> (a java.lang.Object)
        at org.apache.tomcat.util.net.NioEndpoint.serverSocketAccept(NioEndpoint.java:469)
        at org.apache.tomcat.util.net.NioEndpoint.serverSocketAccept(NioEndpoint.java:71)
        at org.apache.tomcat.util.net.Acceptor.run(Acceptor.java:95)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-ClientPoller" #136 daemon prio=5 os_prio=31 tid=0x00007fc9dd876800 nid=0x6503 runnable [0x0000700006cb0000]
   java.lang.Thread.State: RUNNABLE
        at sun.nio.ch.KQueueArrayWrapper.kevent0(Native Method)
        at sun.nio.ch.KQueueArrayWrapper.poll(KQueueArrayWrapper.java:198)
        at sun.nio.ch.KQueueSelectorImpl.doSelect(KQueueSelectorImpl.java:117)
        at sun.nio.ch.SelectorImpl.lockAndDoSelect(SelectorImpl.java:86)
        - locked <0x000000076f2978c8> (a sun.nio.ch.Util$3)
        - locked <0x000000076f2978b8> (a java.util.Collections$UnmodifiableSet)
        - locked <0x000000076f297798> (a sun.nio.ch.KQueueSelectorImpl)
        at sun.nio.ch.SelectorImpl.select(SelectorImpl.java:97)
        at org.apache.tomcat.util.net.NioEndpoint$Poller.run(NioEndpoint.java:709)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-10" #135 daemon prio=5 os_prio=31 tid=0x00007fc9de1af000 nid=0x9d03 waiting on condition [0x0000700006bad000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-9" #134 daemon prio=5 os_prio=31 tid=0x00007fc9de1ab800 nid=0x6403 waiting on condition [0x0000700006aaa000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-8" #133 daemon prio=5 os_prio=31 tid=0x00007fc9de873000 nid=0x9f03 waiting on condition [0x00007000069a7000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-7" #132 daemon prio=5 os_prio=31 tid=0x00007fc9df0a1800 nid=0xa103 waiting on condition [0x00007000068a4000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-6" #131 daemon prio=5 os_prio=31 tid=0x00007fc9df242800 nid=0x6103 waiting on condition [0x00007000067a1000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-5" #130 daemon prio=5 os_prio=31 tid=0x00007fc9de872000 nid=0x5f03 waiting on condition [0x000070000669e000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-4" #129 daemon prio=5 os_prio=31 tid=0x00007fc9de1a6000 nid=0x5e03 waiting on condition [0x000070000659b000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-3" #128 daemon prio=5 os_prio=31 tid=0x00007fc9de871800 nid=0x5c03 waiting on condition [0x0000700006498000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-2" #127 daemon prio=5 os_prio=31 tid=0x00007fc9dead9000 nid=0x5b03 waiting on condition [0x0000700006395000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-1" #126 daemon prio=5 os_prio=31 tid=0x00007fc9ddb00000 nid=0x5a03 waiting on condition [0x0000700006292000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-BlockPoller" #125 daemon prio=5 os_prio=31 tid=0x00007fc9df242000 nid=0xa503 runnable [0x000070000618f000]
   java.lang.Thread.State: RUNNABLE
        at sun.nio.ch.KQueueArrayWrapper.kevent0(Native Method)
        at sun.nio.ch.KQueueArrayWrapper.poll(KQueueArrayWrapper.java:198)
        at sun.nio.ch.KQueueSelectorImpl.doSelect(KQueueSelectorImpl.java:117)
        at sun.nio.ch.SelectorImpl.lockAndDoSelect(SelectorImpl.java:86)
        - locked <0x000000076f1eea30> (a sun.nio.ch.Util$3)
        - locked <0x000000076f1ee198> (a java.util.Collections$UnmodifiableSet)
        - locked <0x000000076f1ee010> (a sun.nio.ch.KQueueSelectorImpl)
        at sun.nio.ch.SelectorImpl.select(SelectorImpl.java:97)
        at org.apache.tomcat.util.net.NioBlockingSelector$BlockPoller.run(NioBlockingSelector.java:313)

   Locked ownable synchronizers:
        - None

"container-0" #124 prio=5 os_prio=31 tid=0x00007fc9df06a000 nid=0x5803 waiting on condition [0x000070000608c000]
   java.lang.Thread.State: TIMED_WAITING (sleeping)
        at java.lang.Thread.sleep(Native Method)
        at org.apache.catalina.core.StandardServer.await(StandardServer.java:570)
        at org.springframework.boot.web.embedded.tomcat.TomcatWebServer$1.run(TomcatWebServer.java:197)

   Locked ownable synchronizers:
        - None

"Catalina-utility-2" #123 prio=1 os_prio=31 tid=0x00007fc9de886000 nid=0xa80f waiting on condition [0x0000700005f89000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076c88ab58> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1088)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"Catalina-utility-1" #122 prio=1 os_prio=31 tid=0x00007fc9de884000 nid=0x5667 waiting on condition [0x0000700005e86000]
   java.lang.Thread.State: TIMED_WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076c88ab58> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:215)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:2078)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1093)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"RMI Scheduler(0)" #15 daemon prio=5 os_prio=31 tid=0x00007fc9de9ee000 nid=0x5503 waiting on condition [0x0000700005d83000]
   java.lang.Thread.State: TIMED_WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x00000006c0015410> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:215)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:2078)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1093)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"Attach Listener" #13 daemon prio=9 os_prio=31 tid=0x00007fc9df149800 nid=0x3c07 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"RMI TCP Accept-0" #11 daemon prio=5 os_prio=31 tid=0x00007fc9df100000 nid=0x4003 runnable [0x0000700005977000]
   java.lang.Thread.State: RUNNABLE
        at java.net.PlainSocketImpl.socketAccept(Native Method)
        at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:409)
        at java.net.ServerSocket.implAccept(ServerSocket.java:545)
        at java.net.ServerSocket.accept(ServerSocket.java:513)
        at sun.management.jmxremote.LocalRMIServerSocketFactory$1.accept(LocalRMIServerSocketFactory.java:52)
        at sun.rmi.transport.tcp.TCPTransport$AcceptLoop.executeAcceptLoop(TCPTransport.java:405)
        at sun.rmi.transport.tcp.TCPTransport$AcceptLoop.run(TCPTransport.java:377)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"Service Thread" #9 daemon prio=9 os_prio=31 tid=0x00007fc9df0ce800 nid=0x4103 runnable [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"C1 CompilerThread2" #8 daemon prio=9 os_prio=31 tid=0x00007fc9df0ce000 nid=0x4203 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"C2 CompilerThread1" #7 daemon prio=9 os_prio=31 tid=0x00007fc9de0a3800 nid=0x3503 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"C2 CompilerThread0" #6 daemon prio=9 os_prio=31 tid=0x00007fc9de89b000 nid=0x3403 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"Monitor Ctrl-Break" #5 daemon prio=5 os_prio=31 tid=0x00007fc9df0ca000 nid=0x3303 runnable [0x0000700005468000]
   java.lang.Thread.State: RUNNABLE
        at java.net.SocketInputStream.socketRead0(Native Method)
        at java.net.SocketInputStream.socketRead(SocketInputStream.java:116)
        at java.net.SocketInputStream.read(SocketInputStream.java:171)
        at java.net.SocketInputStream.read(SocketInputStream.java:141)
        at sun.nio.cs.StreamDecoder.readBytes(StreamDecoder.java:284)
        at sun.nio.cs.StreamDecoder.implRead(StreamDecoder.java:326)
        at sun.nio.cs.StreamDecoder.read(StreamDecoder.java:178)
        - locked <0x00000006c001b760> (a java.io.InputStreamReader)
        at java.io.InputStreamReader.read(InputStreamReader.java:184)
        at java.io.BufferedReader.fill(BufferedReader.java:161)
        at java.io.BufferedReader.readLine(BufferedReader.java:324)
        - locked <0x00000006c001b760> (a java.io.InputStreamReader)
        at java.io.BufferedReader.readLine(BufferedReader.java:389)
        at com.intellij.rt.execution.application.AppMainV2$1.run(AppMainV2.java:64)

   Locked ownable synchronizers:
        - None

"Signal Dispatcher" #4 daemon prio=9 os_prio=31 tid=0x00007fc9de824000 nid=0x4503 runnable [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"Finalizer" #3 daemon prio=8 os_prio=31 tid=0x00007fc9dd811800 nid=0x4f03 in Object.wait() [0x0000700005262000]
   java.lang.Thread.State: WAITING (on object monitor)
        at java.lang.Object.wait(Native Method)
        - waiting on <0x00000006c0008348> (a java.lang.ref.ReferenceQueue$Lock)
        at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:144)
        - locked <0x00000006c0008348> (a java.lang.ref.ReferenceQueue$Lock)
        at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:165)
        at java.lang.ref.Finalizer$FinalizerThread.run(Finalizer.java:216)

   Locked ownable synchronizers:
        - None

"Reference Handler" #2 daemon prio=10 os_prio=31 tid=0x00007fc9de02a000 nid=0x5003 in Object.wait() [0x000070000515f000]
   java.lang.Thread.State: WAITING (on object monitor)
        at java.lang.Object.wait(Native Method)
        - waiting on <0x00000006c001b940> (a java.lang.ref.Reference$Lock)
        at java.lang.Object.wait(Object.java:502)
        at java.lang.ref.Reference.tryHandlePending(Reference.java:191)
        - locked <0x00000006c001b940> (a java.lang.ref.Reference$Lock)
        at java.lang.ref.Reference$ReferenceHandler.run(Reference.java:153)

   Locked ownable synchronizers:
        - None

"VM Thread" os_prio=31 tid=0x00007fc9df00b800 nid=0x2c03 runnable 

"GC task thread#0 (ParallelGC)" os_prio=31 tid=0x00007fc9de805000 nid=0x1e07 runnable 

"GC task thread#1 (ParallelGC)" os_prio=31 tid=0x00007fc9de003800 nid=0x2a03 runnable 

"GC task thread#2 (ParallelGC)" os_prio=31 tid=0x00007fc9df002000 nid=0x5403 runnable 

"GC task thread#3 (ParallelGC)" os_prio=31 tid=0x00007fc9df002800 nid=0x5203 runnable 

"VM Periodic Task Thread" os_prio=31 tid=0x00007fc9df11a800 nid=0x3a03 waiting on condition 

JNI global references: 1087


Found one Java-level deadlock:
=============================
"mythread2":
  waiting for ownable synchronizer 0x000000076f5d4330, (a java.util.concurrent.locks.ReentrantLock$NonfairSync),
  which is held by "mythread1"
"mythread1":
  waiting for ownable synchronizer 0x000000076f5d4360, (a java.util.concurrent.locks.ReentrantLock$NonfairSync),
  which is held by "mythread2"

Java stack information for the threads listed above:
===================================================
"mythread2":
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$2.run(ThreadDumpDemoApplication.java:34)
"mythread1":
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$1.run(ThreadDumpDemoApplication.java:22)

Found 1 deadlock.

前面的信息其实上次就看过了，后面就可以发现有个死锁了，

上面比较长，把主要的截出来，就是这边的，这点就很强大了。

jmap

惯例还是看一下帮助信息

这个相对命令比较多，不过因为现在 dump 下来我们可能会用文件模式，然后将文件下载下来使用 mat 进行分析，所以可以使用
jmap -dump:live,format=b,file=heap.bin <pid>
命令照着上面看的就是打印活着的对象，然后以二进制格式，文件名叫 heap.bin 然后最后就是进程 id，打印出来以后可以用 mat 打开

这样就可以很清晰的看到应用里的各种信息，jmap 直接在命令中还可以看很多信息，比如使用jmap -histo <pid>打印对象的实例数和对象占用的内存

jmap -finalizerinfo <pid> 打印正在等候回收的对象

小tips

对于一些应用内存已经占满了，jstack 和 jmap 可能会连不上的情况，可以使用-F参数强制打印线程或者 dump 文件，但是要注意这两者使用的用户必须与 java 进程启动用户一致，并且使用的 jdk 也要一致

发表于 分类于 ， ， 阅读次数： Disqus：

这周因为没有准备技术方面的内容加之之前有想分享下我和跑步的一些事情，我从小学开始就是个体育渣，因为体重大非常胖，小学的时候要做仰卧起坐，基本是一个都起不来，然后那时候跑步也是要我命那种，跟另外一个比较胖的同学在跑步队尾苟延残喘，只有立定跳远还行。

时光飞逝，我在初中高中的时候因为爱打篮球，以为自己体质已经有了质的变化，所以在体育课跑步的时候妄图跟一位体育非常好的同学一起跑，结果跟的快断气了，最终还是确认了自己是个体育渣，特别是到了大学的第一次体测跑一千米，跑完直接吐了，一则是大学太宅不运动，二则的确是底子不好。那么怎么会去跑步了呢，其实也没什么特殊的原因，就是工作以后因为运动得更少，体质差，而且越来越胖，所以就想运动下，加之跑步也是我觉得成本最低的运动了，刚好那时候17 年租的地方附近小区周围的路车不太多，一圈刚好一公里多，就觉得开始跑跑看，其实想想以前觉得一千米是非常远的，学校塑胶跑道才 400 米，一千米要两圈半，太难了，但是后来在这个小区周围跑的时候好像跑了一圈以后还能再跑一点，最后跑了两圈，可把自己牛坏了，我都能跑两千米了，哈哈，这是个什么概念呢，大学里最让我绝望的两项体育相关的内容就是一千米和十二分钟跑，一千米把我跑吐了，十二分钟跑及格五圈半也能让我跑完花一周时间恢复以及提前一周心理压力爆炸，虽然我那时候跑的不快，但是已经能跑两千米了，瞬间让自己自信心爆炸，并且跑完步出完汗的感觉是非常棒的，毕竟吃奶茶鸡排都能心安理得了，谁叫我跑步了呢😄，其实现在回去看，那时候跑得还算快的，因为还比较瘦，现在要跑得那么快心跳就太快了，关于心跳什么的后面说，开始建立起自信心之后，对跑步这件事就开始不那么排斥跟害怕了，毕竟我能跑两千米了，然后试试三公里，哇，也可以了呢，三公里是什么概念呢，我大学里跑过最多的一次是十二分钟跑五圈半还是六圈，也就是两公里多，不到三公里，几乎是生涯最长了，一时间产生了一些我可能是个被埋没的运动天才的错觉，其实细想下也能明白，只是速度足够慢了就能跑多一点，毕竟提测一千米是要跑进四分钟才及格，自己跑的时候一千米跑六分多钟已经算不慢了（对我自己来说），但是即使是这样还是对把跑步坚持下去这件事有了很大的正面激励作用，并且由于那时候上下班骑车，整个体重控制的比较理想，导致一时间误会跑步就能非常快的减肥（其实这是我跑步历程中比较大的误区之一），因为会在跑步前后称下体重，如果跑个五公里（后面可以跑五公里了），可能体重就能降 0.5 千克，但实际上这只是这五公里跑步身体流失的水分，喝杯水就回来了，那时候能控制体重主要是骑车跟跑步一起的作用，并且工作压力相对来讲比较小，没有过劳肥。

后面其实跑步慢慢变得一个比较习惯的运动了，从三公里，到五公里，到七公里，再到十公里，十公里差不多对我来说是个坎，一直还不能比较轻松的跑十公里，可能近一两年好了一些（原谅我只是跟自己比较，跟那些大神比差得不知道多远），其实对我来说每次都是个突破，因为其实与他人比较没有特别大意义，比较顶尖的差得太远，比较普通的也不行，都会打击自信心，比较比我差的就更没意义了，所以其实能挑战自己，能把自己的上限提高才是最有意义的，这也是我看着朋友圈里的一些大神的速度除了佩服赞叹之外没什么其他的惭愧或者说嫌弃自己的感觉（阿 Q 精神😄）。

一直感性地觉得，跑步能解压，跑完浑身汗，有种把身体的负能量都排出去的感觉，也把吃太多的罪恶感排解掉了🤦‍♂️，之前朋友有看一本书，书名差不多叫越跑越接近自己，这个也是我觉得挺准确的一句话，当跑到接近极限了，还想再继续再跑一点，再跑一点就能突破自己上一次的最远记录了，再跑一点就能又一次突破自己了，成人以后，毕业以后，进入社会以后，世事总是难以件件顺遂，磕磕绊绊的往前走，总觉得要崩溃了，但是还是得坚持，再熬一下，再拼一下，可能还是失败，但人生呢，运气好的人和事总是小概率的，唯有面对挫折，还是日拱一卒，来日方长，我们再坚持下，没准下一次，没准再跑一会，就能突破自己，达到新的境界。

另外个人后期对跑步的一些知识和理解也变得深入一些，比如伤膝盖，其实跑步的确伤膝盖，需要做一些准备和防护，最好的是适合自己的跑鞋和比较好的路（最好的是塑胶跑道了），也要注意热身跟跑后的拉伸（虽然我做的很差），还有就是注意心率，每个人有自己的适宜心率，我这就不冒充科普达人了，可以自行搜索关键字，先说到这吧~

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Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

发表于 更新于 分类于 ， ， ， ， 阅读次数： Disqus：

redis是现在服务端很常用的缓存中间件，其实原来还有memcache之类的竞品，但是现在貌似 redis 快一统江湖，这里当然不是在吹，只是个人角度的一个感觉，不权威只是主观感觉。
redis 主要有五种数据结构，Strings，Lists，Sets，Hashes，Sorted Sets，这五种数据结构先简单介绍下，Strings类型的其实就是我们最常用的 key-value，实际开发中也会用的最多；Lists是列表，这个有些会用来做队列，因为 redis 目前常用的版本支持丰富的列表操作；还有是Sets集合，这个主要的特点就是集合中元素不重复，可以用在有这类需求的场景里；Hashes是叫散列，类似于 Python 中的字典结构；还有就是Sorted Sets这个是个有序集合；一眼看这些其实没啥特别的，除了最后这个有序集合，不过去了解背后的实现方式还是比较有意思的。

SDS 简单动态字符串

先从Strings开始说，了解过 C 语言的应该知道，C 语言中的字符串其实是个 char[] 字符数组，redis 也不例外，只是最开始的版本就对这个做了一丢丢的优化，而正是这一丢丢的优化，让这个 redis 的使用效率提升了数倍

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struct sdshdr {
    // 字符串长度
    int len;
    // 字符串空余字符数
    int free;
    // 字符串内容
    char buf[];
};

这里引用了 redis 在 github 上最早的 2.2 版本的代码，代码路径是https://github.com/antirez/redis/blob/2.2/src/sds.h,可以看到这个结构体里只有仨元素，两个 int 型和一个 char 型数组，两个 int 型其实就是我说的优化，因为 C 语言本身的字符串数组，有两个问题，一个是要知道它实际已被占用的长度，需要去遍历这个数组，第二个就是比较容易踩坑的是遍历的时候要注意它有个以\0作为结尾的特点；通过上面的两个 int 型参数，一个是知道字符串目前的长度，一个是知道字符串还剩余多少位空间，这样子坐着两个操作从 O(N)简化到了O(1)了，还有第二个 free 还有个比较重要的作用就是能防止 C 字符串的溢出问题，在存储之前可以先判断 free 长度，如果长度不够就先扩容了，先介绍到这，这个系列可以写蛮多的，慢慢介绍吧

链表

链表是比较常见的数据结构了，但是因为 redis 是用 C 写的，所以在不依赖第三方库的情况下只能自己写一个了，redis 的链表是个有头的链表，而且是无环的，具体的结构我也找了 github 上最早版本的代码

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typedef struct listNode {
    // 前置节点
    struct listNode *prev;
    // 后置节点
    struct listNode *next;
    // 值
    void *value;
} listNode;

typedef struct list {
    // 链表表头
    listNode *head;
    // 当前节点，也可以说是最后节点
    listNode *tail;
    // 节点复制函数
    void *(*dup)(void *ptr);
    // 节点值释放函数
    void (*free)(void *ptr);
    // 节点值比较函数
    int (*match)(void *ptr, void *key);
    // 链表包含的节点数量
    unsigned int len;
} list;

代码地址是这个https://github.com/antirez/redis/blob/2.2/src/adlist.h
可以看下节点是由listNode承载的，包括值和一个指向前节点跟一个指向后一节点的两个指针，然后值是 void 指针类型，所以可以承载不同类型的值
然后是 list结构用来承载一个链表，包含了表头，和表尾，复制函数，释放函数和比较函数，还有链表长度，因为包含了前两个节点，找到表尾节点跟表头都是 O(1)的时间复杂度，还有节点数量，其实这个跟 SDS 是同一个做法，就是空间换时间，这也是写代码里比较常见的做法，以此让一些高频的操作提速。

字典

字典也是个常用的数据结构，其实只是叫法不同，数据结构中叫 hash 散列，Java 中叫 Map，PHP 中是数组 array，Python 中也叫字典 dict，因为纯 C 语言本身不带这些数据结构，所以这也是个痛并快乐着的过程，享受 C 语言的高性能的同时也要接受它只提供了语言的基本功能的现实，各种轮子都需要自己造，redis 同样实现了自己的字典
下面来看看代码

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typedef struct dictEntry {
    void *key;
    void *val;
    struct dictEntry *next;
} dictEntry;

typedef struct dictType {
    unsigned int (*hashFunction)(const void *key);
    void *(*keyDup)(void *privdata, const void *key);
    void *(*valDup)(void *privdata, const void *obj);
    int (*keyCompare)(void *privdata, const void *key1, const void *key2);
    void (*keyDestructor)(void *privdata, void *key);
    void (*valDestructor)(void *privdata, void *obj);
} dictType;

/* This is our hash table structure. Every dictionary has two of this as we
 * implement incremental rehashing, for the old to the new table. */
typedef struct dictht {
    dictEntry **table;
    unsigned long size;
    unsigned long sizemask;
    unsigned long used;
} dictht;

typedef struct dict {
    dictType *type;
    void *privdata;
    dictht ht[2];
    int rehashidx; /* rehashing not in progress if rehashidx == -1 */
    int iterators; /* number of iterators currently running */
} dict;

看了下这个 2.2 版本的代码跟最新版的其实也差的不是很多，所以还是照旧用老代码，可以看到上面四个结构体中，其实只有三个是存储数据用的，dictType 是用来放操作函数的，那么三个存放数据的结构体分别是干嘛的，这时候感觉需要一个图来说明比较好，稍等，我去画个图~

这个图看着应该比较清楚这些都是用来干嘛的了，dict 是我们的主体结构，它有一个指向 dictType 的指针，这里面包含了字典的操作函数，然后是一个私有数据指针，接下来是一个 dictht 的数组，包含两个dictht，这个就是用来存数据的了，然后是 rehashidx 表示重哈希的状态，当是-1 的时候表示当前没有重哈希，iterators 表示正在遍历的迭代器的数量。
首先说说为啥需要有两个 dictht，这是因为字典 dict 这个数据结构随着数据量的增减，会需要在中途做扩容或者缩容操作，如果只有一个的话，对它进行扩容缩容时会影响正常的访问和修改操作，或者说保证正常查询，修改的正确性会比较复杂，并且因为需要高效利用空间，不能一下子申请一个非常大的空间来存很少的数据。当 dict 中 dictht 中的数据量超过 size 的时候负载就超过了 1，就需要进行扩容，这里的其实跟 Java 中的 HashMap 比较类似，超过一定的负载之后进行扩容。这里为啥 size 会超过 1 呢，可能有部分不了解这类结构的同学会比较奇怪，其实就是上图中画的，在数据结构中对于散列的冲突有几类解决方法，比如转换成链表，二次散列，找下个空槽等，这里就使用了链表法，或者说拉链法。当一个新元素通过 hashFunction 得出的 key 跟 sizemask 取模之后的值相同了，那就将其放在原来的节点之前，变成链表挂在数组 dictht.table下面，放在原有节点前是考虑到可能会优先访问。
忘了说明下 dictht 跟 dictEntry 的关系了，dictht 就是个哈希表，它里面是个dictEntry 的二维数组，而 dictEntry 是个包含了 key-value 结构之外还有一个 next 指针，因此可以将哈希冲突的以链表的形式保存下来。
在重点说下重哈希，可能同样写 Java 的同学对这个比较有感觉，跟 HashMap 一样，会以 2 的 N 次方进行扩容，那么扩容的方法就会比较简单，每个键重哈希要不就在原来这个槽，要不就在原来的槽加原 dictht.size 的位置；然后是重头戏，具体是怎么做扩容呢，其实这里就把第二个 ht 用上了，其实这两个hashtable 的具体作用有点类似于 jvm 中的两个 survival 区，但是又不全一样，因为 redis 在扩容的时候是采用的渐进式地重哈希，什么叫渐进式的呢，就是它不是像 jvm 那种标记复制的模式直接将一个 eden 区和原来的 survival 区存活的对象复制到另一个 survival 区，而是在每一次添加，删除，查找或者更新操作时，都会额外的帮忙搬运一部分的原 dictht 中的数据，这里会根据 rehashidx 的值来判断，如果是-1 表示并没有在重哈希中，如果是 0 表示开始重哈希了，然后rehashidx 还会随着每次的帮忙搬运往上加，但全部被搬运完成后 rehashidx 又变回了-1，又可以扯到Java 中的 Concurrent HashMap, 他在扩容的时候也使用了类似的操作。

发表于 更新于 分类于 ， ， 阅读次数： Disqus：

这是个 Java 面试的高频问题，我也遇到过，以往都是觉得这类题没意思，网上一搜一大堆，也不愿意记，其实说回来，主要还是没静下心来好好去理解，今天无意中看到一个课程，基本帮我把一些疑惑的点讲清楚了，首先单例是啥意思，这个其实是有范围一说，比如我起了个Spring Boot应用，在这个应用范围内，我的常规 bean 是单例的，意味着 getBean 的时候其实永远只会拿到那一个对象，那要怎么来写一个单例呢，首先就是传说中的饿汉模式，也是最简单的

饿汉模式

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public class Singleton1 {
    // 首先，将构造方法变成私有的
    private Singleton1() {};
    // 创建私有静态实例，这样第一次使用的时候就会进行创建
    private static Singleton instance = new Singleton1();

    // 使用这个对象都是通过这个 getInstance 来获取
    public static Singleton1 getInstance() {
        return instance;
    }
    // 瞎写一个静态方法。这里想说的是，如果我们只是要调用 Singleton.getDate(...)，
    // 本来是不想要生成 Singleton 实例的，不过没办法，已经生成了
    public static Date getDate(String mode) {return new Date();}
}

上面借鉴了一些代码，其实这是最基本，也不会错的方法，但是正如其中getDate方法里说的问题，有时候并没有想那这个对象，但是因为我调用了这个类的静态方法，导致对象已经生成了，可能这也是饿汉模式名字的来由，不管三七二十一给你生成个单例就完事了，不管有没有用，但是这种个人觉得也没啥大问题，如果是面试的话最好说出来它的缺点

饱汉模式

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public class Singleton2 {
    // 首先，也是先堵死 new Singleton() 这条路,将构造方法变成私有
    private Singleton2() {}
    // 和饿汉模式相比，这边不需要先实例化出来，注意这里的 volatile，它是必须的
    private static volatile Singleton2 instance = null;

    private int m = 9;

    public static Singleton getInstance() {
        if (instance == null) {
            // 加锁
            synchronized (Singleton2.class) {
                // 这一次判断也是必须的，不然会有并发问题
                if (instance == null) {
                    instance = new Singleton2();
                }
            }
        }
        return instance;
    }
}

这里容易错的有三点，理解了其实就比较好记了

第一点，为啥不在 getInstance 上整个代码块加 synchronized，这个其实比较容易理解，就是锁的力度太大，性能太差了，这点其实也要去理解，可以举个夸张的例子，比如我一个电商的服务，如果为了避免一个人的订单出现问题，是不是可以从请求入口就把他锁住，到请求结束释放，那么里面做的事情都有保障，然而这显然不可能，因为我们想要这种竞态条件抢占资源的时间尽量减少，防止其他线程等待。
第二点，为啥synchronized之已经检查了 instance == null,还要在里面再检查一次，这个有个术语，叫 double check lock,但是为啥要这么做呢，其实很简单，想象当有两个线程，都过了第一步为空判断，这个时候只有一个线程能拿到这个锁，另一个线程就等待了，如果不再判断一次，那么第一个线程新建完对象释放锁之后，第二个线程又能拿到锁，再去创建一个对象。
第三点，为啥要volatile关键字，原先对它的理解是它修饰的变量在 JMM 中能及时将变量值写到主存中，但是它还有个很重要的作用，就是防止指令重排序，instance = new Singleton();这行代码其实在底层是分成三条指令执行的，第一条是在堆上申请了一块内存放这个对象，但是对象的字段啥的都还是默认值，第二条是设置对象的值，比如上面的 m 是 9，然后第三条是将这个对象和虚拟机栈上的指针建立引用关联，那么如果我不用volatile关键字，这三条指令就有可能出现重排，比如变成了 1-3-2 这种顺序，当执行完第二步时，有个线程来访问这个对象了，先判断是不是空，发现不是空的，就拿去直接用了，是不是就出现问题了，所以这个volatile也是不可缺少的

嵌套类

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public class Singleton3 {

    private Singleton3() {}
    // 主要是使用了 嵌套类可以访问外部类的静态属性和静态方法 的特性
    private static class Holder {
        private static Singleton3 instance = new Singleton3();
    }
    public static Singleton3 getInstance() {
        return Holder.instance;
    }
}

这个我个人感觉是饿汉模式的升级版，可以在调用getInstance的时候去实例化对象，也是比较推荐的

枚举单例

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public enum Singleton {
    INSTANCE;
    
    public void doSomething(){
        //todo doSomething
    }
}

枚举很特殊，它在类加载的时候会初始化里面的所有的实例，而且 JVM 保证了它们不会再被实例化，所以它天生就是单例的。

发表于 更新于 分类于 ， ， 阅读次数： Disqus：

看完了村上春树的《1Q84》，这应该是第五本看的他的书了，继 跑步，挪威的森林，刺杀骑士团长，海边的卡夫卡之后，不是其中最长的，好像是海边的卡夫卡还是刺杀骑士团长比较长一点，都是在微信读书上看的，比较方便，最开始在上面看的是高晓松的《鱼羊野史》，不知道为啥取这个名字，但是还是满吸引我的，不过由于去年的种种，没有很多心思把它看完，而且本身的组织形式就是比较松散的，看到哪算哪，其实一些野史部分是我比较喜欢，有些谈到人物的就不太有兴趣，而且类似于大祥哥吃的东西，反正都是哇，怎么这么好吃，嗯，太爱（niu）你（bi）了，高晓松就是这个人是我最喜欢的 xxx 家，我也没去细究过他有没有说重复过，反正是不太爱，后来因为这书还一度对战争史有了浓厚的兴趣，然而事实告诉我，大部头的战争史，其实正史我是真的啃不下去，我可能只对其中 10%的内容感兴趣，不过终于也在今年把它看完了，好像高晓松的晓说也最终季了，貌似其中讲朝鲜战争的还被和谐了，看样子是说出了一些故事（truth）。

本来只是想把 《1Q84》的读后感写下，现在觉得还是把这篇当成我今年的读书总结吧，不过先从《1Q84》说起。

严格来讲，这不是很书面化的读后感，可能我想写的也只是像聊天一样的说下我读过的书，包括的技术博客其实也是类似的，以后或许会转变，但是目前水平如此吧，写多了可能会变好，也可能不会。

开始正文吧，这书有点类似于海边的卡夫卡，一开始是通过两条故事线，穿插着叙述，一条是青豆的，不算是个职业杀手的女杀手，要去解决一个经常家暴的斯文败类，穿着描述得比较性感吧，杀人方式是通过比较长的细针，从脖子后面一个精巧的位置插入，可以造成是未知原因死亡的假象，可能会推断成心梗之类的，这里有个前置的细节，就是青豆是乘坐一辆很高级的出租车，内饰什么的都非常有质感，有点不像一辆出租车，然后车里放了一首比较小众的歌，雅纳切克的《小交响曲》，但是青豆知道它，这跟后面的情节也有些许关系，这是女主人公青豆的出场；相应的男主的出场印象不是太深刻，男主叫天吾，是个不知名的作家，跟一个叫小松的编辑有比较好的关系，虽然天吾还没有拿到比较有分量的奖项，但是小松很看好他，也让他帮忙审校一个新作家奖的投稿文章，虽然天吾自身还没获得过这个奖，天吾还有个正式工作，是当数学老师，天吾在学生时代是个数学天才，但后面有对文学产生了兴趣，文学还不足以养活自己，靠着教课还是能保持温饱；

接下来是正式故事的起点了，就是小松收到了一部小说投稿，名叫《空气蛹》，是个叫深绘里的女孩子投的稿，小松对他赋予了很高的评价，这里好像记岔了，好像是天吾对这部小说很有好感，但是小松比较怀疑，然后小松看了之后也有了浓厚的兴趣，这里就是开端了，小松想让天吾来重写润色这部《空气蛹》，因为故事本身很有分量，但是描写手法叙事方式等都很拙劣，而天吾正好擅长这个，小松对天吾的评价是，描写技巧无可挑剔，就是故事主体的火花还没际遇迸发，需要一个导火索，这个就可以类比我们程序员，很多比较初中级的程序员主要擅长在原来的代码上修修改改或者给他分配个小功能，比较高级的程序员就需要能做一些项目的架构设计，核心的技术方案设计，以前我也觉得写文档这个比较无聊，但是当一个项目真的比较庞大，复杂的时候，整体和核心部分的架构设计和方案还是需要有文档沉淀的，不然别人不知道没法接受，自己过段时间也会忘记。

对于小松的这个建议，他的初衷是想搅一搅这个死气沉沉套路颇深的文坛，因为本身《空气蛹》这部小说的内容很吸引人，小松想通过天吾的润色补充让这部小说冲击新人奖，有种恶作剧的意图，天吾对此表示很多担心和顾虑，小松的这个建议其实也是一种文学作假，有两方面的担心，一方面是原作者深绘里是否同意如此操作，一方面是外界如果发现了这个事实会有什么样的后果，但是小松表示不用担心，前一步由小松牵线，让天吾跟原作者深绘里当面沟通这个代写是否被允许，结果当然是被允许了，这里有了对深绘里的初步描写，按我的理解是比较仙的感觉，然后语言沟通有些吃力，或者说有她自己的特色，当面沟通时貌似是让深绘里回去再考虑下，然后后面再由天吾去深绘里寄宿的戎野老师家沟通具体的细节。

2019年12月18日23:37:19 更新
去到戎野老师家之后，天吾知道了关于深绘里的一些事情，深绘里的父亲与戎野老师应该是老友，深绘里的父亲在当初成立了一个叫”先驱”的公社，一个独立运行的社会组织，以运营农场作为物资来源，追求更为松散的共同体，即不过分激进地公有制，进行松散的共同生活，承认私有财产，简而言之就是这样一个能稳定存活下来的独立社会组织，但是随着稳定运行，内部的激进派和稳健派开始出现分歧，不可磨合，后来两派就分裂了，深绘里的父亲，深田保留在了稳健派，但是此时其实深田保内心是矛盾的，以为一开始其实是他倡导的独立革命才组织起了这群人，然而现在他又认清了现实社会已经不太相信能通过革命来独立的可能性，后来激进派便开始越加封闭，而且进行军事训练和思想教育，而后这个先驱的激进派别便有了新的名字”黎明”，深绘里也是在此时从先驱逃离来投靠戎野老师
暂时先写到这，未完待续~

发表于 更新于 分类于 ， ， ， 阅读次数： Disqus：

今天看了一下 redis 分布式锁 redlock 的实现，简单记录下，

加锁

原先我对 redis 锁的概念就是加锁使用 setnx，解锁使用 lua 脚本，但是 setnx 具体是啥，lua 脚本是啥不是很清楚
首先简单思考下这个问题，首先为啥不是先 get 一下 key 存不存在，然后再 set 一个 key value，因为加锁这个操作我们是要保证两点，一个是不能中途被打断，也就是说要原子性，如果是先 get 一下 key，如果不存在再 set 值的话，那就不是原子操作了；第二个是可不可以直接 set 值呢，显然不行，锁要保证唯一性，有且只能有一个线程或者其他应用单位获得该锁，正好 setnx 给了我们这种原子命令

然后是 setnx 的键和值分别是啥，键比较容易想到是要锁住的资源，比如 user_id, 这里有个我自己之前比较容易陷进去的误区，但是这个误区后
面再说，这里其实是把user_id 作为要锁住的资源，在我获得锁的时候别的线程不允许操作，以此保证业务的正确性，不会被多个线程同时修改，确定了键，再来看看值是啥，其实原先我认为值是啥都没关系，我只要锁住了，光键就够我用了，但是考虑下多个线程的问题，如果我这个线程加了锁，然后我因为 gc 停顿等原因卡死了，这个时候redis 的锁或者说就是 redis 的缓存已经过期了，这时候另一个线程获得锁成功，然后我这个线程又活过来了，然后我就仍然认为我拿着锁，我去对数据进行修改或者释放锁，是不是就出现问题了，所以是不是我们还需要一个东西来区分这个锁是哪个线程加的，所以我们可以将值设置成为一个线程独有识别的值，至少在相对长的一段时间内不会重复。

上面其实还有两个问题，一个是当 gc 超时时，我这个线程如何知道我手里的锁已经过期了，一种方法是我在加好锁之后就维护一个超时时间，这里其实还有个问题，不过跟第二个问题相关，就一起说了，就是设置超时时间，有些对于不是锁的 redis 缓存操作可以是先设置好值，然后在设置过期时间，那么这就又有上面说到的不是原子性的问题，那么就需要在同一条指令里把超时时间也设置了，幸好 redis 提供了这种支持

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SET resource_name my_random_value NX PX 30000

这里借鉴一下解释下，resource_name就是 key，代表要锁住的东西，my_random_value就是识别我这个线程的，NX代表只有在不存在的时候才设置，然后PX 30000表示超时时间是 30秒自动过期

PS：记录下我原先有的一个误区，是不是要用 key 来区分加锁的线程，这样只有一个用处，就是自身线程可以识别是否是自己加的锁，但是最大的问题是别的线程不知道，其实这个用户的出发点是我在担心前面提过的一个问题，就是当 gc 停顿后，我要去判断当前的这个锁是否是我加的，还有就是当释放锁的时候，如果保证不会错误释放了其他线程加的锁，但是这样附带很多其他问题，最大的就是其他线程怎么知道能不能加这个锁。

解锁

当线程在锁过期之前就处理完了业务逻辑，那就可以提前释放这个锁，那么提前释放要怎么操作，直接del key显然是不行的，因为这样就是我前面想用线程随机值加资源名作为锁的初衷，我不能去释放别的线程加的锁，那么我要怎么办呢，先 get 一下看是不是我的？那又变成非原子的操作了，幸好redis 也考虑到了这个问题，给了lua 脚本来操作这种

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if redis.call("get",KEYS[1]) == ARGV[1] then
    return redis.call("del",KEYS[1])
else
    return 0
end

这里的KEYS[1]就是前面加锁的resource_name,ARGV[1]就是线程的随机值my_random_value

多节点

前面说的其实是单节点 redis 作为分布式锁的情况，那么当我们的 redis 有多节点的情况呢，如果多节点下处于加锁或者解锁或者锁有效情况下
redis 的某个节点宕掉了怎么办，这里就有一些需要思考的地方，是否单独搞一个单节点的 redis作为分布式锁专用的，但是如果这个单节点的挂了呢，还有就是成本问题，所以我们需要一个多节点的分布式锁方案
这里就引出了开头说到的redlock，这个可是 redis的作者写的, 他的加锁过程是分以下几步去做这个事情

  • 获取当前时间（毫秒数）。
  • 按顺序依次向N个Redis节点执行获取锁的操作。这个获取操作跟前面基于单Redis节点的获取锁的过程相同，包含随机字符串my_random_value，也包含过期时间(比如PX 30000，即锁的有效时间)。为了保证在某个Redis节点不可用的时候算法能够继续运行，这个获取锁的操作还有一个超时时间(time out)，它要远小于锁的有效时间（几十毫秒量级）。客户端在向某个Redis节点获取锁失败以后，应该立即尝试下一个Redis节点。这里的失败，应该包含任何类型的失败，比如该Redis节点不可用，或者该Redis节点上的锁已经被其它客户端持有（注：Redlock原文中这里只提到了Redis节点不可用的情况，但也应该包含其它的失败情况）。
  • 计算整个获取锁的过程总共消耗了多长时间，计算方法是用当前时间减去第1步记录的时间。如果客户端从大多数Redis节点（>= N/2+1）成功获取到了锁，并且获取锁总共消耗的时间没有超过锁的有效时间(lock validity time)，那么这时客户端才认为最终获取锁成功；否则，认为最终获取锁失败。
  • 如果最终获取锁成功了，那么这个锁的有效时间应该重新计算，它等于最初的锁的有效时间减去第3步计算出来的获取锁消耗的时间。
  • 如果最终获取锁失败了（可能由于获取到锁的Redis节点个数少于N/2+1，或者整个获取锁的过程消耗的时间超过了锁的最初有效时间），那么客户端应该立即向所有Redis节点发起释放锁的操作（即前面介绍的Redis Lua脚本）。
    释放锁的过程比较简单：客户端向所有Redis节点发起释放锁的操作，不管这些节点当时在获取锁的时候成功与否。这里为什么要向所有的节点发送释放锁的操作呢，这里是因为有部分的节点的失败原因可能是加锁时阻塞，加锁成功的结果没有及时返回，所以为了防止这种情况还是需要向所有发起这个释放锁的操作。
    初步记录就先到这。

发表于 更新于 分类于 ， ， ， 阅读次数： Disqus：

对 Java 的 gc 实现比较感兴趣，原先一般都是看周志明的书，但其实并没有讲具体的 gc 源码，而是把整个思路和流程讲解了一下
特别是 G1 的具体实现
一般对 G1 的理解其实就是把原先整块的新生代老年代分成了以 region 为单位的小块内存，简而言之，就是原先对新生代老年代的收集会涉及到整个代的堆内存空间，而G1 把它变成了更细致的小块内存
这带来了一个很明显的好处和一个很明显的坏处，好处是内存收集可以更灵活，耗时会变短，但整个收集的处理复杂度就变高了
目前看了一点点关于 G1 收集的预期时间相关的代码

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HeapWord* G1CollectedHeap::do_collection_pause(size_t word_size,
                                               uint gc_count_before,
                                               bool* succeeded,
                                               GCCause::Cause gc_cause) {
  assert_heap_not_locked_and_not_at_safepoint();
  VM_G1CollectForAllocation op(word_size,
                               gc_count_before,
                               gc_cause,
                               false, /* should_initiate_conc_mark */
                               g1_policy()->max_pause_time_ms());
  VMThread::execute(&op);

  HeapWord* result = op.result();
  bool ret_succeeded = op.prologue_succeeded() && op.pause_succeeded();
  assert(result == NULL || ret_succeeded,
         "the result should be NULL if the VM did not succeed");
  *succeeded = ret_succeeded;

  assert_heap_not_locked();
  return result;
}

这里就是收集时需要停顿的，其中VMThread::execute(&op);是具体执行的，真正执行的是VM_G1CollectForAllocation::doit方法

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void VM_G1CollectForAllocation::doit() {
  G1CollectedHeap* g1h = G1CollectedHeap::heap();
  assert(!_should_initiate_conc_mark || g1h->should_do_concurrent_full_gc(_gc_cause),
      "only a GC locker, a System.gc(), stats update, whitebox, or a hum allocation induced GC should start a cycle");

  if (_word_size > 0) {
    // An allocation has been requested. So, try to do that first.
    _result = g1h->attempt_allocation_at_safepoint(_word_size,
                                                   false /* expect_null_cur_alloc_region */);
    if (_result != NULL) {
      // If we can successfully allocate before we actually do the
      // pause then we will consider this pause successful.
      _pause_succeeded = true;
      return;
    }
  }

  GCCauseSetter x(g1h, _gc_cause);
  if (_should_initiate_conc_mark) {
    // It's safer to read old_marking_cycles_completed() here, given
    // that noone else will be updating it concurrently. Since we'll
    // only need it if we're initiating a marking cycle, no point in
    // setting it earlier.
    _old_marking_cycles_completed_before = g1h->old_marking_cycles_completed();

    // At this point we are supposed to start a concurrent cycle. We
    // will do so if one is not already in progress.
    bool res = g1h->g1_policy()->force_initial_mark_if_outside_cycle(_gc_cause);

    // The above routine returns true if we were able to force the
    // next GC pause to be an initial mark; it returns false if a
    // marking cycle is already in progress.
    //
    // If a marking cycle is already in progress just return and skip the
    // pause below - if the reason for requesting this initial mark pause
    // was due to a System.gc() then the requesting thread should block in
    // doit_epilogue() until the marking cycle is complete.
    //
    // If this initial mark pause was requested as part of a humongous
    // allocation then we know that the marking cycle must just have
    // been started by another thread (possibly also allocating a humongous
    // object) as there was no active marking cycle when the requesting
    // thread checked before calling collect() in
    // attempt_allocation_humongous(). Retrying the GC, in this case,
    // will cause the requesting thread to spin inside collect() until the
    // just started marking cycle is complete - which may be a while. So
    // we do NOT retry the GC.
    if (!res) {
      assert(_word_size == 0, "Concurrent Full GC/Humongous Object IM shouldn't be allocating");
      if (_gc_cause != GCCause::_g1_humongous_allocation) {
        _should_retry_gc = true;
      }
      return;
    }
  }

  // Try a partial collection of some kind.
  _pause_succeeded = g1h->do_collection_pause_at_safepoint(_target_pause_time_ms);

  if (_pause_succeeded) {
    if (_word_size > 0) {
      // An allocation had been requested. Do it, eventually trying a stronger
      // kind of GC.
      _result = g1h->satisfy_failed_allocation(_word_size, &_pause_succeeded);
    } else {
      bool should_upgrade_to_full = !g1h->should_do_concurrent_full_gc(_gc_cause) &&
                                    !g1h->has_regions_left_for_allocation();
      if (should_upgrade_to_full) {
        // There has been a request to perform a GC to free some space. We have no
        // information on how much memory has been asked for. In case there are
        // absolutely no regions left to allocate into, do a maximally compacting full GC.
        log_info(gc, ergo)("Attempting maximally compacting collection");
        _pause_succeeded = g1h->do_full_collection(false, /* explicit gc */
                                                   true   /* clear_all_soft_refs */);
      }
    }
    guarantee(_pause_succeeded, "Elevated collections during the safepoint must always succeed.");
  } else {
    assert(_result == NULL, "invariant");
    // The only reason for the pause to not be successful is that, the GC locker is
    // active (or has become active since the prologue was executed). In this case
    // we should retry the pause after waiting for the GC locker to become inactive.
    _should_retry_gc = true;
  }
}

这里可以看到核心的是G1CollectedHeap::do_collection_pause_at_safepoint这个方法，它带上了目标暂停时间的值

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G1CollectedHeap::do_collection_pause_at_safepoint(double target_pause_time_ms) {
  assert_at_safepoint_on_vm_thread();
  guarantee(!is_gc_active(), "collection is not reentrant");

  if (GCLocker::check_active_before_gc()) {
    return false;
  }

  _gc_timer_stw->register_gc_start();

  GCIdMark gc_id_mark;
  _gc_tracer_stw->report_gc_start(gc_cause(), _gc_timer_stw->gc_start());

  SvcGCMarker sgcm(SvcGCMarker::MINOR);
  ResourceMark rm;

  g1_policy()->note_gc_start();

  wait_for_root_region_scanning();

  print_heap_before_gc();
  print_heap_regions();
  trace_heap_before_gc(_gc_tracer_stw);

  _verifier->verify_region_sets_optional();
  _verifier->verify_dirty_young_regions();

  // We should not be doing initial mark unless the conc mark thread is running
  if (!_cm_thread->should_terminate()) {
    // This call will decide whether this pause is an initial-mark
    // pause. If it is, in_initial_mark_gc() will return true
    // for the duration of this pause.
    g1_policy()->decide_on_conc_mark_initiation();
  }

  // We do not allow initial-mark to be piggy-backed on a mixed GC.
  assert(!collector_state()->in_initial_mark_gc() ||
          collector_state()->in_young_only_phase(), "sanity");

  // We also do not allow mixed GCs during marking.
  assert(!collector_state()->mark_or_rebuild_in_progress() || collector_state()->in_young_only_phase(), "sanity");

  // Record whether this pause is an initial mark. When the current
  // thread has completed its logging output and it's safe to signal
  // the CM thread, the flag's value in the policy has been reset.
  bool should_start_conc_mark = collector_state()->in_initial_mark_gc();

  // Inner scope for scope based logging, timers, and stats collection
  {
    EvacuationInfo evacuation_info;

    if (collector_state()->in_initial_mark_gc()) {
      // We are about to start a marking cycle, so we increment the
      // full collection counter.
      increment_old_marking_cycles_started();
      _cm->gc_tracer_cm()->set_gc_cause(gc_cause());
    }

    _gc_tracer_stw->report_yc_type(collector_state()->yc_type());

    GCTraceCPUTime tcpu;

    G1HeapVerifier::G1VerifyType verify_type;
    FormatBuffer<> gc_string("Pause Young ");
    if (collector_state()->in_initial_mark_gc()) {
      gc_string.append("(Concurrent Start)");
      verify_type = G1HeapVerifier::G1VerifyConcurrentStart;
    } else if (collector_state()->in_young_only_phase()) {
      if (collector_state()->in_young_gc_before_mixed()) {
        gc_string.append("(Prepare Mixed)");
      } else {
        gc_string.append("(Normal)");
      }
      verify_type = G1HeapVerifier::G1VerifyYoungNormal;
    } else {
      gc_string.append("(Mixed)");
      verify_type = G1HeapVerifier::G1VerifyMixed;
    }
    GCTraceTime(Info, gc) tm(gc_string, NULL, gc_cause(), true);

    uint active_workers = AdaptiveSizePolicy::calc_active_workers(workers()->total_workers(),
                                                                  workers()->active_workers(),
                                                                  Threads::number_of_non_daemon_threads());
    active_workers = workers()->update_active_workers(active_workers);
    log_info(gc,task)("Using %u workers of %u for evacuation", active_workers, workers()->total_workers());

    TraceCollectorStats tcs(g1mm()->incremental_collection_counters());
    TraceMemoryManagerStats tms(&_memory_manager, gc_cause(),
                                collector_state()->yc_type() == Mixed /* allMemoryPoolsAffected */);

    G1HeapTransition heap_transition(this);
    size_t heap_used_bytes_before_gc = used();

    // Don't dynamically change the number of GC threads this early.  A value of
    // 0 is used to indicate serial work.  When parallel work is done,
    // it will be set.

    { // Call to jvmpi::post_class_unload_events must occur outside of active GC
      IsGCActiveMark x;

      gc_prologue(false);

      if (VerifyRememberedSets) {
        log_info(gc, verify)("[Verifying RemSets before GC]");
        VerifyRegionRemSetClosure v_cl;
        heap_region_iterate(&v_cl);
      }

      _verifier->verify_before_gc(verify_type);

      _verifier->check_bitmaps("GC Start");

#if COMPILER2_OR_JVMCI
      DerivedPointerTable::clear();
#endif

      // Please see comment in g1CollectedHeap.hpp and
      // G1CollectedHeap::ref_processing_init() to see how
      // reference processing currently works in G1.

      // Enable discovery in the STW reference processor
      _ref_processor_stw->enable_discovery();

      {
        // We want to temporarily turn off discovery by the
        // CM ref processor, if necessary, and turn it back on
        // on again later if we do. Using a scoped
        // NoRefDiscovery object will do this.
        NoRefDiscovery no_cm_discovery(_ref_processor_cm);

        // Forget the current alloc region (we might even choose it to be part
        // of the collection set!).
        _allocator->release_mutator_alloc_region();

        // This timing is only used by the ergonomics to handle our pause target.
        // It is unclear why this should not include the full pause. We will
        // investigate this in CR 7178365.
        //
        // Preserving the old comment here if that helps the investigation:
        //
        // The elapsed time induced by the start time below deliberately elides
        // the possible verification above.
        double sample_start_time_sec = os::elapsedTime();

        g1_policy()->record_collection_pause_start(sample_start_time_sec);

        if (collector_state()->in_initial_mark_gc()) {
          concurrent_mark()->pre_initial_mark();
        }

        g1_policy()->finalize_collection_set(target_pause_time_ms, &_survivor);

        evacuation_info.set_collectionset_regions(collection_set()->region_length());

        // Make sure the remembered sets are up to date. This needs to be
        // done before register_humongous_regions_with_cset(), because the
        // remembered sets are used there to choose eager reclaim candidates.
        // If the remembered sets are not up to date we might miss some
        // entries that need to be handled.
        g1_rem_set()->cleanupHRRS();

        register_humongous_regions_with_cset();

        assert(_verifier->check_cset_fast_test(), "Inconsistency in the InCSetState table.");

        // We call this after finalize_cset() to
        // ensure that the CSet has been finalized.
        _cm->verify_no_cset_oops();

        if (_hr_printer.is_active()) {
          G1PrintCollectionSetClosure cl(&_hr_printer);
          _collection_set.iterate(&cl);
        }

        // Initialize the GC alloc regions.
        _allocator->init_gc_alloc_regions(evacuation_info);

        G1ParScanThreadStateSet per_thread_states(this, workers()->active_workers(), collection_set()->young_region_length());
        pre_evacuate_collection_set();

        // Actually do the work...
        evacuate_collection_set(&per_thread_states);

        post_evacuate_collection_set(evacuation_info, &per_thread_states);

        const size_t* surviving_young_words = per_thread_states.surviving_young_words();
        free_collection_set(&_collection_set, evacuation_info, surviving_young_words);

        eagerly_reclaim_humongous_regions();

        record_obj_copy_mem_stats();
        _survivor_evac_stats.adjust_desired_plab_sz();
        _old_evac_stats.adjust_desired_plab_sz();

        double start = os::elapsedTime();
        start_new_collection_set();
        g1_policy()->phase_times()->record_start_new_cset_time_ms((os::elapsedTime() - start) * 1000.0);

        if (evacuation_failed()) {
          set_used(recalculate_used());
          if (_archive_allocator != NULL) {
            _archive_allocator->clear_used();
          }
          for (uint i = 0; i < ParallelGCThreads; i++) {
            if (_evacuation_failed_info_array[i].has_failed()) {
              _gc_tracer_stw->report_evacuation_failed(_evacuation_failed_info_array[i]);
            }
          }
        } else {
          // The "used" of the the collection set have already been subtracted
          // when they were freed.  Add in the bytes evacuated.
          increase_used(g1_policy()->bytes_copied_during_gc());
        }

        if (collector_state()->in_initial_mark_gc()) {
          // We have to do this before we notify the CM threads that
          // they can start working to make sure that all the
          // appropriate initialization is done on the CM object.
          concurrent_mark()->post_initial_mark();
          // Note that we don't actually trigger the CM thread at
          // this point. We do that later when we're sure that
          // the current thread has completed its logging output.
        }

        allocate_dummy_regions();

        _allocator->init_mutator_alloc_region();

        {
          size_t expand_bytes = _heap_sizing_policy->expansion_amount();
          if (expand_bytes > 0) {
            size_t bytes_before = capacity();
            // No need for an ergo logging here,
            // expansion_amount() does this when it returns a value > 0.
            double expand_ms;
            if (!expand(expand_bytes, _workers, &expand_ms)) {
              // We failed to expand the heap. Cannot do anything about it.
            }
            g1_policy()->phase_times()->record_expand_heap_time(expand_ms);
          }
        }

        // We redo the verification but now wrt to the new CSet which
        // has just got initialized after the previous CSet was freed.
        _cm->verify_no_cset_oops();

        // This timing is only used by the ergonomics to handle our pause target.
        // It is unclear why this should not include the full pause. We will
        // investigate this in CR 7178365.
        double sample_end_time_sec = os::elapsedTime();
        double pause_time_ms = (sample_end_time_sec - sample_start_time_sec) * MILLIUNITS;
        size_t total_cards_scanned = g1_policy()->phase_times()->sum_thread_work_items(G1GCPhaseTimes::ScanRS, G1GCPhaseTimes::ScanRSScannedCards);
        g1_policy()->record_collection_pause_end(pause_time_ms, total_cards_scanned, heap_used_bytes_before_gc);

        evacuation_info.set_collectionset_used_before(collection_set()->bytes_used_before());
        evacuation_info.set_bytes_copied(g1_policy()->bytes_copied_during_gc());

        if (VerifyRememberedSets) {
          log_info(gc, verify)("[Verifying RemSets after GC]");
          VerifyRegionRemSetClosure v_cl;
          heap_region_iterate(&v_cl);
        }

        _verifier->verify_after_gc(verify_type);
        _verifier->check_bitmaps("GC End");

        assert(!_ref_processor_stw->discovery_enabled(), "Postcondition");
        _ref_processor_stw->verify_no_references_recorded();

        // CM reference discovery will be re-enabled if necessary.
      }

#ifdef TRACESPINNING
      ParallelTaskTerminator::print_termination_counts();
#endif

      gc_epilogue(false);
    }

    // Print the remainder of the GC log output.
    if (evacuation_failed()) {
      log_info(gc)("To-space exhausted");
    }

    g1_policy()->print_phases();
    heap_transition.print();

    // It is not yet to safe to tell the concurrent mark to
    // start as we have some optional output below. We don't want the
    // output from the concurrent mark thread interfering with this
    // logging output either.

    _hrm.verify_optional();
    _verifier->verify_region_sets_optional();

    TASKQUEUE_STATS_ONLY(print_taskqueue_stats());
    TASKQUEUE_STATS_ONLY(reset_taskqueue_stats());

    print_heap_after_gc();
    print_heap_regions();
    trace_heap_after_gc(_gc_tracer_stw);

    // We must call G1MonitoringSupport::update_sizes() in the same scoping level
    // as an active TraceMemoryManagerStats object (i.e. before the destructor for the
    // TraceMemoryManagerStats is called) so that the G1 memory pools are updated
    // before any GC notifications are raised.
    g1mm()->update_sizes();

    _gc_tracer_stw->report_evacuation_info(&evacuation_info);
    _gc_tracer_stw->report_tenuring_threshold(_g1_policy->tenuring_threshold());
    _gc_timer_stw->register_gc_end();
    _gc_tracer_stw->report_gc_end(_gc_timer_stw->gc_end(), _gc_timer_stw->time_partitions());
  }
  // It should now be safe to tell the concurrent mark thread to start
  // without its logging output interfering with the logging output
  // that came from the pause.

  if (should_start_conc_mark) {
    // CAUTION: after the doConcurrentMark() call below,
    // the concurrent marking thread(s) could be running
    // concurrently with us. Make sure that anything after
    // this point does not assume that we are the only GC thread
    // running. Note: of course, the actual marking work will
    // not start until the safepoint itself is released in
    // SuspendibleThreadSet::desynchronize().
    do_concurrent_mark();
  }

  return true;
}

往下走就是这一步G1Policy::finalize_collection_set,去处理新生代和老年代

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void G1Policy::finalize_collection_set(double target_pause_time_ms, G1SurvivorRegions* survivor) {
  double time_remaining_ms = _collection_set->finalize_young_part(target_pause_time_ms, survivor);
  _collection_set->finalize_old_part(time_remaining_ms);
}

这里分别调用了两个方法，可以看到剩余时间是往下传的，来看一下具体的方法

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double G1CollectionSet::finalize_young_part(double target_pause_time_ms, G1SurvivorRegions* survivors) {
  double young_start_time_sec = os::elapsedTime();

  finalize_incremental_building();

  guarantee(target_pause_time_ms > 0.0,
            "target_pause_time_ms = %1.6lf should be positive", target_pause_time_ms);

  size_t pending_cards = _policy->pending_cards();
  double base_time_ms = _policy->predict_base_elapsed_time_ms(pending_cards);
  double time_remaining_ms = MAX2(target_pause_time_ms - base_time_ms, 0.0);

  log_trace(gc, ergo, cset)("Start choosing CSet. pending cards: " SIZE_FORMAT " predicted base time: %1.2fms remaining time: %1.2fms target pause time: %1.2fms",
                            pending_cards, base_time_ms, time_remaining_ms, target_pause_time_ms);

  // The young list is laid with the survivor regions from the previous
  // pause are appended to the RHS of the young list, i.e.
  //   [Newly Young Regions ++ Survivors from last pause].

  uint survivor_region_length = survivors->length();
  uint eden_region_length = _g1h->eden_regions_count();
  init_region_lengths(eden_region_length, survivor_region_length);

  verify_young_cset_indices();

  // Clear the fields that point to the survivor list - they are all young now.
  survivors->convert_to_eden();

  _bytes_used_before = _inc_bytes_used_before;
  time_remaining_ms = MAX2(time_remaining_ms - _inc_predicted_elapsed_time_ms, 0.0);

  log_trace(gc, ergo, cset)("Add young regions to CSet. eden: %u regions, survivors: %u regions, predicted young region time: %1.2fms, target pause time: %1.2fms",
                            eden_region_length, survivor_region_length, _inc_predicted_elapsed_time_ms, target_pause_time_ms);

  // The number of recorded young regions is the incremental
  // collection set's current size
  set_recorded_rs_lengths(_inc_recorded_rs_lengths);

  double young_end_time_sec = os::elapsedTime();
  phase_times()->record_young_cset_choice_time_ms((young_end_time_sec - young_start_time_sec) * 1000.0);

  return time_remaining_ms;
}

下面是老年代的部分

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void G1CollectionSet::finalize_old_part(double time_remaining_ms) {
  double non_young_start_time_sec = os::elapsedTime();
  double predicted_old_time_ms = 0.0;

  if (collector_state()->in_mixed_phase()) {
    cset_chooser()->verify();
    const uint min_old_cset_length = _policy->calc_min_old_cset_length();
    const uint max_old_cset_length = _policy->calc_max_old_cset_length();

    uint expensive_region_num = 0;
    bool check_time_remaining = _policy->adaptive_young_list_length();

    HeapRegion* hr = cset_chooser()->peek();
    while (hr != NULL) {
      if (old_region_length() >= max_old_cset_length) {
        // Added maximum number of old regions to the CSet.
        log_debug(gc, ergo, cset)("Finish adding old regions to CSet (old CSet region num reached max). old %u regions, max %u regions",
                                  old_region_length(), max_old_cset_length);
        break;
      }

      // Stop adding regions if the remaining reclaimable space is
      // not above G1HeapWastePercent.
      size_t reclaimable_bytes = cset_chooser()->remaining_reclaimable_bytes();
      double reclaimable_percent = _policy->reclaimable_bytes_percent(reclaimable_bytes);
      double threshold = (double) G1HeapWastePercent;
      if (reclaimable_percent <= threshold) {
        // We've added enough old regions that the amount of uncollected
        // reclaimable space is at or below the waste threshold. Stop
        // adding old regions to the CSet.
        log_debug(gc, ergo, cset)("Finish adding old regions to CSet (reclaimable percentage not over threshold). "
                                  "old %u regions, max %u regions, reclaimable: " SIZE_FORMAT "B (%1.2f%%) threshold: " UINTX_FORMAT "%%",
                                  old_region_length(), max_old_cset_length, reclaimable_bytes, reclaimable_percent, G1HeapWastePercent);
        break;
      }

      double predicted_time_ms = predict_region_elapsed_time_ms(hr);
      if (check_time_remaining) {
        if (predicted_time_ms > time_remaining_ms) {
          // Too expensive for the current CSet.

          if (old_region_length() >= min_old_cset_length) {
            // We have added the minimum number of old regions to the CSet,
            // we are done with this CSet.
            log_debug(gc, ergo, cset)("Finish adding old regions to CSet (predicted time is too high). "
                                      "predicted time: %1.2fms, remaining time: %1.2fms old %u regions, min %u regions",
                                      predicted_time_ms, time_remaining_ms, old_region_length(), min_old_cset_length);
            break;
          }

          // We'll add it anyway given that we haven't reached the
          // minimum number of old regions.
          expensive_region_num += 1;
        }
      } else {
        if (old_region_length() >= min_old_cset_length) {
          // In the non-auto-tuning case, we'll finish adding regions
          // to the CSet if we reach the minimum.

          log_debug(gc, ergo, cset)("Finish adding old regions to CSet (old CSet region num reached min). old %u regions, min %u regions",
                                    old_region_length(), min_old_cset_length);
          break;
        }
      }

      // We will add this region to the CSet.
      time_remaining_ms = MAX2(time_remaining_ms - predicted_time_ms, 0.0);
      predicted_old_time_ms += predicted_time_ms;
      cset_chooser()->pop(); // already have region via peek()
      _g1h->old_set_remove(hr);
      add_old_region(hr);

      hr = cset_chooser()->peek();
    }
    if (hr == NULL) {
      log_debug(gc, ergo, cset)("Finish adding old regions to CSet (candidate old regions not available)");
    }

    if (expensive_region_num > 0) {
      // We print the information once here at the end, predicated on
      // whether we added any apparently expensive regions or not, to
      // avoid generating output per region.
      log_debug(gc, ergo, cset)("Added expensive regions to CSet (old CSet region num not reached min)."
                                "old: %u regions, expensive: %u regions, min: %u regions, remaining time: %1.2fms",
                                old_region_length(), expensive_region_num, min_old_cset_length, time_remaining_ms);
    }

    cset_chooser()->verify();
  }

  stop_incremental_building();

  log_debug(gc, ergo, cset)("Finish choosing CSet. old: %u regions, predicted old region time: %1.2fms, time remaining: %1.2f",
                            old_region_length(), predicted_old_time_ms, time_remaining_ms);

  double non_young_end_time_sec = os::elapsedTime();
  phase_times()->record_non_young_cset_choice_time_ms((non_young_end_time_sec - non_young_start_time_sec) * 1000.0);

  QuickSort::sort(_collection_set_regions, _collection_set_cur_length, compare_region_idx, true);
}

上面第三行是个判断，当前是否是 mixed 回收阶段，如果不是的话其实是没有老年代什么事的，所以可以看到代码基本是从这个 if 判断
if (collector_state()->in_mixed_phase()) {开始往下走的
先写到这，偏向于做笔记用，有错轻拍

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Nicksxs's Blog

What hurts more, the pain of hard work or the pain of regret?

发表于 更新于 分类于 ， ， ， ， 阅读次数： Disqus：

redis是现在服务端很常用的缓存中间件，其实原来还有memcache之类的竞品，但是现在貌似 redis 快一统江湖，这里当然不是在吹，只是个人角度的一个感觉，不权威只是主观感觉。
redis 主要有五种数据结构，Strings，Lists，Sets，Hashes，Sorted Sets，这五种数据结构先简单介绍下，Strings类型的其实就是我们最常用的 key-value，实际开发中也会用的最多；Lists是列表，这个有些会用来做队列，因为 redis 目前常用的版本支持丰富的列表操作；还有是Sets集合，这个主要的特点就是集合中元素不重复，可以用在有这类需求的场景里；Hashes是叫散列，类似于 Python 中的字典结构；还有就是Sorted Sets这个是个有序集合；一眼看这些其实没啥特别的，除了最后这个有序集合，不过去了解背后的实现方式还是比较有意思的。

SDS 简单动态字符串

先从Strings开始说，了解过 C 语言的应该知道，C 语言中的字符串其实是个 char[] 字符数组，redis 也不例外，只是最开始的版本就对这个做了一丢丢的优化，而正是这一丢丢的优化，让这个 redis 的使用效率提升了数倍

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struct sdshdr {
    // 字符串长度
    int len;
    // 字符串空余字符数
    int free;
    // 字符串内容
    char buf[];
};

这里引用了 redis 在 github 上最早的 2.2 版本的代码，代码路径是https://github.com/antirez/redis/blob/2.2/src/sds.h,可以看到这个结构体里只有仨元素，两个 int 型和一个 char 型数组，两个 int 型其实就是我说的优化，因为 C 语言本身的字符串数组，有两个问题，一个是要知道它实际已被占用的长度，需要去遍历这个数组，第二个就是比较容易踩坑的是遍历的时候要注意它有个以\0作为结尾的特点；通过上面的两个 int 型参数，一个是知道字符串目前的长度，一个是知道字符串还剩余多少位空间，这样子坐着两个操作从 O(N)简化到了O(1)了，还有第二个 free 还有个比较重要的作用就是能防止 C 字符串的溢出问题，在存储之前可以先判断 free 长度，如果长度不够就先扩容了，先介绍到这，这个系列可以写蛮多的，慢慢介绍吧

链表

链表是比较常见的数据结构了，但是因为 redis 是用 C 写的，所以在不依赖第三方库的情况下只能自己写一个了，redis 的链表是个有头的链表，而且是无环的，具体的结构我也找了 github 上最早版本的代码

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typedef struct listNode {
    // 前置节点
    struct listNode *prev;
    // 后置节点
    struct listNode *next;
    // 值
    void *value;
} listNode;

typedef struct list {
    // 链表表头
    listNode *head;
    // 当前节点，也可以说是最后节点
    listNode *tail;
    // 节点复制函数
    void *(*dup)(void *ptr);
    // 节点值释放函数
    void (*free)(void *ptr);
    // 节点值比较函数
    int (*match)(void *ptr, void *key);
    // 链表包含的节点数量
    unsigned int len;
} list;

代码地址是这个https://github.com/antirez/redis/blob/2.2/src/adlist.h
可以看下节点是由listNode承载的，包括值和一个指向前节点跟一个指向后一节点的两个指针，然后值是 void 指针类型，所以可以承载不同类型的值
然后是 list结构用来承载一个链表，包含了表头，和表尾，复制函数，释放函数和比较函数，还有链表长度，因为包含了前两个节点，找到表尾节点跟表头都是 O(1)的时间复杂度，还有节点数量，其实这个跟 SDS 是同一个做法，就是空间换时间，这也是写代码里比较常见的做法，以此让一些高频的操作提速。

字典

字典也是个常用的数据结构，其实只是叫法不同，数据结构中叫 hash 散列，Java 中叫 Map，PHP 中是数组 array，Python 中也叫字典 dict，因为纯 C 语言本身不带这些数据结构，所以这也是个痛并快乐着的过程，享受 C 语言的高性能的同时也要接受它只提供了语言的基本功能的现实，各种轮子都需要自己造，redis 同样实现了自己的字典
下面来看看代码

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typedef struct dictEntry {
    void *key;
    void *val;
    struct dictEntry *next;
} dictEntry;

typedef struct dictType {
    unsigned int (*hashFunction)(const void *key);
    void *(*keyDup)(void *privdata, const void *key);
    void *(*valDup)(void *privdata, const void *obj);
    int (*keyCompare)(void *privdata, const void *key1, const void *key2);
    void (*keyDestructor)(void *privdata, void *key);
    void (*valDestructor)(void *privdata, void *obj);
} dictType;

/* This is our hash table structure. Every dictionary has two of this as we
 * implement incremental rehashing, for the old to the new table. */
typedef struct dictht {
    dictEntry **table;
    unsigned long size;
    unsigned long sizemask;
    unsigned long used;
} dictht;

typedef struct dict {
    dictType *type;
    void *privdata;
    dictht ht[2];
    int rehashidx; /* rehashing not in progress if rehashidx == -1 */
    int iterators; /* number of iterators currently running */
} dict;

看了下这个 2.2 版本的代码跟最新版的其实也差的不是很多，所以还是照旧用老代码，可以看到上面四个结构体中，其实只有三个是存储数据用的，dictType 是用来放操作函数的，那么三个存放数据的结构体分别是干嘛的，这时候感觉需要一个图来说明比较好，稍等，我去画个图~

这个图看着应该比较清楚这些都是用来干嘛的了，dict 是我们的主体结构，它有一个指向 dictType 的指针，这里面包含了字典的操作函数，然后是一个私有数据指针，接下来是一个 dictht 的数组，包含两个dictht，这个就是用来存数据的了，然后是 rehashidx 表示重哈希的状态，当是-1 的时候表示当前没有重哈希，iterators 表示正在遍历的迭代器的数量。
首先说说为啥需要有两个 dictht，这是因为字典 dict 这个数据结构随着数据量的增减，会需要在中途做扩容或者缩容操作，如果只有一个的话，对它进行扩容缩容时会影响正常的访问和修改操作，或者说保证正常查询，修改的正确性会比较复杂，并且因为需要高效利用空间，不能一下子申请一个非常大的空间来存很少的数据。当 dict 中 dictht 中的数据量超过 size 的时候负载就超过了 1，就需要进行扩容，这里的其实跟 Java 中的 HashMap 比较类似，超过一定的负载之后进行扩容。这里为啥 size 会超过 1 呢，可能有部分不了解这类结构的同学会比较奇怪，其实就是上图中画的，在数据结构中对于散列的冲突有几类解决方法，比如转换成链表，二次散列，找下个空槽等，这里就使用了链表法，或者说拉链法。当一个新元素通过 hashFunction 得出的 key 跟 sizemask 取模之后的值相同了，那就将其放在原来的节点之前，变成链表挂在数组 dictht.table下面，放在原有节点前是考虑到可能会优先访问。
忘了说明下 dictht 跟 dictEntry 的关系了，dictht 就是个哈希表，它里面是个dictEntry 的二维数组，而 dictEntry 是个包含了 key-value 结构之外还有一个 next 指针，因此可以将哈希冲突的以链表的形式保存下来。
在重点说下重哈希，可能同样写 Java 的同学对这个比较有感觉，跟 HashMap 一样，会以 2 的 N 次方进行扩容，那么扩容的方法就会比较简单，每个键重哈希要不就在原来这个槽，要不就在原来的槽加原 dictht.size 的位置；然后是重头戏，具体是怎么做扩容呢，其实这里就把第二个 ht 用上了，其实这两个hashtable 的具体作用有点类似于 jvm 中的两个 survival 区，但是又不全一样，因为 redis 在扩容的时候是采用的渐进式地重哈希，什么叫渐进式的呢，就是它不是像 jvm 那种标记复制的模式直接将一个 eden 区和原来的 survival 区存活的对象复制到另一个 survival 区，而是在每一次添加，删除，查找或者更新操作时，都会额外的帮忙搬运一部分的原 dictht 中的数据，这里会根据 rehashidx 的值来判断，如果是-1 表示并没有在重哈希中，如果是 0 表示开始重哈希了，然后rehashidx 还会随着每次的帮忙搬运往上加，但全部被搬运完成后 rehashidx 又变回了-1，又可以扯到Java 中的 Concurrent HashMap, 他在扩容的时候也使用了类似的操作。

发表于 更新于 分类于 ， ， 阅读次数： Disqus：

这是个 Java 面试的高频问题，我也遇到过，以往都是觉得这类题没意思，网上一搜一大堆，也不愿意记，其实说回来，主要还是没静下心来好好去理解，今天无意中看到一个课程，基本帮我把一些疑惑的点讲清楚了，首先单例是啥意思，这个其实是有范围一说，比如我起了个Spring Boot应用，在这个应用范围内，我的常规 bean 是单例的，意味着 getBean 的时候其实永远只会拿到那一个对象，那要怎么来写一个单例呢，首先就是传说中的饿汉模式，也是最简单的

饿汉模式

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public class Singleton1 {
    // 首先，将构造方法变成私有的
    private Singleton1() {};
    // 创建私有静态实例，这样第一次使用的时候就会进行创建
    private static Singleton instance = new Singleton1();

    // 使用这个对象都是通过这个 getInstance 来获取
    public static Singleton1 getInstance() {
        return instance;
    }
    // 瞎写一个静态方法。这里想说的是，如果我们只是要调用 Singleton.getDate(...)，
    // 本来是不想要生成 Singleton 实例的，不过没办法，已经生成了
    public static Date getDate(String mode) {return new Date();}
}

上面借鉴了一些代码，其实这是最基本，也不会错的方法，但是正如其中getDate方法里说的问题，有时候并没有想那这个对象，但是因为我调用了这个类的静态方法，导致对象已经生成了，可能这也是饿汉模式名字的来由，不管三七二十一给你生成个单例就完事了，不管有没有用，但是这种个人觉得也没啥大问题，如果是面试的话最好说出来它的缺点

饱汉模式

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public class Singleton2 {
    // 首先，也是先堵死 new Singleton() 这条路,将构造方法变成私有
    private Singleton2() {}
    // 和饿汉模式相比，这边不需要先实例化出来，注意这里的 volatile，它是必须的
    private static volatile Singleton2 instance = null;

    private int m = 9;

    public static Singleton getInstance() {
        if (instance == null) {
            // 加锁
            synchronized (Singleton2.class) {
                // 这一次判断也是必须的，不然会有并发问题
                if (instance == null) {
                    instance = new Singleton2();
                }
            }
        }
        return instance;
    }
}

这里容易错的有三点，理解了其实就比较好记了

第一点，为啥不在 getInstance 上整个代码块加 synchronized，这个其实比较容易理解，就是锁的力度太大，性能太差了，这点其实也要去理解，可以举个夸张的例子，比如我一个电商的服务，如果为了避免一个人的订单出现问题，是不是可以从请求入口就把他锁住，到请求结束释放，那么里面做的事情都有保障，然而这显然不可能，因为我们想要这种竞态条件抢占资源的时间尽量减少，防止其他线程等待。
第二点，为啥synchronized之已经检查了 instance == null,还要在里面再检查一次，这个有个术语，叫 double check lock,但是为啥要这么做呢，其实很简单，想象当有两个线程，都过了第一步为空判断，这个时候只有一个线程能拿到这个锁，另一个线程就等待了，如果不再判断一次，那么第一个线程新建完对象释放锁之后，第二个线程又能拿到锁，再去创建一个对象。
第三点，为啥要volatile关键字，原先对它的理解是它修饰的变量在 JMM 中能及时将变量值写到主存中，但是它还有个很重要的作用，就是防止指令重排序，instance = new Singleton();这行代码其实在底层是分成三条指令执行的，第一条是在堆上申请了一块内存放这个对象，但是对象的字段啥的都还是默认值，第二条是设置对象的值，比如上面的 m 是 9，然后第三条是将这个对象和虚拟机栈上的指针建立引用关联，那么如果我不用volatile关键字，这三条指令就有可能出现重排，比如变成了 1-3-2 这种顺序，当执行完第二步时，有个线程来访问这个对象了，先判断是不是空，发现不是空的，就拿去直接用了，是不是就出现问题了，所以这个volatile也是不可缺少的

嵌套类

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public class Singleton3 {

    private Singleton3() {}
    // 主要是使用了 嵌套类可以访问外部类的静态属性和静态方法 的特性
    private static class Holder {
        private static Singleton3 instance = new Singleton3();
    }
    public static Singleton3 getInstance() {
        return Holder.instance;
    }
}

这个我个人感觉是饿汉模式的升级版，可以在调用getInstance的时候去实例化对象，也是比较推荐的

枚举单例

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public enum Singleton {
    INSTANCE;
    
    public void doSomething(){
        //todo doSomething
    }
}

枚举很特殊，它在类加载的时候会初始化里面的所有的实例，而且 JVM 保证了它们不会再被实例化，所以它天生就是单例的。

发表于 更新于 分类于 ， ， 阅读次数： Disqus：

看完了村上春树的《1Q84》，这应该是第五本看的他的书了，继 跑步，挪威的森林，刺杀骑士团长，海边的卡夫卡之后，不是其中最长的，好像是海边的卡夫卡还是刺杀骑士团长比较长一点，都是在微信读书上看的，比较方便，最开始在上面看的是高晓松的《鱼羊野史》，不知道为啥取这个名字，但是还是满吸引我的，不过由于去年的种种，没有很多心思把它看完，而且本身的组织形式就是比较松散的，看到哪算哪，其实一些野史部分是我比较喜欢，有些谈到人物的就不太有兴趣，而且类似于大祥哥吃的东西，反正都是哇，怎么这么好吃，嗯，太爱（niu）你（bi）了，高晓松就是这个人是我最喜欢的 xxx 家，我也没去细究过他有没有说重复过，反正是不太爱，后来因为这书还一度对战争史有了浓厚的兴趣，然而事实告诉我，大部头的战争史，其实正史我是真的啃不下去，我可能只对其中 10%的内容感兴趣，不过终于也在今年把它看完了，好像高晓松的晓说也最终季了，貌似其中讲朝鲜战争的还被和谐了，看样子是说出了一些故事（truth）。

本来只是想把 《1Q84》的读后感写下，现在觉得还是把这篇当成我今年的读书总结吧，不过先从《1Q84》说起。

严格来讲，这不是很书面化的读后感，可能我想写的也只是像聊天一样的说下我读过的书，包括的技术博客其实也是类似的，以后或许会转变，但是目前水平如此吧，写多了可能会变好，也可能不会。

开始正文吧，这书有点类似于海边的卡夫卡，一开始是通过两条故事线，穿插着叙述，一条是青豆的，不算是个职业杀手的女杀手，要去解决一个经常家暴的斯文败类，穿着描述得比较性感吧，杀人方式是通过比较长的细针，从脖子后面一个精巧的位置插入，可以造成是未知原因死亡的假象，可能会推断成心梗之类的，这里有个前置的细节，就是青豆是乘坐一辆很高级的出租车，内饰什么的都非常有质感，有点不像一辆出租车，然后车里放了一首比较小众的歌，雅纳切克的《小交响曲》，但是青豆知道它，这跟后面的情节也有些许关系，这是女主人公青豆的出场；相应的男主的出场印象不是太深刻，男主叫天吾，是个不知名的作家，跟一个叫小松的编辑有比较好的关系，虽然天吾还没有拿到比较有分量的奖项，但是小松很看好他，也让他帮忙审校一个新作家奖的投稿文章，虽然天吾自身还没获得过这个奖，天吾还有个正式工作，是当数学老师，天吾在学生时代是个数学天才，但后面有对文学产生了兴趣，文学还不足以养活自己，靠着教课还是能保持温饱；

接下来是正式故事的起点了，就是小松收到了一部小说投稿，名叫《空气蛹》，是个叫深绘里的女孩子投的稿，小松对他赋予了很高的评价，这里好像记岔了，好像是天吾对这部小说很有好感，但是小松比较怀疑，然后小松看了之后也有了浓厚的兴趣，这里就是开端了，小松想让天吾来重写润色这部《空气蛹》，因为故事本身很有分量，但是描写手法叙事方式等都很拙劣，而天吾正好擅长这个，小松对天吾的评价是，描写技巧无可挑剔，就是故事主体的火花还没际遇迸发，需要一个导火索，这个就可以类比我们程序员，很多比较初中级的程序员主要擅长在原来的代码上修修改改或者给他分配个小功能，比较高级的程序员就需要能做一些项目的架构设计，核心的技术方案设计，以前我也觉得写文档这个比较无聊，但是当一个项目真的比较庞大，复杂的时候，整体和核心部分的架构设计和方案还是需要有文档沉淀的，不然别人不知道没法接受，自己过段时间也会忘记。

对于小松的这个建议，他的初衷是想搅一搅这个死气沉沉套路颇深的文坛，因为本身《空气蛹》这部小说的内容很吸引人，小松想通过天吾的润色补充让这部小说冲击新人奖，有种恶作剧的意图，天吾对此表示很多担心和顾虑，小松的这个建议其实也是一种文学作假，有两方面的担心，一方面是原作者深绘里是否同意如此操作，一方面是外界如果发现了这个事实会有什么样的后果，但是小松表示不用担心，前一步由小松牵线，让天吾跟原作者深绘里当面沟通这个代写是否被允许，结果当然是被允许了，这里有了对深绘里的初步描写，按我的理解是比较仙的感觉，然后语言沟通有些吃力，或者说有她自己的特色，当面沟通时貌似是让深绘里回去再考虑下，然后后面再由天吾去深绘里寄宿的戎野老师家沟通具体的细节。

2019年12月18日23:37:19 更新
去到戎野老师家之后，天吾知道了关于深绘里的一些事情，深绘里的父亲与戎野老师应该是老友，深绘里的父亲在当初成立了一个叫”先驱”的公社，一个独立运行的社会组织，以运营农场作为物资来源，追求更为松散的共同体，即不过分激进地公有制，进行松散的共同生活，承认私有财产，简而言之就是这样一个能稳定存活下来的独立社会组织，但是随着稳定运行，内部的激进派和稳健派开始出现分歧，不可磨合，后来两派就分裂了，深绘里的父亲，深田保留在了稳健派，但是此时其实深田保内心是矛盾的，以为一开始其实是他倡导的独立革命才组织起了这群人，然而现在他又认清了现实社会已经不太相信能通过革命来独立的可能性，后来激进派便开始越加封闭，而且进行军事训练和思想教育，而后这个先驱的激进派别便有了新的名字”黎明”，深绘里也是在此时从先驱逃离来投靠戎野老师
暂时先写到这，未完待续~

发表于 更新于 分类于 ， ， ， 阅读次数： Disqus：

今天看了一下 redis 分布式锁 redlock 的实现，简单记录下，

加锁

原先我对 redis 锁的概念就是加锁使用 setnx，解锁使用 lua 脚本，但是 setnx 具体是啥，lua 脚本是啥不是很清楚
首先简单思考下这个问题，首先为啥不是先 get 一下 key 存不存在，然后再 set 一个 key value，因为加锁这个操作我们是要保证两点，一个是不能中途被打断，也就是说要原子性，如果是先 get 一下 key，如果不存在再 set 值的话，那就不是原子操作了；第二个是可不可以直接 set 值呢，显然不行，锁要保证唯一性，有且只能有一个线程或者其他应用单位获得该锁，正好 setnx 给了我们这种原子命令

然后是 setnx 的键和值分别是啥，键比较容易想到是要锁住的资源，比如 user_id, 这里有个我自己之前比较容易陷进去的误区，但是这个误区后
面再说，这里其实是把user_id 作为要锁住的资源，在我获得锁的时候别的线程不允许操作，以此保证业务的正确性，不会被多个线程同时修改，确定了键，再来看看值是啥，其实原先我认为值是啥都没关系，我只要锁住了，光键就够我用了，但是考虑下多个线程的问题，如果我这个线程加了锁，然后我因为 gc 停顿等原因卡死了，这个时候redis 的锁或者说就是 redis 的缓存已经过期了，这时候另一个线程获得锁成功，然后我这个线程又活过来了，然后我就仍然认为我拿着锁，我去对数据进行修改或者释放锁，是不是就出现问题了，所以是不是我们还需要一个东西来区分这个锁是哪个线程加的，所以我们可以将值设置成为一个线程独有识别的值，至少在相对长的一段时间内不会重复。

上面其实还有两个问题，一个是当 gc 超时时，我这个线程如何知道我手里的锁已经过期了，一种方法是我在加好锁之后就维护一个超时时间，这里其实还有个问题，不过跟第二个问题相关，就一起说了，就是设置超时时间，有些对于不是锁的 redis 缓存操作可以是先设置好值，然后在设置过期时间，那么这就又有上面说到的不是原子性的问题，那么就需要在同一条指令里把超时时间也设置了，幸好 redis 提供了这种支持

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SET resource_name my_random_value NX PX 30000

这里借鉴一下解释下，resource_name就是 key，代表要锁住的东西，my_random_value就是识别我这个线程的，NX代表只有在不存在的时候才设置，然后PX 30000表示超时时间是 30秒自动过期

PS：记录下我原先有的一个误区，是不是要用 key 来区分加锁的线程，这样只有一个用处，就是自身线程可以识别是否是自己加的锁，但是最大的问题是别的线程不知道，其实这个用户的出发点是我在担心前面提过的一个问题，就是当 gc 停顿后，我要去判断当前的这个锁是否是我加的，还有就是当释放锁的时候，如果保证不会错误释放了其他线程加的锁，但是这样附带很多其他问题，最大的就是其他线程怎么知道能不能加这个锁。

解锁

当线程在锁过期之前就处理完了业务逻辑，那就可以提前释放这个锁，那么提前释放要怎么操作，直接del key显然是不行的，因为这样就是我前面想用线程随机值加资源名作为锁的初衷，我不能去释放别的线程加的锁，那么我要怎么办呢，先 get 一下看是不是我的？那又变成非原子的操作了，幸好redis 也考虑到了这个问题，给了lua 脚本来操作这种

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if redis.call("get",KEYS[1]) == ARGV[1] then
    return redis.call("del",KEYS[1])
else
    return 0
end

这里的KEYS[1]就是前面加锁的resource_name,ARGV[1]就是线程的随机值my_random_value

多节点

前面说的其实是单节点 redis 作为分布式锁的情况，那么当我们的 redis 有多节点的情况呢，如果多节点下处于加锁或者解锁或者锁有效情况下
redis 的某个节点宕掉了怎么办，这里就有一些需要思考的地方，是否单独搞一个单节点的 redis作为分布式锁专用的，但是如果这个单节点的挂了呢，还有就是成本问题，所以我们需要一个多节点的分布式锁方案
这里就引出了开头说到的redlock，这个可是 redis的作者写的, 他的加锁过程是分以下几步去做这个事情

  • 获取当前时间（毫秒数）。
  • 按顺序依次向N个Redis节点执行获取锁的操作。这个获取操作跟前面基于单Redis节点的获取锁的过程相同，包含随机字符串my_random_value，也包含过期时间(比如PX 30000，即锁的有效时间)。为了保证在某个Redis节点不可用的时候算法能够继续运行，这个获取锁的操作还有一个超时时间(time out)，它要远小于锁的有效时间（几十毫秒量级）。客户端在向某个Redis节点获取锁失败以后，应该立即尝试下一个Redis节点。这里的失败，应该包含任何类型的失败，比如该Redis节点不可用，或者该Redis节点上的锁已经被其它客户端持有（注：Redlock原文中这里只提到了Redis节点不可用的情况，但也应该包含其它的失败情况）。
  • 计算整个获取锁的过程总共消耗了多长时间，计算方法是用当前时间减去第1步记录的时间。如果客户端从大多数Redis节点（>= N/2+1）成功获取到了锁，并且获取锁总共消耗的时间没有超过锁的有效时间(lock validity time)，那么这时客户端才认为最终获取锁成功；否则，认为最终获取锁失败。
  • 如果最终获取锁成功了，那么这个锁的有效时间应该重新计算，它等于最初的锁的有效时间减去第3步计算出来的获取锁消耗的时间。
  • 如果最终获取锁失败了（可能由于获取到锁的Redis节点个数少于N/2+1，或者整个获取锁的过程消耗的时间超过了锁的最初有效时间），那么客户端应该立即向所有Redis节点发起释放锁的操作（即前面介绍的Redis Lua脚本）。
    释放锁的过程比较简单：客户端向所有Redis节点发起释放锁的操作，不管这些节点当时在获取锁的时候成功与否。这里为什么要向所有的节点发送释放锁的操作呢，这里是因为有部分的节点的失败原因可能是加锁时阻塞，加锁成功的结果没有及时返回，所以为了防止这种情况还是需要向所有发起这个释放锁的操作。
    初步记录就先到这。

发表于 更新于 分类于 ， ， ， 阅读次数： Disqus：

对 Java 的 gc 实现比较感兴趣，原先一般都是看周志明的书，但其实并没有讲具体的 gc 源码，而是把整个思路和流程讲解了一下
特别是 G1 的具体实现
一般对 G1 的理解其实就是把原先整块的新生代老年代分成了以 region 为单位的小块内存，简而言之，就是原先对新生代老年代的收集会涉及到整个代的堆内存空间，而G1 把它变成了更细致的小块内存
这带来了一个很明显的好处和一个很明显的坏处，好处是内存收集可以更灵活，耗时会变短，但整个收集的处理复杂度就变高了
目前看了一点点关于 G1 收集的预期时间相关的代码

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HeapWord* G1CollectedHeap::do_collection_pause(size_t word_size,
                                               uint gc_count_before,
                                               bool* succeeded,
                                               GCCause::Cause gc_cause) {
  assert_heap_not_locked_and_not_at_safepoint();
  VM_G1CollectForAllocation op(word_size,
                               gc_count_before,
                               gc_cause,
                               false, /* should_initiate_conc_mark */
                               g1_policy()->max_pause_time_ms());
  VMThread::execute(&op);

  HeapWord* result = op.result();
  bool ret_succeeded = op.prologue_succeeded() && op.pause_succeeded();
  assert(result == NULL || ret_succeeded,
         "the result should be NULL if the VM did not succeed");
  *succeeded = ret_succeeded;

  assert_heap_not_locked();
  return result;
}

这里就是收集时需要停顿的，其中VMThread::execute(&op);是具体执行的，真正执行的是VM_G1CollectForAllocation::doit方法

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void VM_G1CollectForAllocation::doit() {
  G1CollectedHeap* g1h = G1CollectedHeap::heap();
  assert(!_should_initiate_conc_mark || g1h->should_do_concurrent_full_gc(_gc_cause),
      "only a GC locker, a System.gc(), stats update, whitebox, or a hum allocation induced GC should start a cycle");

  if (_word_size > 0) {
    // An allocation has been requested. So, try to do that first.
    _result = g1h->attempt_allocation_at_safepoint(_word_size,
                                                   false /* expect_null_cur_alloc_region */);
    if (_result != NULL) {
      // If we can successfully allocate before we actually do the
      // pause then we will consider this pause successful.
      _pause_succeeded = true;
      return;
    }
  }

  GCCauseSetter x(g1h, _gc_cause);
  if (_should_initiate_conc_mark) {
    // It's safer to read old_marking_cycles_completed() here, given
    // that noone else will be updating it concurrently. Since we'll
    // only need it if we're initiating a marking cycle, no point in
    // setting it earlier.
    _old_marking_cycles_completed_before = g1h->old_marking_cycles_completed();

    // At this point we are supposed to start a concurrent cycle. We
    // will do so if one is not already in progress.
    bool res = g1h->g1_policy()->force_initial_mark_if_outside_cycle(_gc_cause);

    // The above routine returns true if we were able to force the
    // next GC pause to be an initial mark; it returns false if a
    // marking cycle is already in progress.
    //
    // If a marking cycle is already in progress just return and skip the
    // pause below - if the reason for requesting this initial mark pause
    // was due to a System.gc() then the requesting thread should block in
    // doit_epilogue() until the marking cycle is complete.
    //
    // If this initial mark pause was requested as part of a humongous
    // allocation then we know that the marking cycle must just have
    // been started by another thread (possibly also allocating a humongous
    // object) as there was no active marking cycle when the requesting
    // thread checked before calling collect() in
    // attempt_allocation_humongous(). Retrying the GC, in this case,
    // will cause the requesting thread to spin inside collect() until the
    // just started marking cycle is complete - which may be a while. So
    // we do NOT retry the GC.
    if (!res) {
      assert(_word_size == 0, "Concurrent Full GC/Humongous Object IM shouldn't be allocating");
      if (_gc_cause != GCCause::_g1_humongous_allocation) {
        _should_retry_gc = true;
      }
      return;
    }
  }

  // Try a partial collection of some kind.
  _pause_succeeded = g1h->do_collection_pause_at_safepoint(_target_pause_time_ms);

  if (_pause_succeeded) {
    if (_word_size > 0) {
      // An allocation had been requested. Do it, eventually trying a stronger
      // kind of GC.
      _result = g1h->satisfy_failed_allocation(_word_size, &_pause_succeeded);
    } else {
      bool should_upgrade_to_full = !g1h->should_do_concurrent_full_gc(_gc_cause) &&
                                    !g1h->has_regions_left_for_allocation();
      if (should_upgrade_to_full) {
        // There has been a request to perform a GC to free some space. We have no
        // information on how much memory has been asked for. In case there are
        // absolutely no regions left to allocate into, do a maximally compacting full GC.
        log_info(gc, ergo)("Attempting maximally compacting collection");
        _pause_succeeded = g1h->do_full_collection(false, /* explicit gc */
                                                   true   /* clear_all_soft_refs */);
      }
    }
    guarantee(_pause_succeeded, "Elevated collections during the safepoint must always succeed.");
  } else {
    assert(_result == NULL, "invariant");
    // The only reason for the pause to not be successful is that, the GC locker is
    // active (or has become active since the prologue was executed). In this case
    // we should retry the pause after waiting for the GC locker to become inactive.
    _should_retry_gc = true;
  }
}

这里可以看到核心的是G1CollectedHeap::do_collection_pause_at_safepoint这个方法，它带上了目标暂停时间的值

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G1CollectedHeap::do_collection_pause_at_safepoint(double target_pause_time_ms) {
  assert_at_safepoint_on_vm_thread();
  guarantee(!is_gc_active(), "collection is not reentrant");

  if (GCLocker::check_active_before_gc()) {
    return false;
  }

  _gc_timer_stw->register_gc_start();

  GCIdMark gc_id_mark;
  _gc_tracer_stw->report_gc_start(gc_cause(), _gc_timer_stw->gc_start());

  SvcGCMarker sgcm(SvcGCMarker::MINOR);
  ResourceMark rm;

  g1_policy()->note_gc_start();

  wait_for_root_region_scanning();

  print_heap_before_gc();
  print_heap_regions();
  trace_heap_before_gc(_gc_tracer_stw);

  _verifier->verify_region_sets_optional();
  _verifier->verify_dirty_young_regions();

  // We should not be doing initial mark unless the conc mark thread is running
  if (!_cm_thread->should_terminate()) {
    // This call will decide whether this pause is an initial-mark
    // pause. If it is, in_initial_mark_gc() will return true
    // for the duration of this pause.
    g1_policy()->decide_on_conc_mark_initiation();
  }

  // We do not allow initial-mark to be piggy-backed on a mixed GC.
  assert(!collector_state()->in_initial_mark_gc() ||
          collector_state()->in_young_only_phase(), "sanity");

  // We also do not allow mixed GCs during marking.
  assert(!collector_state()->mark_or_rebuild_in_progress() || collector_state()->in_young_only_phase(), "sanity");

  // Record whether this pause is an initial mark. When the current
  // thread has completed its logging output and it's safe to signal
  // the CM thread, the flag's value in the policy has been reset.
  bool should_start_conc_mark = collector_state()->in_initial_mark_gc();

  // Inner scope for scope based logging, timers, and stats collection
  {
    EvacuationInfo evacuation_info;

    if (collector_state()->in_initial_mark_gc()) {
      // We are about to start a marking cycle, so we increment the
      // full collection counter.
      increment_old_marking_cycles_started();
      _cm->gc_tracer_cm()->set_gc_cause(gc_cause());
    }

    _gc_tracer_stw->report_yc_type(collector_state()->yc_type());

    GCTraceCPUTime tcpu;

    G1HeapVerifier::G1VerifyType verify_type;
    FormatBuffer<> gc_string("Pause Young ");
    if (collector_state()->in_initial_mark_gc()) {
      gc_string.append("(Concurrent Start)");
      verify_type = G1HeapVerifier::G1VerifyConcurrentStart;
    } else if (collector_state()->in_young_only_phase()) {
      if (collector_state()->in_young_gc_before_mixed()) {
        gc_string.append("(Prepare Mixed)");
      } else {
        gc_string.append("(Normal)");
      }
      verify_type = G1HeapVerifier::G1VerifyYoungNormal;
    } else {
      gc_string.append("(Mixed)");
      verify_type = G1HeapVerifier::G1VerifyMixed;
    }
    GCTraceTime(Info, gc) tm(gc_string, NULL, gc_cause(), true);

    uint active_workers = AdaptiveSizePolicy::calc_active_workers(workers()->total_workers(),
                                                                  workers()->active_workers(),
                                                                  Threads::number_of_non_daemon_threads());
    active_workers = workers()->update_active_workers(active_workers);
    log_info(gc,task)("Using %u workers of %u for evacuation", active_workers, workers()->total_workers());

    TraceCollectorStats tcs(g1mm()->incremental_collection_counters());
    TraceMemoryManagerStats tms(&_memory_manager, gc_cause(),
                                collector_state()->yc_type() == Mixed /* allMemoryPoolsAffected */);

    G1HeapTransition heap_transition(this);
    size_t heap_used_bytes_before_gc = used();

    // Don't dynamically change the number of GC threads this early.  A value of
    // 0 is used to indicate serial work.  When parallel work is done,
    // it will be set.

    { // Call to jvmpi::post_class_unload_events must occur outside of active GC
      IsGCActiveMark x;

      gc_prologue(false);

      if (VerifyRememberedSets) {
        log_info(gc, verify)("[Verifying RemSets before GC]");
        VerifyRegionRemSetClosure v_cl;
        heap_region_iterate(&v_cl);
      }

      _verifier->verify_before_gc(verify_type);

      _verifier->check_bitmaps("GC Start");

#if COMPILER2_OR_JVMCI
      DerivedPointerTable::clear();
#endif

      // Please see comment in g1CollectedHeap.hpp and
      // G1CollectedHeap::ref_processing_init() to see how
      // reference processing currently works in G1.

      // Enable discovery in the STW reference processor
      _ref_processor_stw->enable_discovery();

      {
        // We want to temporarily turn off discovery by the
        // CM ref processor, if necessary, and turn it back on
        // on again later if we do. Using a scoped
        // NoRefDiscovery object will do this.
        NoRefDiscovery no_cm_discovery(_ref_processor_cm);

        // Forget the current alloc region (we might even choose it to be part
        // of the collection set!).
        _allocator->release_mutator_alloc_region();

        // This timing is only used by the ergonomics to handle our pause target.
        // It is unclear why this should not include the full pause. We will
        // investigate this in CR 7178365.
        //
        // Preserving the old comment here if that helps the investigation:
        //
        // The elapsed time induced by the start time below deliberately elides
        // the possible verification above.
        double sample_start_time_sec = os::elapsedTime();

        g1_policy()->record_collection_pause_start(sample_start_time_sec);

        if (collector_state()->in_initial_mark_gc()) {
          concurrent_mark()->pre_initial_mark();
        }

        g1_policy()->finalize_collection_set(target_pause_time_ms, &_survivor);

        evacuation_info.set_collectionset_regions(collection_set()->region_length());

        // Make sure the remembered sets are up to date. This needs to be
        // done before register_humongous_regions_with_cset(), because the
        // remembered sets are used there to choose eager reclaim candidates.
        // If the remembered sets are not up to date we might miss some
        // entries that need to be handled.
        g1_rem_set()->cleanupHRRS();

        register_humongous_regions_with_cset();

        assert(_verifier->check_cset_fast_test(), "Inconsistency in the InCSetState table.");

        // We call this after finalize_cset() to
        // ensure that the CSet has been finalized.
        _cm->verify_no_cset_oops();

        if (_hr_printer.is_active()) {
          G1PrintCollectionSetClosure cl(&_hr_printer);
          _collection_set.iterate(&cl);
        }

        // Initialize the GC alloc regions.
        _allocator->init_gc_alloc_regions(evacuation_info);

        G1ParScanThreadStateSet per_thread_states(this, workers()->active_workers(), collection_set()->young_region_length());
        pre_evacuate_collection_set();

        // Actually do the work...
        evacuate_collection_set(&per_thread_states);

        post_evacuate_collection_set(evacuation_info, &per_thread_states);

        const size_t* surviving_young_words = per_thread_states.surviving_young_words();
        free_collection_set(&_collection_set, evacuation_info, surviving_young_words);

        eagerly_reclaim_humongous_regions();

        record_obj_copy_mem_stats();
        _survivor_evac_stats.adjust_desired_plab_sz();
        _old_evac_stats.adjust_desired_plab_sz();

        double start = os::elapsedTime();
        start_new_collection_set();
        g1_policy()->phase_times()->record_start_new_cset_time_ms((os::elapsedTime() - start) * 1000.0);

        if (evacuation_failed()) {
          set_used(recalculate_used());
          if (_archive_allocator != NULL) {
            _archive_allocator->clear_used();
          }
          for (uint i = 0; i < ParallelGCThreads; i++) {
            if (_evacuation_failed_info_array[i].has_failed()) {
              _gc_tracer_stw->report_evacuation_failed(_evacuation_failed_info_array[i]);
            }
          }
        } else {
          // The "used" of the the collection set have already been subtracted
          // when they were freed.  Add in the bytes evacuated.
          increase_used(g1_policy()->bytes_copied_during_gc());
        }

        if (collector_state()->in_initial_mark_gc()) {
          // We have to do this before we notify the CM threads that
          // they can start working to make sure that all the
          // appropriate initialization is done on the CM object.
          concurrent_mark()->post_initial_mark();
          // Note that we don't actually trigger the CM thread at
          // this point. We do that later when we're sure that
          // the current thread has completed its logging output.
        }

        allocate_dummy_regions();

        _allocator->init_mutator_alloc_region();

        {
          size_t expand_bytes = _heap_sizing_policy->expansion_amount();
          if (expand_bytes > 0) {
            size_t bytes_before = capacity();
            // No need for an ergo logging here,
            // expansion_amount() does this when it returns a value > 0.
            double expand_ms;
            if (!expand(expand_bytes, _workers, &expand_ms)) {
              // We failed to expand the heap. Cannot do anything about it.
            }
            g1_policy()->phase_times()->record_expand_heap_time(expand_ms);
          }
        }

        // We redo the verification but now wrt to the new CSet which
        // has just got initialized after the previous CSet was freed.
        _cm->verify_no_cset_oops();

        // This timing is only used by the ergonomics to handle our pause target.
        // It is unclear why this should not include the full pause. We will
        // investigate this in CR 7178365.
        double sample_end_time_sec = os::elapsedTime();
        double pause_time_ms = (sample_end_time_sec - sample_start_time_sec) * MILLIUNITS;
        size_t total_cards_scanned = g1_policy()->phase_times()->sum_thread_work_items(G1GCPhaseTimes::ScanRS, G1GCPhaseTimes::ScanRSScannedCards);
        g1_policy()->record_collection_pause_end(pause_time_ms, total_cards_scanned, heap_used_bytes_before_gc);

        evacuation_info.set_collectionset_used_before(collection_set()->bytes_used_before());
        evacuation_info.set_bytes_copied(g1_policy()->bytes_copied_during_gc());

        if (VerifyRememberedSets) {
          log_info(gc, verify)("[Verifying RemSets after GC]");
          VerifyRegionRemSetClosure v_cl;
          heap_region_iterate(&v_cl);
        }

        _verifier->verify_after_gc(verify_type);
        _verifier->check_bitmaps("GC End");

        assert(!_ref_processor_stw->discovery_enabled(), "Postcondition");
        _ref_processor_stw->verify_no_references_recorded();

        // CM reference discovery will be re-enabled if necessary.
      }

#ifdef TRACESPINNING
      ParallelTaskTerminator::print_termination_counts();
#endif

      gc_epilogue(false);
    }

    // Print the remainder of the GC log output.
    if (evacuation_failed()) {
      log_info(gc)("To-space exhausted");
    }

    g1_policy()->print_phases();
    heap_transition.print();

    // It is not yet to safe to tell the concurrent mark to
    // start as we have some optional output below. We don't want the
    // output from the concurrent mark thread interfering with this
    // logging output either.

    _hrm.verify_optional();
    _verifier->verify_region_sets_optional();

    TASKQUEUE_STATS_ONLY(print_taskqueue_stats());
    TASKQUEUE_STATS_ONLY(reset_taskqueue_stats());

    print_heap_after_gc();
    print_heap_regions();
    trace_heap_after_gc(_gc_tracer_stw);

    // We must call G1MonitoringSupport::update_sizes() in the same scoping level
    // as an active TraceMemoryManagerStats object (i.e. before the destructor for the
    // TraceMemoryManagerStats is called) so that the G1 memory pools are updated
    // before any GC notifications are raised.
    g1mm()->update_sizes();

    _gc_tracer_stw->report_evacuation_info(&evacuation_info);
    _gc_tracer_stw->report_tenuring_threshold(_g1_policy->tenuring_threshold());
    _gc_timer_stw->register_gc_end();
    _gc_tracer_stw->report_gc_end(_gc_timer_stw->gc_end(), _gc_timer_stw->time_partitions());
  }
  // It should now be safe to tell the concurrent mark thread to start
  // without its logging output interfering with the logging output
  // that came from the pause.

  if (should_start_conc_mark) {
    // CAUTION: after the doConcurrentMark() call below,
    // the concurrent marking thread(s) could be running
    // concurrently with us. Make sure that anything after
    // this point does not assume that we are the only GC thread
    // running. Note: of course, the actual marking work will
    // not start until the safepoint itself is released in
    // SuspendibleThreadSet::desynchronize().
    do_concurrent_mark();
  }

  return true;
}

往下走就是这一步G1Policy::finalize_collection_set,去处理新生代和老年代

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void G1Policy::finalize_collection_set(double target_pause_time_ms, G1SurvivorRegions* survivor) {
  double time_remaining_ms = _collection_set->finalize_young_part(target_pause_time_ms, survivor);
  _collection_set->finalize_old_part(time_remaining_ms);
}

这里分别调用了两个方法，可以看到剩余时间是往下传的，来看一下具体的方法

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double G1CollectionSet::finalize_young_part(double target_pause_time_ms, G1SurvivorRegions* survivors) {
  double young_start_time_sec = os::elapsedTime();

  finalize_incremental_building();

  guarantee(target_pause_time_ms > 0.0,
            "target_pause_time_ms = %1.6lf should be positive", target_pause_time_ms);

  size_t pending_cards = _policy->pending_cards();
  double base_time_ms = _policy->predict_base_elapsed_time_ms(pending_cards);
  double time_remaining_ms = MAX2(target_pause_time_ms - base_time_ms, 0.0);

  log_trace(gc, ergo, cset)("Start choosing CSet. pending cards: " SIZE_FORMAT " predicted base time: %1.2fms remaining time: %1.2fms target pause time: %1.2fms",
                            pending_cards, base_time_ms, time_remaining_ms, target_pause_time_ms);

  // The young list is laid with the survivor regions from the previous
  // pause are appended to the RHS of the young list, i.e.
  //   [Newly Young Regions ++ Survivors from last pause].

  uint survivor_region_length = survivors->length();
  uint eden_region_length = _g1h->eden_regions_count();
  init_region_lengths(eden_region_length, survivor_region_length);

  verify_young_cset_indices();

  // Clear the fields that point to the survivor list - they are all young now.
  survivors->convert_to_eden();

  _bytes_used_before = _inc_bytes_used_before;
  time_remaining_ms = MAX2(time_remaining_ms - _inc_predicted_elapsed_time_ms, 0.0);

  log_trace(gc, ergo, cset)("Add young regions to CSet. eden: %u regions, survivors: %u regions, predicted young region time: %1.2fms, target pause time: %1.2fms",
                            eden_region_length, survivor_region_length, _inc_predicted_elapsed_time_ms, target_pause_time_ms);

  // The number of recorded young regions is the incremental
  // collection set's current size
  set_recorded_rs_lengths(_inc_recorded_rs_lengths);

  double young_end_time_sec = os::elapsedTime();
  phase_times()->record_young_cset_choice_time_ms((young_end_time_sec - young_start_time_sec) * 1000.0);

  return time_remaining_ms;
}

下面是老年代的部分

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void G1CollectionSet::finalize_old_part(double time_remaining_ms) {
  double non_young_start_time_sec = os::elapsedTime();
  double predicted_old_time_ms = 0.0;

  if (collector_state()->in_mixed_phase()) {
    cset_chooser()->verify();
    const uint min_old_cset_length = _policy->calc_min_old_cset_length();
    const uint max_old_cset_length = _policy->calc_max_old_cset_length();

    uint expensive_region_num = 0;
    bool check_time_remaining = _policy->adaptive_young_list_length();

    HeapRegion* hr = cset_chooser()->peek();
    while (hr != NULL) {
      if (old_region_length() >= max_old_cset_length) {
        // Added maximum number of old regions to the CSet.
        log_debug(gc, ergo, cset)("Finish adding old regions to CSet (old CSet region num reached max). old %u regions, max %u regions",
                                  old_region_length(), max_old_cset_length);
        break;
      }

      // Stop adding regions if the remaining reclaimable space is
      // not above G1HeapWastePercent.
      size_t reclaimable_bytes = cset_chooser()->remaining_reclaimable_bytes();
      double reclaimable_percent = _policy->reclaimable_bytes_percent(reclaimable_bytes);
      double threshold = (double) G1HeapWastePercent;
      if (reclaimable_percent <= threshold) {
        // We've added enough old regions that the amount of uncollected
        // reclaimable space is at or below the waste threshold. Stop
        // adding old regions to the CSet.
        log_debug(gc, ergo, cset)("Finish adding old regions to CSet (reclaimable percentage not over threshold). "
                                  "old %u regions, max %u regions, reclaimable: " SIZE_FORMAT "B (%1.2f%%) threshold: " UINTX_FORMAT "%%",
                                  old_region_length(), max_old_cset_length, reclaimable_bytes, reclaimable_percent, G1HeapWastePercent);
        break;
      }

      double predicted_time_ms = predict_region_elapsed_time_ms(hr);
      if (check_time_remaining) {
        if (predicted_time_ms > time_remaining_ms) {
          // Too expensive for the current CSet.

          if (old_region_length() >= min_old_cset_length) {
            // We have added the minimum number of old regions to the CSet,
            // we are done with this CSet.
            log_debug(gc, ergo, cset)("Finish adding old regions to CSet (predicted time is too high). "
                                      "predicted time: %1.2fms, remaining time: %1.2fms old %u regions, min %u regions",
                                      predicted_time_ms, time_remaining_ms, old_region_length(), min_old_cset_length);
            break;
          }

          // We'll add it anyway given that we haven't reached the
          // minimum number of old regions.
          expensive_region_num += 1;
        }
      } else {
        if (old_region_length() >= min_old_cset_length) {
          // In the non-auto-tuning case, we'll finish adding regions
          // to the CSet if we reach the minimum.

          log_debug(gc, ergo, cset)("Finish adding old regions to CSet (old CSet region num reached min). old %u regions, min %u regions",
                                    old_region_length(), min_old_cset_length);
          break;
        }
      }

      // We will add this region to the CSet.
      time_remaining_ms = MAX2(time_remaining_ms - predicted_time_ms, 0.0);
      predicted_old_time_ms += predicted_time_ms;
      cset_chooser()->pop(); // already have region via peek()
      _g1h->old_set_remove(hr);
      add_old_region(hr);

      hr = cset_chooser()->peek();
    }
    if (hr == NULL) {
      log_debug(gc, ergo, cset)("Finish adding old regions to CSet (candidate old regions not available)");
    }

    if (expensive_region_num > 0) {
      // We print the information once here at the end, predicated on
      // whether we added any apparently expensive regions or not, to
      // avoid generating output per region.
      log_debug(gc, ergo, cset)("Added expensive regions to CSet (old CSet region num not reached min)."
                                "old: %u regions, expensive: %u regions, min: %u regions, remaining time: %1.2fms",
                                old_region_length(), expensive_region_num, min_old_cset_length, time_remaining_ms);
    }

    cset_chooser()->verify();
  }

  stop_incremental_building();

  log_debug(gc, ergo, cset)("Finish choosing CSet. old: %u regions, predicted old region time: %1.2fms, time remaining: %1.2f",
                            old_region_length(), predicted_old_time_ms, time_remaining_ms);

  double non_young_end_time_sec = os::elapsedTime();
  phase_times()->record_non_young_cset_choice_time_ms((non_young_end_time_sec - non_young_start_time_sec) * 1000.0);

  QuickSort::sort(_collection_set_regions, _collection_set_cur_length, compare_region_idx, true);
}

上面第三行是个判断，当前是否是 mixed 回收阶段，如果不是的话其实是没有老年代什么事的，所以可以看到代码基本是从这个 if 判断
if (collector_state()->in_mixed_phase()) {开始往下走的
先写到这，偏向于做笔记用，有错轻拍

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\ No newline at end of file diff --git a/search.xml b/search.xml index 603107a184..f24f32f471 100644 --- a/search.xml +++ b/search.xml @@ -1,5 +1,25 @@ + + 村上春树《1Q84》读后感 + /2019/12/18/1Q84%E8%AF%BB%E5%90%8E%E6%84%9F/ + 看完了村上春树的《1Q84》，这应该是第五本看的他的书了，继 跑步，挪威的森林，刺杀骑士团长，海边的卡夫卡之后，不是其中最长的，好像是海边的卡夫卡还是刺杀骑士团长比较长一点，都是在微信读书上看的，比较方便，最开始在上面看的是高晓松的《鱼羊野史》，不知道为啥取这个名字，但是还是满吸引我的，不过由于去年的种种，没有很多心思把它看完，而且本身的组织形式就是比较松散的，看到哪算哪，其实一些野史部分是我比较喜欢，有些谈到人物的就不太有兴趣，而且类似于大祥哥吃的东西，反正都是哇，怎么这么好吃，嗯，太爱（niu）你（bi）了，高晓松就是这个人是我最喜欢的 xxx 家，我也没去细究过他有没有说重复过，反正是不太爱，后来因为这书还一度对战争史有了浓厚的兴趣，然而事实告诉我，大部头的战争史，其实正史我是真的啃不下去，我可能只对其中 10%的内容感兴趣，不过终于也在今年把它看完了，好像高晓松的晓说也最终季了，貌似其中讲朝鲜战争的还被和谐了，看样子是说出了一些故事（truth）。

+

本来只是想把 《1Q84》的读后感写下，现在觉得还是把这篇当成我今年的读书总结吧，不过先从《1Q84》说起。

+

严格来讲，这不是很书面化的读后感，可能我想写的也只是像聊天一样的说下我读过的书，包括的技术博客其实也是类似的，以后或许会转变，但是目前水平如此吧，写多了可能会变好，也可能不会。

+

开始正文吧，这书有点类似于海边的卡夫卡，一开始是通过两条故事线，穿插着叙述，一条是青豆的，不算是个职业杀手的女杀手，要去解决一个经常家暴的斯文败类，穿着描述得比较性感吧，杀人方式是通过比较长的细针，从脖子后面一个精巧的位置插入，可以造成是未知原因死亡的假象，可能会推断成心梗之类的，这里有个前置的细节，就是青豆是乘坐一辆很高级的出租车，内饰什么的都非常有质感，有点不像一辆出租车，然后车里放了一首比较小众的歌，雅纳切克的《小交响曲》，但是青豆知道它，这跟后面的情节也有些许关系，这是女主人公青豆的出场；相应的男主的出场印象不是太深刻，男主叫天吾，是个不知名的作家，跟一个叫小松的编辑有比较好的关系，虽然天吾还没有拿到比较有分量的奖项，但是小松很看好他，也让他帮忙审校一个新作家奖的投稿文章，虽然天吾自身还没获得过这个奖，天吾还有个正式工作，是当数学老师，天吾在学生时代是个数学天才，但后面有对文学产生了兴趣，文学还不足以养活自己，靠着教课还是能保持温饱；

+

接下来是正式故事的起点了，就是小松收到了一部小说投稿，名叫《空气蛹》，是个叫深绘里的女孩子投的稿，小松对他赋予了很高的评价，这里好像记岔了，好像是天吾对这部小说很有好感，但是小松比较怀疑，然后小松看了之后也有了浓厚的兴趣，这里就是开端了，小松想让天吾来重写润色这部《空气蛹》，因为故事本身很有分量，但是描写手法叙事方式等都很拙劣，而天吾正好擅长这个，小松对天吾的评价是，描写技巧无可挑剔，就是故事主体的火花还没际遇迸发，需要一个导火索，这个就可以类比我们程序员，很多比较初中级的程序员主要擅长在原来的代码上修修改改或者给他分配个小功能，比较高级的程序员就需要能做一些项目的架构设计，核心的技术方案设计，以前我也觉得写文档这个比较无聊，但是当一个项目真的比较庞大，复杂的时候，整体和核心部分的架构设计和方案还是需要有文档沉淀的，不然别人不知道没法接受，自己过段时间也会忘记。

+

对于小松的这个建议，他的初衷是想搅一搅这个死气沉沉套路颇深的文坛，因为本身《空气蛹》这部小说的内容很吸引人，小松想通过天吾的润色补充让这部小说冲击新人奖，有种恶作剧的意图，天吾对此表示很多担心和顾虑，小松的这个建议其实也是一种文学作假，有两方面的担心，一方面是原作者深绘里是否同意如此操作，一方面是外界如果发现了这个事实会有什么样的后果，但是小松表示不用担心，前一步由小松牵线，让天吾跟原作者深绘里当面沟通这个代写是否被允许，结果当然是被允许了，这里有了对深绘里的初步描写，按我的理解是比较仙的感觉，然后语言沟通有些吃力，或者说有她自己的特色，当面沟通时貌似是让深绘里回去再考虑下，然后后面再由天吾去深绘里寄宿的戎野老师家沟通具体的细节。

+

2019年12月18日23:37:19 更新
去到戎野老师家之后，天吾知道了关于深绘里的一些事情，深绘里的父亲与戎野老师应该是老友，深绘里的父亲在当初成立了一个叫”先驱”的公社，一个独立运行的社会组织，以运营农场作为物资来源，追求更为松散的共同体，即不过分激进地公有制，进行松散的共同生活，承认私有财产，简而言之就是这样一个能稳定存活下来的独立社会组织，但是随着稳定运行，内部的激进派和稳健派开始出现分歧，不可磨合，后来两派就分裂了，深绘里的父亲，深田保留在了稳健派，但是此时其实深田保内心是矛盾的，以为一开始其实是他倡导的独立革命才组织起了这群人，然而现在他又认清了现实社会已经不太相信能通过革命来独立的可能性，后来激进派便开始越加封闭，而且进行军事训练和思想教育，而后这个先驱的激进派别便有了新的名字”黎明”，深绘里也是在此时从先驱逃离来投靠戎野老师
暂时先写到这，未完待续~

+]]> + + 读后感 + 生活 + 村上春树 + + + 读后感 + + 2019年终总结 /2020/02/01/2019%E5%B9%B4%E7%BB%88%E6%80%BB%E7%BB%93/ @@ -30,23 +50,28 @@ - 村上春树《1Q84》读后感 - /2019/12/18/1Q84%E8%AF%BB%E5%90%8E%E6%84%9F/ - 看完了村上春树的《1Q84》，这应该是第五本看的他的书了，继 跑步，挪威的森林，刺杀骑士团长，海边的卡夫卡之后，不是其中最长的，好像是海边的卡夫卡还是刺杀骑士团长比较长一点，都是在微信读书上看的，比较方便，最开始在上面看的是高晓松的《鱼羊野史》，不知道为啥取这个名字，但是还是满吸引我的，不过由于去年的种种，没有很多心思把它看完，而且本身的组织形式就是比较松散的，看到哪算哪，其实一些野史部分是我比较喜欢，有些谈到人物的就不太有兴趣，而且类似于大祥哥吃的东西，反正都是哇，怎么这么好吃，嗯，太爱（niu）你（bi）了，高晓松就是这个人是我最喜欢的 xxx 家，我也没去细究过他有没有说重复过，反正是不太爱，后来因为这书还一度对战争史有了浓厚的兴趣，然而事实告诉我，大部头的战争史，其实正史我是真的啃不下去，我可能只对其中 10%的内容感兴趣，不过终于也在今年把它看完了，好像高晓松的晓说也最终季了，貌似其中讲朝鲜战争的还被和谐了，看样子是说出了一些故事（truth）。

-

本来只是想把 《1Q84》的读后感写下，现在觉得还是把这篇当成我今年的读书总结吧，不过先从《1Q84》说起。

-

严格来讲，这不是很书面化的读后感，可能我想写的也只是像聊天一样的说下我读过的书，包括的技术博客其实也是类似的，以后或许会转变，但是目前水平如此吧，写多了可能会变好，也可能不会。

-

开始正文吧，这书有点类似于海边的卡夫卡，一开始是通过两条故事线，穿插着叙述，一条是青豆的，不算是个职业杀手的女杀手，要去解决一个经常家暴的斯文败类，穿着描述得比较性感吧，杀人方式是通过比较长的细针，从脖子后面一个精巧的位置插入，可以造成是未知原因死亡的假象，可能会推断成心梗之类的，这里有个前置的细节，就是青豆是乘坐一辆很高级的出租车，内饰什么的都非常有质感，有点不像一辆出租车，然后车里放了一首比较小众的歌，雅纳切克的《小交响曲》，但是青豆知道它，这跟后面的情节也有些许关系，这是女主人公青豆的出场；相应的男主的出场印象不是太深刻，男主叫天吾，是个不知名的作家，跟一个叫小松的编辑有比较好的关系，虽然天吾还没有拿到比较有分量的奖项，但是小松很看好他，也让他帮忙审校一个新作家奖的投稿文章，虽然天吾自身还没获得过这个奖，天吾还有个正式工作，是当数学老师，天吾在学生时代是个数学天才，但后面有对文学产生了兴趣，文学还不足以养活自己，靠着教课还是能保持温饱；

-

接下来是正式故事的起点了，就是小松收到了一部小说投稿，名叫《空气蛹》，是个叫深绘里的女孩子投的稿，小松对他赋予了很高的评价，这里好像记岔了，好像是天吾对这部小说很有好感，但是小松比较怀疑，然后小松看了之后也有了浓厚的兴趣，这里就是开端了，小松想让天吾来重写润色这部《空气蛹》，因为故事本身很有分量，但是描写手法叙事方式等都很拙劣，而天吾正好擅长这个，小松对天吾的评价是，描写技巧无可挑剔，就是故事主体的火花还没际遇迸发，需要一个导火索，这个就可以类比我们程序员，很多比较初中级的程序员主要擅长在原来的代码上修修改改或者给他分配个小功能，比较高级的程序员就需要能做一些项目的架构设计，核心的技术方案设计，以前我也觉得写文档这个比较无聊，但是当一个项目真的比较庞大，复杂的时候，整体和核心部分的架构设计和方案还是需要有文档沉淀的，不然别人不知道没法接受，自己过段时间也会忘记。

-

对于小松的这个建议，他的初衷是想搅一搅这个死气沉沉套路颇深的文坛，因为本身《空气蛹》这部小说的内容很吸引人，小松想通过天吾的润色补充让这部小说冲击新人奖，有种恶作剧的意图，天吾对此表示很多担心和顾虑，小松的这个建议其实也是一种文学作假，有两方面的担心，一方面是原作者深绘里是否同意如此操作，一方面是外界如果发现了这个事实会有什么样的后果，但是小松表示不用担心，前一步由小松牵线，让天吾跟原作者深绘里当面沟通这个代写是否被允许，结果当然是被允许了，这里有了对深绘里的初步描写，按我的理解是比较仙的感觉，然后语言沟通有些吃力，或者说有她自己的特色，当面沟通时貌似是让深绘里回去再考虑下，然后后面再由天吾去深绘里寄宿的戎野老师家沟通具体的细节。

-

2019年12月18日23:37:19 更新
去到戎野老师家之后，天吾知道了关于深绘里的一些事情，深绘里的父亲与戎野老师应该是老友，深绘里的父亲在当初成立了一个叫”先驱”的公社，一个独立运行的社会组织，以运营农场作为物资来源，追求更为松散的共同体，即不过分激进地公有制，进行松散的共同生活，承认私有财产，简而言之就是这样一个能稳定存活下来的独立社会组织，但是随着稳定运行，内部的激进派和稳健派开始出现分歧，不可磨合，后来两派就分裂了，深绘里的父亲，深田保留在了稳健派，但是此时其实深田保内心是矛盾的，以为一开始其实是他倡导的独立革命才组织起了这群人，然而现在他又认清了现实社会已经不太相信能通过革命来独立的可能性，后来激进派便开始越加封闭，而且进行军事训练和思想教育，而后这个先驱的激进派别便有了新的名字”黎明”，深绘里也是在此时从先驱逃离来投靠戎野老师
暂时先写到这，未完待续~

+ 2020 年终总结 + /2021/03/31/2020-%E5%B9%B4%E7%BB%88%E6%80%BB%E7%BB%93/ + 拖更原因

这篇年终总结本来应该在农历过完年就出来的，结果是对没有受疫情影响的春节放假时间空闲情况预估太良好，虽然公司调了几天假，但是因为春节期间疫情状况比较好，本来酒店都不让接待聚餐什么的，后来统统放开，结果就是从初一到初六每天要不就是去亲戚家，要不就是去酒店饭店吃饭，计划很丰满，现实很骨感，时间感觉一下就没了，然后年后感觉有点犯懒了，所以才拖到现在。

+

生活-健身跑步

去年（19 年）的时候跑步突破了 300 公里，然后20 年给自己定了个 400 公里的目标，结果意料之中的没成功，原因可能疫情算一点吧，后面买了跑步机之后，基本周末回家都能跑一下，但是最后还是只跑了300 多公里，总的keep 记录跑量也没超过 1000 公里，所以跑步这个目标还是没成功的，不过还算是比去年多跑一点，这样也算后面好突破点，后面的目标就不定的太高了，每年能比前一年多一点就好，其实跑步已经从一种减肥方式变成一种习惯了，一周一次的跑步已经比较难有效减重了，但是对于保持精力和身体状态还是很有效和重要的，只是对于目前的体重还是要多减下去一些跑步才好，太重了对膝盖负担太大了，可惜还是时间呐，游泳骑车什么的都需要更苛刻的条件和时间，饮食呢控制起来比较难（贪吃
终于在 3 月底之前跑到了 1000 公里，迟了三个月，不过也总算达到了，只是体重控制还是不行，有试着走走楼梯，但是感觉对膝盖负担比较大，得再想想用什么方式

+

+

技术成长

一直提不起笔来写这篇年终总结还有个比较大的原因是觉得20 年的成长不如预期，大小目标都没怎么完成，比如深入了解 jvm，是想能有些深入的见解，而不再是某些点的比较片面的理解，系统性的归纳总结也比较少，每个方向或多或少有些看法和理解，但是不全面，一些东西看过了也会忘记，需要温故而知新，比如 AQS 的内容，第一次读其实理解比较浅，后面就强迫自己去读，去写，才有了一些比之前更深入的理解，因为很多文章都是带有作者思路的引导，适不适合自己都要看是否能从他的思路把它看懂，有些就差别很大，这个跟看书也一样，有些书大众一致推荐，一般情况下大多是经典的好的，但是也有可能是不太适合自己的，可能有时候机缘巧合看到的反而让人茅塞顿开，在 todo 里已经积攒了好多的点和面需要去学习实践，一方面是自己懒，一方面是时间也相对偏少，看看 21 年能不能有所提升，加强“时间管理”，哈哈

+

技术上主要是看了 mysql 的 mvcc 相关内容，rocketmq 的，redis 的代码，还有 mybatis 等，其实每一个都能写很多，也有很多值得学习的，需要全面系统学习，之前想好好画一个思维导图，将整个技术体系都梳理下，还只做了一点点，方式也有点问题，应该从大到小，而不是深度优先，细节有很多，每一个方面都有自己比较熟悉擅长的，也有不太了解的，可以做一个评分，这个也是亟待改善的，希望今年能完成。

+

博客

博客方面 20 年一年整是写了 53 篇，差不多是一周一篇的节奏，这个还是不错的，虽然博客质量参差不齐，但是这个更新频率还是比较好的，并且也定了个潜规则，可以一周技术一周生活，这样能缓解水文的频率，提高些技术文章的质量，虽然结果并没有好多少，不过感觉还是可以这么坚持的，能提高一些技术文章的质量那就更好了

]]> 生活 - 读后感 - 村上春树 + 年终总结 + 2020 + 年终总结 + 2020 - 读后感 + 生活 + 年终总结 + 2020 + 2021 + 拖更 @@ -64,33 +89,8 @@ 生活 - 年中总结 - 2020 - - - - 2020 年终总结 - /2021/03/31/2020-%E5%B9%B4%E7%BB%88%E6%80%BB%E7%BB%93/ - 拖更原因

这篇年终总结本来应该在农历过完年就出来的，结果是对没有受疫情影响的春节放假时间空闲情况预估太良好，虽然公司调了几天假，但是因为春节期间疫情状况比较好，本来酒店都不让接待聚餐什么的，后来统统放开，结果就是从初一到初六每天要不就是去亲戚家，要不就是去酒店饭店吃饭，计划很丰满，现实很骨感，时间感觉一下就没了，然后年后感觉有点犯懒了，所以才拖到现在。

-

生活-健身跑步

去年（19 年）的时候跑步突破了 300 公里，然后20 年给自己定了个 400 公里的目标，结果意料之中的没成功，原因可能疫情算一点吧，后面买了跑步机之后，基本周末回家都能跑一下，但是最后还是只跑了300 多公里，总的keep 记录跑量也没超过 1000 公里，所以跑步这个目标还是没成功的，不过还算是比去年多跑一点，这样也算后面好突破点，后面的目标就不定的太高了，每年能比前一年多一点就好，其实跑步已经从一种减肥方式变成一种习惯了，一周一次的跑步已经比较难有效减重了，但是对于保持精力和身体状态还是很有效和重要的，只是对于目前的体重还是要多减下去一些跑步才好，太重了对膝盖负担太大了，可惜还是时间呐，游泳骑车什么的都需要更苛刻的条件和时间，饮食呢控制起来比较难（贪吃
终于在 3 月底之前跑到了 1000 公里，迟了三个月，不过也总算达到了，只是体重控制还是不行，有试着走走楼梯，但是感觉对膝盖负担比较大，得再想想用什么方式

-

-

技术成长

一直提不起笔来写这篇年终总结还有个比较大的原因是觉得20 年的成长不如预期，大小目标都没怎么完成，比如深入了解 jvm，是想能有些深入的见解，而不再是某些点的比较片面的理解，系统性的归纳总结也比较少，每个方向或多或少有些看法和理解，但是不全面，一些东西看过了也会忘记，需要温故而知新，比如 AQS 的内容，第一次读其实理解比较浅，后面就强迫自己去读，去写，才有了一些比之前更深入的理解，因为很多文章都是带有作者思路的引导，适不适合自己都要看是否能从他的思路把它看懂，有些就差别很大，这个跟看书也一样，有些书大众一致推荐，一般情况下大多是经典的好的，但是也有可能是不太适合自己的，可能有时候机缘巧合看到的反而让人茅塞顿开，在 todo 里已经积攒了好多的点和面需要去学习实践，一方面是自己懒，一方面是时间也相对偏少，看看 21 年能不能有所提升，加强“时间管理”，哈哈

-

技术上主要是看了 mysql 的 mvcc 相关内容，rocketmq 的，redis 的代码，还有 mybatis 等，其实每一个都能写很多，也有很多值得学习的，需要全面系统学习，之前想好好画一个思维导图，将整个技术体系都梳理下，还只做了一点点，方式也有点问题，应该从大到小，而不是深度优先，细节有很多，每一个方面都有自己比较熟悉擅长的，也有不太了解的，可以做一个评分，这个也是亟待改善的，希望今年能完成。

-

博客

博客方面 20 年一年整是写了 53 篇，差不多是一周一篇的节奏，这个还是不错的，虽然博客质量参差不齐，但是这个更新频率还是比较好的，并且也定了个潜规则，可以一周技术一周生活，这样能缓解水文的频率，提高些技术文章的质量，虽然结果并没有好多少，不过感觉还是可以这么坚持的，能提高一些技术文章的质量那就更好了

-]]> - - 生活 - 年终总结 - 2020 - 年终总结 - 2020 - - - 生活 - 年终总结 2020 - 2021 - 拖更 + 年中总结 @@ -110,8 +110,8 @@ 生活 - 年中总结 2021 + 年中总结 技术 读书 @@ -133,6 +133,22 @@ 拖更 + + 2022 年终总结 + /2023/01/15/2022-%E5%B9%B4%E7%BB%88%E6%80%BB%E7%BB%93/ + 一年又一年，时间匆匆，这一年过得不太容易，很多事情都是来得猝不及防，很多规划也照例是没有完成，今年更多了一些，又是比较丧的一篇总结
工作上的变化让我多理解了一些社会跟职场的现实吧，可能的确是我不够优秀，也可能是其他，说回我自身，在工作中今年应该是收获比较一般的一年，不能说没有，对原先不熟悉的业务的掌握程度有了比较大的提升，只是问题依旧存在，也挺难推动完全改变，只能尽自己所能，而这一点也主要是在团队中的定位因为前面说的一些原因，在前期不明确，限制比较大，虽然现在并没有完全解决，但也有了一些明显的改善，如果明年继续为这家公司服务，希望能有所突破，在人心沟通上的技巧总是比较反感，可也是不得不使用或者说被迫学习使用的，LD说我的对错观太强了，拗不过来，希望能有所改变。
长远的规划上没有什么明确的想法，很容易否定原来的各种想法，见识过各种现实的残酷，明白以前的一些想法不够全面或者比较幼稚，想有更上一层楼的机会，只是不希望是通过自己不认可的方式。比较能接受的是通过提升自己的技术和执行力，能够有更进一步的可能。
技术上是挺失败的去年跟前年还是能看一些书，学一些东西，今年少了很多，可能对原来比较熟悉的都有些遗忘，最近有在改善博客的内容，能更多的是系列化的，由浅入深，只是还很不完善，没什么规划，体系上也还不完整，不过还是以mybatis作为一个开头，后续新开始的内容或者原先写过的相关的都能做个整理，不再是想到啥就写点啥。最近的一个重点是在k8s上，学习方式跟一些特别优秀的人比起来还是会慢一些，不过也是自己的方法，能够更深入的理解整个体系，并讲解出来，可能会尝试采用视频的方式，对一些比较好的内容做尝试，看看会不会有比较好的数据和反馈，在22年还苟着周更的独立技术博客也算是比较稀有了的，其他站的发布也要勤一些，形成所谓的“矩阵”。
跑步减肥这个么还是比较惨，22年只跑了368公里，比21年少了85公里，有一些客观但很多是主观的原因，还是需要跑起来，只是减肥也很迫切，体重比较大跑步还是有些压力的，买了动感单车，就是时间稍长屁股痛这个目前比较难解决，骑还是每天在骑就是强度跟时间不太够，要保证每天30分钟的量可能会比较好。
加油吧，愿23年家人和自己都健康，顺遂。大家也一样。

+]]> + + 生活 + 年终总结 + + + 生活 + 年终总结 + 2022 + 2023 + + 34_Search_for_a_Range /2016/08/14/34-Search-for-a-Range/ @@ -151,23 +167,6 @@ c++ - - AbstractQueuedSynchronizer - /2019/09/23/AbstractQueuedSynchronizer/ - 最近看了大神的 AQS 的文章，之前总是断断续续地看一点，每次都知难而退，下次看又从头开始，昨天总算硬着头皮看完了第一部分
首先 AQS 只要有这些属性

-
// 头结点，你直接把它当做 当前持有锁的线程 可能是最好理解的
private transient volatile Node head;

// 阻塞的尾节点，每个新的节点进来，都插入到最后，也就形成了一个链表
private transient volatile Node tail;

// 这个是最重要的，代表当前锁的状态，0代表没有被占用，大于 0 代表有线程持有当前锁
// 这个值可以大于 1，是因为锁可以重入，每次重入都加上 1
private volatile int state;

// 代表当前持有独占锁的线程，举个最重要的使用例子，因为锁可以重入
// reentrantLock.lock()可以嵌套调用多次，所以每次用这个来判断当前线程是否已经拥有了锁
// if (currentThread == getExclusiveOwnerThread()) {state++}
private transient Thread exclusiveOwnerThread; //继承自AbstractOwnableSynchronizer
-

大概了解了 aqs 底层的双向等待队列，
结构是这样的

每个 node 里面主要是的代码结构也比较简单

-
static final class Node {
    // 标识节点当前在共享模式下
    static final Node SHARED = new Node();
    // 标识节点当前在独占模式下
    static final Node EXCLUSIVE = null;

    // ======== 下面的几个int常量是给waitStatus用的 ===========
    /** waitStatus value to indicate thread has cancelled */
    // 代码此线程取消了争抢这个锁
    static final int CANCELLED =  1;
    /** waitStatus value to indicate successor's thread needs unparking */
    // 官方的描述是，其表示当前node的后继节点对应的线程需要被唤醒
    static final int SIGNAL    = -1;
    /** waitStatus value to indicate thread is waiting on condition */
    // 本文不分析condition，所以略过吧，下一篇文章会介绍这个
    static final int CONDITION = -2;
    /**
     * waitStatus value to indicate the next acquireShared should
     * unconditionally propagate
     */
    // 同样的不分析，略过吧
    static final int PROPAGATE = -3;
    // =====================================================


    // 取值为上面的1、-1、-2、-3，或者0(以后会讲到)
    // 这么理解，暂时只需要知道如果这个值 大于0 代表此线程取消了等待，
    //    ps: 半天抢不到锁，不抢了，ReentrantLock是可以指定timeouot的。。。
    volatile int waitStatus;
    // 前驱节点的引用
    volatile Node prev;
    // 后继节点的引用
    volatile Node next;
    // 这个就是线程本尊
    volatile Thread thread;

}
-

其实可以主要关注这个 waitStatus 因为这个是后面的节点给前面的节点设置的，等于-1 的时候代表后面有节点等待，需要去唤醒，
这里使用了一个变种的 CLH 队列实现，CLH 队列相关内容可以查看这篇 自旋锁、排队自旋锁、MCS锁、CLH锁

-]]> - - java - - - java - aqs - - AQS篇二 之 Condition 浅析笔记 /2021/02/21/AQS-%E4%B9%8B-Condition-%E6%B5%85%E6%9E%90%E7%AC%94%E8%AE%B0/ @@ -199,9 +198,9 @@ java - aqs 并发 j.u.c + aqs condition await signal @@ -209,6 +208,58 @@ unlock + + AQS篇一 + /2021/02/14/AQS%E7%AF%87%E4%B8%80/ + 很多东西都是时看时新，而且时间长了也会忘，所以再来复习下，也会有一些新的角度看法这次来聊下AQS的内容，主要是这几个点，

+

第一个线程

第一个线程抢到锁了，此时state跟阻塞队列是怎么样的，其实这里是之前没理解对的地方

+
/**
         * Fair version of tryAcquire.  Don't grant access unless
         * recursive call or no waiters or is first.
         */
        protected final boolean tryAcquire(int acquires) {
            final Thread current = Thread.currentThread();
            int c = getState();
            // 这里如果state还是0说明锁还空着
            if (c == 0) {
                // 因为是公平锁版本的，先去看下是否阻塞队列里有排着队的
                if (!hasQueuedPredecessors() &&
                    compareAndSetState(0, acquires)) {
                    // 没有排队的，并且state使用cas设置成功的就标记当前占有锁的线程是我
                    setExclusiveOwnerThread(current);
                    // 然后其实就返回了，包括阻塞队列的head和tail节点和waitStatus都没有设置
                    return true;
                }
            }
            else if (current == getExclusiveOwnerThread()) {
                int nextc = c + acquires;
                if (nextc < 0)
                    throw new Error("Maximum lock count exceeded");
                setState(nextc);
                return true;
            }
            // 这里就是第二个线程会返回false
            return false;
        }
    }
+ +

第二个线程

当第二个线程进来的时候应该是怎么样，结合代码来看

+
/**
     * Acquires in exclusive mode, ignoring interrupts.  Implemented
     * by invoking at least once {@link #tryAcquire},
     * returning on success.  Otherwise the thread is queued, possibly
     * repeatedly blocking and unblocking, invoking {@link
     * #tryAcquire} until success.  This method can be used
     * to implement method {@link Lock#lock}.
     *
     * @param arg the acquire argument.  This value is conveyed to
     *        {@link #tryAcquire} but is otherwise uninterpreted and
     *        can represent anything you like.
     */
    public final void acquire(int arg) {
        // 前面第一种情况是tryAcquire直接成功了，这个if判断第一个条件就是false，就不往下执行了
        // 如果是第二个线程，第一个条件获取锁不成功，条件判断!tryAcquire(arg) == true，就会走
        // acquireQueued(addWaiter(Node.EXCLUSIVE), arg)
        if (!tryAcquire(arg) &&
            acquireQueued(addWaiter(Node.EXCLUSIVE), arg))
            selfInterrupt();
    }
+ +

然后来看下addWaiter的逻辑

+
/**
     * Creates and enqueues node for current thread and given mode.
     *
     * @param mode Node.EXCLUSIVE for exclusive, Node.SHARED for shared
     * @return the new node
     */
    private Node addWaiter(Node mode) {
        // 这里是包装成一个node
        Node node = new Node(Thread.currentThread(), mode);
        // Try the fast path of enq; backup to full enq on failure
        // 最快的方式就是把当前线程的节点放在阻塞队列的最后
        Node pred = tail;
        // 只有当tail，也就是pred不为空的时候可以直接接上
        if (pred != null) {
            node.prev = pred;
            // 如果这里cas成功了，就直接接上返回了
            if (compareAndSetTail(pred, node)) {
                pred.next = node;
                return node;
            }
        }
        // 不然就会继续走到这里
        enq(node);
        return node;
    }
+ +

然后就是enq的逻辑了

+
/**
     * Inserts node into queue, initializing if necessary. See picture above.
     * @param node the node to insert
     * @return node's predecessor
     */
    private Node enq(final Node node) {
        for (;;) {
            // 如果状态没变化的话，tail这时还是null的
            Node t = tail;
            if (t == null) { // Must initialize
                // 这里就会初始化头结点，就是个空节点
                if (compareAndSetHead(new Node()))
                    // tail也赋值成head
                    tail = head;
            } else {
                // 这里就设置tail了
                node.prev = t;
                if (compareAndSetTail(t, node)) {
                    t.next = node;
                    return t;
                }
            }
        }
    }
+ +

所以从这里可以看出来，其实head头结点不是个真实的带有线程的节点，并且不是在第一个线程进来的时候设置的

+

解锁

通过代码来看下

+
/**
     * Attempts to release this lock.
     *
     * <p>If the current thread is the holder of this lock then the hold
     * count is decremented.  If the hold count is now zero then the lock
     * is released.  If the current thread is not the holder of this
     * lock then {@link IllegalMonitorStateException} is thrown.
     *
     * @throws IllegalMonitorStateException if the current thread does not
     *         hold this lock
     */
    public void unlock() {
        // 释放锁
        sync.release(1);
    }
/**
     * Releases in exclusive mode.  Implemented by unblocking one or
     * more threads if {@link #tryRelease} returns true.
     * This method can be used to implement method {@link Lock#unlock}.
     *
     * @param arg the release argument.  This value is conveyed to
     *        {@link #tryRelease} but is otherwise uninterpreted and
     *        can represent anything you like.
     * @return the value returned from {@link #tryRelease}
     */
    public final boolean release(int arg) {
        // 尝试去释放
        if (tryRelease(arg)) {
            Node h = head;
            if (h != null && h.waitStatus != 0)
                unparkSuccessor(h);
            return true;
        }
        return false;
    }
protected final boolean tryRelease(int releases) {
            int c = getState() - releases;
            if (Thread.currentThread() != getExclusiveOwnerThread())
                throw new IllegalMonitorStateException();
            boolean free = false;
    		// 判断是否完全释放锁，因为可重入
            if (c == 0) {
                free = true;
                setExclusiveOwnerThread(null);
            }
            setState(c);
            return free;
        }
// 这段代码和上面的一致，只是为了顺序性，又拷下来看下

public final boolean release(int arg) {
        // 尝试去释放，如果是完全释放，返回的就是true，否则是false
        if (tryRelease(arg)) {
            Node h = head;
            // 这里判断头结点是否为空以及waitStatus的状态，前面说了head节点其实是
            // 在第二个线程进来的时候初始化的，如果是空的话说明没后续节点，并且waitStatus
            // 也表示了后续的等待状态
            if (h != null && h.waitStatus != 0)
                unparkSuccessor(h);
            return true;
        }
        return false;
    }

/**
     * Wakes up node's successor, if one exists.
     *
     * @param node the node
     */
// 唤醒后继节点
    private void unparkSuccessor(Node node) {
        /*
         * If status is negative (i.e., possibly needing signal) try
         * to clear in anticipation of signalling.  It is OK if this
         * fails or if status is changed by waiting thread.
         */
        int ws = node.waitStatus;
        if (ws < 0)
            compareAndSetWaitStatus(node, ws, 0);

        /*
         * Thread to unpark is held in successor, which is normally
         * just the next node.  But if cancelled or apparently null,
         * traverse backwards from tail to find the actual
         * non-cancelled successor.
         */
        Node s = node.next;
        // 如果后继节点是空或者当前节点取消等待了
        if (s == null || s.waitStatus > 0) {
            s = null;
            // 从后往前找，找到非取消的节点，注意这里不是找到就退出，而是一直找到头
            // 所以不必担心中间有取消的
            for (Node t = tail; t != null && t != node; t = t.prev)
                if (t.waitStatus <= 0)
                    s = t;
        }
        if (s != null)
            // 将其唤醒
            LockSupport.unpark(s.thread);
    }
+ + + + +]]> + + Java + 并发 + + + java + 并发 + j.u.c + aqs + + + + AbstractQueuedSynchronizer + /2019/09/23/AbstractQueuedSynchronizer/ + 最近看了大神的 AQS 的文章，之前总是断断续续地看一点，每次都知难而退，下次看又从头开始，昨天总算硬着头皮看完了第一部分
首先 AQS 只要有这些属性

+
// 头结点，你直接把它当做 当前持有锁的线程 可能是最好理解的
private transient volatile Node head;

// 阻塞的尾节点，每个新的节点进来，都插入到最后，也就形成了一个链表
private transient volatile Node tail;

// 这个是最重要的，代表当前锁的状态，0代表没有被占用，大于 0 代表有线程持有当前锁
// 这个值可以大于 1，是因为锁可以重入，每次重入都加上 1
private volatile int state;

// 代表当前持有独占锁的线程，举个最重要的使用例子，因为锁可以重入
// reentrantLock.lock()可以嵌套调用多次，所以每次用这个来判断当前线程是否已经拥有了锁
// if (currentThread == getExclusiveOwnerThread()) {state++}
private transient Thread exclusiveOwnerThread; //继承自AbstractOwnableSynchronizer
+

大概了解了 aqs 底层的双向等待队列，
结构是这样的

每个 node 里面主要是的代码结构也比较简单

+
static final class Node {
    // 标识节点当前在共享模式下
    static final Node SHARED = new Node();
    // 标识节点当前在独占模式下
    static final Node EXCLUSIVE = null;

    // ======== 下面的几个int常量是给waitStatus用的 ===========
    /** waitStatus value to indicate thread has cancelled */
    // 代码此线程取消了争抢这个锁
    static final int CANCELLED =  1;
    /** waitStatus value to indicate successor's thread needs unparking */
    // 官方的描述是，其表示当前node的后继节点对应的线程需要被唤醒
    static final int SIGNAL    = -1;
    /** waitStatus value to indicate thread is waiting on condition */
    // 本文不分析condition，所以略过吧，下一篇文章会介绍这个
    static final int CONDITION = -2;
    /**
     * waitStatus value to indicate the next acquireShared should
     * unconditionally propagate
     */
    // 同样的不分析，略过吧
    static final int PROPAGATE = -3;
    // =====================================================


    // 取值为上面的1、-1、-2、-3，或者0(以后会讲到)
    // 这么理解，暂时只需要知道如果这个值 大于0 代表此线程取消了等待，
    //    ps: 半天抢不到锁，不抢了，ReentrantLock是可以指定timeouot的。。。
    volatile int waitStatus;
    // 前驱节点的引用
    volatile Node prev;
    // 后继节点的引用
    volatile Node next;
    // 这个就是线程本尊
    volatile Thread thread;

}
+

其实可以主要关注这个 waitStatus 因为这个是后面的节点给前面的节点设置的，等于-1 的时候代表后面有节点等待，需要去唤醒，
这里使用了一个变种的 CLH 队列实现，CLH 队列相关内容可以查看这篇 自旋锁、排队自旋锁、MCS锁、CLH锁

+]]> + + java + + + java + aqs + + add-two-number /2015/04/14/Add-Two-Number/ @@ -229,6 +280,26 @@ c++ + + Apollo 如何获取当前环境 + /2022/09/04/Apollo-%E5%A6%82%E4%BD%95%E8%8E%B7%E5%8F%96%E5%BD%93%E5%89%8D%E7%8E%AF%E5%A2%83/ + 在用 Apollo 作为配置中心的过程中才到过几个坑，这边记录下，因为运行 java 服务的启动参数一般比较固定，所以我们在一个新环境里运行的时候没有特意去检查，然后突然发现业务上有一些数据异常，排查之后才发现java 服务连接了测试环境的 apollo，而原因是因为环境变量传了-Denv=fat，而在我们的环境配置中 fat 就是代表测试环境， 其实应该是-Denv=pro，而 apollo 总共有这些环境

+
public enum Env{
  LOCAL, DEV, FWS, FAT, UAT, LPT, PRO, TOOLS, UNKNOWN;

  public static Env fromString(String env) {
    Env environment = EnvUtils.transformEnv(env);
    Preconditions.checkArgument(environment != UNKNOWN, String.format("Env %s is invalid", env));
    return environment;
  }
}
+

而这些解释

+
/**
 * Here is the brief description for all the predefined environments:
 * <ul>
 *   <li>LOCAL: Local Development environment, assume you are working at the beach with no network access</li>
 *   <li>DEV: Development environment</li>
 *   <li>FWS: Feature Web Service Test environment</li>
 *   <li>FAT: Feature Acceptance Test environment</li>
 *   <li>UAT: User Acceptance Test environment</li>
 *   <li>LPT: Load and Performance Test environment</li>
 *   <li>PRO: Production environment</li>
 *   <li>TOOLS: Tooling environment, a special area in production environment which allows
 * access to test environment, e.g. Apollo Portal should be deployed in tools environment</li>
 * </ul>
 */
+

那如果要在运行时知道 apollo 当前使用的环境可以用这个

+
Env apolloEnv = ApolloInjector.getInstance(ConfigUtil.class).getApolloEnv();
+

简单记录下。

+]]> + + Java + + + Java + Apollo + environment + + Apollo 客户端启动过程分析 /2022/09/18/Apollo-%E5%AE%A2%E6%88%B7%E7%AB%AF%E5%90%AF%E5%8A%A8%E8%BF%87%E7%A8%8B%E5%88%86%E6%9E%90/ @@ -279,19 +350,27 @@ - 2022 年终总结 - /2023/01/15/2022-%E5%B9%B4%E7%BB%88%E6%80%BB%E7%BB%93/ - 一年又一年，时间匆匆，这一年过得不太容易，很多事情都是来得猝不及防，很多规划也照例是没有完成，今年更多了一些，又是比较丧的一篇总结
工作上的变化让我多理解了一些社会跟职场的现实吧，可能的确是我不够优秀，也可能是其他，说回我自身，在工作中今年应该是收获比较一般的一年，不能说没有，对原先不熟悉的业务的掌握程度有了比较大的提升，只是问题依旧存在，也挺难推动完全改变，只能尽自己所能，而这一点也主要是在团队中的定位因为前面说的一些原因，在前期不明确，限制比较大，虽然现在并没有完全解决，但也有了一些明显的改善，如果明年继续为这家公司服务，希望能有所突破，在人心沟通上的技巧总是比较反感，可也是不得不使用或者说被迫学习使用的，LD说我的对错观太强了，拗不过来，希望能有所改变。
长远的规划上没有什么明确的想法，很容易否定原来的各种想法，见识过各种现实的残酷，明白以前的一些想法不够全面或者比较幼稚，想有更上一层楼的机会，只是不希望是通过自己不认可的方式。比较能接受的是通过提升自己的技术和执行力，能够有更进一步的可能。
技术上是挺失败的去年跟前年还是能看一些书，学一些东西，今年少了很多，可能对原来比较熟悉的都有些遗忘，最近有在改善博客的内容，能更多的是系列化的，由浅入深，只是还很不完善，没什么规划，体系上也还不完整，不过还是以mybatis作为一个开头，后续新开始的内容或者原先写过的相关的都能做个整理，不再是想到啥就写点啥。最近的一个重点是在k8s上，学习方式跟一些特别优秀的人比起来还是会慢一些，不过也是自己的方法，能够更深入的理解整个体系，并讲解出来，可能会尝试采用视频的方式，对一些比较好的内容做尝试，看看会不会有比较好的数据和反馈，在22年还苟着周更的独立技术博客也算是比较稀有了的，其他站的发布也要勤一些，形成所谓的“矩阵”。
跑步减肥这个么还是比较惨，22年只跑了368公里，比21年少了85公里，有一些客观但很多是主观的原因，还是需要跑起来，只是减肥也很迫切，体重比较大跑步还是有些压力的，买了动感单车，就是时间稍长屁股痛这个目前比较难解决，骑还是每天在骑就是强度跟时间不太够，要保证每天30分钟的量可能会比较好。
加油吧，愿23年家人和自己都健康，顺遂。大家也一样。

+ Apollo 的 value 注解是怎么自动更新的 + /2020/11/01/Apollo-%E7%9A%84-value-%E6%B3%A8%E8%A7%A3%E6%98%AF%E6%80%8E%E4%B9%88%E8%87%AA%E5%8A%A8%E6%9B%B4%E6%96%B0%E7%9A%84/ + 在前司和目前公司，用的配置中心都是使用的 Apollo，经过了业界验证，比较强大的配置管理系统，特别是在0.10 后开始支持对使用 value 注解的配置值进行自动更新，今天刚好有个同学问到我，就顺便写篇文章记录下，其实也是借助于 spring 强大的 bean 生命周期管理，可以实现BeanPostProcessor接口，使用postProcessBeforeInitialization方法，来对bean 内部的属性和方法进行判断，是否有 value 注解，如果有就是将它注册到一个 map 中，可以看到这个方法com.ctrip.framework.apollo.spring.annotation.SpringValueProcessor#processField

+
@Override
  protected void processField(Object bean, String beanName, Field field) {
    // register @Value on field
    Value value = field.getAnnotation(Value.class);
    if (value == null) {
      return;
    }
    Set<String> keys = placeholderHelper.extractPlaceholderKeys(value.value());

    if (keys.isEmpty()) {
      return;
    }

    for (String key : keys) {
      SpringValue springValue = new SpringValue(key, value.value(), bean, beanName, field, false);
      springValueRegistry.register(beanFactory, key, springValue);
      logger.debug("Monitoring {}", springValue);
    }
  }
+

然后我们看下这个springValueRegistry是啥玩意

+
public class SpringValueRegistry {
  private static final long CLEAN_INTERVAL_IN_SECONDS = 5;
  private final Map<BeanFactory, Multimap<String, SpringValue>> registry = Maps.newConcurrentMap();
  private final AtomicBoolean initialized = new AtomicBoolean(false);
  private final Object LOCK = new Object();

  public void register(BeanFactory beanFactory, String key, SpringValue springValue) {
    if (!registry.containsKey(beanFactory)) {
      synchronized (LOCK) {
        if (!registry.containsKey(beanFactory)) {
          registry.put(beanFactory, LinkedListMultimap.<String, SpringValue>create());
        }
      }
    }

    registry.get(beanFactory).put(key, springValue);

    // lazy initialize
    if (initialized.compareAndSet(false, true)) {
      initialize();
    }
  }
+

这类其实就是个 map 来存放 springvalue，然后有com.ctrip.framework.apollo.spring.property.AutoUpdateConfigChangeListener来监听更新操作，当有变更时

+
@Override
 public void onChange(ConfigChangeEvent changeEvent) {
   Set<String> keys = changeEvent.changedKeys();
   if (CollectionUtils.isEmpty(keys)) {
     return;
   }
   for (String key : keys) {
     // 1. check whether the changed key is relevant
     Collection<SpringValue> targetValues = springValueRegistry.get(beanFactory, key);
     if (targetValues == null || targetValues.isEmpty()) {
       continue;
     }

     // 2. check whether the value is really changed or not (since spring property sources have hierarchies)
     // 这里其实有一点比较绕，是因为 Apollo 里的 namespace 划分，会出现 key 相同，但是 namespace 不同的情况，所以会有个优先级存在，所以需要去校验 environment 里面的是否已经更新，如果未更新则表示不需要更新
     if (!shouldTriggerAutoUpdate(changeEvent, key)) {
       continue;
     }

     // 3. update the value
     for (SpringValue val : targetValues) {
       updateSpringValue(val);
     }
   }
 }
+

其实原理很简单，就是得了解知道下

]]> - 生活 - 年终总结 + Java + Apollo + value - 生活 - 年终总结 - 2022 - 2023 + Java + Apollo + environment + value + 注解 @@ -346,35 +425,17 @@ - Apollo 的 value 注解是怎么自动更新的 - /2020/11/01/Apollo-%E7%9A%84-value-%E6%B3%A8%E8%A7%A3%E6%98%AF%E6%80%8E%E4%B9%88%E8%87%AA%E5%8A%A8%E6%9B%B4%E6%96%B0%E7%9A%84/ - 在前司和目前公司，用的配置中心都是使用的 Apollo，经过了业界验证，比较强大的配置管理系统，特别是在0.10 后开始支持对使用 value 注解的配置值进行自动更新，今天刚好有个同学问到我，就顺便写篇文章记录下，其实也是借助于 spring 强大的 bean 生命周期管理，可以实现BeanPostProcessor接口，使用postProcessBeforeInitialization方法，来对bean 内部的属性和方法进行判断，是否有 value 注解，如果有就是将它注册到一个 map 中，可以看到这个方法com.ctrip.framework.apollo.spring.annotation.SpringValueProcessor#processField

-
@Override
  protected void processField(Object bean, String beanName, Field field) {
    // register @Value on field
    Value value = field.getAnnotation(Value.class);
    if (value == null) {
      return;
    }
    Set<String> keys = placeholderHelper.extractPlaceholderKeys(value.value());

    if (keys.isEmpty()) {
      return;
    }

    for (String key : keys) {
      SpringValue springValue = new SpringValue(key, value.value(), bean, beanName, field, false);
      springValueRegistry.register(beanFactory, key, springValue);
      logger.debug("Monitoring {}", springValue);
    }
  }
-

然后我们看下这个springValueRegistry是啥玩意

-
public class SpringValueRegistry {
  private static final long CLEAN_INTERVAL_IN_SECONDS = 5;
  private final Map<BeanFactory, Multimap<String, SpringValue>> registry = Maps.newConcurrentMap();
  private final AtomicBoolean initialized = new AtomicBoolean(false);
  private final Object LOCK = new Object();

  public void register(BeanFactory beanFactory, String key, SpringValue springValue) {
    if (!registry.containsKey(beanFactory)) {
      synchronized (LOCK) {
        if (!registry.containsKey(beanFactory)) {
          registry.put(beanFactory, LinkedListMultimap.<String, SpringValue>create());
        }
      }
    }

    registry.get(beanFactory).put(key, springValue);

    // lazy initialize
    if (initialized.compareAndSet(false, true)) {
      initialize();
    }
  }
-

这类其实就是个 map 来存放 springvalue，然后有com.ctrip.framework.apollo.spring.property.AutoUpdateConfigChangeListener来监听更新操作，当有变更时

-
@Override
 public void onChange(ConfigChangeEvent changeEvent) {
   Set<String> keys = changeEvent.changedKeys();
   if (CollectionUtils.isEmpty(keys)) {
     return;
   }
   for (String key : keys) {
     // 1. check whether the changed key is relevant
     Collection<SpringValue> targetValues = springValueRegistry.get(beanFactory, key);
     if (targetValues == null || targetValues.isEmpty()) {
       continue;
     }

     // 2. check whether the value is really changed or not (since spring property sources have hierarchies)
     // 这里其实有一点比较绕，是因为 Apollo 里的 namespace 划分，会出现 key 相同，但是 namespace 不同的情况，所以会有个优先级存在，所以需要去校验 environment 里面的是否已经更新，如果未更新则表示不需要更新
     if (!shouldTriggerAutoUpdate(changeEvent, key)) {
       continue;
     }

     // 3. update the value
     for (SpringValue val : targetValues) {
       updateSpringValue(val);
     }
   }
 }
-

其实原理很简单，就是得了解知道下

-]]> - - Java - Apollo - value - - - Java - Apollo - value - 注解 - environment - - - - Disruptor 系列二 - /2022/02/27/Disruptor-%E7%B3%BB%E5%88%97%E4%BA%8C/ - 这里开始慢慢深入的讲一下 disruptor，首先是 lock free , 相比于前面介绍的两个阻塞队列，
disruptor 本身是不直接使用锁的，因为本身的设计是单个线程去生产，通过 cas 来维护头指针，
不直接维护尾指针，这样就减少了锁的使用，提升了性能；第二个是这次介绍的重点，
减少 false sharing 的情况，也就是常说的 伪共享 问题，那么什么叫 伪共享 呢，
这里要扯到一些 cpu 缓存的知识，

譬如我在用的这个笔记本

这里就可能看到 L2 Cache 就是针对每个核的

这里可以看到现代 CPU 的结构里，分为三级缓存，越靠近 cpu 的速度越快，存储容量越小，
而 L1 跟 L2 是 CPU 核专属的每个核都有自己的 L1 和 L2 的，其中 L1 还分为数据和指令，
像我上面的图中显示的 L1 Cache 只有 64KB 大小，其中数据 32KB，指令 32KB，
而 L2 则有 256KB，L3 有 4MB，其中的 Line Size 是我们这里比较重要的一个值，
CPU 其实会就近地从 Cache 中读取数据，碰到 Cache Miss 就再往下一级 Cache 读取，
每次读取是按照缓存行 Cache Line 读取，并且也遵循了“就近原则”，
也就是相近的数据有可能也会马上被读取，所以以行的形式读取，然而这也造成了 false sharing，
因为类似于 ArrayBlockingQueue，需要有 takeIndex , putIndex , count , 因为在同一个类中，
很有可能存在于同一个 Cache Line 中，但是这几个值会被不同的线程修改，
导致从 Cache 取出来以后立马就会被失效，所谓的就近原则也就没用了，
因为需要反复地标记 dirty 脏位，然后把 Cache 刷掉，就造成了false sharing这种情况
而在 disruptor 中则使用了填充的方式，让我的头指针能够不产生false sharing

-
class LhsPadding
{
    protected long p1, p2, p3, p4, p5, p6, p7;
}

class Value extends LhsPadding
{
    protected volatile long value;
}

class RhsPadding extends Value
{
    protected long p9, p10, p11, p12, p13, p14, p15;
}

/**
 * <p>Concurrent sequence class used for tracking the progress of
 * the ring buffer and event processors.  Support a number
 * of concurrent operations including CAS and order writes.
 *
 * <p>Also attempts to be more efficient with regards to false
 * sharing by adding padding around the volatile field.
 */
public class Sequence extends RhsPadding
{
-

通过代码可以看到，sequence 中其实真正有意义的是 value 字段，因为需要在多线程环境下可见也
使用了volatile 关键字，而 LhsPadding 和 RhsPadding 分别在value 前后填充了各
7 个 long 型的变量，long 型的变量在 Java 中是占用 8 bytes，这样就相当于不管怎么样，
value 都会单独使用一个缓存行，使得其不会产生 false sharing 的问题。

+ Disruptor 系列一 + /2022/02/13/Disruptor-%E7%B3%BB%E5%88%97%E4%B8%80/ + 很久之前就听说过这个框架，不过之前有点跟消息队列混起来，这个也是种队列，但不是跟 rocketmq，nsq 那种一样的，而是在进程内部提供队列服务的，偏向于取代ArrayBlockingQueue，因为这个阻塞队列是使用了锁来控制阻塞，关于并发其实有一些通用的最佳实践，就是用锁，即使是 JDK 提供的锁，也是比较耗资源的，当然这是跟不加锁的对比，同样是锁，JDK 的实现还是性能比较优秀的。常见的阻塞队列中例如 ArrayBlockingQueue 和 LinkedBlockingQueue 都有锁的身影的存在，区别在于 ArrayBlockingQueue 是一把锁，后者是两把锁，不过重点不在几把锁，这里其实是两个问题，一个是所谓的 lock free, 对于一个单生产者的 disruptor 来说，因为写入是只有一个线程的，是可以不用加锁，多生产者的时候使用的是 cas 来获取对应的写入坑位，另一个是解决“伪共享”问题，后面可以详细点分析，先介绍下使用
首先是数据源

+
public class LongEvent {
    private long value;

    public void set(long value) {
        this.value = value;
    }

    public long getValue() {
        return value;
    }

    public void setValue(long value) {
        this.value = value;
    }
}
+

事件生产

+
public class LongEventFactory implements EventFactory<LongEvent>
{
    public LongEvent newInstance()
    {
        return new LongEvent();
    }
}
+

事件处理器

+
public class LongEventHandler implements EventHandler<LongEvent> {

    // event 事件，
    // sequence 当前的序列 
    // 是否当前批次最后一个数据
    public void onEvent(LongEvent event, long sequence, boolean endOfBatch)
    {
        String str = String.format("long event : %s l:%s b:%s", event.getValue(), sequence, endOfBatch);
        System.out.println(str);
    }
}

+

主方法代码

+
package disruptor;

import com.lmax.disruptor.RingBuffer;
import com.lmax.disruptor.dsl.Disruptor;
import com.lmax.disruptor.util.DaemonThreadFactory;

import java.nio.ByteBuffer;

public class LongEventMain
{
    public static void main(String[] args) throws Exception
    {
        // 这个需要是 2 的幂次，这样在定位的时候只需要位移操作，也能减少各种计算操作
        int bufferSize = 1024; 

        Disruptor<LongEvent> disruptor = 
                new Disruptor<>(LongEvent::new, bufferSize, DaemonThreadFactory.INSTANCE);

        // 类似于注册处理器
        disruptor.handleEventsWith(new LongEventHandler());
        // 或者直接用 lambda
        disruptor.handleEventsWith((event, sequence, endOfBatch) ->
                System.out.println("Event: " + event));
        // 启动我们的 disruptor
        disruptor.start(); 


        RingBuffer<LongEvent> ringBuffer = disruptor.getRingBuffer(); 
        ByteBuffer bb = ByteBuffer.allocate(8);
        for (long l = 0; true; l++)
        {
            bb.putLong(0, l);
            // 生产事件
            ringBuffer.publishEvent((event, sequence, buffer) -> event.set(buffer.getLong(0)), bb);
            Thread.sleep(1000);
        }
    }
}
+

运行下可以看到运行结果

这里其实就只是最简单的使用，生产者只有一个，然后也不是批量的。

]]> Java @@ -385,23 +446,44 @@ - Apollo 如何获取当前环境 - /2022/09/04/Apollo-%E5%A6%82%E4%BD%95%E8%8E%B7%E5%8F%96%E5%BD%93%E5%89%8D%E7%8E%AF%E5%A2%83/ - 在用 Apollo 作为配置中心的过程中才到过几个坑，这边记录下，因为运行 java 服务的启动参数一般比较固定，所以我们在一个新环境里运行的时候没有特意去检查，然后突然发现业务上有一些数据异常，排查之后才发现java 服务连接了测试环境的 apollo，而原因是因为环境变量传了-Denv=fat，而在我们的环境配置中 fat 就是代表测试环境， 其实应该是-Denv=pro，而 apollo 总共有这些环境

-
public enum Env{
  LOCAL, DEV, FWS, FAT, UAT, LPT, PRO, TOOLS, UNKNOWN;

  public static Env fromString(String env) {
    Env environment = EnvUtils.transformEnv(env);
    Preconditions.checkArgument(environment != UNKNOWN, String.format("Env %s is invalid", env));
    return environment;
  }
}
-

而这些解释

-
/**
 * Here is the brief description for all the predefined environments:
 * <ul>
 *   <li>LOCAL: Local Development environment, assume you are working at the beach with no network access</li>
 *   <li>DEV: Development environment</li>
 *   <li>FWS: Feature Web Service Test environment</li>
 *   <li>FAT: Feature Acceptance Test environment</li>
 *   <li>UAT: User Acceptance Test environment</li>
 *   <li>LPT: Load and Performance Test environment</li>
 *   <li>PRO: Production environment</li>
 *   <li>TOOLS: Tooling environment, a special area in production environment which allows
 * access to test environment, e.g. Apollo Portal should be deployed in tools environment</li>
 * </ul>
 */
-

那如果要在运行时知道 apollo 当前使用的环境可以用这个

-
Env apolloEnv = ApolloInjector.getInstance(ConfigUtil.class).getApolloEnv();
-

简单记录下。

+ Disruptor 系列三 + /2022/09/25/Disruptor-%E7%B3%BB%E5%88%97%E4%B8%89/ + 原来一直有点被误导，
gatingSequences用来标识每个 processer 的操作位点，但是怎么记录更新有点搞不清楚
其实问题在于 gatingSequences 是个 Sequence 数组，首先要看下怎么加进去的，
可以看到是在 com.lmax.disruptor.RingBuffer#addGatingSequences 这个方法里添加
首先是 com.lmax.disruptor.dsl.Disruptor#handleEventsWith(com.lmax.disruptor.EventHandler<? super T>...)
然后执行 com.lmax.disruptor.dsl.Disruptor#createEventProcessors(com.lmax.disruptor.Sequence[], com.lmax.disruptor.EventHandler<? super T>[])

+
EventHandlerGroup<T> createEventProcessors(
        final Sequence[] barrierSequences,
        final EventHandler<? super T>[] eventHandlers)
    {
        checkNotStarted();

        final Sequence[] processorSequences = new Sequence[eventHandlers.length];
        final SequenceBarrier barrier = ringBuffer.newBarrier(barrierSequences);

        for (int i = 0, eventHandlersLength = eventHandlers.length; i < eventHandlersLength; i++)
        {
            final EventHandler<? super T> eventHandler = eventHandlers[i];

            // 这里将 handler 包装成一个 BatchEventProcessor
            final BatchEventProcessor<T> batchEventProcessor =
                new BatchEventProcessor<>(ringBuffer, barrier, eventHandler);

            if (exceptionHandler != null)
            {
                batchEventProcessor.setExceptionHandler(exceptionHandler);
            }

            consumerRepository.add(batchEventProcessor, eventHandler, barrier);
            processorSequences[i] = batchEventProcessor.getSequence();
        }

        updateGatingSequencesForNextInChain(barrierSequences, processorSequences);

        return new EventHandlerGroup<>(this, consumerRepository, processorSequences);
    }
+ +

在 BatchEventProcessor 在类内有个定义 sequence

+
private final Sequence sequence = new Sequence(Sequencer.INITIAL_CURSOR_VALUE);
+

然后在上面循环中的这一句取出来

+
processorSequences[i] = batchEventProcessor.getSequence();
+

调用com.lmax.disruptor.dsl.Disruptor#updateGatingSequencesForNextInChain 方法

+
private void updateGatingSequencesForNextInChain(final Sequence[] barrierSequences, final Sequence[] processorSequences)
    {
        if (processorSequences.length > 0)
        {
            // 然后在这里添加
            ringBuffer.addGatingSequences(processorSequences);
            for (final Sequence barrierSequence : barrierSequences)
            {
                ringBuffer.removeGatingSequence(barrierSequence);
            }
            consumerRepository.unMarkEventProcessorsAsEndOfChain(barrierSequences);
        }
    }
+ +

而如何更新则是在处理器 com.lmax.disruptor.BatchEventProcessor#run 中

+
public void run()
    {
        if (running.compareAndSet(IDLE, RUNNING))
        {
            sequenceBarrier.clearAlert();

            notifyStart();
            try
            {
                if (running.get() == RUNNING)
                {
                    processEvents();
                }
            }
            finally
            {
                notifyShutdown();
                running.set(IDLE);
            }
        }
        else
        {
            // This is a little bit of guess work.  The running state could of changed to HALTED by
            // this point.  However, Java does not have compareAndExchange which is the only way
            // to get it exactly correct.
            if (running.get() == RUNNING)
            {
                throw new IllegalStateException("Thread is already running");
            }
            else
            {
                earlyExit();
            }
        }
    }
+

然后是

+
private void processEvents()
    {
        T event = null;
        long nextSequence = sequence.get() + 1L;

        while (true)
        {
            try
            {
                final long availableSequence = sequenceBarrier.waitFor(nextSequence);
                if (batchStartAware != null)
                {
                    batchStartAware.onBatchStart(availableSequence - nextSequence + 1);
                }

                while (nextSequence <= availableSequence)
                {
                    event = dataProvider.get(nextSequence);
                    eventHandler.onEvent(event, nextSequence, nextSequence == availableSequence);
                    nextSequence++;
                }
                // 如果正常处理完，那就是会更新为 availableSequence，因为都处理好了
                sequence.set(availableSequence);
            }
            catch (final TimeoutException e)
            {
                notifyTimeout(sequence.get());
            }
            catch (final AlertException ex)
            {
                if (running.get() != RUNNING)
                {
                    break;
                }
            }
            catch (final Throwable ex)
            {
                handleEventException(ex, nextSequence, event);
                // 如果是异常就只是 nextSequence
                sequence.set(nextSequence);
                nextSequence++;
            }
        }
    }
]]> Java Java - Apollo - environment + Disruptor + + + + Disruptor 系列二 + /2022/02/27/Disruptor-%E7%B3%BB%E5%88%97%E4%BA%8C/ + 这里开始慢慢深入的讲一下 disruptor，首先是 lock free , 相比于前面介绍的两个阻塞队列，
disruptor 本身是不直接使用锁的，因为本身的设计是单个线程去生产，通过 cas 来维护头指针，
不直接维护尾指针，这样就减少了锁的使用，提升了性能；第二个是这次介绍的重点，
减少 false sharing 的情况，也就是常说的 伪共享 问题，那么什么叫 伪共享 呢，
这里要扯到一些 cpu 缓存的知识，

譬如我在用的这个笔记本

这里就可能看到 L2 Cache 就是针对每个核的

这里可以看到现代 CPU 的结构里，分为三级缓存，越靠近 cpu 的速度越快，存储容量越小，
而 L1 跟 L2 是 CPU 核专属的每个核都有自己的 L1 和 L2 的，其中 L1 还分为数据和指令，
像我上面的图中显示的 L1 Cache 只有 64KB 大小，其中数据 32KB，指令 32KB，
而 L2 则有 256KB，L3 有 4MB，其中的 Line Size 是我们这里比较重要的一个值，
CPU 其实会就近地从 Cache 中读取数据，碰到 Cache Miss 就再往下一级 Cache 读取，
每次读取是按照缓存行 Cache Line 读取，并且也遵循了“就近原则”，
也就是相近的数据有可能也会马上被读取，所以以行的形式读取，然而这也造成了 false sharing，
因为类似于 ArrayBlockingQueue，需要有 takeIndex , putIndex , count , 因为在同一个类中，
很有可能存在于同一个 Cache Line 中，但是这几个值会被不同的线程修改，
导致从 Cache 取出来以后立马就会被失效，所谓的就近原则也就没用了，
因为需要反复地标记 dirty 脏位，然后把 Cache 刷掉，就造成了false sharing这种情况
而在 disruptor 中则使用了填充的方式，让我的头指针能够不产生false sharing

+
class LhsPadding
{
    protected long p1, p2, p3, p4, p5, p6, p7;
}

class Value extends LhsPadding
{
    protected volatile long value;
}

class RhsPadding extends Value
{
    protected long p9, p10, p11, p12, p13, p14, p15;
}

/**
 * <p>Concurrent sequence class used for tracking the progress of
 * the ring buffer and event processors.  Support a number
 * of concurrent operations including CAS and order writes.
 *
 * <p>Also attempts to be more efficient with regards to false
 * sharing by adding padding around the volatile field.
 */
public class Sequence extends RhsPadding
{
+

通过代码可以看到，sequence 中其实真正有意义的是 value 字段，因为需要在多线程环境下可见也
使用了volatile 关键字，而 LhsPadding 和 RhsPadding 分别在value 前后填充了各
7 个 long 型的变量，long 型的变量在 Java 中是占用 8 bytes，这样就相当于不管怎么样，
value 都会单独使用一个缓存行，使得其不会产生 false sharing 的问题。

+]]> + + Java + + + Java + Disruptor @@ -546,6 +628,20 @@ JVM + + Java 线程池系列-准备篇 + /2024/02/04/Java-%E7%BA%BF%E7%A8%8B%E6%B1%A0%E7%B3%BB%E5%88%97-%E5%87%86%E5%A4%87%E7%AF%87/ + Java 线程池是 Java 并发体系里的重要组成部分，不过说起线程池一般都是几个参数，以及参数的含义和逻辑，为了更适合刚开始学习的同学或者说有一些会对这么个习惯性的概括讲法有点疑惑的，我们就从零开始，从最基础的开始看起，先来看下里面用来判断线程池状态和线程数量的部分

+
private final AtomicInteger ctl = new AtomicInteger(ctlOf(RUNNING, 0));
private static final int COUNT_BITS = Integer.SIZE - 3;
private static final int CAPACITY   = (1 << COUNT_BITS) - 1;

// runState is stored in the high-order bits
private static final int RUNNING    = -1 << COUNT_BITS;
private static final int SHUTDOWN   =  0 << COUNT_BITS;
private static final int STOP       =  1 << COUNT_BITS;
private static final int TIDYING    =  2 << COUNT_BITS;
private static final int TERMINATED =  3 << COUNT_BITS;

// Packing and unpacking ctl
private static int runStateOf(int c)     { return c & ~CAPACITY; }
private static int workerCountOf(int c)  { return c & CAPACITY; }
private static int ctlOf(int rs, int wc) { return rs | wc; }
+

这里我们先看下 COUNT_BITS 它是 Integer.SIZE - 3，Integer.SIZE 这个是 32，也就是代表了 Java 用了四个 Byte 来存一个 Integer, 那么 COUNT_BITS 就是 29，
这个 29 是用了干嘛的呢，逐步往下看，为什么先介绍 COUNT_BITS，因为第一行的 ctl 的值是通过 ctlOf(RUNNING, 0) 算出来的，而 RUNNING 又是通过等于 -1 左移 COUNT_BITS 位来得到，移动 29 位后，还剩下三位，而这三位只需要表示后面五种状态，其中只有 RUNNING 是负值，这样就巧妙的只利用了 ctl 的前三位来存储线程池的状态而后面的 29 位就是用来存储线程数量的，具体怎么取呢，我们在来看下 CAPACITY 它是 (1 << COUNT_BITS) - 1 把 1 左移 29 位后减 1，也就是 536870911，这里再补充下，左移一位就等于是乘以 2，左移 29 位就是乘以 2 的 29 次，减了 1 就是 29 位能存的最大值，代表线程池最大的线程容量，用二进制来表示就是 32 位长度的int，前三位是 0，后 29 位是 1，代表了线程池的容量，那么 runStateOf 和 workerCountOf 的理解就很简单了，
runStateOf 是 c 跟 CAPACITY 取反之后的值做”与”操作，CAPACITY 取反就变成了前三位是 1，后面的二十九位是 0，而对于”与”操作，后面的二十九位无论是什么都会被忽略，也就是取了前三位的值
workerCountOf 正好相反，直接跟 CAPACITY 做 “与” 操作，也就是取后二十九位的值
ctlOf 就是直接对 rs 与 wc 做了 “或” 操作
而前面也提到了只有 RUNNING 是负数，那么就可以直接做大小比较来判断线程池状态
这个可能对很多同学来说是非常简单的，但是对于一部分同学来说就是个拦路虎，希望能对这部分同学有所帮助。

+]]> + + Java + + + Java + + Java 线程池系列-实战篇 /2024/03/17/Java-%E7%BA%BF%E7%A8%8B%E6%B1%A0%E7%B3%BB%E5%88%97-%E5%AE%9E%E6%88%98%E7%AF%87/ @@ -572,59 +668,39 @@ - AQS篇一 - /2021/02/14/AQS%E7%AF%87%E4%B8%80/ - 很多东西都是时看时新，而且时间长了也会忘，所以再来复习下，也会有一些新的角度看法这次来聊下AQS的内容，主要是这几个点，

-

第一个线程

第一个线程抢到锁了，此时state跟阻塞队列是怎么样的，其实这里是之前没理解对的地方

-
/**
         * Fair version of tryAcquire.  Don't grant access unless
         * recursive call or no waiters or is first.
         */
        protected final boolean tryAcquire(int acquires) {
            final Thread current = Thread.currentThread();
            int c = getState();
            // 这里如果state还是0说明锁还空着
            if (c == 0) {
                // 因为是公平锁版本的，先去看下是否阻塞队列里有排着队的
                if (!hasQueuedPredecessors() &&
                    compareAndSetState(0, acquires)) {
                    // 没有排队的，并且state使用cas设置成功的就标记当前占有锁的线程是我
                    setExclusiveOwnerThread(current);
                    // 然后其实就返回了，包括阻塞队列的head和tail节点和waitStatus都没有设置
                    return true;
                }
            }
            else if (current == getExclusiveOwnerThread()) {
                int nextc = c + acquires;
                if (nextc < 0)
                    throw new Error("Maximum lock count exceeded");
                setState(nextc);
                return true;
            }
            // 这里就是第二个线程会返回false
            return false;
        }
    }
- -

第二个线程

当第二个线程进来的时候应该是怎么样，结合代码来看

-
/**
     * Acquires in exclusive mode, ignoring interrupts.  Implemented
     * by invoking at least once {@link #tryAcquire},
     * returning on success.  Otherwise the thread is queued, possibly
     * repeatedly blocking and unblocking, invoking {@link
     * #tryAcquire} until success.  This method can be used
     * to implement method {@link Lock#lock}.
     *
     * @param arg the acquire argument.  This value is conveyed to
     *        {@link #tryAcquire} but is otherwise uninterpreted and
     *        can represent anything you like.
     */
    public final void acquire(int arg) {
        // 前面第一种情况是tryAcquire直接成功了，这个if判断第一个条件就是false，就不往下执行了
        // 如果是第二个线程，第一个条件获取锁不成功，条件判断!tryAcquire(arg) == true，就会走
        // acquireQueued(addWaiter(Node.EXCLUSIVE), arg)
        if (!tryAcquire(arg) &&
            acquireQueued(addWaiter(Node.EXCLUSIVE), arg))
            selfInterrupt();
    }
- -

然后来看下addWaiter的逻辑

-
/**
     * Creates and enqueues node for current thread and given mode.
     *
     * @param mode Node.EXCLUSIVE for exclusive, Node.SHARED for shared
     * @return the new node
     */
    private Node addWaiter(Node mode) {
        // 这里是包装成一个node
        Node node = new Node(Thread.currentThread(), mode);
        // Try the fast path of enq; backup to full enq on failure
        // 最快的方式就是把当前线程的节点放在阻塞队列的最后
        Node pred = tail;
        // 只有当tail，也就是pred不为空的时候可以直接接上
        if (pred != null) {
            node.prev = pred;
            // 如果这里cas成功了，就直接接上返回了
            if (compareAndSetTail(pred, node)) {
                pred.next = node;
                return node;
            }
        }
        // 不然就会继续走到这里
        enq(node);
        return node;
    }
- -

然后就是enq的逻辑了

-
/**
     * Inserts node into queue, initializing if necessary. See picture above.
     * @param node the node to insert
     * @return node's predecessor
     */
    private Node enq(final Node node) {
        for (;;) {
            // 如果状态没变化的话，tail这时还是null的
            Node t = tail;
            if (t == null) { // Must initialize
                // 这里就会初始化头结点，就是个空节点
                if (compareAndSetHead(new Node()))
                    // tail也赋值成head
                    tail = head;
            } else {
                // 这里就设置tail了
                node.prev = t;
                if (compareAndSetTail(t, node)) {
                    t.next = node;
                    return t;
                }
            }
        }
    }
- -

所以从这里可以看出来，其实head头结点不是个真实的带有线程的节点，并且不是在第一个线程进来的时候设置的

-

解锁

通过代码来看下

-
/**
     * Attempts to release this lock.
     *
     * <p>If the current thread is the holder of this lock then the hold
     * count is decremented.  If the hold count is now zero then the lock
     * is released.  If the current thread is not the holder of this
     * lock then {@link IllegalMonitorStateException} is thrown.
     *
     * @throws IllegalMonitorStateException if the current thread does not
     *         hold this lock
     */
    public void unlock() {
        // 释放锁
        sync.release(1);
    }
/**
     * Releases in exclusive mode.  Implemented by unblocking one or
     * more threads if {@link #tryRelease} returns true.
     * This method can be used to implement method {@link Lock#unlock}.
     *
     * @param arg the release argument.  This value is conveyed to
     *        {@link #tryRelease} but is otherwise uninterpreted and
     *        can represent anything you like.
     * @return the value returned from {@link #tryRelease}
     */
    public final boolean release(int arg) {
        // 尝试去释放
        if (tryRelease(arg)) {
            Node h = head;
            if (h != null && h.waitStatus != 0)
                unparkSuccessor(h);
            return true;
        }
        return false;
    }
protected final boolean tryRelease(int releases) {
            int c = getState() - releases;
            if (Thread.currentThread() != getExclusiveOwnerThread())
                throw new IllegalMonitorStateException();
            boolean free = false;
    		// 判断是否完全释放锁，因为可重入
            if (c == 0) {
                free = true;
                setExclusiveOwnerThread(null);
            }
            setState(c);
            return free;
        }
// 这段代码和上面的一致，只是为了顺序性，又拷下来看下

public final boolean release(int arg) {
        // 尝试去释放，如果是完全释放，返回的就是true，否则是false
        if (tryRelease(arg)) {
            Node h = head;
            // 这里判断头结点是否为空以及waitStatus的状态，前面说了head节点其实是
            // 在第二个线程进来的时候初始化的，如果是空的话说明没后续节点，并且waitStatus
            // 也表示了后续的等待状态
            if (h != null && h.waitStatus != 0)
                unparkSuccessor(h);
            return true;
        }
        return false;
    }

/**
     * Wakes up node's successor, if one exists.
     *
     * @param node the node
     */
// 唤醒后继节点
    private void unparkSuccessor(Node node) {
        /*
         * If status is negative (i.e., possibly needing signal) try
         * to clear in anticipation of signalling.  It is OK if this
         * fails or if status is changed by waiting thread.
         */
        int ws = node.waitStatus;
        if (ws < 0)
            compareAndSetWaitStatus(node, ws, 0);

        /*
         * Thread to unpark is held in successor, which is normally
         * just the next node.  But if cancelled or apparently null,
         * traverse backwards from tail to find the actual
         * non-cancelled successor.
         */
        Node s = node.next;
        // 如果后继节点是空或者当前节点取消等待了
        if (s == null || s.waitStatus > 0) {
            s = null;
            // 从后往前找，找到非取消的节点，注意这里不是找到就退出，而是一直找到头
            // 所以不必担心中间有取消的
            for (Node t = tail; t != null && t != node; t = t.prev)
                if (t.waitStatus <= 0)
                    s = t;
        }
        if (s != null)
            // 将其唤醒
            LockSupport.unpark(s.thread);
    }
- - - - + Java 线程池系列-第一篇 + /2024/02/11/Java-%E7%BA%BF%E7%A8%8B%E6%B1%A0%E7%B3%BB%E5%88%97-%E7%AC%AC%E4%B8%80%E7%AF%87/ + 这一篇我们继续聊线程池，一般线程池会介绍我们的参数，我先不一样一些
我们先来翻译一下

+
 An {@link ExecutorService} that executes each submitted task using
 one of possibly several pooled threads, normally configured
 using {@link Executors} factory methods.
 // executorService 使用一个线程池中的线程来执行每个提交的任务，经常使用 Executors 工厂方法

 <p>Thread pools address two different problems: they usually
 provide improved performance when executing large numbers of
 asynchronous tasks, due to reduced per-task invocation overhead,
 and they provide a means of bounding and managing the resources,
 including threads, consumed when executing a collection of tasks.
 Each {@code ThreadPoolExecutor} also maintains some basic
 statistics, such as the number of completed tasks.
 // 线程池解决两个不同的问题，通常是为了在提交大量异步任务时，通过减少每个任务的调度开销来提高性能
 // 并且提供了一种管理和约束资源，包括线程消耗的方法，每个 ThreadPoolExecutor还会管理一些基础的统计信息
 // 比如完成的任务数量
 

 <p>To be useful across a wide range of contexts, this class
 provides many adjustable parameters and extensibility
 hooks. However, programmers are urged to use the more convenient
 {@link Executors} factory methods {@link
 Executors#newCachedThreadPool} (unbounded thread pool, with
 automatic thread reclamation), {@link Executors#newFixedThreadPool}
 (fixed size thread pool) and {@link
 Executors#newSingleThreadExecutor} (single background thread), that
 preconfigure settings for the most common usage
 scenarios. Otherwise, use the following guide when manually
 configuring and tuning this class:
 // 为了在各种情况下都能派上用场，该类提供了许多可调整的参数和扩展钩子。不过，我们建议程序员使用更方便的 Executors 工厂方法 Executors.
 // newCachedThreadPool（无限制线程池，可自动回收线程）、Executors.newFixedThreadPool（固定大小线程池）和 Executors.
 // newSingleThreadExecutor（单后台线程），这些方法可为最常见的使用场景预先配置设置。否则，在手动配置和调整该类时，请使用以下指南：

 Core and maximum pool sizes
 // 核心和最大线程池大小
    A ThreadPoolExecutor will automatically adjust the pool size (see getPoolSize) according to the bounds set by corePoolSize (see getCorePoolSize) and maximumPoolSize (see getMaximumPoolSize). When a new task is submitted in method execute(Runnable), and fewer than corePoolSize threads are running, a new thread is created to handle the request, even if other worker threads are idle. If there are more than corePoolSize but less than maximumPoolSize threads running, a new thread will be created only if the queue is full. By setting corePoolSize and maximumPoolSize the same, you create a fixed-size thread pool. By setting maximumPoolSize to an essentially unbounded value such as Integer.MAX_VALUE, you allow the pool to accommodate an arbitrary number of concurrent tasks. Most typically, core and maximum pool sizes are set only upon construction, but they may also be changed dynamically using setCorePoolSize and setMaximumPoolSize.
    // ThreadPoolExecutor 会根据 corePoolSize（参见 getCorePoolSize）和 maximumPoolSize（参见 getMaximumPoolSize）设置的界限自动调整池大小（参见 getPoolSize）。在方法 execute(Runnable) 中提交新任务时，如果运行的线程少于 corePoolSize，即使其他工作线程处于空闲状态，也会创建一个新线程来处理请求。如果运行的线程多于 corePoolSize 但少于 maximumPoolSize，则只有在队列已满时才会创建新线程。如果将 corePoolSize 和 maximumPoolSize 设置为相同，就可以创建一个固定大小的线程池。如果将 maximumPoolSize 设置为 Integer.MAX_VALUE 等基本无限制的值，就可以让池容纳任意数量的并发任务。通常，核心和最大线程池大小只在构建时设置，但也可以使用 setCorePoolSize 和 setMaximumPoolSize 动态更改。

On-demand construction
// 按需构建
    By default, even core threads are initially created and started only when new tasks arrive, but this can be overridden dynamically using method prestartCoreThread or prestartAllCoreThreads. You probably want to prestart threads if you construct the pool with a non-empty queue.
    // 默认情况下，即使是核心线程也是只有当新任务到来时才会初始创建和启动，但这可以使用方法 prestartCoreThread 或 prestartAllCoreThreads 进行动态重载。如果使用非空队列构建线程池，则可能需要预启动线程。
Creating new threads
// 创建新线程
    /** New threads are created using a ThreadFactory. If not otherwise specified, a Executors.defaultThreadFactory is used, that creates threads to all be in the same ThreadGroup and with the same NORM_PRIORITY priority and non-daemon status. By supplying a different ThreadFactory, you can alter the thread's name, thread group, priority, daemon status, etc. If a ThreadFactory fails to create a thread when asked by returning null from newThread, the executor will continue, but might not be able to execute any tasks. Threads should possess the "modifyThread" RuntimePermission. If worker threads or other threads using the pool do not possess this permission, service may be degraded: configuration changes may not take effect in a timely manner, and a shutdown pool may remain in a state in which termination is possible but not completed. */
    // 新线程是使用线程工厂（ThreadFactory）创建的。如果未另行指定，将使用 Executors.defaultThreadFactory 创建线程，创建的线程将全部位于同一线程组，并具有相同的 NORM_PRIORITY 优先级和非守护进程状态。通过提供不同的 ThreadFactory，可以更改线程的名称、线程组、优先级、守护进程状态等。如果线程工厂无法按要求创建线程，从 newThread 返回空值，执行器将继续运行，但可能无法执行任何任务。线程应拥有 "modifyThread "运行时权限。如果工作线程或使用池的其他线程不具备此权限，服务可能会降级：配置更改可能无法及时生效，关闭的池可能会一直处于可以终止但无法完成的状态。
Keep-alive times
// 保活时间
    If the pool currently has more than corePoolSize threads, excess threads will be terminated if they have been idle for more than the keepAliveTime (see getKeepAliveTime(TimeUnit)). This provides a means of reducing resource consumption when the pool is not being actively used. If the pool becomes more active later, new threads will be constructed. This parameter can also be changed dynamically using method setKeepAliveTime(long, TimeUnit). Using a value of Long.MAX_VALUE TimeUnit.NANOSECONDS effectively disables idle threads from ever terminating prior to shut down. By default, the keep-alive policy applies only when there are more than corePoolSize threads. But method allowCoreThreadTimeOut(boolean) can be used to apply this time-out policy to core threads as well, so long as the keepAliveTime value is non-zero.
    // 如果当前池中的线程数超过 corePoolSize，多余的线程在闲置时间超过 keepAliveTime（请参阅 getKeepAliveTime(TimeUnit)）时将被终止。这提供了一种在线程池未被频繁使用时减少资源消耗的方法。如果以后池变得更加活跃，就会构建新线程。也可以使用方法 setKeepAliveTime(long, TimeUnit) 动态更改该参数。使用 Long.MAX_VALUE TimeUnit.NANOSECONDS 值可有效禁止闲置线程在关闭前终止。默认情况下，只有当线程数超过 corePoolSize 时，才会采用保持连接策略。但只要 keepAliveTime 值不为零，就可以使用方法 allowCoreThreadTimeOut(boolean) 将超时策略也应用到核心线程。
Queuing
// 队列
    Any BlockingQueue may be used to transfer and hold submitted tasks. The use of this queue interacts with pool sizing:
    // 任何阻塞队列（BlockingQueue）都可用于传输和保留已提交的任务。该队列的使用与线程池大小有关：
    If fewer than corePoolSize threads are running, the Executor always prefers adding a new thread rather than queuing.
    // 如果运行的线程少于 corePoolSize，执行器总是倾向于添加新线程而不是队列。
    If corePoolSize or more threads are running, the Executor always prefers queuing a request rather than adding a new thread.
    // 如果运行的线程数大于或等于 corePoolSize，执行器总是倾向于将请求排队，而不是添加新线程。
    If a request cannot be queued, a new thread is created unless this would exceed maximumPoolSize, in which case, the task will be rejected.
    // 如果请求无法进队列，执行器会创建一个新线程，除非这样做会超过最大线程池大小（maximumPoolSize），在这种情况下，任务会被拒绝。
    There are three general strategies for queuing:
    // 入队一般有三种策略：
    Direct handoffs. A good default choice for a work queue is a SynchronousQueue that hands off tasks to threads without otherwise holding them. Here, an attempt to queue a task will fail if no threads are immediately available to run it, so a new thread will be constructed. This policy avoids lockups when handling sets of requests that might have internal dependencies. Direct handoffs generally require unbounded maximumPoolSizes to avoid rejection of new submitted tasks. This in turn admits the possibility of unbounded thread growth when commands continue to arrive on average faster than they can be processed.
    // 直接交接。工作队列的一个很好的默认选择是同步队列（SynchronousQueue），它可以将任务移交给线程，而不会以其他方式保留任务。在这里，如果没有线程可立即运行任务，则队列任务的尝试将失败，因此会构建一个新的线程。在处理可能存在内部依赖关系的请求集时，这种策略可以避免死锁。直接交接通常需要无限制的最大线程池大小，以避免新提交的任务被拒绝。反过来，当命令的平均到达速度超过其处理速度时，就有可能导致线程无限制增长。
    /** Unbounded queues. Using an unbounded queue (for example a LinkedBlockingQueue without a predefined capacity) will cause new tasks to wait in the queue when all corePoolSize threads are busy. Thus, no more than corePoolSize threads will ever be created. (And the value of the maximumPoolSize therefore doesn't have any effect.) This may be appropriate when each task is completely independent of others, so tasks cannot affect each others execution; for example, in a web page server. While this style of queuing can be useful in smoothing out transient bursts of requests, it admits the possibility of unbounded work queue growth when commands continue to arrive on average faster than they can be processed. */
    // 无界队列。使用无界队列（例如没有预定义容量的 LinkedBlockingQueue）会导致新任务在所有 corePoolSize 线程都繁忙时在队列中等待。因此，创建的线程不会超过 corePoolSize。(当每个任务都完全独立于其他任务，因此任务之间不会相互影响执行时，例如在网页服务器中，这种方式可能比较合适。虽然这种队列方式在平滑瞬时突发请求方面很有用，但当命令的平均到达速度持续超过其处理速度时，就会导致工作队列无限制地增长。
    Bounded queues. A bounded queue (for example, an ArrayBlockingQueue) helps prevent resource exhaustion when used with finite maximumPoolSizes, but can be more difficult to tune and control. Queue sizes and maximum pool sizes may be traded off for each other: Using large queues and small pools minimizes CPU usage, OS resources, and context-switching overhead, but can lead to artificially low throughput. If tasks frequently block (for example if they are I/O bound), a system may be able to schedule time for more threads than you otherwise allow. Use of small queues generally requires larger pool sizes, which keeps CPUs busier but may encounter unacceptable scheduling overhead, which also decreases throughput.
    // 有界队列 有界队列（例如 ArrayBlockingQueue）与有限的最大线程池大小一起使用时，有助于防止资源耗尽，但可能更难调整和控制。队列大小和最大池大小可以相互权衡： 使用大队列和小池可以最大限度地减少 CPU 占用率、操作系统资源和上下文切换开销，但会导致人为的低吞吐量。如果任务经常出现阻塞（例如，如果任务受 I/O 约束），系统可能会为更多线程安排时间，而不考虑其他因素。使用小队列通常需要更大的池规模，这将使 CPU 更繁忙，但可能会遇到无法接受的调度开销，这也会降低吞吐量。
Rejected tasks
// 被拒绝的任务
    New tasks submitted in method execute(Runnable) will be rejected when the Executor has been shut down, and also when the Executor uses finite bounds for both maximum threads and work queue capacity, and is saturated. In either case, the execute method invokes the RejectedExecutionHandler.rejectedExecution(Runnable, ThreadPoolExecutor) method of its RejectedExecutionHandler. Four predefined handler policies are provided:
    // 如果执行器已关闭，或者执行器使用了最大线程数和工作队列容量的有限界限，并已达到饱和，那么在 execute(Runnable) 方法中提交的新任务将被拒绝。在这两种情况下，execute 方法都会调用其 RejectedExecutionHandler 的 RejectedExecutionHandler.rejectedExecution(Runnable, ThreadPoolExecutor) 方法。提供了四种预定义的处理程序策略：
    In the default ThreadPoolExecutor.AbortPolicy, the handler throws a runtime RejectedExecutionException upon rejection.
    // 在默认的 ThreadPoolExecutor.AbortPolicy 中，处理程序会在拒绝时抛出运行时 RejectedExecutionException。
    In ThreadPoolExecutor.CallerRunsPolicy, the thread that invokes execute itself runs the task. This provides a simple feedback control mechanism that will slow down the rate that new tasks are submitted.
    // 在 ThreadPoolExecutor.CallerRunsPolicy 中，调用执行本身的线程会运行任务。这提供了一个简单的反馈控制机制，可减慢提交新任务的速度。
    In ThreadPoolExecutor.DiscardPolicy, a task that cannot be executed is simply dropped.
    // 在 ThreadPoolExecutor.DiscardPolicy 中，无法执行的任务会被直接丢弃。
    In ThreadPoolExecutor.DiscardOldestPolicy, if the executor is not shut down, the task at the head of the work queue is dropped, and then execution is retried (which can fail again, causing this to be repeated.)
    // 在 ThreadPoolExecutor.DiscardOldestPolicy 中，如果执行器没有关闭，工作队列头部的任务就会被丢弃，然后重新执行（可能会再次失败，导致重复执行）。
    It is possible to define and use other kinds of RejectedExecutionHandler classes. Doing so requires some care especially when policies are designed to work only under particular capacity or queuing policies.
    // 我们还可以定义和使用其他类型的 RejectedExecutionHandler 类。这样做需要小心谨慎，尤其是当策略设计为仅在特定容量或队列策略下运行时。
Hook methods
// 钩子方法
    This class provides protected overridable beforeExecute(Thread, Runnable) and afterExecute(Runnable, Throwable) methods that are called before and after execution of each task. These can be used to manipulate the execution environment; for example, reinitializing ThreadLocals, gathering statistics, or adding log entries. Additionally, method terminated can be overridden to perform any special processing that needs to be done once the Executor has fully terminated.
    // 该类提供 protected 的可重载 beforeExecute(Thread, Runnable) 和 afterExecute(Runnable, Throwable) 方法，可在每个任务执行前后调用。这些方法可用于操纵执行环境，例如，重新初始化线程位置、收集统计数据或添加日志条目。此外，还可以重写终止方法，以便在执行器完全终止后执行任何需要进行的特殊处理。(一些动态线程池技术就用到了这两个方法)
    If hook or callback methods throw exceptions, internal worker threads may in turn fail and abruptly terminate.
    // 如果钩子或回调方法抛出异常，内部工作线程可能会失败并突然终止。
Queue maintenance
// 队列维护
    Method getQueue() allows access to the work queue for purposes of monitoring and debugging. Use of this method for any other purpose is strongly discouraged. Two supplied methods, remove(Runnable) and purge are available to assist in storage reclamation when large numbers of queued tasks become cancelled.
    // 方法 getQueue() 允许访问工作队列，以便进行监控和调试。强烈建议不要将此方法用于任何其他目的。当大量队列任务被取消时，可使用 remove(Runnable) 和 purge 这两个提供的方法来帮助回收存储空间。(不建议直接将获取到的队列进行修改操作)
Finalization
// 终止
    A pool that is no longer referenced in a program AND has no remaining threads will be shutdown automatically. If you would like to ensure that unreferenced pools are reclaimed even if users forget to call shutdown, then you must arrange that unused threads eventually die, by setting appropriate keep-alive times, using a lower bound of zero core threads and/or setting allowCoreThreadTimeOut(boolean).
    // 程序中不再引用且没有剩余线程的池将自动关闭。如果要确保即使用户忘记调用 shutdown 也能回收未引用的池，则必须通过设置适当的保持连接时间、使用零核心线程下限和/或设置 allowCoreThreadTimeOut(boolean) 来使得未使用的线程最终被停止。
+

通过前面的简单翻译我们就能大致略窥得线程池配置全貌，继续看一个构造方法

+
public ThreadPoolExecutor(int corePoolSize,
                          int maximumPoolSize,
                          long keepAliveTime,
                          TimeUnit unit,
                          BlockingQueue<Runnable> workQueue) {
    this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
         Executors.defaultThreadFactory(), defaultHandler);
}
private static final RejectedExecutionHandler defaultHandler =
    new AbortPolicy();
+

这个构造方法就主要配置了 corePoolSize 核心线程数，maximumPoolSize 最大线程数, keepAliveTime 线程保活时间，unit 时间单位，workQueue 工作队列，而传入后可以看到使用了默认的线程工厂和默认的拒绝处理器

+
public ThreadPoolExecutor(int corePoolSize,
                          int maximumPoolSize,
                          long keepAliveTime,
                          TimeUnit unit,
                          BlockingQueue<Runnable> workQueue,
                          ThreadFactory threadFactory,
                          RejectedExecutionHandler handler) {
    if (corePoolSize < 0 ||
        maximumPoolSize <= 0 ||
        maximumPoolSize < corePoolSize ||
        keepAliveTime < 0)
        throw new IllegalArgumentException();
    if (workQueue == null || threadFactory == null || handler == null)
        throw new NullPointerException();
    this.acc = System.getSecurityManager() == null ?
            null :
            AccessController.getContext();
    this.corePoolSize = corePoolSize;
    this.maximumPoolSize = maximumPoolSize;
    this.workQueue = workQueue;
    this.keepAliveTime = unit.toNanos(keepAliveTime);
    this.threadFactory = threadFactory;
    this.handler = handler;
}
+

最终会执行到这里做一些校验判断，包括几个参数校验和配置赋值

]]> Java - 并发 - java - aqs - 并发 - j.u.c + Java - Disruptor 系列一 - /2022/02/13/Disruptor-%E7%B3%BB%E5%88%97%E4%B8%80/ - 很久之前就听说过这个框架，不过之前有点跟消息队列混起来，这个也是种队列，但不是跟 rocketmq，nsq 那种一样的，而是在进程内部提供队列服务的，偏向于取代ArrayBlockingQueue，因为这个阻塞队列是使用了锁来控制阻塞，关于并发其实有一些通用的最佳实践，就是用锁，即使是 JDK 提供的锁，也是比较耗资源的，当然这是跟不加锁的对比，同样是锁，JDK 的实现还是性能比较优秀的。常见的阻塞队列中例如 ArrayBlockingQueue 和 LinkedBlockingQueue 都有锁的身影的存在，区别在于 ArrayBlockingQueue 是一把锁，后者是两把锁，不过重点不在几把锁，这里其实是两个问题，一个是所谓的 lock free, 对于一个单生产者的 disruptor 来说，因为写入是只有一个线程的，是可以不用加锁，多生产者的时候使用的是 cas 来获取对应的写入坑位，另一个是解决“伪共享”问题，后面可以详细点分析，先介绍下使用
首先是数据源

-
public class LongEvent {
    private long value;

    public void set(long value) {
        this.value = value;
    }

    public long getValue() {
        return value;
    }

    public void setValue(long value) {
        this.value = value;
    }
}
-

事件生产

-
public class LongEventFactory implements EventFactory<LongEvent>
{
    public LongEvent newInstance()
    {
        return new LongEvent();
    }
}
-

事件处理器

-
public class LongEventHandler implements EventHandler<LongEvent> {

    // event 事件，
    // sequence 当前的序列 
    // 是否当前批次最后一个数据
    public void onEvent(LongEvent event, long sequence, boolean endOfBatch)
    {
        String str = String.format("long event : %s l:%s b:%s", event.getValue(), sequence, endOfBatch);
        System.out.println(str);
    }
}

-

主方法代码

-
package disruptor;

import com.lmax.disruptor.RingBuffer;
import com.lmax.disruptor.dsl.Disruptor;
import com.lmax.disruptor.util.DaemonThreadFactory;

import java.nio.ByteBuffer;

public class LongEventMain
{
    public static void main(String[] args) throws Exception
    {
        // 这个需要是 2 的幂次，这样在定位的时候只需要位移操作，也能减少各种计算操作
        int bufferSize = 1024; 

        Disruptor<LongEvent> disruptor = 
                new Disruptor<>(LongEvent::new, bufferSize, DaemonThreadFactory.INSTANCE);

        // 类似于注册处理器
        disruptor.handleEventsWith(new LongEventHandler());
        // 或者直接用 lambda
        disruptor.handleEventsWith((event, sequence, endOfBatch) ->
                System.out.println("Event: " + event));
        // 启动我们的 disruptor
        disruptor.start(); 


        RingBuffer<LongEvent> ringBuffer = disruptor.getRingBuffer(); 
        ByteBuffer bb = ByteBuffer.allocate(8);
        for (long l = 0; true; l++)
        {
            bb.putLong(0, l);
            // 生产事件
            ringBuffer.publishEvent((event, sequence, buffer) -> event.set(buffer.getLong(0)), bb);
            Thread.sleep(1000);
        }
    }
}
-

运行下可以看到运行结果

这里其实就只是最简单的使用，生产者只有一个，然后也不是批量的。

+ Java 线程池系列-第三篇 + /2024/02/24/Java-%E7%BA%BF%E7%A8%8B%E6%B1%A0%E7%B3%BB%E5%88%97-%E7%AC%AC%E4%B8%89%E7%AF%87/ + 第三篇我们要来讲下 Worker 这个“打工人”，线程池里实际在干活的同学
Worker 实现了 Runnable 接口，所以在前面介绍的 addWorker 中
线程启动其实就调用了下面的 run 方法，而 run 方法则调用了内部的
runWorker 方法

+

private final class Worker
    extends AbstractQueuedSynchronizer
    implements Runnable
{
    /**
     * This class will never be serialized, but we provide a
     * serialVersionUID to suppress a javac warning.
     */
    private static final long serialVersionUID = 6138294804551838833L;

    /** Thread this worker is running in.  Null if factory fails. */
    final Thread thread;
    /** Initial task to run.  Possibly null. */
    Runnable firstTask;
    /** Per-thread task counter */
    volatile long completedTasks;

    /**
     * Creates with given first task and thread from ThreadFactory.
     * @param firstTask the first task (null if none)
     */
    Worker(Runnable firstTask) {
        setState(-1); // inhibit interrupts until runWorker
        this.firstTask = firstTask;
        this.thread = getThreadFactory().newThread(this);
    }

    /** Delegates main run loop to outer runWorker  */
    // 启动线程 Worker
    public void run() {
        runWorker(this);
    }
+

介绍下这个 runWorker 方法
这里就会先处理 firstTask，如果 firstTask 是 null 则会去队列里取
里面会有两个钩子，一个是执行前，一个是执行后，注意这个循环是没有常规
退出逻辑的，说明是一直在往队列里获取，除非获取队列里的任务超时失败了
这样就到最后会去执行 processWorkerExit

+
final void runWorker(Worker w) {
        Thread wt = Thread.currentThread();
        Runnable task = w.firstTask;
        w.firstTask = null;
        w.unlock(); // allow interrupts
        boolean completedAbruptly = true;
        try {
            // firstTask 不为空或者从队列里获取到任务
            while (task != null || (task = getTask()) != null) {
                w.lock();
                // If pool is stopping, ensure thread is interrupted;
                // if not, ensure thread is not interrupted.  This
                // requires a recheck in second case to deal with
                // shutdownNow race while clearing interrupt
                if ((runStateAtLeast(ctl.get(), STOP) ||
                     (Thread.interrupted() &&
                      runStateAtLeast(ctl.get(), STOP))) &&
                    !wt.isInterrupted())
                    wt.interrupt();
                try {
                    // 前置执行钩子
                    beforeExecute(wt, task);
                    Throwable thrown = null;
                    try {
                        // 任务执行
                        task.run();
                    } catch (RuntimeException x) {
                        thrown = x; throw x;
                    } catch (Error x) {
                        thrown = x; throw x;
                    } catch (Throwable x) {
                        thrown = x; throw new Error(x);
                    } finally {
                        // 执行完后的钩子
                        afterExecute(task, thrown);
                    }
                } finally {
                    // 最后会执行到这，清空任务
                    task = null;
                    w.completedTasks++;
                    w.unlock();
                }
            }
            completedAbruptly = false;
        } finally {
            // 循环的最后就会去退出Worker
            processWorkerExit(w, completedAbruptly);
        }
    }
+

而这个 processWorkerExit 也有个比较特殊的逻辑
照理我们会想到这里可能就是线程在处理完队列里的任务
以后，就会判断下是否要退出，如果是核心线程的话就不用
如果是非核心线程就会退出了，但是这里其实有个替换逻辑
就是最后有个 addWorker 调用

+
private void processWorkerExit(Worker w, boolean completedAbruptly) {
    if (completedAbruptly) // If abrupt, then workerCount wasn't adjusted
        decrementWorkerCount();

    final ReentrantLock mainLock = this.mainLock;
    mainLock.lock();
    try {
        completedTaskCount += w.completedTasks;
        workers.remove(w);
    } finally {
        mainLock.unlock();
    }

    tryTerminate();

    int c = ctl.get();
    // 判断状态
    if (runStateLessThan(c, STOP)) {
        if (!completedAbruptly) {
            // 核心线程是否也需要退出
            int min = allowCoreThreadTimeOut ? 0 : corePoolSize;
            if (min == 0 && ! workQueue.isEmpty())
                min = 1;
            // 这里代表非核心线程就可以不用替换，也就是回收线程了
            if (workerCountOf(c) >= min)
                return; // replacement not needed
        }
        // 否则是替换线程
        addWorker(null, false);
    }
}
+

这里主要讲了线程 Worker 运行的逻辑

]]> Java Java - Disruptor @@ -644,29 +720,20 @@ - Disruptor 系列三 - /2022/09/25/Disruptor-%E7%B3%BB%E5%88%97%E4%B8%89/ - 原来一直有点被误导，
gatingSequences用来标识每个 processer 的操作位点，但是怎么记录更新有点搞不清楚
其实问题在于 gatingSequences 是个 Sequence 数组，首先要看下怎么加进去的，
可以看到是在 com.lmax.disruptor.RingBuffer#addGatingSequences 这个方法里添加
首先是 com.lmax.disruptor.dsl.Disruptor#handleEventsWith(com.lmax.disruptor.EventHandler<? super T>...)
然后执行 com.lmax.disruptor.dsl.Disruptor#createEventProcessors(com.lmax.disruptor.Sequence[], com.lmax.disruptor.EventHandler<? super T>[])

-
EventHandlerGroup<T> createEventProcessors(
        final Sequence[] barrierSequences,
        final EventHandler<? super T>[] eventHandlers)
    {
        checkNotStarted();

        final Sequence[] processorSequences = new Sequence[eventHandlers.length];
        final SequenceBarrier barrier = ringBuffer.newBarrier(barrierSequences);

        for (int i = 0, eventHandlersLength = eventHandlers.length; i < eventHandlersLength; i++)
        {
            final EventHandler<? super T> eventHandler = eventHandlers[i];

            // 这里将 handler 包装成一个 BatchEventProcessor
            final BatchEventProcessor<T> batchEventProcessor =
                new BatchEventProcessor<>(ringBuffer, barrier, eventHandler);

            if (exceptionHandler != null)
            {
                batchEventProcessor.setExceptionHandler(exceptionHandler);
            }

            consumerRepository.add(batchEventProcessor, eventHandler, barrier);
            processorSequences[i] = batchEventProcessor.getSequence();
        }

        updateGatingSequencesForNextInChain(barrierSequences, processorSequences);

        return new EventHandlerGroup<>(this, consumerRepository, processorSequences);
    }
- -

在 BatchEventProcessor 在类内有个定义 sequence

-
private final Sequence sequence = new Sequence(Sequencer.INITIAL_CURSOR_VALUE);
-

然后在上面循环中的这一句取出来

-
processorSequences[i] = batchEventProcessor.getSequence();
-

调用com.lmax.disruptor.dsl.Disruptor#updateGatingSequencesForNextInChain 方法

-
private void updateGatingSequencesForNextInChain(final Sequence[] barrierSequences, final Sequence[] processorSequences)
    {
        if (processorSequences.length > 0)
        {
            // 然后在这里添加
            ringBuffer.addGatingSequences(processorSequences);
            for (final Sequence barrierSequence : barrierSequences)
            {
                ringBuffer.removeGatingSequence(barrierSequence);
            }
            consumerRepository.unMarkEventProcessorsAsEndOfChain(barrierSequences);
        }
    }
+ Java 线程池系列-第四篇 + /2024/03/03/Java-%E7%BA%BF%E7%A8%8B%E6%B1%A0%E7%B3%BB%E5%88%97-%E7%AC%AC%E5%9B%9B%E7%AF%87/ + 这一篇主要补充两个内容，第一部分就是获取任务的逻辑
首先是状态判断，如果是停止了，SHUTDOWN或更大的了，就需要减小工作线程数量
并返回 null，使得工作线程 worker 退出，然后再判断线程数量和超时，同样如果超过了就会返回 null
然后就是去阻塞队列里获取任务，这里是阻塞着获取的

+
private Runnable getTask() {
        boolean timedOut = false; // Did the last poll() time out?

        for (;;) {
            int c = ctl.get();
            int rs = runStateOf(c);

            // Check if queue empty only if necessary.
            // 状态异常，如果是大于等于 SHUTDOWN 的，则协助关闭线程池
            if (rs >= SHUTDOWN && (rs >= STOP || workQueue.isEmpty())) {
                decrementWorkerCount();
                return null;
            }

            int wc = workerCountOf(c);

            // Are workers subject to culling?
            boolean timed = allowCoreThreadTimeOut || wc > corePoolSize;

            // 如果线程数量超过核心线程数，则帮助减少线程
            if ((wc > maximumPoolSize || (timed && timedOut))
                && (wc > 1 || workQueue.isEmpty())) {
                if (compareAndDecrementWorkerCount(c))
                    return null;
                continue;
            }

            // 如果前面的不符合，则从阻塞队列获取任务
            try {
                Runnable r = timed ?
                    workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
                    workQueue.take();
                if (r != null)
                    return r;
                timedOut = true;
            } catch (InterruptedException retry) {
                timedOut = false;
            }
        }
    }
-

而如何更新则是在处理器 com.lmax.disruptor.BatchEventProcessor#run 中

-
public void run()
    {
        if (running.compareAndSet(IDLE, RUNNING))
        {
            sequenceBarrier.clearAlert();

            notifyStart();
            try
            {
                if (running.get() == RUNNING)
                {
                    processEvents();
                }
            }
            finally
            {
                notifyShutdown();
                running.set(IDLE);
            }
        }
        else
        {
            // This is a little bit of guess work.  The running state could of changed to HALTED by
            // this point.  However, Java does not have compareAndExchange which is the only way
            // to get it exactly correct.
            if (running.get() == RUNNING)
            {
                throw new IllegalStateException("Thread is already running");
            }
            else
            {
                earlyExit();
            }
        }
    }
-

然后是

-
private void processEvents()
    {
        T event = null;
        long nextSequence = sequence.get() + 1L;

        while (true)
        {
            try
            {
                final long availableSequence = sequenceBarrier.waitFor(nextSequence);
                if (batchStartAware != null)
                {
                    batchStartAware.onBatchStart(availableSequence - nextSequence + 1);
                }

                while (nextSequence <= availableSequence)
                {
                    event = dataProvider.get(nextSequence);
                    eventHandler.onEvent(event, nextSequence, nextSequence == availableSequence);
                    nextSequence++;
                }
                // 如果正常处理完，那就是会更新为 availableSequence，因为都处理好了
                sequence.set(availableSequence);
            }
            catch (final TimeoutException e)
            {
                notifyTimeout(sequence.get());
            }
            catch (final AlertException ex)
            {
                if (running.get() != RUNNING)
                {
                    break;
                }
            }
            catch (final Throwable ex)
            {
                handleEventException(ex, nextSequence, event);
                // 如果是异常就只是 nextSequence
                sequence.set(nextSequence);
                nextSequence++;
            }
        }
    }
+

阻塞队列的 poll 主要是通过锁，和notEmpty这个 condition 来等待制定的时间
指定时间后开始 dequeue 出队

+
public E poll(long timeout, TimeUnit unit) throws InterruptedException {
    long nanos = unit.toNanos(timeout);
    final ReentrantLock lock = this.lock;
    lock.lockInterruptibly();
    try {
        while (count == 0) {
            if (nanos <= 0)
                return null;
            nanos = notEmpty.awaitNanos(nanos);
        }
        return dequeue();
    } finally {
        lock.unlock();
    }
}
+

第二部分比较重要，有的同学的问题是为什么不一开始开到最大线程，而是达到核心线程数后就进队列了，
其实池化技术最简单的原因就是希望能够复用这些线程，因为创建销毁他们的成本太大了，如果直接最大线程数的话
其实都不用用到线程池技术了，直接有多少任务就开多少线程，用完就丢了，阐述下我认为比较重要的概念点

]]> Java Java - Disruptor @@ -699,41 +766,6 @@ 题解 - - Java 线程池系列-第三篇 - /2024/02/24/Java-%E7%BA%BF%E7%A8%8B%E6%B1%A0%E7%B3%BB%E5%88%97-%E7%AC%AC%E4%B8%89%E7%AF%87/ - 第三篇我们要来讲下 Worker 这个“打工人”，线程池里实际在干活的同学
Worker 实现了 Runnable 接口，所以在前面介绍的 addWorker 中
线程启动其实就调用了下面的 run 方法，而 run 方法则调用了内部的
runWorker 方法

-

private final class Worker
    extends AbstractQueuedSynchronizer
    implements Runnable
{
    /**
     * This class will never be serialized, but we provide a
     * serialVersionUID to suppress a javac warning.
     */
    private static final long serialVersionUID = 6138294804551838833L;

    /** Thread this worker is running in.  Null if factory fails. */
    final Thread thread;
    /** Initial task to run.  Possibly null. */
    Runnable firstTask;
    /** Per-thread task counter */
    volatile long completedTasks;

    /**
     * Creates with given first task and thread from ThreadFactory.
     * @param firstTask the first task (null if none)
     */
    Worker(Runnable firstTask) {
        setState(-1); // inhibit interrupts until runWorker
        this.firstTask = firstTask;
        this.thread = getThreadFactory().newThread(this);
    }

    /** Delegates main run loop to outer runWorker  */
    // 启动线程 Worker
    public void run() {
        runWorker(this);
    }
-

介绍下这个 runWorker 方法
这里就会先处理 firstTask，如果 firstTask 是 null 则会去队列里取
里面会有两个钩子，一个是执行前，一个是执行后，注意这个循环是没有常规
退出逻辑的，说明是一直在往队列里获取，除非获取队列里的任务超时失败了
这样就到最后会去执行 processWorkerExit

-
final void runWorker(Worker w) {
        Thread wt = Thread.currentThread();
        Runnable task = w.firstTask;
        w.firstTask = null;
        w.unlock(); // allow interrupts
        boolean completedAbruptly = true;
        try {
            // firstTask 不为空或者从队列里获取到任务
            while (task != null || (task = getTask()) != null) {
                w.lock();
                // If pool is stopping, ensure thread is interrupted;
                // if not, ensure thread is not interrupted.  This
                // requires a recheck in second case to deal with
                // shutdownNow race while clearing interrupt
                if ((runStateAtLeast(ctl.get(), STOP) ||
                     (Thread.interrupted() &&
                      runStateAtLeast(ctl.get(), STOP))) &&
                    !wt.isInterrupted())
                    wt.interrupt();
                try {
                    // 前置执行钩子
                    beforeExecute(wt, task);
                    Throwable thrown = null;
                    try {
                        // 任务执行
                        task.run();
                    } catch (RuntimeException x) {
                        thrown = x; throw x;
                    } catch (Error x) {
                        thrown = x; throw x;
                    } catch (Throwable x) {
                        thrown = x; throw new Error(x);
                    } finally {
                        // 执行完后的钩子
                        afterExecute(task, thrown);
                    }
                } finally {
                    // 最后会执行到这，清空任务
                    task = null;
                    w.completedTasks++;
                    w.unlock();
                }
            }
            completedAbruptly = false;
        } finally {
            // 循环的最后就会去退出Worker
            processWorkerExit(w, completedAbruptly);
        }
    }
-

而这个 processWorkerExit 也有个比较特殊的逻辑
照理我们会想到这里可能就是线程在处理完队列里的任务
以后，就会判断下是否要退出，如果是核心线程的话就不用
如果是非核心线程就会退出了，但是这里其实有个替换逻辑
就是最后有个 addWorker 调用

-
private void processWorkerExit(Worker w, boolean completedAbruptly) {
    if (completedAbruptly) // If abrupt, then workerCount wasn't adjusted
        decrementWorkerCount();

    final ReentrantLock mainLock = this.mainLock;
    mainLock.lock();
    try {
        completedTaskCount += w.completedTasks;
        workers.remove(w);
    } finally {
        mainLock.unlock();
    }

    tryTerminate();

    int c = ctl.get();
    // 判断状态
    if (runStateLessThan(c, STOP)) {
        if (!completedAbruptly) {
            // 核心线程是否也需要退出
            int min = allowCoreThreadTimeOut ? 0 : corePoolSize;
            if (min == 0 && ! workQueue.isEmpty())
                min = 1;
            // 这里代表非核心线程就可以不用替换，也就是回收线程了
            if (workerCountOf(c) >= min)
                return; // replacement not needed
        }
        // 否则是替换线程
        addWorker(null, false);
    }
}
-

这里主要讲了线程 Worker 运行的逻辑

-]]> - - Java - - - Java - - - - Java 线程池系列-第四篇 - /2024/03/03/Java-%E7%BA%BF%E7%A8%8B%E6%B1%A0%E7%B3%BB%E5%88%97-%E7%AC%AC%E5%9B%9B%E7%AF%87/ - 这一篇主要补充两个内容，第一部分就是获取任务的逻辑
首先是状态判断，如果是停止了，SHUTDOWN或更大的了，就需要减小工作线程数量
并返回 null，使得工作线程 worker 退出，然后再判断线程数量和超时，同样如果超过了就会返回 null
然后就是去阻塞队列里获取任务，这里是阻塞着获取的

-
private Runnable getTask() {
        boolean timedOut = false; // Did the last poll() time out?

        for (;;) {
            int c = ctl.get();
            int rs = runStateOf(c);

            // Check if queue empty only if necessary.
            // 状态异常，如果是大于等于 SHUTDOWN 的，则协助关闭线程池
            if (rs >= SHUTDOWN && (rs >= STOP || workQueue.isEmpty())) {
                decrementWorkerCount();
                return null;
            }

            int wc = workerCountOf(c);

            // Are workers subject to culling?
            boolean timed = allowCoreThreadTimeOut || wc > corePoolSize;

            // 如果线程数量超过核心线程数，则帮助减少线程
            if ((wc > maximumPoolSize || (timed && timedOut))
                && (wc > 1 || workQueue.isEmpty())) {
                if (compareAndDecrementWorkerCount(c))
                    return null;
                continue;
            }

            // 如果前面的不符合，则从阻塞队列获取任务
            try {
                Runnable r = timed ?
                    workQueue.poll(keepAliveTime, TimeUnit.NANOSECONDS) :
                    workQueue.take();
                if (r != null)
                    return r;
                timedOut = true;
            } catch (InterruptedException retry) {
                timedOut = false;
            }
        }
    }
- -

阻塞队列的 poll 主要是通过锁，和notEmpty这个 condition 来等待制定的时间
指定时间后开始 dequeue 出队

-
public E poll(long timeout, TimeUnit unit) throws InterruptedException {
    long nanos = unit.toNanos(timeout);
    final ReentrantLock lock = this.lock;
    lock.lockInterruptibly();
    try {
        while (count == 0) {
            if (nanos <= 0)
                return null;
            nanos = notEmpty.awaitNanos(nanos);
        }
        return dequeue();
    } finally {
        lock.unlock();
    }
}
-

第二部分比较重要，有的同学的问题是为什么不一开始开到最大线程，而是达到核心线程数后就进队列了，
其实池化技术最简单的原因就是希望能够复用这些线程，因为创建销毁他们的成本太大了，如果直接最大线程数的话
其实都不用用到线程池技术了，直接有多少任务就开多少线程，用完就丢了，阐述下我认为比较重要的概念点

-]]> - - Java - - - Java - - Leetcode 028 实现 strStr() ( Implement strStr() ) 题解分析 /2021/10/31/Leetcode-028-%E5%AE%9E%E7%8E%B0-strStr-Implement-strStr-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ @@ -818,6 +850,39 @@ 二叉树 + + Leetcode 105 从前序与中序遍历序列构造二叉树(Construct Binary Tree from Preorder and Inorder Traversal) 题解分析 + /2020/12/13/Leetcode-105-%E4%BB%8E%E5%89%8D%E5%BA%8F%E4%B8%8E%E4%B8%AD%E5%BA%8F%E9%81%8D%E5%8E%86%E5%BA%8F%E5%88%97%E6%9E%84%E9%80%A0%E4%BA%8C%E5%8F%89%E6%A0%91-Construct-Binary-Tree-from-Preorder-and-Inorder-Traversal-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ + 题目介绍

Given preorder and inorder traversal of a tree, construct the binary tree.
给定一棵树的前序和中序遍历，构造出一棵二叉树

+

注意

You may assume that duplicates do not exist in the tree.
你可以假设树中没有重复的元素。(PS: 不然就没法做了呀)

+

例子:

preorder = [3,9,20,15,7]
inorder = [9,3,15,20,7]
+

返回的二叉树

+
  3
 / \
9  20
  /  \
 15   7
+ + +

简要分析

看到这个题可以想到一个比较常规的解法就是递归拆树，前序就是根左右，中序就是左根右，然后就是通过前序已经确定的根在中序中找到，然后去划分左右子树，这个例子里是 3，找到中序中的位置，那么就可以确定，9 是左子树，15,20,7是右子树，然后对应的可以根据左右子树的元素数量在前序中划分左右子树，再继续递归就行

+
class Solution {
    public TreeNode buildTree(int[] preorder, int[] inorder) {
      // 获取下数组长度
        int n = preorder.length;
        // 排除一下异常和边界
        if (n != inorder.length) {
            return null;
        }
        if (n == 0) {
            return null;
        }
        if (n == 1) {
            return new TreeNode(preorder[0]);
        }
        // 获得根节点
        TreeNode node = new TreeNode(preorder[0]);
        int pos = 0;
        // 找到中序中的位置
        for (int i = 0; i < inorder.length; i++) {
            if (node.val == inorder[i]) {
                pos = i;
                break;
            }
        }
        // 划分左右再进行递归，注意下`Arrays.copyOfRange`的用法
        node.left = buildTree(Arrays.copyOfRange(preorder, 1, pos + 1), Arrays.copyOfRange(inorder, 0, pos));
        node.right = buildTree(Arrays.copyOfRange(preorder, pos + 1, n), Arrays.copyOfRange(inorder, pos + 1, n));
        return node;
    }
}
]]> + + leetcode + Java + Binary Tree + java + Binary Tree + DFS + + + leetcode + java + 题解 + Binary Tree + 二叉树 + 递归 + Preorder Traversal + Inorder Traversal + 前序 + 中序 + + Leetcode 1115 交替打印 FooBar ( Print FooBar Alternately *Medium* ) 题解分析 /2022/05/01/Leetcode-1115-%E4%BA%A4%E6%9B%BF%E6%89%93%E5%8D%B0-FooBar-Print-FooBar-Alternately-Medium-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ @@ -876,39 +941,6 @@ DP - - Leetcode 105 从前序与中序遍历序列构造二叉树(Construct Binary Tree from Preorder and Inorder Traversal) 题解分析 - /2020/12/13/Leetcode-105-%E4%BB%8E%E5%89%8D%E5%BA%8F%E4%B8%8E%E4%B8%AD%E5%BA%8F%E9%81%8D%E5%8E%86%E5%BA%8F%E5%88%97%E6%9E%84%E9%80%A0%E4%BA%8C%E5%8F%89%E6%A0%91-Construct-Binary-Tree-from-Preorder-and-Inorder-Traversal-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ - 题目介绍

Given preorder and inorder traversal of a tree, construct the binary tree.
给定一棵树的前序和中序遍历，构造出一棵二叉树

-

注意

You may assume that duplicates do not exist in the tree.
你可以假设树中没有重复的元素。(PS: 不然就没法做了呀)

-

例子:

preorder = [3,9,20,15,7]
inorder = [9,3,15,20,7]
-

返回的二叉树

-
  3
 / \
9  20
  /  \
 15   7
- - -

简要分析

看到这个题可以想到一个比较常规的解法就是递归拆树，前序就是根左右，中序就是左根右，然后就是通过前序已经确定的根在中序中找到，然后去划分左右子树，这个例子里是 3，找到中序中的位置，那么就可以确定，9 是左子树，15,20,7是右子树，然后对应的可以根据左右子树的元素数量在前序中划分左右子树，再继续递归就行

-
class Solution {
    public TreeNode buildTree(int[] preorder, int[] inorder) {
      // 获取下数组长度
        int n = preorder.length;
        // 排除一下异常和边界
        if (n != inorder.length) {
            return null;
        }
        if (n == 0) {
            return null;
        }
        if (n == 1) {
            return new TreeNode(preorder[0]);
        }
        // 获得根节点
        TreeNode node = new TreeNode(preorder[0]);
        int pos = 0;
        // 找到中序中的位置
        for (int i = 0; i < inorder.length; i++) {
            if (node.val == inorder[i]) {
                pos = i;
                break;
            }
        }
        // 划分左右再进行递归，注意下`Arrays.copyOfRange`的用法
        node.left = buildTree(Arrays.copyOfRange(preorder, 1, pos + 1), Arrays.copyOfRange(inorder, 0, pos));
        node.right = buildTree(Arrays.copyOfRange(preorder, pos + 1, n), Arrays.copyOfRange(inorder, pos + 1, n));
        return node;
    }
}
]]> - - leetcode - Java - Binary Tree - java - Binary Tree - DFS - - - leetcode - java - 题解 - Binary Tree - 二叉树 - 递归 - Preorder Traversal - Inorder Traversal - 前序 - 中序 - - Leetcode 124 二叉树中的最大路径和(Binary Tree Maximum Path Sum) 题解分析 /2021/01/24/Leetcode-124-%E4%BA%8C%E5%8F%89%E6%A0%91%E4%B8%AD%E7%9A%84%E6%9C%80%E5%A4%A7%E8%B7%AF%E5%BE%84%E5%92%8C-Binary-Tree-Maximum-Path-Sum-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ @@ -1048,39 +1080,6 @@ 3Sum Closest - - Leetcode 1862 向下取整数对和 ( Sum of Floored Pairs *Hard* ) 题解分析 - /2022/09/11/Leetcode-1862-%E5%90%91%E4%B8%8B%E5%8F%96%E6%95%B4%E6%95%B0%E5%AF%B9%E5%92%8C-Sum-of-Floored-Pairs-Hard-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ - 题目介绍

Given an integer array nums, return the sum of floor(nums[i] / nums[j]) for all pairs of indices 0 <= i, j < nums.length in the array. Since the answer may be too large, return it modulo 10^9 + 7.

-

The floor() function returns the integer part of the division.

-

对应中文
给你一个整数数组 nums ，请你返回所有下标对 0 <= i, j < nums.length 的 floor(nums[i] / nums[j]) 结果之和。由于答案可能会很大，请你返回答案对10^9 + 7 取余 的结果。

-

函数 floor() 返回输入数字的整数部分。

-

示例

Example 1:

-

Input: nums = [2,5,9]
Output: 10
Explanation:
floor(2 / 5) = floor(2 / 9) = floor(5 / 9) = 0
floor(2 / 2) = floor(5 / 5) = floor(9 / 9) = 1
floor(5 / 2) = 2
floor(9 / 2) = 4
floor(9 / 5) = 1
We calculate the floor of the division for every pair of indices in the array then sum them up.

-
-

Example 2:

-

Input: nums = [7,7,7,7,7,7,7]
Output: 49

-
-

Constraints:

    -
  • 1 <= nums.length <= 10^5
    • -
  • 1 <= nums[i] <= 10^5
    • -
-

简析

这题不愧是 hard，要不是看了讨论区的一个大神的解答感觉从头做得想好久，
主要是两点，对于任何一个在里面的数，随便举个例子是 k，最简单的就是循环所有数对 k 除一下，
这样效率会很低，那么对于 k 有什么规律呢，就是对于所有小于 k 的数，往下取整都是 0，所以不用考虑，
对于所有大于 k 的数我们可以分成一个个的区间，[k,2k-1),[2k,3k-1),[3k,4k-1)……对于这些区间的
除了 k 往下取整，每个区间内的都是一样的，所以可以简化为对于任意一个 k，我只要知道与k 相同的有多少个，然后比 k 大的各个区间各有多少个数就可以了

-

代码

static final int MAXE5 = 100_000;

static final int MODULUSE9 = 1_000_000_000 + 7;

public int sumOfFlooredPairs(int[] nums) {
    int[] counts = new int[MAXE5+1];
    for (int num : nums) {
        counts[num]++;
    }
    // 这里就是很巧妙的给后一个加上前一个的值，这样其实前后任意两者之差就是这中间的元素数量
    for (int i = 1; i <= MAXE5; i++) {
        counts[i] += counts[i - 1];
    }
    long total = 0;
    for (int i = 1; i <= MAXE5; i++) {
        long sum = 0;
        if (counts[i] == counts[i-1]) {
            continue;
        }
        for (int j = 1; i*j <= MAXE5; j++) {
            int min = i * j - 1;
            int upper = i * (j + 1) - 1;
            // 在每一个区间内的数量，
            sum += (counts[Math.min(upper, MAXE5)] - counts[min]) * (long)j;
        }
        // 左边乘数的数量，即 i 位置的元素数量
        total = (total + (sum % MODULUSE9  ) * (counts[i] - counts[i-1])) % MODULUSE9;
    }
    return (int)total;
}
- -

贴出来大神的解析,解析

-

结果

-]]> - - Java - leetcode - - - leetcode - java - 题解 - - Leetcode 160 相交链表(intersection-of-two-linked-lists) 题解分析 /2021/01/10/Leetcode-160-%E7%9B%B8%E4%BA%A4%E9%93%BE%E8%A1%A8-intersection-of-two-linked-lists-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ @@ -1107,21 +1106,36 @@ - Java 线程池系列-第一篇 - /2024/02/11/Java-%E7%BA%BF%E7%A8%8B%E6%B1%A0%E7%B3%BB%E5%88%97-%E7%AC%AC%E4%B8%80%E7%AF%87/ - 这一篇我们继续聊线程池，一般线程池会介绍我们的参数，我先不一样一些
我们先来翻译一下

-
 An {@link ExecutorService} that executes each submitted task using
 one of possibly several pooled threads, normally configured
 using {@link Executors} factory methods.
 // executorService 使用一个线程池中的线程来执行每个提交的任务，经常使用 Executors 工厂方法

 <p>Thread pools address two different problems: they usually
 provide improved performance when executing large numbers of
 asynchronous tasks, due to reduced per-task invocation overhead,
 and they provide a means of bounding and managing the resources,
 including threads, consumed when executing a collection of tasks.
 Each {@code ThreadPoolExecutor} also maintains some basic
 statistics, such as the number of completed tasks.
 // 线程池解决两个不同的问题，通常是为了在提交大量异步任务时，通过减少每个任务的调度开销来提高性能
 // 并且提供了一种管理和约束资源，包括线程消耗的方法，每个 ThreadPoolExecutor还会管理一些基础的统计信息
 // 比如完成的任务数量
 

 <p>To be useful across a wide range of contexts, this class
 provides many adjustable parameters and extensibility
 hooks. However, programmers are urged to use the more convenient
 {@link Executors} factory methods {@link
 Executors#newCachedThreadPool} (unbounded thread pool, with
 automatic thread reclamation), {@link Executors#newFixedThreadPool}
 (fixed size thread pool) and {@link
 Executors#newSingleThreadExecutor} (single background thread), that
 preconfigure settings for the most common usage
 scenarios. Otherwise, use the following guide when manually
 configuring and tuning this class:
 // 为了在各种情况下都能派上用场，该类提供了许多可调整的参数和扩展钩子。不过，我们建议程序员使用更方便的 Executors 工厂方法 Executors.
 // newCachedThreadPool（无限制线程池，可自动回收线程）、Executors.newFixedThreadPool（固定大小线程池）和 Executors.
 // newSingleThreadExecutor（单后台线程），这些方法可为最常见的使用场景预先配置设置。否则，在手动配置和调整该类时，请使用以下指南：

 Core and maximum pool sizes
 // 核心和最大线程池大小
    A ThreadPoolExecutor will automatically adjust the pool size (see getPoolSize) according to the bounds set by corePoolSize (see getCorePoolSize) and maximumPoolSize (see getMaximumPoolSize). When a new task is submitted in method execute(Runnable), and fewer than corePoolSize threads are running, a new thread is created to handle the request, even if other worker threads are idle. If there are more than corePoolSize but less than maximumPoolSize threads running, a new thread will be created only if the queue is full. By setting corePoolSize and maximumPoolSize the same, you create a fixed-size thread pool. By setting maximumPoolSize to an essentially unbounded value such as Integer.MAX_VALUE, you allow the pool to accommodate an arbitrary number of concurrent tasks. Most typically, core and maximum pool sizes are set only upon construction, but they may also be changed dynamically using setCorePoolSize and setMaximumPoolSize.
    // ThreadPoolExecutor 会根据 corePoolSize（参见 getCorePoolSize）和 maximumPoolSize（参见 getMaximumPoolSize）设置的界限自动调整池大小（参见 getPoolSize）。在方法 execute(Runnable) 中提交新任务时，如果运行的线程少于 corePoolSize，即使其他工作线程处于空闲状态，也会创建一个新线程来处理请求。如果运行的线程多于 corePoolSize 但少于 maximumPoolSize，则只有在队列已满时才会创建新线程。如果将 corePoolSize 和 maximumPoolSize 设置为相同，就可以创建一个固定大小的线程池。如果将 maximumPoolSize 设置为 Integer.MAX_VALUE 等基本无限制的值，就可以让池容纳任意数量的并发任务。通常，核心和最大线程池大小只在构建时设置，但也可以使用 setCorePoolSize 和 setMaximumPoolSize 动态更改。

On-demand construction
// 按需构建
    By default, even core threads are initially created and started only when new tasks arrive, but this can be overridden dynamically using method prestartCoreThread or prestartAllCoreThreads. You probably want to prestart threads if you construct the pool with a non-empty queue.
    // 默认情况下，即使是核心线程也是只有当新任务到来时才会初始创建和启动，但这可以使用方法 prestartCoreThread 或 prestartAllCoreThreads 进行动态重载。如果使用非空队列构建线程池，则可能需要预启动线程。
Creating new threads
// 创建新线程
    /** New threads are created using a ThreadFactory. If not otherwise specified, a Executors.defaultThreadFactory is used, that creates threads to all be in the same ThreadGroup and with the same NORM_PRIORITY priority and non-daemon status. By supplying a different ThreadFactory, you can alter the thread's name, thread group, priority, daemon status, etc. If a ThreadFactory fails to create a thread when asked by returning null from newThread, the executor will continue, but might not be able to execute any tasks. Threads should possess the "modifyThread" RuntimePermission. If worker threads or other threads using the pool do not possess this permission, service may be degraded: configuration changes may not take effect in a timely manner, and a shutdown pool may remain in a state in which termination is possible but not completed. */
    // 新线程是使用线程工厂（ThreadFactory）创建的。如果未另行指定，将使用 Executors.defaultThreadFactory 创建线程，创建的线程将全部位于同一线程组，并具有相同的 NORM_PRIORITY 优先级和非守护进程状态。通过提供不同的 ThreadFactory，可以更改线程的名称、线程组、优先级、守护进程状态等。如果线程工厂无法按要求创建线程，从 newThread 返回空值，执行器将继续运行，但可能无法执行任何任务。线程应拥有 "modifyThread "运行时权限。如果工作线程或使用池的其他线程不具备此权限，服务可能会降级：配置更改可能无法及时生效，关闭的池可能会一直处于可以终止但无法完成的状态。
Keep-alive times
// 保活时间
    If the pool currently has more than corePoolSize threads, excess threads will be terminated if they have been idle for more than the keepAliveTime (see getKeepAliveTime(TimeUnit)). This provides a means of reducing resource consumption when the pool is not being actively used. If the pool becomes more active later, new threads will be constructed. This parameter can also be changed dynamically using method setKeepAliveTime(long, TimeUnit). Using a value of Long.MAX_VALUE TimeUnit.NANOSECONDS effectively disables idle threads from ever terminating prior to shut down. By default, the keep-alive policy applies only when there are more than corePoolSize threads. But method allowCoreThreadTimeOut(boolean) can be used to apply this time-out policy to core threads as well, so long as the keepAliveTime value is non-zero.
    // 如果当前池中的线程数超过 corePoolSize，多余的线程在闲置时间超过 keepAliveTime（请参阅 getKeepAliveTime(TimeUnit)）时将被终止。这提供了一种在线程池未被频繁使用时减少资源消耗的方法。如果以后池变得更加活跃，就会构建新线程。也可以使用方法 setKeepAliveTime(long, TimeUnit) 动态更改该参数。使用 Long.MAX_VALUE TimeUnit.NANOSECONDS 值可有效禁止闲置线程在关闭前终止。默认情况下，只有当线程数超过 corePoolSize 时，才会采用保持连接策略。但只要 keepAliveTime 值不为零，就可以使用方法 allowCoreThreadTimeOut(boolean) 将超时策略也应用到核心线程。
Queuing
// 队列
    Any BlockingQueue may be used to transfer and hold submitted tasks. The use of this queue interacts with pool sizing:
    // 任何阻塞队列（BlockingQueue）都可用于传输和保留已提交的任务。该队列的使用与线程池大小有关：
    If fewer than corePoolSize threads are running, the Executor always prefers adding a new thread rather than queuing.
    // 如果运行的线程少于 corePoolSize，执行器总是倾向于添加新线程而不是队列。
    If corePoolSize or more threads are running, the Executor always prefers queuing a request rather than adding a new thread.
    // 如果运行的线程数大于或等于 corePoolSize，执行器总是倾向于将请求排队，而不是添加新线程。
    If a request cannot be queued, a new thread is created unless this would exceed maximumPoolSize, in which case, the task will be rejected.
    // 如果请求无法进队列，执行器会创建一个新线程，除非这样做会超过最大线程池大小（maximumPoolSize），在这种情况下，任务会被拒绝。
    There are three general strategies for queuing:
    // 入队一般有三种策略：
    Direct handoffs. A good default choice for a work queue is a SynchronousQueue that hands off tasks to threads without otherwise holding them. Here, an attempt to queue a task will fail if no threads are immediately available to run it, so a new thread will be constructed. This policy avoids lockups when handling sets of requests that might have internal dependencies. Direct handoffs generally require unbounded maximumPoolSizes to avoid rejection of new submitted tasks. This in turn admits the possibility of unbounded thread growth when commands continue to arrive on average faster than they can be processed.
    // 直接交接。工作队列的一个很好的默认选择是同步队列（SynchronousQueue），它可以将任务移交给线程，而不会以其他方式保留任务。在这里，如果没有线程可立即运行任务，则队列任务的尝试将失败，因此会构建一个新的线程。在处理可能存在内部依赖关系的请求集时，这种策略可以避免死锁。直接交接通常需要无限制的最大线程池大小，以避免新提交的任务被拒绝。反过来，当命令的平均到达速度超过其处理速度时，就有可能导致线程无限制增长。
    /** Unbounded queues. Using an unbounded queue (for example a LinkedBlockingQueue without a predefined capacity) will cause new tasks to wait in the queue when all corePoolSize threads are busy. Thus, no more than corePoolSize threads will ever be created. (And the value of the maximumPoolSize therefore doesn't have any effect.) This may be appropriate when each task is completely independent of others, so tasks cannot affect each others execution; for example, in a web page server. While this style of queuing can be useful in smoothing out transient bursts of requests, it admits the possibility of unbounded work queue growth when commands continue to arrive on average faster than they can be processed. */
    // 无界队列。使用无界队列（例如没有预定义容量的 LinkedBlockingQueue）会导致新任务在所有 corePoolSize 线程都繁忙时在队列中等待。因此，创建的线程不会超过 corePoolSize。(当每个任务都完全独立于其他任务，因此任务之间不会相互影响执行时，例如在网页服务器中，这种方式可能比较合适。虽然这种队列方式在平滑瞬时突发请求方面很有用，但当命令的平均到达速度持续超过其处理速度时，就会导致工作队列无限制地增长。
    Bounded queues. A bounded queue (for example, an ArrayBlockingQueue) helps prevent resource exhaustion when used with finite maximumPoolSizes, but can be more difficult to tune and control. Queue sizes and maximum pool sizes may be traded off for each other: Using large queues and small pools minimizes CPU usage, OS resources, and context-switching overhead, but can lead to artificially low throughput. If tasks frequently block (for example if they are I/O bound), a system may be able to schedule time for more threads than you otherwise allow. Use of small queues generally requires larger pool sizes, which keeps CPUs busier but may encounter unacceptable scheduling overhead, which also decreases throughput.
    // 有界队列 有界队列（例如 ArrayBlockingQueue）与有限的最大线程池大小一起使用时，有助于防止资源耗尽，但可能更难调整和控制。队列大小和最大池大小可以相互权衡： 使用大队列和小池可以最大限度地减少 CPU 占用率、操作系统资源和上下文切换开销，但会导致人为的低吞吐量。如果任务经常出现阻塞（例如，如果任务受 I/O 约束），系统可能会为更多线程安排时间，而不考虑其他因素。使用小队列通常需要更大的池规模，这将使 CPU 更繁忙，但可能会遇到无法接受的调度开销，这也会降低吞吐量。
Rejected tasks
// 被拒绝的任务
    New tasks submitted in method execute(Runnable) will be rejected when the Executor has been shut down, and also when the Executor uses finite bounds for both maximum threads and work queue capacity, and is saturated. In either case, the execute method invokes the RejectedExecutionHandler.rejectedExecution(Runnable, ThreadPoolExecutor) method of its RejectedExecutionHandler. Four predefined handler policies are provided:
    // 如果执行器已关闭，或者执行器使用了最大线程数和工作队列容量的有限界限，并已达到饱和，那么在 execute(Runnable) 方法中提交的新任务将被拒绝。在这两种情况下，execute 方法都会调用其 RejectedExecutionHandler 的 RejectedExecutionHandler.rejectedExecution(Runnable, ThreadPoolExecutor) 方法。提供了四种预定义的处理程序策略：
    In the default ThreadPoolExecutor.AbortPolicy, the handler throws a runtime RejectedExecutionException upon rejection.
    // 在默认的 ThreadPoolExecutor.AbortPolicy 中，处理程序会在拒绝时抛出运行时 RejectedExecutionException。
    In ThreadPoolExecutor.CallerRunsPolicy, the thread that invokes execute itself runs the task. This provides a simple feedback control mechanism that will slow down the rate that new tasks are submitted.
    // 在 ThreadPoolExecutor.CallerRunsPolicy 中，调用执行本身的线程会运行任务。这提供了一个简单的反馈控制机制，可减慢提交新任务的速度。
    In ThreadPoolExecutor.DiscardPolicy, a task that cannot be executed is simply dropped.
    // 在 ThreadPoolExecutor.DiscardPolicy 中，无法执行的任务会被直接丢弃。
    In ThreadPoolExecutor.DiscardOldestPolicy, if the executor is not shut down, the task at the head of the work queue is dropped, and then execution is retried (which can fail again, causing this to be repeated.)
    // 在 ThreadPoolExecutor.DiscardOldestPolicy 中，如果执行器没有关闭，工作队列头部的任务就会被丢弃，然后重新执行（可能会再次失败，导致重复执行）。
    It is possible to define and use other kinds of RejectedExecutionHandler classes. Doing so requires some care especially when policies are designed to work only under particular capacity or queuing policies.
    // 我们还可以定义和使用其他类型的 RejectedExecutionHandler 类。这样做需要小心谨慎，尤其是当策略设计为仅在特定容量或队列策略下运行时。
Hook methods
// 钩子方法
    This class provides protected overridable beforeExecute(Thread, Runnable) and afterExecute(Runnable, Throwable) methods that are called before and after execution of each task. These can be used to manipulate the execution environment; for example, reinitializing ThreadLocals, gathering statistics, or adding log entries. Additionally, method terminated can be overridden to perform any special processing that needs to be done once the Executor has fully terminated.
    // 该类提供 protected 的可重载 beforeExecute(Thread, Runnable) 和 afterExecute(Runnable, Throwable) 方法，可在每个任务执行前后调用。这些方法可用于操纵执行环境，例如，重新初始化线程位置、收集统计数据或添加日志条目。此外，还可以重写终止方法，以便在执行器完全终止后执行任何需要进行的特殊处理。(一些动态线程池技术就用到了这两个方法)
    If hook or callback methods throw exceptions, internal worker threads may in turn fail and abruptly terminate.
    // 如果钩子或回调方法抛出异常，内部工作线程可能会失败并突然终止。
Queue maintenance
// 队列维护
    Method getQueue() allows access to the work queue for purposes of monitoring and debugging. Use of this method for any other purpose is strongly discouraged. Two supplied methods, remove(Runnable) and purge are available to assist in storage reclamation when large numbers of queued tasks become cancelled.
    // 方法 getQueue() 允许访问工作队列，以便进行监控和调试。强烈建议不要将此方法用于任何其他目的。当大量队列任务被取消时，可使用 remove(Runnable) 和 purge 这两个提供的方法来帮助回收存储空间。(不建议直接将获取到的队列进行修改操作)
Finalization
// 终止
    A pool that is no longer referenced in a program AND has no remaining threads will be shutdown automatically. If you would like to ensure that unreferenced pools are reclaimed even if users forget to call shutdown, then you must arrange that unused threads eventually die, by setting appropriate keep-alive times, using a lower bound of zero core threads and/or setting allowCoreThreadTimeOut(boolean).
    // 程序中不再引用且没有剩余线程的池将自动关闭。如果要确保即使用户忘记调用 shutdown 也能回收未引用的池，则必须通过设置适当的保持连接时间、使用零核心线程下限和/或设置 allowCoreThreadTimeOut(boolean) 来使得未使用的线程最终被停止。
-

通过前面的简单翻译我们就能大致略窥得线程池配置全貌，继续看一个构造方法

-
public ThreadPoolExecutor(int corePoolSize,
                          int maximumPoolSize,
                          long keepAliveTime,
                          TimeUnit unit,
                          BlockingQueue<Runnable> workQueue) {
    this(corePoolSize, maximumPoolSize, keepAliveTime, unit, workQueue,
         Executors.defaultThreadFactory(), defaultHandler);
}
private static final RejectedExecutionHandler defaultHandler =
    new AbortPolicy();
-

这个构造方法就主要配置了 corePoolSize 核心线程数，maximumPoolSize 最大线程数, keepAliveTime 线程保活时间，unit 时间单位，workQueue 工作队列，而传入后可以看到使用了默认的线程工厂和默认的拒绝处理器

-
public ThreadPoolExecutor(int corePoolSize,
                          int maximumPoolSize,
                          long keepAliveTime,
                          TimeUnit unit,
                          BlockingQueue<Runnable> workQueue,
                          ThreadFactory threadFactory,
                          RejectedExecutionHandler handler) {
    if (corePoolSize < 0 ||
        maximumPoolSize <= 0 ||
        maximumPoolSize < corePoolSize ||
        keepAliveTime < 0)
        throw new IllegalArgumentException();
    if (workQueue == null || threadFactory == null || handler == null)
        throw new NullPointerException();
    this.acc = System.getSecurityManager() == null ?
            null :
            AccessController.getContext();
    this.corePoolSize = corePoolSize;
    this.maximumPoolSize = maximumPoolSize;
    this.workQueue = workQueue;
    this.keepAliveTime = unit.toNanos(keepAliveTime);
    this.threadFactory = threadFactory;
    this.handler = handler;
}
-

最终会执行到这里做一些校验判断，包括几个参数校验和配置赋值

+ Leetcode 1862 向下取整数对和 ( Sum of Floored Pairs *Hard* ) 题解分析 + /2022/09/11/Leetcode-1862-%E5%90%91%E4%B8%8B%E5%8F%96%E6%95%B4%E6%95%B0%E5%AF%B9%E5%92%8C-Sum-of-Floored-Pairs-Hard-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ + 题目介绍

Given an integer array nums, return the sum of floor(nums[i] / nums[j]) for all pairs of indices 0 <= i, j < nums.length in the array. Since the answer may be too large, return it modulo 10^9 + 7.

+

The floor() function returns the integer part of the division.

+

对应中文
给你一个整数数组 nums ，请你返回所有下标对 0 <= i, j < nums.length 的 floor(nums[i] / nums[j]) 结果之和。由于答案可能会很大，请你返回答案对10^9 + 7 取余 的结果。

+

函数 floor() 返回输入数字的整数部分。

+

示例

Example 1:

+

Input: nums = [2,5,9]
Output: 10
Explanation:
floor(2 / 5) = floor(2 / 9) = floor(5 / 9) = 0
floor(2 / 2) = floor(5 / 5) = floor(9 / 9) = 1
floor(5 / 2) = 2
floor(9 / 2) = 4
floor(9 / 5) = 1
We calculate the floor of the division for every pair of indices in the array then sum them up.

+
+

Example 2:

+

Input: nums = [7,7,7,7,7,7,7]
Output: 49

+
+

Constraints:

    +
  • 1 <= nums.length <= 10^5
    • +
  • 1 <= nums[i] <= 10^5
    • +
+

简析

这题不愧是 hard，要不是看了讨论区的一个大神的解答感觉从头做得想好久，
主要是两点，对于任何一个在里面的数，随便举个例子是 k，最简单的就是循环所有数对 k 除一下，
这样效率会很低，那么对于 k 有什么规律呢，就是对于所有小于 k 的数，往下取整都是 0，所以不用考虑，
对于所有大于 k 的数我们可以分成一个个的区间，[k,2k-1),[2k,3k-1),[3k,4k-1)……对于这些区间的
除了 k 往下取整，每个区间内的都是一样的，所以可以简化为对于任意一个 k，我只要知道与k 相同的有多少个，然后比 k 大的各个区间各有多少个数就可以了

+

代码

static final int MAXE5 = 100_000;

static final int MODULUSE9 = 1_000_000_000 + 7;

public int sumOfFlooredPairs(int[] nums) {
    int[] counts = new int[MAXE5+1];
    for (int num : nums) {
        counts[num]++;
    }
    // 这里就是很巧妙的给后一个加上前一个的值，这样其实前后任意两者之差就是这中间的元素数量
    for (int i = 1; i <= MAXE5; i++) {
        counts[i] += counts[i - 1];
    }
    long total = 0;
    for (int i = 1; i <= MAXE5; i++) {
        long sum = 0;
        if (counts[i] == counts[i-1]) {
            continue;
        }
        for (int j = 1; i*j <= MAXE5; j++) {
            int min = i * j - 1;
            int upper = i * (j + 1) - 1;
            // 在每一个区间内的数量，
            sum += (counts[Math.min(upper, MAXE5)] - counts[min]) * (long)j;
        }
        // 左边乘数的数量，即 i 位置的元素数量
        total = (total + (sum % MODULUSE9  ) * (counts[i] - counts[i-1])) % MODULUSE9;
    }
    return (int)total;
}
+ +

贴出来大神的解析,解析

+

结果

]]> Java + leetcode - Java + leetcode + java + 题解 @@ -1232,6 +1246,49 @@ Lowest Common Ancestor of a Binary Tree + + Leetcode 25 Reverse Nodes in k-Group 题解分析 + /2020/08/16/Leetcode-25-Reverse-Nodes-in-k-Group-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90-1/ + Given a linked list, reverse the nodes of a linked list k at a time and return its modified list.

+

k is a positive integer and is less than or equal to the length of the linked list. If the number of nodes is not a multiple of k then left-out nodes in the end should remain as it is.

+

Example:

Given this linked list: 1->2->3->4->5

+

For k = 2, you should return: 2->1->4->3->5

+

For k = 3, you should return: 3->2->1->4->5

+

Note:

    +
  • Only constant extra memory is allowed.
    • +
  • You may not alter the values in the list’s nodes, only nodes itself may be changed.
    • +
+

这个题也算是经典中的经典了，各种算法题中的保留曲目，可能不全一样，不过反正都是逆转，这个算是比较难度大的，普通的应该就是整个链表反转，或者只对一个链表中的 m 到 n 位做翻转，这里是 k 个一组做翻转，其实这道题比较难的点是两个，一个是想清楚怎么处理，一个是代码的处理
简单来看下

+
public ListNode reverseKGroup(ListNode head, int k) {
    if (k <= 1) {
        return head;
    }
    if (head == null) {
        return null;
    }
    ListNode tempEnd = head;
    ListNode tempHead = head;
    ListNode lastHead = null;
    boolean isHeadSet = false;
    while (true) {
        // k 个一组获取头尾
        for (int i = 0; i < k - 1; i++) {
            System.out.println(tempEnd.val);
            if (tempEnd.next != null) {
                tempEnd  = tempEnd.next;
            } else {
                tempEnd = null;
                break;
            }
        }
        if (tempEnd != null) {
            if (!isHeadSet) {
                // 只有在第一组返回的时候需要赋值给 head
                head = reverse(null, tempHead, tempEnd);
                isHeadSet = !isHeadSet;
            } else {
                // 后面的需要将前一组的尾巴传进去，作为后一组头
                reverse(lastHead, tempHead, tempEnd);
            }
            if (tempHead.next != null) {
                // 如果后续节点还有
                lastHead = tempHead;
                tempEnd = tempHead.next;
                tempHead = tempHead.next;
            } else {
                break;
            }
        } else {
            break;
        }
    }

    return head;
}
public ListNode reverse(ListNode lastHead, ListNode tempHead, ListNode tempEnd) {
    // k 个一组的头尾传进来
    ListNode tail = null;
    while (tail != tempEnd) {
        // tail 表示是将头往后换时，把后面那个先拿着
        tail = tempHead.next;
        // 然后就是交换
        tempHead.next = tempEnd.next;
        tempEnd.next = tempHead;
        tempHead = tail;
    }
    if (lastHead !=null) {
        // 如果不是第一组，则需要接上前一组的尾巴
        lastHead.next = tail;
    }
    return tail;
}
]]> + + Java + leetcode + + + leetcode + java + 题解 + + + + Leetcode 25 Reverse Nodes in k-Group 题解分析-再解分析 + /2024/01/21/Leetcode-25-Reverse-Nodes-in-k-Group-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ + 上一次主要是给了一个解题方案，没有具体讲解，这次又做到了就来看下几种方案，链表转置一直是我比较疑惑的问题，特别是边界处理，而这个问题要把难度加大了
我先讲一下我一开始的思路和解题方法，首先就是写一个转置方法，就处理 k 个一组的内部转置，然后外部循环处理分组以及前后连接等问题，但是这里就涉及到一个问题，就是前后连接的话对于整个链表头，也就是第一个 k 元素组来说，头是个空的，就需要额外处理，一开始就是用判空做额外处理，然后在前后连接的时候也有一些困扰，看了自己的代码库发现其实之前也做过，而且发现这个思路跟以前做的还是一样的，只不过在处理 k 个元素内部的转置的时候有了点差异

一开始的思路是这样的，想了下其实还是比较有问题，从处理难度上来说，在 k 组内处理的时候一开始 A 节点会是悬空的，然后得处理到组内最后一个元素的时候再接上，逻辑会更复杂，而另一种思路就是直接把 A 先挪到 C 后面，这样每次只需要移动一个，可能思路上会更清晰一点

也就是这样的，这种方案就是之前发过的题解代码，上一篇

+

而最后这种则代码会简单一些，但是需要一定的理解成本，比较重要的一点是我们加了个虚拟的头结点，第一步会先获取下链表的总长度，然后在内循环里处理转置，重点就是分四步，
也就是图里的，第一步先把 cur 的下一个节点设置成 next 的 next 节点，这里就是图里 A 连接到 C，第二步是把 next 的 next 节点设置成虚拟头的 next节点，第三步是把 pre 的next 节点设置成 next，第四步是 next 往后移动

+
cur.next = next.next;
next.next = pre.next;
pre.next = next;
next = cur.next;
+ +


在备注下代码

+]]> + + Java + leetcode + + + leetcode + java + 题解 + + Leetcode 278 第一个错误的版本 ( First Bad Version *Easy* ) 题解分析 /2022/08/14/Leetcode-278-%E7%AC%AC%E4%B8%80%E4%B8%AA%E9%94%99%E8%AF%AF%E7%9A%84%E7%89%88%E6%9C%AC-First-Bad-Version-Easy-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ @@ -1393,6 +1450,32 @@ 矩阵 + + Leetcode 572 Subtree of Another Tree 题解分析 + /2024/01/28/Leetcode-572-Subtree-of-Another-Tree-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ + 题目介绍

Given the roots of two binary trees root and subRoot, return true if there is a subtree of root with the same structure and node values of subRoot and false otherwise.

+

A subtree of a binary tree tree is a tree that consists of a node in tree and all of this node’s descendants. The tree tree could also be considered as a subtree of itself.

+

示例 1

+
+

Input: root = [3,4,5,1,2], subRoot = [4,1,2]
Output: true

+
+

示例 2

+
+

Input: root = [3,4,5,1,2,null,null,null,null,0], subRoot = [4,1,2]
Output: false

+
+

解析

需要判断subRoot 为根节点的这棵树是不是 root 为根节点的这个树的子树，题应该不是特别难理解，只是需要注意，这里是子树，而不是一个子结构，也就是示例 2 的判断结果是 false，因为左边子树还有个 0，只能认为是左边的一部分，但不是子树，思路分析也不难，就是递归去判断，只不过是两种维度，第一种就是找到子树的根节点，也就是在 root 树找到 subRoot 的根节点相同的节点，这个就会用到递归，如果找到了一个，就开始递归的对比所有子节点，必须完全一样

+

代码

public boolean isSubtree(TreeNode root, TreeNode subRoot) {
       if (subRoot == null || root == null) {
           return false;
       }
       if (root.val == subRoot.val) {
           // 如果 root 节点跟 subRoot 节点相同，就开始递归对比所有的子节点
           if (isSameTree(root.left, subRoot.left) && isSameTree(root.right, subRoot.right)) {
               return true;
           }
       }
       // 如果 root 节点不同，就开始递归往下找与 subRoot 相同的起始节点，这里是或的关系，因为在左右子树任一找到一个就行
       return isSubtree(root.left, subRoot) || isSubtree(root.right, subRoot);
   }
   // 需要完全相同，也就是说不能像示例 2 那样多一个子节点这种，以及其他不同的情况，反正就是要完全一样
   public boolean isSameTree(TreeNode root, TreeNode subTree) {
       // 如果递归到这个节点都为空也认为是相同的
       if (root == null && subTree == null) {
           return true;
       }
       // 因为有前面的判断，这里就隐含了 subTree != null 这个条件
       if (root == null) {
           return false;
       }
       // 也因为有前面的判断，这里就隐含了  root != null 这个条件
       if (subTree == null) {
           return false;
       }
       // 两个都不为空，但是值不相同，也是 false
       if (root.val != subTree.val) {
           return false;
       }
       // 跟节点相同，就开始递归判断左右子树，必须两者都相同
       return isSameTree(root.left, subTree.left) && isSameTree(root.right, subTree.right);
   }
+]]> + + Java + leetcode + + + leetcode + java + 题解 + + Leetcode 698 划分为k个相等的子集 ( Partition to K Equal Sum Subsets *Medium* ) 题解分析 /2022/06/19/Leetcode-698-%E5%88%92%E5%88%86%E4%B8%BAk%E4%B8%AA%E7%9B%B8%E7%AD%89%E7%9A%84%E5%AD%90%E9%9B%86-Partition-to-K-Equal-Sum-Subsets-Medium-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ @@ -1487,20 +1570,6 @@ Remove Duplicates from Sorted List - - Java 线程池系列-准备篇 - /2024/02/04/Java-%E7%BA%BF%E7%A8%8B%E6%B1%A0%E7%B3%BB%E5%88%97-%E5%87%86%E5%A4%87%E7%AF%87/ - Java 线程池是 Java 并发体系里的重要组成部分，不过说起线程池一般都是几个参数，以及参数的含义和逻辑，为了更适合刚开始学习的同学或者说有一些会对这么个习惯性的概括讲法有点疑惑的，我们就从零开始，从最基础的开始看起，先来看下里面用来判断线程池状态和线程数量的部分

-
private final AtomicInteger ctl = new AtomicInteger(ctlOf(RUNNING, 0));
private static final int COUNT_BITS = Integer.SIZE - 3;
private static final int CAPACITY   = (1 << COUNT_BITS) - 1;

// runState is stored in the high-order bits
private static final int RUNNING    = -1 << COUNT_BITS;
private static final int SHUTDOWN   =  0 << COUNT_BITS;
private static final int STOP       =  1 << COUNT_BITS;
private static final int TIDYING    =  2 << COUNT_BITS;
private static final int TERMINATED =  3 << COUNT_BITS;

// Packing and unpacking ctl
private static int runStateOf(int c)     { return c & ~CAPACITY; }
private static int workerCountOf(int c)  { return c & CAPACITY; }
private static int ctlOf(int rs, int wc) { return rs | wc; }
-

这里我们先看下 COUNT_BITS 它是 Integer.SIZE - 3，Integer.SIZE 这个是 32，也就是代表了 Java 用了四个 Byte 来存一个 Integer, 那么 COUNT_BITS 就是 29，
这个 29 是用了干嘛的呢，逐步往下看，为什么先介绍 COUNT_BITS，因为第一行的 ctl 的值是通过 ctlOf(RUNNING, 0) 算出来的，而 RUNNING 又是通过等于 -1 左移 COUNT_BITS 位来得到，移动 29 位后，还剩下三位，而这三位只需要表示后面五种状态，其中只有 RUNNING 是负值，这样就巧妙的只利用了 ctl 的前三位来存储线程池的状态而后面的 29 位就是用来存储线程数量的，具体怎么取呢，我们在来看下 CAPACITY 它是 (1 << COUNT_BITS) - 1 把 1 左移 29 位后减 1，也就是 536870911，这里再补充下，左移一位就等于是乘以 2，左移 29 位就是乘以 2 的 29 次，减了 1 就是 29 位能存的最大值，代表线程池最大的线程容量，用二进制来表示就是 32 位长度的int，前三位是 0，后 29 位是 1，代表了线程池的容量，那么 runStateOf 和 workerCountOf 的理解就很简单了，
runStateOf 是 c 跟 CAPACITY 取反之后的值做”与”操作，CAPACITY 取反就变成了前三位是 1，后面的二十九位是 0，而对于”与”操作，后面的二十九位无论是什么都会被忽略，也就是取了前三位的值
workerCountOf 正好相反，直接跟 CAPACITY 做 “与” 操作，也就是取后二十九位的值
ctlOf 就是直接对 rs 与 wc 做了 “或” 操作
而前面也提到了只有 RUNNING 是负数，那么就可以直接做大小比较来判断线程池状态
这个可能对很多同学来说是非常简单的，但是对于一部分同学来说就是个拦路虎，希望能对这部分同学有所帮助。

-]]> - - Java - - - Java - - Leetcode 885 螺旋矩阵 III ( Spiral Matrix III *Medium* ) 题解分析 /2022/08/23/Leetcode-885-%E8%9E%BA%E6%97%8B%E7%9F%A9%E9%98%B5-III-Spiral-Matrix-III-Medium-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ @@ -1569,8 +1638,8 @@ ]]> Linux - 命令 小技巧 + 命令 grep grep 查日志 @@ -1635,56 +1704,32 @@ - Leetcode 25 Reverse Nodes in k-Group 题解分析 - /2020/08/16/Leetcode-25-Reverse-Nodes-in-k-Group-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90-1/ - Given a linked list, reverse the nodes of a linked list k at a time and return its modified list.

-

k is a positive integer and is less than or equal to the length of the linked list. If the number of nodes is not a multiple of k then left-out nodes in the end should remain as it is.

-

Example:

Given this linked list: 1->2->3->4->5

-

For k = 2, you should return: 2->1->4->3->5

-

For k = 3, you should return: 3->2->1->4->5

-

Note:

    -
  • Only constant extra memory is allowed.
    • -
  • You may not alter the values in the list’s nodes, only nodes itself may be changed.
    • -
-

这个题也算是经典中的经典了，各种算法题中的保留曲目，可能不全一样，不过反正都是逆转，这个算是比较难度大的，普通的应该就是整个链表反转，或者只对一个链表中的 m 到 n 位做翻转，这里是 k 个一组做翻转，其实这道题比较难的点是两个，一个是想清楚怎么处理，一个是代码的处理
简单来看下

-
public ListNode reverseKGroup(ListNode head, int k) {
    if (k <= 1) {
        return head;
    }
    if (head == null) {
        return null;
    }
    ListNode tempEnd = head;
    ListNode tempHead = head;
    ListNode lastHead = null;
    boolean isHeadSet = false;
    while (true) {
        // k 个一组获取头尾
        for (int i = 0; i < k - 1; i++) {
            System.out.println(tempEnd.val);
            if (tempEnd.next != null) {
                tempEnd  = tempEnd.next;
            } else {
                tempEnd = null;
                break;
            }
        }
        if (tempEnd != null) {
            if (!isHeadSet) {
                // 只有在第一组返回的时候需要赋值给 head
                head = reverse(null, tempHead, tempEnd);
                isHeadSet = !isHeadSet;
            } else {
                // 后面的需要将前一组的尾巴传进去，作为后一组头
                reverse(lastHead, tempHead, tempEnd);
            }
            if (tempHead.next != null) {
                // 如果后续节点还有
                lastHead = tempHead;
                tempEnd = tempHead.next;
                tempHead = tempHead.next;
            } else {
                break;
            }
        } else {
            break;
        }
    }

    return head;
}
public ListNode reverse(ListNode lastHead, ListNode tempHead, ListNode tempEnd) {
    // k 个一组的头尾传进来
    ListNode tail = null;
    while (tail != tempEnd) {
        // tail 表示是将头往后换时，把后面那个先拿着
        tail = tempHead.next;
        // 然后就是交换
        tempHead.next = tempEnd.next;
        tempEnd.next = tempHead;
        tempHead = tail;
    }
    if (lastHead !=null) {
        // 如果不是第一组，则需要接上前一组的尾巴
        lastHead.next = tail;
    }
    return tail;
}
]]> - - Java - leetcode - - - leetcode - java - 题解 - - - - Leetcode 25 Reverse Nodes in k-Group 题解分析-再解分析 - /2024/01/21/Leetcode-25-Reverse-Nodes-in-k-Group-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ - 上一次主要是给了一个解题方案，没有具体讲解，这次又做到了就来看下几种方案，链表转置一直是我比较疑惑的问题，特别是边界处理，而这个问题要把难度加大了
我先讲一下我一开始的思路和解题方法，首先就是写一个转置方法，就处理 k 个一组的内部转置，然后外部循环处理分组以及前后连接等问题，但是这里就涉及到一个问题，就是前后连接的话对于整个链表头，也就是第一个 k 元素组来说，头是个空的，就需要额外处理，一开始就是用判空做额外处理，然后在前后连接的时候也有一些困扰，看了自己的代码库发现其实之前也做过，而且发现这个思路跟以前做的还是一样的，只不过在处理 k 个元素内部的转置的时候有了点差异

一开始的思路是这样的，想了下其实还是比较有问题，从处理难度上来说，在 k 组内处理的时候一开始 A 节点会是悬空的，然后得处理到组内最后一个元素的时候再接上，逻辑会更复杂，而另一种思路就是直接把 A 先挪到 C 后面，这样每次只需要移动一个，可能思路上会更清晰一点

也就是这样的，这种方案就是之前发过的题解代码，上一篇

-

而最后这种则代码会简单一些，但是需要一定的理解成本，比较重要的一点是我们加了个虚拟的头结点，第一步会先获取下链表的总长度，然后在内循环里处理转置，重点就是分四步，
也就是图里的，第一步先把 cur 的下一个节点设置成 next 的 next 节点，这里就是图里 A 连接到 C，第二步是把 next 的 next 节点设置成虚拟头的 next节点，第三步是把 pre 的next 节点设置成 next，第四步是 next 往后移动

-
cur.next = next.next;
next.next = pre.next;
pre.next = next;
next = cur.next;
+ Number of 1 Bits + /2015/03/11/Number-Of-1-Bits/ + Number of 1 Bits

Write a function that takes an unsigned integer and returns the number of ’1’ bits it has (also known as the Hamming weight). For example, the 32-bit integer ‘11’ has binary representation 00000000000000000000000000001011, so the function should return 3.

-


在备注下代码

-]]> +

分析

从1位到2位到4位逐步的交换

+
+

code

int hammingWeight(uint32_t n) {
        const uint32_t m1  = 0x55555555; //binary: 0101...  
        const uint32_t m2  = 0x33333333; //binary: 00110011..  
        const uint32_t m4  = 0x0f0f0f0f; //binary:  4 zeros,  4 ones ...  
        const uint32_t m8  = 0x00ff00ff; //binary:  8 zeros,  8 ones ...  
        const uint32_t m16 = 0x0000ffff; //binary: 16 zeros, 16 ones ...  
        
        n = (n & m1 ) + ((n >>  1) & m1 ); //put count of each  2 bits into those  2 bits   
        n = (n & m2 ) + ((n >>  2) & m2 ); //put count of each  4 bits into those  4 bits   
        n = (n & m4 ) + ((n >>  4) & m4 ); //put count of each  8 bits into those  8 bits   
        n = (n & m8 ) + ((n >>  8) & m8 ); //put count of each 16 bits into those 16 bits   
        n = (n & m16) + ((n >> 16) & m16); //put count of each 32 bits into those 32 bits   
        return n; 

}
]]> - Java leetcode leetcode - java - 题解 + c++ - Number of 1 Bits - /2015/03/11/Number-Of-1-Bits/ - Number of 1 Bits

Write a function that takes an unsigned integer and returns the number of ’1’ bits it has (also known as the Hamming weight). For example, the 32-bit integer ‘11’ has binary representation 00000000000000000000000000001011, so the function should return 3.

- -

分析

从1位到2位到4位逐步的交换

-
-

code

int hammingWeight(uint32_t n) {
        const uint32_t m1  = 0x55555555; //binary: 0101...  
        const uint32_t m2  = 0x33333333; //binary: 00110011..  
        const uint32_t m4  = 0x0f0f0f0f; //binary:  4 zeros,  4 ones ...  
        const uint32_t m8  = 0x00ff00ff; //binary:  8 zeros,  8 ones ...  
        const uint32_t m16 = 0x0000ffff; //binary: 16 zeros, 16 ones ...  
        
        n = (n & m1 ) + ((n >>  1) & m1 ); //put count of each  2 bits into those  2 bits   
        n = (n & m2 ) + ((n >>  2) & m2 ); //put count of each  4 bits into those  4 bits   
        n = (n & m4 ) + ((n >>  4) & m4 ); //put count of each  8 bits into those  8 bits   
        n = (n & m8 ) + ((n >>  8) & m8 ); //put count of each 16 bits into those 16 bits   
        n = (n & m16) + ((n >> 16) & m16); //put count of each 32 bits into those 32 bits   
        return n; 

}
]]> + Path Sum + /2015/01/04/Path-Sum/ + problem

Given a binary tree and a sum, determine if the tree has a root-to-leaf path such that adding up all the values along the path equals the given sum.

+ +

For example:
Given the below binary tree and sum = 22,

+
      5
     / \
    4   8
   /   / \
  11  13  4
 /  \      \
7    2      1
+

return true, as there exist a root-to-leaf path 5->4->11->2 which sum is 22.

+

Analysis

using simple deep first search

+

code

/*
  Definition for binary tree
  struct TreeNode {
      int val;
      TreeNode *left;
      TreeNode *right;
      TreeNode(int x) : val(x), left(NULL), right(NULL)}
  };
 */
class Solution {
public:
    bool deep_first_search(TreeNode *node, int sum, int curSum)
    {
        if (node == NULL)
            return false;
        
        if (node->left == NULL && node->right == NULL)
            return curSum + node->val == sum;
               
        return deep_first_search(node->left, sum, curSum + node->val) || deep_first_search(node->right, sum, curSum + node->val);
    }
    
    bool hasPathSum(TreeNode *root, int sum) {
        // Start typing your C/C++ solution below
        // DO NOT write int main() function
        return deep_first_search(root, sum, 0);
    }
};
+]]> leetcode @@ -1858,25 +1903,6 @@ SpringBoot - - Path Sum - /2015/01/04/Path-Sum/ - problem

Given a binary tree and a sum, determine if the tree has a root-to-leaf path such that adding up all the values along the path equals the given sum.

- -

For example:
Given the below binary tree and sum = 22,

-
      5
     / \
    4   8
   /   / \
  11  13  4
 /  \      \
7    2      1
-

return true, as there exist a root-to-leaf path 5->4->11->2 which sum is 22.

-

Analysis

using simple deep first search

-

code

/*
  Definition for binary tree
  struct TreeNode {
      int val;
      TreeNode *left;
      TreeNode *right;
      TreeNode(int x) : val(x), left(NULL), right(NULL)}
  };
 */
class Solution {
public:
    bool deep_first_search(TreeNode *node, int sum, int curSum)
    {
        if (node == NULL)
            return false;
        
        if (node->left == NULL && node->right == NULL)
            return curSum + node->val == sum;
               
        return deep_first_search(node->left, sum, curSum + node->val) || deep_first_search(node->right, sum, curSum + node->val);
    }
    
    bool hasPathSum(TreeNode *root, int sum) {
        // Start typing your C/C++ solution below
        // DO NOT write int main() function
        return deep_first_search(root, sum, 0);
    }
};
-]]> - - leetcode - - - leetcode - c++ - - Tomcat 系列篇三-介绍下 Coyote /2023/09/24/Tomcat-%E7%B3%BB%E5%88%97%E7%AF%87%E4%B8%89-%E4%BB%8B%E7%BB%8D%E4%B8%8B-Coyote/ @@ -2283,22 +2309,6 @@ cluster - - dnsmasq的一个使用注意点 - /2023/04/16/dnsmasq%E7%9A%84%E4%B8%80%E4%B8%AA%E4%BD%BF%E7%94%A8%E6%B3%A8%E6%84%8F%E7%82%B9/ - 在本地使用了 valet 做 php 的开发环境，因为可以指定自定义域名和证书，碰巧最近公司的网络环境比较糟糕，就想要在自定义 dns 上下点功夫，本来我们经常要在 dns 那配置个内部的 dns 地址，就想是不是可以通过 dnsmasq 来解决，
却在第一步碰到个低级的问题，在 dnsmasq 的主配置文件里
我配置了解析文件路径配置
像这样

-
resolv-file=/opt/homebrew/etc/dnsmasq.d/resolv.dnsmasq.conf
-

结果发现 dnsmasq 就起不来了，因为是 brew 服务的形式起来，发现日志也没有， dnsmasq 配置文件本身也没什么日志，这个是最讨厌的，网上搜了一圈也都没有， brew services 的服务如果启动状态是 error，并且服务本身没有日志的话就是一头雾水，并且对于 plist 来说，即使我手动加了标准输出和错误输出，brew services restart 的时候也是会被重新覆盖，
后来仔细看了下这个问题，发现它下面有这么一行配置

-
conf-dir=/opt/homebrew/etc/dnsmasq.d/,*.conf
-

想了一下发现这个问题其实很简单，dnsmasq 应该是不支持同一配置文件加载两次，
我把 resolv 文件放在了同一个配置文件目录下，所以就被加载了两次，所以改掉目录就行了，但是目前看 dnsmasq 还不符合我的要求，也有可能我还没完全了解 dnsmasq 的使用方法，我想要的是比如按特定的域名后缀来配置对应的 dns 服务器，这样就不太会被影响，可以试试 AdGuard 看

-]]> - - dns - - - dnsmasq - - binary-watch /2016/09/29/binary-watch/ @@ -2323,6 +2333,22 @@ c++ + + dnsmasq的一个使用注意点 + /2023/04/16/dnsmasq%E7%9A%84%E4%B8%80%E4%B8%AA%E4%BD%BF%E7%94%A8%E6%B3%A8%E6%84%8F%E7%82%B9/ + 在本地使用了 valet 做 php 的开发环境，因为可以指定自定义域名和证书，碰巧最近公司的网络环境比较糟糕，就想要在自定义 dns 上下点功夫，本来我们经常要在 dns 那配置个内部的 dns 地址，就想是不是可以通过 dnsmasq 来解决，
却在第一步碰到个低级的问题，在 dnsmasq 的主配置文件里
我配置了解析文件路径配置
像这样

+
resolv-file=/opt/homebrew/etc/dnsmasq.d/resolv.dnsmasq.conf
+

结果发现 dnsmasq 就起不来了，因为是 brew 服务的形式起来，发现日志也没有， dnsmasq 配置文件本身也没什么日志，这个是最讨厌的，网上搜了一圈也都没有， brew services 的服务如果启动状态是 error，并且服务本身没有日志的话就是一头雾水，并且对于 plist 来说，即使我手动加了标准输出和错误输出，brew services restart 的时候也是会被重新覆盖，
后来仔细看了下这个问题，发现它下面有这么一行配置

+
conf-dir=/opt/homebrew/etc/dnsmasq.d/,*.conf
+

想了一下发现这个问题其实很简单，dnsmasq 应该是不支持同一配置文件加载两次，
我把 resolv 文件放在了同一个配置文件目录下，所以就被加载了两次，所以改掉目录就行了，但是目前看 dnsmasq 还不符合我的要求，也有可能我还没完全了解 dnsmasq 的使用方法，我想要的是比如按特定的域名后缀来配置对应的 dns 服务器，这样就不太会被影响，可以试试 AdGuard 看

+]]> + + dns + + + dnsmasq + + docker-mysql-cluster /2016/08/14/docker-mysql-cluster/ @@ -2602,36 +2628,6 @@ headscale - - invert-binary-tree - /2015/06/22/invert-binary-tree/ - Invert a binary tree

-
     4
-   /   \
-  2     7
- / \   / \
-1   3 6   9
-
-

to

-
     4
-   /   \
-  7     2
- / \   / \
-9   6 3   1
-
-

Trivia:
This problem was inspired by this original tweet by Max Howell:

-
-

Google: 90% of our engineers use the software you wrote (Homebrew),
but you can’t invert a binary tree on a whiteboard so fuck off.

-
-
/**
 * Definition for a binary tree node.
 * struct TreeNode {
 *     int val;
 *     TreeNode *left;
 *     TreeNode *right;
 *     TreeNode(int x) : val(x), left(NULL), right(NULL) {}
 * };
 */
class Solution {
public:
    TreeNode* invertTree(TreeNode* root) {
        if(root == NULL) return root;
        TreeNode* temp;
        temp = invertTree(root->left);
        root->left = invertTree(root->right);
        root->right = temp;
        return root;
    }
};
]]> - - leetcode - - - leetcode - c++ - - hexo 配置系列-接入Algolia搜索 /2023/04/02/hexo-%E9%85%8D%E7%BD%AE%E7%B3%BB%E5%88%97-%E6%8E%A5%E5%85%A5Algolia%E6%90%9C%E7%B4%A2/ @@ -2653,6 +2649,36 @@ hexo + + invert-binary-tree + /2015/06/22/invert-binary-tree/ + Invert a binary tree

+
     4
+   /   \
+  2     7
+ / \   / \
+1   3 6   9
+
+

to

+
     4
+   /   \
+  7     2
+ / \   / \
+9   6 3   1
+
+

Trivia:
This problem was inspired by this original tweet by Max Howell:

+
+

Google: 90% of our engineers use the software you wrote (Homebrew),
but you can’t invert a binary tree on a whiteboard so fuck off.

+
+
/**
 * Definition for a binary tree node.
 * struct TreeNode {
 *     int val;
 *     TreeNode *left;
 *     TreeNode *right;
 *     TreeNode(int x) : val(x), left(NULL), right(NULL) {}
 * };
 */
class Solution {
public:
    TreeNode* invertTree(TreeNode* root) {
        if(root == NULL) return root;
        TreeNode* temp;
        temp = invertTree(root->left);
        root->left = invertTree(root->right);
        root->right = temp;
        return root;
    }
};
]]> + + leetcode + + + leetcode + c++ + + java 中发起 http 请求时证书问题解决记录 /2023/07/29/java-%E4%B8%AD%E5%8F%91%E8%B5%B7-http-%E8%AF%B7%E6%B1%82%E6%97%B6%E8%AF%81%E4%B9%A6%E9%97%AE%E9%A2%98%E8%A7%A3%E5%86%B3%E8%AE%B0%E5%BD%95/ @@ -2667,19 +2693,6 @@ java - - C++ 指针使用中的一个小问题 - /2014/12/23/my-new-post/ - 在工作中碰到的一点C++指针上的一点小问题
-

在C++中，应该是从C语言就开始了，除了void型指针之外都是需要有分配对应的内存才可以使用，同时malloc与free成对使用，new与delete成对使用，否则造成内存泄漏。

-]]> - - C++ - - - 博客，文章 - - minimum-size-subarray-sum-209 /2016/10/11/minimum-size-subarray-sum-209/ @@ -2696,6 +2709,19 @@ c++ + + C++ 指针使用中的一个小问题 + /2014/12/23/my-new-post/ + 在工作中碰到的一点C++指针上的一点小问题
+

在C++中，应该是从C语言就开始了，除了void型指针之外都是需要有分配对应的内存才可以使用，同时malloc与free成对使用，new与delete成对使用，否则造成内存泄漏。

+]]> + + C++ + + + 博客，文章 + + mybatis 的 foreach 使用的注意点 /2022/07/09/mybatis-%E7%9A%84-foreach-%E4%BD%BF%E7%94%A8%E7%9A%84%E6%B3%A8%E6%84%8F%E7%82%B9/ @@ -2864,39 +2890,6 @@

然后是还回连接

protected void pushConnection(PooledConnection conn) throws SQLException {
    // 加锁
    lock.lock();
    try {
      // 从活跃连接中移除当前连接
      state.activeConnections.remove(conn);
      if (conn.isValid()) {
        // 当前的空闲连接数小于连接池中允许的最大空闲连接数
        if (state.idleConnections.size() < poolMaximumIdleConnections && conn.getConnectionTypeCode() == expectedConnectionTypeCode) {
          // 记录借出时间
          state.accumulatedCheckoutTime += conn.getCheckoutTime();
          if (!conn.getRealConnection().getAutoCommit()) {
            // 同样是做回滚
            conn.getRealConnection().rollback();
          }
          // 新建一个连接
          PooledConnection newConn = new PooledConnection(conn.getRealConnection(), this);
          // 加入到空闲连接列表中
          state.idleConnections.add(newConn);
          newConn.setCreatedTimestamp(conn.getCreatedTimestamp());
          newConn.setLastUsedTimestamp(conn.getLastUsedTimestamp());
          // 原连接失效
          conn.invalidate();
          if (log.isDebugEnabled()) {
            log.debug("Returned connection " + newConn.getRealHashCode() + " to pool.");
          }
          // 提醒前面等待的
          condition.signal();
        } else {
          // 上面是相同的，就是这里是空闲连接数已经超过上限
          state.accumulatedCheckoutTime += conn.getCheckoutTime();
          if (!conn.getRealConnection().getAutoCommit()) {
            conn.getRealConnection().rollback();
          }
          conn.getRealConnection().close();
          if (log.isDebugEnabled()) {
            log.debug("Closed connection " + conn.getRealHashCode() + ".");
          }
          conn.invalidate();
        }
      } else {
        if (log.isDebugEnabled()) {
          log.debug("A bad connection (" + conn.getRealHashCode() + ") attempted to return to the pool, discarding connection.");
        }
        state.badConnectionCount++;
      }
    } finally {
      lock.unlock();
    }
  }
-]]> - - Java - Mybatis - - - Java - Mysql - Mybatis - - - - mybatis系列-sql 类的简要分析 - /2023/03/19/mybatis%E7%B3%BB%E5%88%97-sql-%E7%B1%BB%E7%9A%84%E7%AE%80%E8%A6%81%E5%88%86%E6%9E%90/ - 上次就比较简单的讲了使用，这块也比较简单，因为封装得不是很复杂，首先我们从 select 作为入口来看看，这个具体的实现，

-
String selectSql = new SQL() {{
            SELECT("id", "name");
            FROM("student");
            WHERE("id = #{id}");
        }}.toString();
-

SELECT 方法的实现，

-
public T SELECT(String... columns) {
  sql().statementType = SQLStatement.StatementType.SELECT;
  sql().select.addAll(Arrays.asList(columns));
  return getSelf();
}
-

statementType是个枚举

-
public enum StatementType {
  DELETE, INSERT, SELECT, UPDATE
}
-

那这个就是个 select 语句，然后会把参数转成 list 添加到 select 变量里，
然后是 from 语句，这个大概也能猜到就是设置下表名，

-
public T FROM(String table) {
  sql().tables.add(table);
  return getSelf();
}
-

往 tables 里添加了 table，这个 tables 是什么呢
这里也可以看下所有的变量，

-
StatementType statementType;
List<String> sets = new ArrayList<>();
List<String> select = new ArrayList<>();
List<String> tables = new ArrayList<>();
List<String> join = new ArrayList<>();
List<String> innerJoin = new ArrayList<>();
List<String> outerJoin = new ArrayList<>();
List<String> leftOuterJoin = new ArrayList<>();
List<String> rightOuterJoin = new ArrayList<>();
List<String> where = new ArrayList<>();
List<String> having = new ArrayList<>();
List<String> groupBy = new ArrayList<>();
List<String> orderBy = new ArrayList<>();
List<String> lastList = new ArrayList<>();
List<String> columns = new ArrayList<>();
List<List<String>> valuesList = new ArrayList<>();
-

可以看到是一堆 List 先暂存这些sql 片段，然后再拼装成 sql 语句，
因为它重写了 toString 方法

-
@Override
public String toString() {
  StringBuilder sb = new StringBuilder();
  sql().sql(sb);
  return sb.toString();
}
-

调用的 sql 方法是

-
public String sql(Appendable a) {
      SafeAppendable builder = new SafeAppendable(a);
      if (statementType == null) {
        return null;
      }

      String answer;

      switch (statementType) {
        case DELETE:
          answer = deleteSQL(builder);
          break;

        case INSERT:
          answer = insertSQL(builder);
          break;

        case SELECT:
          answer = selectSQL(builder);
          break;

        case UPDATE:
          answer = updateSQL(builder);
          break;

        default:
          answer = null;
      }

      return answer;
    }
-

根据上面的 statementType判断是个什么 sql，我们这个是 selectSQL 就走的 SELECT 这个分支

-
private String selectSQL(SafeAppendable builder) {
  if (distinct) {
    sqlClause(builder, "SELECT DISTINCT", select, "", "", ", ");
  } else {
    sqlClause(builder, "SELECT", select, "", "", ", ");
  }

  sqlClause(builder, "FROM", tables, "", "", ", ");
  joins(builder);
  sqlClause(builder, "WHERE", where, "(", ")", " AND ");
  sqlClause(builder, "GROUP BY", groupBy, "", "", ", ");
  sqlClause(builder, "HAVING", having, "(", ")", " AND ");
  sqlClause(builder, "ORDER BY", orderBy, "", "", ", ");
  limitingRowsStrategy.appendClause(builder, offset, limit);
  return builder.toString();
}
-

上面的可以看出来就是按我们常规的 sql 理解顺序来处理
就是select ... from ... where ... 这样子
再看下 sqlClause 的代码

-
private void sqlClause(SafeAppendable builder, String keyword, List<String> parts, String open, String close,
                           String conjunction) {
      if (!parts.isEmpty()) {
        if (!builder.isEmpty()) {
          builder.append("\n");
        }
        builder.append(keyword);
        builder.append(" ");
        builder.append(open);
        String last = "________";
        for (int i = 0, n = parts.size(); i < n; i++) {
          String part = parts.get(i);
          if (i > 0 && !part.equals(AND) && !part.equals(OR) && !last.equals(AND) && !last.equals(OR)) {
            builder.append(conjunction);
          }
          builder.append(part);
          last = part;
        }
        builder.append(close);
      }
    }
-

这里的拼接方式还需要判断 AND 和 OR 的判断逻辑，其他就没什么特别的了，只是where 语句中的 lastList 不知道是干嘛的，好像只有添加跟赋值的操作，有知道的大神也可以评论指导下

]]> Java @@ -2937,36 +2930,6 @@

它的入口不是个get方法，而是pop，从含义来来讲就不一样
org.apache.ibatis.datasource.pooled.PooledDataSource#getConnection()

@Override
public Connection getConnection() throws SQLException {
  return popConnection(dataSource.getUsername(), dataSource.getPassword()).getProxyConnection();
}

对于具体怎么获取连接我们可以下一篇具体讲下

-]]> - - Java - Mybatis - - - Java - Mysql - Mybatis - - - - mybatis系列-sql 类的简单使用 - /2023/03/12/mybatis%E7%B3%BB%E5%88%97-sql-%E7%B1%BB%E7%9A%84%E7%AE%80%E5%8D%95%E4%BD%BF%E7%94%A8/ - mybatis 还有个比较有趣的功能，就是使用 SQL 类生成 sql，有点类似于 hibernate 或者像 php 的 laravel 框架等的，就是把sql 这种放在 xml 里或者代码里直接写 sql 用对象的形式

-

select语句

比如这样

-
public static void main(String[] args) {
    String selectSql = new SQL() {{
        SELECT("id", "name");
        FROM("student");
        WHERE("id = #{id}");
    }}.toString();
    System.out.println(selectSql);
}
-

打印出来就是

-
SELECT id, name
FROM student
WHERE (id = #{id})
-

应付简单的 sql 查询基本都可以这么解决，如果习惯这种模式，还是不错的，
其实以面向对象的编程模式来说，这样是比较符合面向对象的，先不深入的解析这块的源码，先从使用角度讲一下

-

比如 update 语句

String updateSql = new SQL() {{
            UPDATE("student");
            SET("name = #{name}");
            WHERE("id = #{id}");
        }}.toString();
-

打印输出就是

-
UPDATE student
SET name = #{name}
WHERE (id = #{id})
- -

insert 语句

String insertSql = new SQL() {{
            INSERT_INTO("student");
            VALUES("name", "#{name}");
            VALUES("age", "#{age}");
        }}.toString();
        System.out.println(insertSql);
-

打印输出

-
INSERT INTO student
 (name, age)
VALUES (#{name}, #{age})
-

delete语句

String deleteSql = new SQL() {{
            DELETE_FROM("student");
            WHERE("id = #{id}");
        }}.toString();
        System.out.println(deleteSql);
-

打印输出

-
DELETE FROM student
WHERE (id = #{id})
]]> Java @@ -3017,6 +2980,69 @@

image

真实的从 ? 替换成具体的变量值，是在这里
org.apache.ibatis.executor.SimpleExecutor#doQuery
调用了 

private Statement prepareStatement(StatementHandler handler, Log statementLog) throws SQLException {
    Statement stmt;
    Connection connection = getConnection(statementLog);
    stmt = handler.prepare(connection, transaction.getTimeout());
    handler.parameterize(stmt);
    return stmt;
  }
  @Override
  public void parameterize(Statement statement) throws SQLException {
    parameterHandler.setParameters((PreparedStatement) statement);
  }
    @Override
  public void setParameters(PreparedStatement ps) {
    ErrorContext.instance().activity("setting parameters").object(mappedStatement.getParameterMap().getId());
    List<ParameterMapping> parameterMappings = boundSql.getParameterMappings();
    if (parameterMappings != null) {
      for (int i = 0; i < parameterMappings.size(); i++) {
        ParameterMapping parameterMapping = parameterMappings.get(i);
        if (parameterMapping.getMode() != ParameterMode.OUT) {
          Object value;
          String propertyName = parameterMapping.getProperty();
          if (boundSql.hasAdditionalParameter(propertyName)) { // issue #448 ask first for additional params
            value = boundSql.getAdditionalParameter(propertyName);
          } else if (parameterObject == null) {
            value = null;
          } else if (typeHandlerRegistry.hasTypeHandler(parameterObject.getClass())) {
            value = parameterObject;
          } else {
            MetaObject metaObject = configuration.newMetaObject(parameterObject);
            value = metaObject.getValue(propertyName);
          }
          TypeHandler typeHandler = parameterMapping.getTypeHandler();
          JdbcType jdbcType = parameterMapping.getJdbcType();
          if (value == null && jdbcType == null) {
            jdbcType = configuration.getJdbcTypeForNull();
          }
          try {
            // --------------------------> 
            // 替换变量
            typeHandler.setParameter(ps, i + 1, value, jdbcType);
          } catch (TypeException | SQLException e) {
            throw new TypeException("Could not set parameters for mapping: " + parameterMapping + ". Cause: " + e, e);
          }
        }
      }
    }
  }
+]]> + + Java + Mybatis + + + Java + Mysql + Mybatis + + + + mybatis系列-sql 类的简单使用 + /2023/03/12/mybatis%E7%B3%BB%E5%88%97-sql-%E7%B1%BB%E7%9A%84%E7%AE%80%E5%8D%95%E4%BD%BF%E7%94%A8/ + mybatis 还有个比较有趣的功能，就是使用 SQL 类生成 sql，有点类似于 hibernate 或者像 php 的 laravel 框架等的，就是把sql 这种放在 xml 里或者代码里直接写 sql 用对象的形式

+

select语句

比如这样

+
public static void main(String[] args) {
    String selectSql = new SQL() {{
        SELECT("id", "name");
        FROM("student");
        WHERE("id = #{id}");
    }}.toString();
    System.out.println(selectSql);
}
+

打印出来就是

+
SELECT id, name
FROM student
WHERE (id = #{id})
+

应付简单的 sql 查询基本都可以这么解决，如果习惯这种模式，还是不错的，
其实以面向对象的编程模式来说，这样是比较符合面向对象的，先不深入的解析这块的源码，先从使用角度讲一下

+

比如 update 语句

String updateSql = new SQL() {{
            UPDATE("student");
            SET("name = #{name}");
            WHERE("id = #{id}");
        }}.toString();
+

打印输出就是

+
UPDATE student
SET name = #{name}
WHERE (id = #{id})
+ +

insert 语句

String insertSql = new SQL() {{
            INSERT_INTO("student");
            VALUES("name", "#{name}");
            VALUES("age", "#{age}");
        }}.toString();
        System.out.println(insertSql);
+

打印输出

+
INSERT INTO student
 (name, age)
VALUES (#{name}, #{age})
+

delete语句

String deleteSql = new SQL() {{
            DELETE_FROM("student");
            WHERE("id = #{id}");
        }}.toString();
        System.out.println(deleteSql);
+

打印输出

+
DELETE FROM student
WHERE (id = #{id})
+]]> + + Java + Mybatis + + + Java + Mysql + Mybatis + + + + mybatis系列-sql 类的简要分析 + /2023/03/19/mybatis%E7%B3%BB%E5%88%97-sql-%E7%B1%BB%E7%9A%84%E7%AE%80%E8%A6%81%E5%88%86%E6%9E%90/ + 上次就比较简单的讲了使用，这块也比较简单，因为封装得不是很复杂，首先我们从 select 作为入口来看看，这个具体的实现，

+
String selectSql = new SQL() {{
            SELECT("id", "name");
            FROM("student");
            WHERE("id = #{id}");
        }}.toString();
+

SELECT 方法的实现，

+
public T SELECT(String... columns) {
  sql().statementType = SQLStatement.StatementType.SELECT;
  sql().select.addAll(Arrays.asList(columns));
  return getSelf();
}
+

statementType是个枚举

+
public enum StatementType {
  DELETE, INSERT, SELECT, UPDATE
}
+

那这个就是个 select 语句，然后会把参数转成 list 添加到 select 变量里，
然后是 from 语句，这个大概也能猜到就是设置下表名，

+
public T FROM(String table) {
  sql().tables.add(table);
  return getSelf();
}
+

往 tables 里添加了 table，这个 tables 是什么呢
这里也可以看下所有的变量，

+
StatementType statementType;
List<String> sets = new ArrayList<>();
List<String> select = new ArrayList<>();
List<String> tables = new ArrayList<>();
List<String> join = new ArrayList<>();
List<String> innerJoin = new ArrayList<>();
List<String> outerJoin = new ArrayList<>();
List<String> leftOuterJoin = new ArrayList<>();
List<String> rightOuterJoin = new ArrayList<>();
List<String> where = new ArrayList<>();
List<String> having = new ArrayList<>();
List<String> groupBy = new ArrayList<>();
List<String> orderBy = new ArrayList<>();
List<String> lastList = new ArrayList<>();
List<String> columns = new ArrayList<>();
List<List<String>> valuesList = new ArrayList<>();
+

可以看到是一堆 List 先暂存这些sql 片段，然后再拼装成 sql 语句，
因为它重写了 toString 方法

+
@Override
public String toString() {
  StringBuilder sb = new StringBuilder();
  sql().sql(sb);
  return sb.toString();
}
+

调用的 sql 方法是

+
public String sql(Appendable a) {
      SafeAppendable builder = new SafeAppendable(a);
      if (statementType == null) {
        return null;
      }

      String answer;

      switch (statementType) {
        case DELETE:
          answer = deleteSQL(builder);
          break;

        case INSERT:
          answer = insertSQL(builder);
          break;

        case SELECT:
          answer = selectSQL(builder);
          break;

        case UPDATE:
          answer = updateSQL(builder);
          break;

        default:
          answer = null;
      }

      return answer;
    }
+

根据上面的 statementType判断是个什么 sql，我们这个是 selectSQL 就走的 SELECT 这个分支

+
private String selectSQL(SafeAppendable builder) {
  if (distinct) {
    sqlClause(builder, "SELECT DISTINCT", select, "", "", ", ");
  } else {
    sqlClause(builder, "SELECT", select, "", "", ", ");
  }

  sqlClause(builder, "FROM", tables, "", "", ", ");
  joins(builder);
  sqlClause(builder, "WHERE", where, "(", ")", " AND ");
  sqlClause(builder, "GROUP BY", groupBy, "", "", ", ");
  sqlClause(builder, "HAVING", having, "(", ")", " AND ");
  sqlClause(builder, "ORDER BY", orderBy, "", "", ", ");
  limitingRowsStrategy.appendClause(builder, offset, limit);
  return builder.toString();
}
+

上面的可以看出来就是按我们常规的 sql 理解顺序来处理
就是select ... from ... where ... 这样子
再看下 sqlClause 的代码

+
private void sqlClause(SafeAppendable builder, String keyword, List<String> parts, String open, String close,
                           String conjunction) {
      if (!parts.isEmpty()) {
        if (!builder.isEmpty()) {
          builder.append("\n");
        }
        builder.append(keyword);
        builder.append(" ");
        builder.append(open);
        String last = "________";
        for (int i = 0, n = parts.size(); i < n; i++) {
          String part = parts.get(i);
          if (i > 0 && !part.equals(AND) && !part.equals(OR) && !last.equals(AND) && !last.equals(OR)) {
            builder.append(conjunction);
          }
          builder.append(part);
          last = part;
        }
        builder.append(close);
      }
    }
+

这里的拼接方式还需要判断 AND 和 OR 的判断逻辑，其他就没什么特别的了，只是where 语句中的 lastList 不知道是干嘛的，好像只有添加跟赋值的操作，有知道的大神也可以评论指导下

]]> Java @@ -3044,6 +3070,37 @@

而获取的逻辑在这

public <T> Class<T> resolveAlias(String string) {
    try {
      if (string == null) {
        return null;
      }
      // issue #748
      // 同样的转成小写
      String key = string.toLowerCase(Locale.ENGLISH);
      Class<T> value;
      if (typeAliases.containsKey(key)) {
        value = (Class<T>) typeAliases.get(key);
      } else {
        // 这里还有从路径下处理的逻辑
        value = (Class<T>) Resources.classForName(string);
      }
      return value;
    } catch (ClassNotFoundException e) {
      throw new TypeException("Could not resolve type alias '" + string + "'.  Cause: " + e, e);
    }
  }

逻辑比较简单，但是在mybatis中也是不可或缺的一块概念

+]]> + + Java + Mybatis + + + Java + Mysql + Mybatis + + + + mybatis系列-入门篇 + /2022/11/27/mybatis%E7%B3%BB%E5%88%97-%E5%85%A5%E9%97%A8%E7%AF%87/ + mybatis是我们比较常用的orm框架，下面是官网的介绍

+
+

MyBatis 是一款优秀的持久层框架，它支持自定义 SQL、存储过程以及高级映射。MyBatis 免除了几乎所有的 JDBC 代码以及设置参数和获取结果集的工作。MyBatis 可以通过简单的 XML 或注解来配置和映射原始类型、接口和 Java POJO（Plain Old Java Objects，普通老式 Java 对象）为数据库中的记录。

+
+

mybatis一大特点，或者说比较为人熟知的应该就是比 hibernate 是更轻量化，为国人所爱好的orm框架，对于hibernate目前还没有深入的拆解过，后续可以也写一下，在使用体验上觉得是个比较精巧的框架，看代码也比较容易，所以就想写个系列，第一篇先是介绍下使用
根据官网的文档上我们先来尝试一下简单使用
首先我们有个简单的配置，这个文件是mybatis-config.xml

+
<?xml version="1.0" encoding="UTF-8" ?>
<!DOCTYPE configuration
        PUBLIC "-//mybatis.org//DTD Config 3.0//EN"
        "https://mybatis.org/dtd/mybatis-3-config.dtd">
<configuration>
    <!-- 需要加入的properties-->
    <properties resource="application-development.properties"/>
    <!-- 指出使用哪个环境，默认是development-->
    <environments default="development">
        <environment id="development">
        <!-- 指定事务管理器类型-->
            <transactionManager type="JDBC"/>
            <!-- 指定数据源类型-->
            <dataSource type="POOLED">
                <!-- 下面就是具体的参数占位了-->
                <property name="driver" value="${driver}"/>
                <property name="url" value="${url}"/>
                <property name="username" value="${username}"/>
                <property name="password" value="${password}"/>
            </dataSource>
        </environment>
    </environments>
    <mappers>
        <!-- 指定mapper xml的位置或文件-->
        <mapper resource="mapper/StudentMapper.xml"/>
    </mappers>
</configuration>
+

在代码里创建mybatis里重要入口

+
String resource = "mybatis-config.xml";
InputStream inputStream = Resources.getResourceAsStream(resource);
SqlSessionFactory sqlSessionFactory = new SqlSessionFactoryBuilder().build(inputStream);
+

然后我们上面的StudentMapper.xml

+
<?xml version="1.0" encoding="UTF-8" ?>
<!DOCTYPE mapper
        PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
        "https://mybatis.org/dtd/mybatis-3-mapper.dtd">
<mapper namespace="com.nicksxs.mybatisdemo.StudentMapper">
    <select id="selectStudent" resultType="com.nicksxs.mybatisdemo.StudentDO">
        select * from student where id = #{id}
    </select>
</mapper>
+

那么我们就要使用这个mapper，

+
String resource = "mybatis-config.xml";
InputStream inputStream = Resources.getResourceAsStream(resource);
SqlSessionFactory sqlSessionFactory = new SqlSessionFactoryBuilder().build(inputStream);
try (SqlSession session = sqlSessionFactory.openSession()) {
    StudentDO studentDO = session.selectOne("com.nicksxs.mybatisdemo.StudentMapper.selectStudent", 1);
    System.out.println("id is " + studentDO.getId() + " name is " +studentDO.getName());
} catch (Exception e) {
    e.printStackTrace();
}
+

sqlSessionFactory是sqlSession的工厂，我们可以通过sqlSessionFactory来创建sqlSession，而SqlSession 提供了在数据库执行 SQL 命令所需的所有方法。你可以通过 SqlSession 实例来直接执行已映射的 SQL 语句。可以看到mapper.xml中有定义mapper的namespace，就可以通过session.selectOne()传入namespace+id来调用这个方法
但是这样调用比较不合理的点，或者说按后面mybatis优化之后我们可以指定mapper接口

+
public interface StudentMapper {

    public StudentDO selectStudent(Long id);
}
+

就可以可以通过mapper接口获取方法，这样就不用涉及到未知的变量转换等异常

+
try (SqlSession session = sqlSessionFactory.openSession()) {
    StudentMapper mapper = session.getMapper(StudentMapper.class);
    StudentDO studentDO = mapper.selectStudent(1L);
    System.out.println("id is " + studentDO.getId() + " name is " +studentDO.getName());
} catch (Exception e) {
    e.printStackTrace();
}
+

这一篇咱们先介绍下简单的使用，后面可以先介绍下这些的原理。

]]> Java @@ -3174,27 +3231,87 @@ - nginx 日志小记 - /2022/04/17/nginx-%E6%97%A5%E5%BF%97%E5%B0%8F%E8%AE%B0/ - nginx 默认的日志有特定的格式，我们也可以自定义，

-

默认的格式是预定义的 combined

-
log_format combined '$remote_addr - $remote_user [$time_local] '
                    '"$request" $status $body_bytes_sent '
                    '"$http_referer" "$http_user_agent"';
+ mybatis系列-第一条sql的细节 + /2022/12/11/mybatis%E7%B3%BB%E5%88%97-%E7%AC%AC%E4%B8%80%E6%9D%A1sql%E7%9A%84%E7%BB%86%E8%8A%82/ + 先补充两个点，
第一是前面我们说了
使用org.apache.ibatis.builder.xml.XMLConfigBuilder 创建了parser解析器，那么解析的结果是什么
看这个方法的返回值

+
public Configuration parse() {
  if (parsed) {
    throw new BuilderException("Each XMLConfigBuilder can only be used once.");
  }
  parsed = true;
  parseConfiguration(parser.evalNode("/configuration"));
  return configuration;
}
-

配置的日志可以使用这个默认的，如果满足需求的话

-
Syntax:	access_log path [format [buffer=size] [gzip[=level]] [flush=time] [if=condition]];
        access_log off;
Default: access_log logs/access.log combined;
Context: http, server, location, if in location, limit_except
+

返回的是 org.apache.ibatis.session.Configuration , 而这个 Configuration 也是 mybatis 中特别重要的配置核心类，贴一下里面的成员变量，

+
public class Configuration {

  protected Environment environment;

  protected boolean safeRowBoundsEnabled;
  protected boolean safeResultHandlerEnabled = true;
  protected boolean mapUnderscoreToCamelCase;
  protected boolean aggressiveLazyLoading;
  protected boolean multipleResultSetsEnabled = true;
  protected boolean useGeneratedKeys;
  protected boolean useColumnLabel = true;
  protected boolean cacheEnabled = true;
  protected boolean callSettersOnNulls;
  protected boolean useActualParamName = true;
  protected boolean returnInstanceForEmptyRow;
  protected boolean shrinkWhitespacesInSql;
  protected boolean nullableOnForEach;
  protected boolean argNameBasedConstructorAutoMapping;

  protected String logPrefix;
  protected Class<? extends Log> logImpl;
  protected Class<? extends VFS> vfsImpl;
  protected Class<?> defaultSqlProviderType;
  protected LocalCacheScope localCacheScope = LocalCacheScope.SESSION;
  protected JdbcType jdbcTypeForNull = JdbcType.OTHER;
  protected Set<String> lazyLoadTriggerMethods = new HashSet<>(Arrays.asList("equals", "clone", "hashCode", "toString"));
  protected Integer defaultStatementTimeout;
  protected Integer defaultFetchSize;
  protected ResultSetType defaultResultSetType;
  protected ExecutorType defaultExecutorType = ExecutorType.SIMPLE;
  protected AutoMappingBehavior autoMappingBehavior = AutoMappingBehavior.PARTIAL;
  protected AutoMappingUnknownColumnBehavior autoMappingUnknownColumnBehavior = AutoMappingUnknownColumnBehavior.NONE;

  protected Properties variables = new Properties();
  protected ReflectorFactory reflectorFactory = new DefaultReflectorFactory();
  protected ObjectFactory objectFactory = new DefaultObjectFactory();
  protected ObjectWrapperFactory objectWrapperFactory = new DefaultObjectWrapperFactory();

  protected boolean lazyLoadingEnabled = false;
  protected ProxyFactory proxyFactory = new JavassistProxyFactory(); // #224 Using internal Javassist instead of OGNL

  protected String databaseId;
  /**
   * Configuration factory class.
   * Used to create Configuration for loading deserialized unread properties.
   *
   * @see <a href='https://github.com/mybatis/old-google-code-issues/issues/300'>Issue 300 (google code)</a>
   */
  protected Class<?> configurationFactory;

  protected final MapperRegistry mapperRegistry = new MapperRegistry(this);
  protected final InterceptorChain interceptorChain = new InterceptorChain();
  protected final TypeHandlerRegistry typeHandlerRegistry = new TypeHandlerRegistry(this);
  protected final TypeAliasRegistry typeAliasRegistry = new TypeAliasRegistry();
  protected final LanguageDriverRegistry languageRegistry = new LanguageDriverRegistry();

  protected final Map<String, MappedStatement> mappedStatements = new StrictMap<MappedStatement>("Mapped Statements collection")
      .conflictMessageProducer((savedValue, targetValue) ->
          ". please check " + savedValue.getResource() + " and " + targetValue.getResource());
  protected final Map<String, Cache> caches = new StrictMap<>("Caches collection");
  protected final Map<String, ResultMap> resultMaps = new StrictMap<>("Result Maps collection");
  protected final Map<String, ParameterMap> parameterMaps = new StrictMap<>("Parameter Maps collection");
  protected final Map<String, KeyGenerator> keyGenerators = new StrictMap<>("Key Generators collection");

  protected final Set<String> loadedResources = new HashSet<>();
  protected final Map<String, XNode> sqlFragments = new StrictMap<>("XML fragments parsed from previous mappers");

  protected final Collection<XMLStatementBuilder> incompleteStatements = new LinkedList<>();
  protected final Collection<CacheRefResolver> incompleteCacheRefs = new LinkedList<>();
  protected final Collection<ResultMapResolver> incompleteResultMaps = new LinkedList<>();
  protected final Collection<MethodResolver> incompleteMethods = new LinkedList<>();
-

而如果需要额外的一些配置的话可以自己定义 log_format ，比如我想要给日志里加上请求时间，那就可以自己定义一个 log_format 比如添加下

-
$request_time
request processing time in seconds with a milliseconds resolution;   
time elapsed between the first bytes were read from the client and the log write after the last bytes were sent to the client
+

这么多成员变量，先不一一解释作用，但是其中的几个参数我们应该是已经知道了的，第一个就是 mappedStatements ，上一篇我们知道被解析的mapper就是放在这里，后面的 resultMaps ，parameterMaps 也比较常用的就是我们参数和结果的映射map，这里跟我之前有一篇解释为啥我们一些变量的使用会比较特殊，比如list，可以参考这篇，keyGenerators是在我们需要定义主键生成器的时候使用。
然后第二点是我们创建的 org.apache.ibatis.session.SqlSessionFactory 是哪个，

+
public SqlSessionFactory build(Configuration config) {
  return new DefaultSqlSessionFactory(config);
}
-
log_format combined_extend '$remote_addr - $remote_user [$time_local] '
                    '"$request" $status $body_bytes_sent '
                    '"$http_referer" "$http_user_agent" "$request_time"';
+

是这个 DefaultSqlSessionFactory ，这是其中一个 SqlSessionFactory 的实现
接下来我们看看 openSession 里干了啥

+
public SqlSession openSession() {
  return openSessionFromDataSource(configuration.getDefaultExecutorType(), null, false);
}
-

然后其他的比如还有 gzip 压缩，可以设置压缩级别，flush 刷盘时间还有根据条件控制

-

这里的条件控制简单看了下还比较厉害

-

比如我想对2xx 跟 3xx 的访问不记录日志

-
map $status $loggable {
    ~^[23]  0;
    default 1;
}

access_log /path/to/access.log combined if=$loggable;
+

这边有几个参数，第一个是默认的执行器类型，往上找找上面贴着的 Configuration 的成员变量里可以看到默认是
protected ExecutorType defaultExecutorType = ExecutorType.SIMPLE;

+

因为没有指明特殊的执行逻辑，所以默认我们也就用简单类型的，第二个参数是是事务级别，第三个是是否自动提交

+
private SqlSession openSessionFromDataSource(ExecutorType execType, TransactionIsolationLevel level, boolean autoCommit) {
  Transaction tx = null;
  try {
    final Environment environment = configuration.getEnvironment();
    final TransactionFactory transactionFactory = getTransactionFactoryFromEnvironment(environment);
    tx = transactionFactory.newTransaction(environment.getDataSource(), level, autoCommit);
    // --------> 先关注这里
    final Executor executor = configuration.newExecutor(tx, execType);
    return new DefaultSqlSession(configuration, executor, autoCommit);
  } catch (Exception e) {
    closeTransaction(tx); // may have fetched a connection so lets call close()
    throw ExceptionFactory.wrapException("Error opening session.  Cause: " + e, e);
  } finally {
    ErrorContext.instance().reset();
  }
}
-

当 $loggable 是 0 或者空时表示 if 条件为否，上面的默认就是 1，只有当请求状态 status 是 2xx 或 3xx 时才是 0，代表不用记录，有了这个特性就可以更灵活地配置日志

-

文章主要参考了 nginx 的 log 模块的文档

+

具体是调用了 Configuration 的这个方法

+
public Executor newExecutor(Transaction transaction, ExecutorType executorType) {
  executorType = executorType == null ? defaultExecutorType : executorType;
  Executor executor;
  if (ExecutorType.BATCH == executorType) {
    executor = new BatchExecutor(this, transaction);
  } else if (ExecutorType.REUSE == executorType) {
    executor = new ReuseExecutor(this, transaction);
  } else {
    // ---------> 会走到这个分支
    executor = new SimpleExecutor(this, transaction);
  }
  if (cacheEnabled) {
    executor = new CachingExecutor(executor);
  }
  executor = (Executor) interceptorChain.pluginAll(executor);
  return executor;
}
+ +

上面传入的 executorType 是 Configuration 的默认类型，也就是 simple 类型，并且 cacheEnabled 在 Configuration 默认为 true，所以会包装成CachingExecutor ,然后后面就是插件了，这块我们先不展开
然后我们的openSession返回的就是创建了DefaultSqlSession

+
public DefaultSqlSession(Configuration configuration, Executor executor, boolean autoCommit) {
    this.configuration = configuration;
    this.executor = executor;
    this.dirty = false;
    this.autoCommit = autoCommit;
  }
+ +

然后就是调用 selectOne, 因为前面已经把这部分代码说过了，就直接跳转过来
org.apache.ibatis.session.defaults.DefaultSqlSession#selectList(java.lang.String, java.lang.Object, org.apache.ibatis.session.RowBounds, org.apache.ibatis.session.ResultHandler)

+
private <E> List<E> selectList(String statement, Object parameter, RowBounds rowBounds, ResultHandler handler) {
  try {
    MappedStatement ms = configuration.getMappedStatement(statement);
    return executor.query(ms, wrapCollection(parameter), rowBounds, handler);
  } catch (Exception e) {
    throw ExceptionFactory.wrapException("Error querying database.  Cause: " + e, e);
  } finally {
    ErrorContext.instance().reset();
  }
}
+ +

因为前面说了 executor 包装了 CachingExecutor ，所以会先调用

+
@Override
public <E> List<E> query(MappedStatement ms, Object parameterObject, RowBounds rowBounds, ResultHandler resultHandler) throws SQLException {
  BoundSql boundSql = ms.getBoundSql(parameterObject);
  CacheKey key = createCacheKey(ms, parameterObject, rowBounds, boundSql);
  return query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
}
+ +

然后是调用的真实的query方法

+
@Override
public <E> List<E> query(MappedStatement ms, Object parameterObject, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql)
    throws SQLException {
  Cache cache = ms.getCache();
  if (cache != null) {
    flushCacheIfRequired(ms);
    if (ms.isUseCache() && resultHandler == null) {
      ensureNoOutParams(ms, boundSql);
      @SuppressWarnings("unchecked")
      List<E> list = (List<E>) tcm.getObject(cache, key);
      if (list == null) {
        list = delegate.query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
        tcm.putObject(cache, key, list); // issue #578 and #116
      }
      return list;
    }
  }
  return delegate.query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
}
+ +

这里是第一次查询，没有缓存就先到最后一行，继续是调用到 org.apache.ibatis.executor.BaseExecutor#queryFromDatabase

+
@Override
  public <E> List<E> query(MappedStatement ms, Object parameter, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql) throws SQLException {
    ErrorContext.instance().resource(ms.getResource()).activity("executing a query").object(ms.getId());
    if (closed) {
      throw new ExecutorException("Executor was closed.");
    }
    if (queryStack == 0 && ms.isFlushCacheRequired()) {
      clearLocalCache();
    }
    List<E> list;
    try {
      queryStack++;
      list = resultHandler == null ? (List<E>) localCache.getObject(key) : null;
      if (list != null) {
        handleLocallyCachedOutputParameters(ms, key, parameter, boundSql);
      } else {
        // ----------->会走到这里
        list = queryFromDatabase(ms, parameter, rowBounds, resultHandler, key, boundSql);
      }
    } finally {
      queryStack--;
    }
    if (queryStack == 0) {
      for (DeferredLoad deferredLoad : deferredLoads) {
        deferredLoad.load();
      }
      // issue #601
      deferredLoads.clear();
      if (configuration.getLocalCacheScope() == LocalCacheScope.STATEMENT) {
        // issue #482
        clearLocalCache();
      }
    }
    return list;
  }
+ +

然后是

+
private <E> List<E> queryFromDatabase(MappedStatement ms, Object parameter, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql) throws SQLException {
  List<E> list;
  localCache.putObject(key, EXECUTION_PLACEHOLDER);
  try {
    list = doQuery(ms, parameter, rowBounds, resultHandler, boundSql);
  } finally {
    localCache.removeObject(key);
  }
  localCache.putObject(key, list);
  if (ms.getStatementType() == StatementType.CALLABLE) {
    localOutputParameterCache.putObject(key, parameter);
  }
  return list;
}
+ +

然后就是 simpleExecutor 的执行过程

+
@Override
public <E> List<E> doQuery(MappedStatement ms, Object parameter, RowBounds rowBounds, ResultHandler resultHandler, BoundSql boundSql) throws SQLException {
  Statement stmt = null;
  try {
    Configuration configuration = ms.getConfiguration();
    StatementHandler handler = configuration.newStatementHandler(wrapper, ms, parameter, rowBounds, resultHandler, boundSql);
    stmt = prepareStatement(handler, ms.getStatementLog());
    return handler.query(stmt, resultHandler);
  } finally {
    closeStatement(stmt);
  }
}
+ +

接下去其实就是跟jdbc交互了

+
@Override
public <E> List<E> query(Statement statement, ResultHandler resultHandler) throws SQLException {
  PreparedStatement ps = (PreparedStatement) statement;
  ps.execute();
  return resultSetHandler.handleResultSets(ps);
}
+ +

com.mysql.cj.jdbc.ClientPreparedStatement#execute

+
public boolean execute() throws SQLException {
        try {
            synchronized(this.checkClosed().getConnectionMutex()) {
                JdbcConnection locallyScopedConn = this.connection;
                if (!this.doPingInstead && !this.checkReadOnlySafeStatement()) {
                    throw SQLError.createSQLException(Messages.getString("PreparedStatement.20") + Messages.getString("PreparedStatement.21"), "S1009", this.exceptionInterceptor);
                } else {
                    ResultSetInternalMethods rs = null;
                    this.lastQueryIsOnDupKeyUpdate = false;
                    if (this.retrieveGeneratedKeys) {
                        this.lastQueryIsOnDupKeyUpdate = this.containsOnDuplicateKeyUpdate();
                    }

                    this.batchedGeneratedKeys = null;
                    this.resetCancelledState();
                    this.implicitlyCloseAllOpenResults();
                    this.clearWarnings();
                    if (this.doPingInstead) {
                        this.doPingInstead();
                        return true;
                    } else {
                        this.setupStreamingTimeout(locallyScopedConn);
                        Message sendPacket = ((PreparedQuery)this.query).fillSendPacket(((PreparedQuery)this.query).getQueryBindings());
                        String oldDb = null;
                        if (!locallyScopedConn.getDatabase().equals(this.getCurrentDatabase())) {
                            oldDb = locallyScopedConn.getDatabase();
                            locallyScopedConn.setDatabase(this.getCurrentDatabase());
                        }

                        CachedResultSetMetaData cachedMetadata = null;
                        boolean cacheResultSetMetadata = (Boolean)locallyScopedConn.getPropertySet().getBooleanProperty(PropertyKey.cacheResultSetMetadata).getValue();
                        if (cacheResultSetMetadata) {
                            cachedMetadata = locallyScopedConn.getCachedMetaData(((PreparedQuery)this.query).getOriginalSql());
                        }

                        locallyScopedConn.setSessionMaxRows(this.getQueryInfo().getFirstStmtChar() == 'S' ? this.maxRows : -1);
                        rs = this.executeInternal(this.maxRows, sendPacket, this.createStreamingResultSet(), this.getQueryInfo().getFirstStmtChar() == 'S', cachedMetadata, false);
                        if (cachedMetadata != null) {
                            locallyScopedConn.initializeResultsMetadataFromCache(((PreparedQuery)this.query).getOriginalSql(), cachedMetadata, rs);
                        } else if (rs.hasRows() && cacheResultSetMetadata) {
                            locallyScopedConn.initializeResultsMetadataFromCache(((PreparedQuery)this.query).getOriginalSql(), (CachedResultSetMetaData)null, rs);
                        }

                        if (this.retrieveGeneratedKeys) {
                            rs.setFirstCharOfQuery(this.getQueryInfo().getFirstStmtChar());
                        }

                        if (oldDb != null) {
                            locallyScopedConn.setDatabase(oldDb);
                        }

                        if (rs != null) {
                            this.lastInsertId = rs.getUpdateID();
                            this.results = rs;
                        }

                        return rs != null && rs.hasRows();
                    }
                }
            }
        } catch (CJException var11) {
            throw SQLExceptionsMapping.translateException(var11, this.getExceptionInterceptor());
        }
    }
+ +]]> + + Java + Mybatis + + + Java + Mysql + Mybatis + + + + nginx 日志小记 + /2022/04/17/nginx-%E6%97%A5%E5%BF%97%E5%B0%8F%E8%AE%B0/ + nginx 默认的日志有特定的格式，我们也可以自定义，

+

默认的格式是预定义的 combined

+
log_format combined '$remote_addr - $remote_user [$time_local] '
                    '"$request" $status $body_bytes_sent '
                    '"$http_referer" "$http_user_agent"';
+ +

配置的日志可以使用这个默认的，如果满足需求的话

+
Syntax:	access_log path [format [buffer=size] [gzip[=level]] [flush=time] [if=condition]];
        access_log off;
Default: access_log logs/access.log combined;
Context: http, server, location, if in location, limit_except
+ +

而如果需要额外的一些配置的话可以自己定义 log_format ，比如我想要给日志里加上请求时间，那就可以自己定义一个 log_format 比如添加下

+
$request_time
request processing time in seconds with a milliseconds resolution;   
time elapsed between the first bytes were read from the client and the log write after the last bytes were sent to the client
+ +
log_format combined_extend '$remote_addr - $remote_user [$time_local] '
                    '"$request" $status $body_bytes_sent '
                    '"$http_referer" "$http_user_agent" "$request_time"';
+ +

然后其他的比如还有 gzip 压缩，可以设置压缩级别，flush 刷盘时间还有根据条件控制

+

这里的条件控制简单看了下还比较厉害

+

比如我想对2xx 跟 3xx 的访问不记录日志

+
map $status $loggable {
    ~^[23]  0;
    default 1;
}

access_log /path/to/access.log combined if=$loggable;
+ +

当 $loggable 是 0 或者空时表示 if 条件为否，上面的默认就是 1，只有当请求状态 status 是 2xx 或 3xx 时才是 0，代表不用记录，有了这个特性就可以更灵活地配置日志

+

文章主要参考了 nginx 的 log 模块的文档

]]> nginx @@ -3247,6 +3364,38 @@ openresty + + pcre-intro-and-a-simple-package + /2015/01/16/pcre-intro-and-a-simple-package/ + Pcre
+

Perl Compatible Regular Expressions (PCRE) is a regular
expression C library inspired by the regular expression
capabilities in the Perl programming language, written
by Philip Hazel, starting in summer 1997.

+
+

因为最近工作内容的一部分需要做字符串的识别处理，所以就顺便用上了之前在PHP中用过的正则，在C/C++中本身不包含正则库，这里使用的pcre，对MFC开发，在这里提供了静态链接库，在引入lib跟.h文件后即可使用。

+ + +

Regular Expression Syntax

然后是一些正则语法，官方的语法文档比较科学严谨，特别是对类似于贪婪匹配等细节的说明，当然一般的使用可以在网上找到很多匹配语法，例如这个。

+

PCRE函数介绍

+

pcre_compile
原型：

+
+
#include <pcre.h>
pcre *pcre_compile(const char *pattern, int options, const char **errptr, int *erroffset, const unsigned char *tableptr);
+

功能：将一个正则表达式编译成一个内部表示，在匹配多个字符串时，可以加速匹配。其同pcre_compile2功能一样只是缺少一个参数errorcodeptr。
参数：
pattern 正则表达式
options 为0，或者其他参数选项
errptr 出错消息
erroffset 出错位置
tableptr 指向一个字符数组的指针，可以设置为空NULL

+
+

pcre_exec
原型：

+
+
#include <pcre.h>
int pcre_exec(const pcre *code, const pcre_extra *extra, const char *subject, int length, int startoffset, int options, int *ovector, int ovecsize)
+

功能：使用编译好的模式进行匹配，采用与Perl相似的算法，返回匹配串的偏移位置。
参数：
code 编译好的模式
extra 指向一个pcre_extra结构体，可以为NULL
subject 需要匹配的字符串
length 匹配的字符串长度（Byte）
startoffset 匹配的开始位置
options 选项位
ovector 指向一个结果的整型数组
ovecsize 数组大小。

+

这里是两个最常用的函数的简单说明，pcre的静态库提供了一系列的函数以供使用，可以参考这个博客说明，另外对于以上函数的具体参数详细说明可以参考官网此处

+

一个丑陋的封装

void COcxDemoDlg::pcre_exec_all(const pcre * re, PCRE_SPTR src, vector<pair<int, int>> &vc)
{
	int rc;
	int ovector[30];
	int i = 0;
	pair<int, int> pr;
	rc = pcre_exec(re, NULL, src, strlen(src), i, 0, ovector, 30);
	for (; rc > 0;)
	{
		i = ovector[1];
		pr.first = ovector[2];
		pr.second = ovector[3];
		vc.push_back(pr);
		rc = pcre_exec(re, NULL, src, strlen(src), i, 0, ovector, 30);
	}
}
+

vector中是全文匹配后的索引对，只是简单地用下。

+]]> + + C++ + + + c++ + mfc + + php-abstract-class-and-interface /2016/11/10/php-abstract-class-and-interface/ @@ -3270,37 +3419,6 @@ php - - mybatis系列-入门篇 - /2022/11/27/mybatis%E7%B3%BB%E5%88%97-%E5%85%A5%E9%97%A8%E7%AF%87/ - mybatis是我们比较常用的orm框架，下面是官网的介绍

-
-

MyBatis 是一款优秀的持久层框架，它支持自定义 SQL、存储过程以及高级映射。MyBatis 免除了几乎所有的 JDBC 代码以及设置参数和获取结果集的工作。MyBatis 可以通过简单的 XML 或注解来配置和映射原始类型、接口和 Java POJO（Plain Old Java Objects，普通老式 Java 对象）为数据库中的记录。

-
-

mybatis一大特点，或者说比较为人熟知的应该就是比 hibernate 是更轻量化，为国人所爱好的orm框架，对于hibernate目前还没有深入的拆解过，后续可以也写一下，在使用体验上觉得是个比较精巧的框架，看代码也比较容易，所以就想写个系列，第一篇先是介绍下使用
根据官网的文档上我们先来尝试一下简单使用
首先我们有个简单的配置，这个文件是mybatis-config.xml

-
<?xml version="1.0" encoding="UTF-8" ?>
<!DOCTYPE configuration
        PUBLIC "-//mybatis.org//DTD Config 3.0//EN"
        "https://mybatis.org/dtd/mybatis-3-config.dtd">
<configuration>
    <!-- 需要加入的properties-->
    <properties resource="application-development.properties"/>
    <!-- 指出使用哪个环境，默认是development-->
    <environments default="development">
        <environment id="development">
        <!-- 指定事务管理器类型-->
            <transactionManager type="JDBC"/>
            <!-- 指定数据源类型-->
            <dataSource type="POOLED">
                <!-- 下面就是具体的参数占位了-->
                <property name="driver" value="${driver}"/>
                <property name="url" value="${url}"/>
                <property name="username" value="${username}"/>
                <property name="password" value="${password}"/>
            </dataSource>
        </environment>
    </environments>
    <mappers>
        <!-- 指定mapper xml的位置或文件-->
        <mapper resource="mapper/StudentMapper.xml"/>
    </mappers>
</configuration>
-

在代码里创建mybatis里重要入口

-
String resource = "mybatis-config.xml";
InputStream inputStream = Resources.getResourceAsStream(resource);
SqlSessionFactory sqlSessionFactory = new SqlSessionFactoryBuilder().build(inputStream);
-

然后我们上面的StudentMapper.xml

-
<?xml version="1.0" encoding="UTF-8" ?>
<!DOCTYPE mapper
        PUBLIC "-//mybatis.org//DTD Mapper 3.0//EN"
        "https://mybatis.org/dtd/mybatis-3-mapper.dtd">
<mapper namespace="com.nicksxs.mybatisdemo.StudentMapper">
    <select id="selectStudent" resultType="com.nicksxs.mybatisdemo.StudentDO">
        select * from student where id = #{id}
    </select>
</mapper>
-

那么我们就要使用这个mapper，

-
String resource = "mybatis-config.xml";
InputStream inputStream = Resources.getResourceAsStream(resource);
SqlSessionFactory sqlSessionFactory = new SqlSessionFactoryBuilder().build(inputStream);
try (SqlSession session = sqlSessionFactory.openSession()) {
    StudentDO studentDO = session.selectOne("com.nicksxs.mybatisdemo.StudentMapper.selectStudent", 1);
    System.out.println("id is " + studentDO.getId() + " name is " +studentDO.getName());
} catch (Exception e) {
    e.printStackTrace();
}
-

sqlSessionFactory是sqlSession的工厂，我们可以通过sqlSessionFactory来创建sqlSession，而SqlSession 提供了在数据库执行 SQL 命令所需的所有方法。你可以通过 SqlSession 实例来直接执行已映射的 SQL 语句。可以看到mapper.xml中有定义mapper的namespace，就可以通过session.selectOne()传入namespace+id来调用这个方法
但是这样调用比较不合理的点，或者说按后面mybatis优化之后我们可以指定mapper接口

-
public interface StudentMapper {

    public StudentDO selectStudent(Long id);
}
-

就可以可以通过mapper接口获取方法，这样就不用涉及到未知的变量转换等异常

-
try (SqlSession session = sqlSessionFactory.openSession()) {
    StudentMapper mapper = session.getMapper(StudentMapper.class);
    StudentDO studentDO = mapper.selectStudent(1L);
    System.out.println("id is " + studentDO.getId() + " name is " +studentDO.getName());
} catch (Exception e) {
    e.printStackTrace();
}
-

这一篇咱们先介绍下简单的使用，后面可以先介绍下这些的原理。

-]]> - - Java - Mybatis - - - Java - Mysql - Mybatis - - php 的调试方法-查看调用堆栈 /2023/12/31/php-%E7%9A%84%E8%B0%83%E8%AF%95%E6%96%B9%E6%B3%95-%E6%9F%A5%E7%9C%8B%E8%B0%83%E7%94%A8%E5%A0%86%E6%A0%88/ @@ -3370,98 +3488,6 @@ php - - pcre-intro-and-a-simple-package - /2015/01/16/pcre-intro-and-a-simple-package/ - Pcre
-

Perl Compatible Regular Expressions (PCRE) is a regular
expression C library inspired by the regular expression
capabilities in the Perl programming language, written
by Philip Hazel, starting in summer 1997.

-
-

因为最近工作内容的一部分需要做字符串的识别处理，所以就顺便用上了之前在PHP中用过的正则，在C/C++中本身不包含正则库，这里使用的pcre，对MFC开发，在这里提供了静态链接库，在引入lib跟.h文件后即可使用。

- - -

Regular Expression Syntax

然后是一些正则语法，官方的语法文档比较科学严谨，特别是对类似于贪婪匹配等细节的说明，当然一般的使用可以在网上找到很多匹配语法，例如这个。

-

PCRE函数介绍

-

pcre_compile
原型：

-
-
#include <pcre.h>
pcre *pcre_compile(const char *pattern, int options, const char **errptr, int *erroffset, const unsigned char *tableptr);
-

功能：将一个正则表达式编译成一个内部表示，在匹配多个字符串时，可以加速匹配。其同pcre_compile2功能一样只是缺少一个参数errorcodeptr。
参数：
pattern 正则表达式
options 为0，或者其他参数选项
errptr 出错消息
erroffset 出错位置
tableptr 指向一个字符数组的指针，可以设置为空NULL

-
-

pcre_exec
原型：

-
-
#include <pcre.h>
int pcre_exec(const pcre *code, const pcre_extra *extra, const char *subject, int length, int startoffset, int options, int *ovector, int ovecsize)
-

功能：使用编译好的模式进行匹配，采用与Perl相似的算法，返回匹配串的偏移位置。
参数：
code 编译好的模式
extra 指向一个pcre_extra结构体，可以为NULL
subject 需要匹配的字符串
length 匹配的字符串长度（Byte）
startoffset 匹配的开始位置
options 选项位
ovector 指向一个结果的整型数组
ovecsize 数组大小。

-

这里是两个最常用的函数的简单说明，pcre的静态库提供了一系列的函数以供使用，可以参考这个博客说明，另外对于以上函数的具体参数详细说明可以参考官网此处

-

一个丑陋的封装

void COcxDemoDlg::pcre_exec_all(const pcre * re, PCRE_SPTR src, vector<pair<int, int>> &vc)
{
	int rc;
	int ovector[30];
	int i = 0;
	pair<int, int> pr;
	rc = pcre_exec(re, NULL, src, strlen(src), i, 0, ovector, 30);
	for (; rc > 0;)
	{
		i = ovector[1];
		pr.first = ovector[2];
		pr.second = ovector[3];
		vc.push_back(pr);
		rc = pcre_exec(re, NULL, src, strlen(src), i, 0, ovector, 30);
	}
}
-

vector中是全文匹配后的索引对，只是简单地用下。

-]]> - - C++ - - - c++ - mfc - - - - mybatis系列-第一条sql的细节 - /2022/12/11/mybatis%E7%B3%BB%E5%88%97-%E7%AC%AC%E4%B8%80%E6%9D%A1sql%E7%9A%84%E7%BB%86%E8%8A%82/ - 先补充两个点，
第一是前面我们说了
使用org.apache.ibatis.builder.xml.XMLConfigBuilder 创建了parser解析器，那么解析的结果是什么
看这个方法的返回值

-
public Configuration parse() {
  if (parsed) {
    throw new BuilderException("Each XMLConfigBuilder can only be used once.");
  }
  parsed = true;
  parseConfiguration(parser.evalNode("/configuration"));
  return configuration;
}
- -

返回的是 org.apache.ibatis.session.Configuration , 而这个 Configuration 也是 mybatis 中特别重要的配置核心类，贴一下里面的成员变量，

-
public class Configuration {

  protected Environment environment;

  protected boolean safeRowBoundsEnabled;
  protected boolean safeResultHandlerEnabled = true;
  protected boolean mapUnderscoreToCamelCase;
  protected boolean aggressiveLazyLoading;
  protected boolean multipleResultSetsEnabled = true;
  protected boolean useGeneratedKeys;
  protected boolean useColumnLabel = true;
  protected boolean cacheEnabled = true;
  protected boolean callSettersOnNulls;
  protected boolean useActualParamName = true;
  protected boolean returnInstanceForEmptyRow;
  protected boolean shrinkWhitespacesInSql;
  protected boolean nullableOnForEach;
  protected boolean argNameBasedConstructorAutoMapping;

  protected String logPrefix;
  protected Class<? extends Log> logImpl;
  protected Class<? extends VFS> vfsImpl;
  protected Class<?> defaultSqlProviderType;
  protected LocalCacheScope localCacheScope = LocalCacheScope.SESSION;
  protected JdbcType jdbcTypeForNull = JdbcType.OTHER;
  protected Set<String> lazyLoadTriggerMethods = new HashSet<>(Arrays.asList("equals", "clone", "hashCode", "toString"));
  protected Integer defaultStatementTimeout;
  protected Integer defaultFetchSize;
  protected ResultSetType defaultResultSetType;
  protected ExecutorType defaultExecutorType = ExecutorType.SIMPLE;
  protected AutoMappingBehavior autoMappingBehavior = AutoMappingBehavior.PARTIAL;
  protected AutoMappingUnknownColumnBehavior autoMappingUnknownColumnBehavior = AutoMappingUnknownColumnBehavior.NONE;

  protected Properties variables = new Properties();
  protected ReflectorFactory reflectorFactory = new DefaultReflectorFactory();
  protected ObjectFactory objectFactory = new DefaultObjectFactory();
  protected ObjectWrapperFactory objectWrapperFactory = new DefaultObjectWrapperFactory();

  protected boolean lazyLoadingEnabled = false;
  protected ProxyFactory proxyFactory = new JavassistProxyFactory(); // #224 Using internal Javassist instead of OGNL

  protected String databaseId;
  /**
   * Configuration factory class.
   * Used to create Configuration for loading deserialized unread properties.
   *
   * @see <a href='https://github.com/mybatis/old-google-code-issues/issues/300'>Issue 300 (google code)</a>
   */
  protected Class<?> configurationFactory;

  protected final MapperRegistry mapperRegistry = new MapperRegistry(this);
  protected final InterceptorChain interceptorChain = new InterceptorChain();
  protected final TypeHandlerRegistry typeHandlerRegistry = new TypeHandlerRegistry(this);
  protected final TypeAliasRegistry typeAliasRegistry = new TypeAliasRegistry();
  protected final LanguageDriverRegistry languageRegistry = new LanguageDriverRegistry();

  protected final Map<String, MappedStatement> mappedStatements = new StrictMap<MappedStatement>("Mapped Statements collection")
      .conflictMessageProducer((savedValue, targetValue) ->
          ". please check " + savedValue.getResource() + " and " + targetValue.getResource());
  protected final Map<String, Cache> caches = new StrictMap<>("Caches collection");
  protected final Map<String, ResultMap> resultMaps = new StrictMap<>("Result Maps collection");
  protected final Map<String, ParameterMap> parameterMaps = new StrictMap<>("Parameter Maps collection");
  protected final Map<String, KeyGenerator> keyGenerators = new StrictMap<>("Key Generators collection");

  protected final Set<String> loadedResources = new HashSet<>();
  protected final Map<String, XNode> sqlFragments = new StrictMap<>("XML fragments parsed from previous mappers");

  protected final Collection<XMLStatementBuilder> incompleteStatements = new LinkedList<>();
  protected final Collection<CacheRefResolver> incompleteCacheRefs = new LinkedList<>();
  protected final Collection<ResultMapResolver> incompleteResultMaps = new LinkedList<>();
  protected final Collection<MethodResolver> incompleteMethods = new LinkedList<>();
- -

这么多成员变量，先不一一解释作用，但是其中的几个参数我们应该是已经知道了的，第一个就是 mappedStatements ，上一篇我们知道被解析的mapper就是放在这里，后面的 resultMaps ，parameterMaps 也比较常用的就是我们参数和结果的映射map，这里跟我之前有一篇解释为啥我们一些变量的使用会比较特殊，比如list，可以参考这篇，keyGenerators是在我们需要定义主键生成器的时候使用。
然后第二点是我们创建的 org.apache.ibatis.session.SqlSessionFactory 是哪个，

-
public SqlSessionFactory build(Configuration config) {
  return new DefaultSqlSessionFactory(config);
}
- -

是这个 DefaultSqlSessionFactory ，这是其中一个 SqlSessionFactory 的实现
接下来我们看看 openSession 里干了啥

-
public SqlSession openSession() {
  return openSessionFromDataSource(configuration.getDefaultExecutorType(), null, false);
}
- -

这边有几个参数，第一个是默认的执行器类型，往上找找上面贴着的 Configuration 的成员变量里可以看到默认是
protected ExecutorType defaultExecutorType = ExecutorType.SIMPLE;

-

因为没有指明特殊的执行逻辑，所以默认我们也就用简单类型的，第二个参数是是事务级别，第三个是是否自动提交

-
private SqlSession openSessionFromDataSource(ExecutorType execType, TransactionIsolationLevel level, boolean autoCommit) {
  Transaction tx = null;
  try {
    final Environment environment = configuration.getEnvironment();
    final TransactionFactory transactionFactory = getTransactionFactoryFromEnvironment(environment);
    tx = transactionFactory.newTransaction(environment.getDataSource(), level, autoCommit);
    // --------> 先关注这里
    final Executor executor = configuration.newExecutor(tx, execType);
    return new DefaultSqlSession(configuration, executor, autoCommit);
  } catch (Exception e) {
    closeTransaction(tx); // may have fetched a connection so lets call close()
    throw ExceptionFactory.wrapException("Error opening session.  Cause: " + e, e);
  } finally {
    ErrorContext.instance().reset();
  }
}
- -

具体是调用了 Configuration 的这个方法

-
public Executor newExecutor(Transaction transaction, ExecutorType executorType) {
  executorType = executorType == null ? defaultExecutorType : executorType;
  Executor executor;
  if (ExecutorType.BATCH == executorType) {
    executor = new BatchExecutor(this, transaction);
  } else if (ExecutorType.REUSE == executorType) {
    executor = new ReuseExecutor(this, transaction);
  } else {
    // ---------> 会走到这个分支
    executor = new SimpleExecutor(this, transaction);
  }
  if (cacheEnabled) {
    executor = new CachingExecutor(executor);
  }
  executor = (Executor) interceptorChain.pluginAll(executor);
  return executor;
}
- -

上面传入的 executorType 是 Configuration 的默认类型，也就是 simple 类型，并且 cacheEnabled 在 Configuration 默认为 true，所以会包装成CachingExecutor ,然后后面就是插件了，这块我们先不展开
然后我们的openSession返回的就是创建了DefaultSqlSession

-
public DefaultSqlSession(Configuration configuration, Executor executor, boolean autoCommit) {
    this.configuration = configuration;
    this.executor = executor;
    this.dirty = false;
    this.autoCommit = autoCommit;
  }
- -

然后就是调用 selectOne, 因为前面已经把这部分代码说过了，就直接跳转过来
org.apache.ibatis.session.defaults.DefaultSqlSession#selectList(java.lang.String, java.lang.Object, org.apache.ibatis.session.RowBounds, org.apache.ibatis.session.ResultHandler)

-
private <E> List<E> selectList(String statement, Object parameter, RowBounds rowBounds, ResultHandler handler) {
  try {
    MappedStatement ms = configuration.getMappedStatement(statement);
    return executor.query(ms, wrapCollection(parameter), rowBounds, handler);
  } catch (Exception e) {
    throw ExceptionFactory.wrapException("Error querying database.  Cause: " + e, e);
  } finally {
    ErrorContext.instance().reset();
  }
}
- -

因为前面说了 executor 包装了 CachingExecutor ，所以会先调用

-
@Override
public <E> List<E> query(MappedStatement ms, Object parameterObject, RowBounds rowBounds, ResultHandler resultHandler) throws SQLException {
  BoundSql boundSql = ms.getBoundSql(parameterObject);
  CacheKey key = createCacheKey(ms, parameterObject, rowBounds, boundSql);
  return query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
}
- -

然后是调用的真实的query方法

-
@Override
public <E> List<E> query(MappedStatement ms, Object parameterObject, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql)
    throws SQLException {
  Cache cache = ms.getCache();
  if (cache != null) {
    flushCacheIfRequired(ms);
    if (ms.isUseCache() && resultHandler == null) {
      ensureNoOutParams(ms, boundSql);
      @SuppressWarnings("unchecked")
      List<E> list = (List<E>) tcm.getObject(cache, key);
      if (list == null) {
        list = delegate.query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
        tcm.putObject(cache, key, list); // issue #578 and #116
      }
      return list;
    }
  }
  return delegate.query(ms, parameterObject, rowBounds, resultHandler, key, boundSql);
}
- -

这里是第一次查询，没有缓存就先到最后一行，继续是调用到 org.apache.ibatis.executor.BaseExecutor#queryFromDatabase

-
@Override
  public <E> List<E> query(MappedStatement ms, Object parameter, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql) throws SQLException {
    ErrorContext.instance().resource(ms.getResource()).activity("executing a query").object(ms.getId());
    if (closed) {
      throw new ExecutorException("Executor was closed.");
    }
    if (queryStack == 0 && ms.isFlushCacheRequired()) {
      clearLocalCache();
    }
    List<E> list;
    try {
      queryStack++;
      list = resultHandler == null ? (List<E>) localCache.getObject(key) : null;
      if (list != null) {
        handleLocallyCachedOutputParameters(ms, key, parameter, boundSql);
      } else {
        // ----------->会走到这里
        list = queryFromDatabase(ms, parameter, rowBounds, resultHandler, key, boundSql);
      }
    } finally {
      queryStack--;
    }
    if (queryStack == 0) {
      for (DeferredLoad deferredLoad : deferredLoads) {
        deferredLoad.load();
      }
      // issue #601
      deferredLoads.clear();
      if (configuration.getLocalCacheScope() == LocalCacheScope.STATEMENT) {
        // issue #482
        clearLocalCache();
      }
    }
    return list;
  }
- -

然后是

-
private <E> List<E> queryFromDatabase(MappedStatement ms, Object parameter, RowBounds rowBounds, ResultHandler resultHandler, CacheKey key, BoundSql boundSql) throws SQLException {
  List<E> list;
  localCache.putObject(key, EXECUTION_PLACEHOLDER);
  try {
    list = doQuery(ms, parameter, rowBounds, resultHandler, boundSql);
  } finally {
    localCache.removeObject(key);
  }
  localCache.putObject(key, list);
  if (ms.getStatementType() == StatementType.CALLABLE) {
    localOutputParameterCache.putObject(key, parameter);
  }
  return list;
}
- -

然后就是 simpleExecutor 的执行过程

-
@Override
public <E> List<E> doQuery(MappedStatement ms, Object parameter, RowBounds rowBounds, ResultHandler resultHandler, BoundSql boundSql) throws SQLException {
  Statement stmt = null;
  try {
    Configuration configuration = ms.getConfiguration();
    StatementHandler handler = configuration.newStatementHandler(wrapper, ms, parameter, rowBounds, resultHandler, boundSql);
    stmt = prepareStatement(handler, ms.getStatementLog());
    return handler.query(stmt, resultHandler);
  } finally {
    closeStatement(stmt);
  }
}
- -

接下去其实就是跟jdbc交互了

-
@Override
public <E> List<E> query(Statement statement, ResultHandler resultHandler) throws SQLException {
  PreparedStatement ps = (PreparedStatement) statement;
  ps.execute();
  return resultSetHandler.handleResultSets(ps);
}
- -

com.mysql.cj.jdbc.ClientPreparedStatement#execute

-
public boolean execute() throws SQLException {
        try {
            synchronized(this.checkClosed().getConnectionMutex()) {
                JdbcConnection locallyScopedConn = this.connection;
                if (!this.doPingInstead && !this.checkReadOnlySafeStatement()) {
                    throw SQLError.createSQLException(Messages.getString("PreparedStatement.20") + Messages.getString("PreparedStatement.21"), "S1009", this.exceptionInterceptor);
                } else {
                    ResultSetInternalMethods rs = null;
                    this.lastQueryIsOnDupKeyUpdate = false;
                    if (this.retrieveGeneratedKeys) {
                        this.lastQueryIsOnDupKeyUpdate = this.containsOnDuplicateKeyUpdate();
                    }

                    this.batchedGeneratedKeys = null;
                    this.resetCancelledState();
                    this.implicitlyCloseAllOpenResults();
                    this.clearWarnings();
                    if (this.doPingInstead) {
                        this.doPingInstead();
                        return true;
                    } else {
                        this.setupStreamingTimeout(locallyScopedConn);
                        Message sendPacket = ((PreparedQuery)this.query).fillSendPacket(((PreparedQuery)this.query).getQueryBindings());
                        String oldDb = null;
                        if (!locallyScopedConn.getDatabase().equals(this.getCurrentDatabase())) {
                            oldDb = locallyScopedConn.getDatabase();
                            locallyScopedConn.setDatabase(this.getCurrentDatabase());
                        }

                        CachedResultSetMetaData cachedMetadata = null;
                        boolean cacheResultSetMetadata = (Boolean)locallyScopedConn.getPropertySet().getBooleanProperty(PropertyKey.cacheResultSetMetadata).getValue();
                        if (cacheResultSetMetadata) {
                            cachedMetadata = locallyScopedConn.getCachedMetaData(((PreparedQuery)this.query).getOriginalSql());
                        }

                        locallyScopedConn.setSessionMaxRows(this.getQueryInfo().getFirstStmtChar() == 'S' ? this.maxRows : -1);
                        rs = this.executeInternal(this.maxRows, sendPacket, this.createStreamingResultSet(), this.getQueryInfo().getFirstStmtChar() == 'S', cachedMetadata, false);
                        if (cachedMetadata != null) {
                            locallyScopedConn.initializeResultsMetadataFromCache(((PreparedQuery)this.query).getOriginalSql(), cachedMetadata, rs);
                        } else if (rs.hasRows() && cacheResultSetMetadata) {
                            locallyScopedConn.initializeResultsMetadataFromCache(((PreparedQuery)this.query).getOriginalSql(), (CachedResultSetMetaData)null, rs);
                        }

                        if (this.retrieveGeneratedKeys) {
                            rs.setFirstCharOfQuery(this.getQueryInfo().getFirstStmtChar());
                        }

                        if (oldDb != null) {
                            locallyScopedConn.setDatabase(oldDb);
                        }

                        if (rs != null) {
                            this.lastInsertId = rs.getUpdateID();
                            this.results = rs;
                        }

                        return rs != null && rs.hasRows();
                    }
                }
            }
        } catch (CJException var11) {
            throw SQLExceptionsMapping.translateException(var11, this.getExceptionInterceptor());
        }
    }
- -]]> - - Java - Mybatis - - - Java - Mysql - Mybatis - - powershell 初体验 /2022/11/13/powershell-%E5%88%9D%E4%BD%93%E9%AA%8C/ @@ -3507,6 +3533,28 @@ powershell + + rabbitmq-tips + /2017/04/25/rabbitmq-tips/ + rabbitmq 介绍

接触了一下rabbitmq，原来在选型的时候是在rabbitmq跟kafka之间做选择，网上搜了一下之后发现kafka的优势在于吞吐量，而rabbitmq相对注重可靠性，因为应用在im上，需要保证消息不能丢失所以就暂时选定rabbitmq，
Message Queue的需求由来已久，80年代最早在金融交易中，高盛等公司采用Teknekron公司的产品，当时的Message queuing软件叫做：the information bus（TIB）。 TIB被电信和通讯公司采用，路透社收购了Teknekron公司。之后，IBM开发了MQSeries，微软开发了Microsoft Message Queue（MSMQ）。这些商业MQ供应商的问题是厂商锁定，价格高昂。2001年，Java Message queuing试图解决锁定和交互性的问题，但对应用来说反而更加麻烦了。
RabbitMQ采用Erlang语言开发。Erlang语言由Ericson设计，专门为开发concurrent和distribution系统的一种语言，在电信领域使用广泛。OTP（Open Telecom Platform）作为Erlang语言的一部分，包含了很多基于Erlang开发的中间件／库／工具，如mnesia／SASL，极大方便了Erlang应用的开发。OTP就类似于Python语言中众多的module，用户借助这些module可以很方便的开发应用。
于是2004年，摩根大通和iMatrix开始着手Advanced Message Queuing Protocol （AMQP）开放标准的开发。2006年，AMQP规范发布。2007年，Rabbit技术公司基于AMQP标准开发的RabbitMQ 1.0 发布。所有主要的编程语言均有与代理接口通讯的客户端库。

+

简单的使用经验

通俗的理解

这里介绍下其中的一些概念，connection表示和队列服务器的连接，一般情况下是tcp连接， channel表示通道，可以在一个连接上建立多个通道，这里主要是节省了tcp连接握手的成本，exchange可以理解成一个路由器，将消息推送给对应的队列queue，其实是像一个订阅的模式。

+

集群经验

rabbitmqctl stop这个是关闭rabbitmq，在搭建集群时候先关闭服务，然后使用rabbitmq-server -detached静默启动，这时候使用rabbitmqctl cluster_status查看集群状态，因为还没将节点加入集群，所以只能看到类似

+
Cluster status of node rabbit@rabbit1 ...
[{nodes,[{disc,[rabbit@rabbit1,rabbit@rabbit2,rabbit@rabbit3]}]},
 {running_nodes,[rabbit@rabbit2,rabbit@rabbit1]}]
...done.
+

然后就可以把当前节点加入集群，

+
rabbit2$ rabbitmqctl stop_app #这个stop_app与stop的区别是前者停的是rabbitmq应用，保留erlang节点，
                              #后者是停止了rabbitmq和erlang节点
Stopping node rabbit@rabbit2 ...done.
rabbit2$ rabbitmqctl join_cluster rabbit@rabbit1 #这里可以用--ram指定将当前节点作为内存节点加入集群
Clustering node rabbit@rabbit2 with [rabbit@rabbit1] ...done.
rabbit2$ rabbitmqctl start_app
Starting node rabbit@rabbit2 ...done.
+

其他可以参考官方文档

+

一些坑

消息丢失

这里碰到过一个坑，对于使用exchange来做消息路由的，会有一个情况，就是在routing_key没被订阅的时候，会将该条找不到路由对应的queue的消息丢掉What happens if we break our contract and send a message with one or four words, like "orange" or "quick.orange.male.rabbit"? Well, these messages won't match any bindings and will be lost.对应链接,而当使用空的exchange时，会保留消息，当出现消费者的时候就可以将收到之前生产者所推送的消息对应链接,这里就是用了空的exchange。

+

集群搭建

集群搭建的时候有个erlang vm生成的random cookie，这个是用来做集群之间认证的，相同的cookie才能连接，但是如果通过vim打开复制后在其他几点新建文件写入会多一个换行，导致集群建立是报错，所以这里最好使用scp等传输命令直接传输cookie文件，同时要注意下cookie的文件权限。
另外在集群搭建的时候如果更改过hostname，那么要把rabbitmq的数据库删除，否则启动后会马上挂掉

+]]> + + php + + + php + mq + im + + redis 的 rdb 和 COW 介绍 /2021/08/15/redis-%E7%9A%84-rdb-%E5%92%8C-COW-%E4%BB%8B%E7%BB%8D/ @@ -3575,22 +3623,17 @@ - redis数据结构介绍五-第五部分 对象 - /2020/01/20/redis%E6%95%B0%E6%8D%AE%E7%BB%93%E6%9E%84%E4%BB%8B%E7%BB%8D%E4%BA%94/ - 前面说了这么些数据结构，其实大家对于 redis 最初的印象应该就是个 key-value 的缓存，类似于 memcache，redis 其实也是个 key-value，key 还是一样的字符串，或者说就是用 redis 自己的动态字符串实现，但是 value 其实就是前面说的那些数据结构，差不多快说完了，还有个 quicklist 后面还有一篇，这里先介绍下 redis 对于这些不同类型的 value 是怎么实现的，首先看下 redisObject 的源码头文件

-
/* The actual Redis Object */
#define OBJ_STRING 0    /* String object. */
#define OBJ_LIST 1      /* List object. */
#define OBJ_SET 2       /* Set object. */
#define OBJ_ZSET 3      /* Sorted set object. */
#define OBJ_HASH 4      /* Hash object. */
/*
 * Objects encoding. Some kind of objects like Strings and Hashes can be
 * internally represented in multiple ways. The 'encoding' field of the object
 * is set to one of this fields for this object. */
#define OBJ_ENCODING_RAW 0     /* Raw representation */
#define OBJ_ENCODING_INT 1     /* Encoded as integer */
#define OBJ_ENCODING_HT 2      /* Encoded as hash table */
#define OBJ_ENCODING_ZIPMAP 3  /* Encoded as zipmap */
#define OBJ_ENCODING_LINKEDLIST 4 /* No longer used: old list encoding. */
#define OBJ_ENCODING_ZIPLIST 5 /* Encoded as ziplist */
#define OBJ_ENCODING_INTSET 6  /* Encoded as intset */
#define OBJ_ENCODING_SKIPLIST 7  /* Encoded as skiplist */
#define OBJ_ENCODING_EMBSTR 8  /* Embedded sds string encoding */
#define OBJ_ENCODING_QUICKLIST 9 /* Encoded as linked list of ziplists */
#define OBJ_ENCODING_STREAM 10 /* Encoded as a radix tree of listpacks */

#define LRU_BITS 24
#define LRU_CLOCK_MAX ((1<<LRU_BITS)-1) /* Max value of obj->lru */
#define LRU_CLOCK_RESOLUTION 1000 /* LRU clock resolution in ms */

#define OBJ_SHARED_REFCOUNT INT_MAX
typedef struct redisObject {
    unsigned type:4;
    unsigned encoding:4;
    unsigned lru:LRU_BITS; /* LRU time (relative to global lru_clock) or
                            * LFU data (least significant 8 bits frequency
                            * and most significant 16 bits access time). */
    int refcount;
    void *ptr;
} robj;
-

主体结构就是这个 redisObject，

-
    -
  • type： 字段表示对象的类型，它对应的就是 redis 的对外暴露的，或者说用户可以使用的五种类型，OBJ_STRING, OBJ_LIST, OBJ_SET, OBJ_ZSET, OBJ_HASH
    • -
  • encoding： 字段表示这个对象在 redis 内部的编码方式，由OBJ_ENCODING_开头的 11 种
    • -
  • lru: 做LRU替换算法用，占24个bit
    • -
  • refcount: 引用计数。它允许robj对象在某些情况下被共享。
    • -
  • ptr: 指向底层实现数据结构的指针
    当 type 是 OBJ_STRING 时，表示类型是个 string，它的编码方式 encoding 可能有 OBJ_ENCODING_RAW，OBJ_ENCODING_INT，OBJ_ENCODING_EMBSTR 三种
    当 type 是 OBJ_LIST 时，表示类型是 list，它的编码方式 encoding 是 OBJ_ENCODING_QUICKLIST，对于早一些的版本，2.2这种可能还会使用 OBJ_ENCODING_ZIPLIST，OBJ_ENCODING_LINKEDLIST
    当 type 是 OBJ_SET 时，是个集合，但是得看具体元素的类型，有可能使用整数集合，OBJ_ENCODING_INTSET, 如果元素不全是整型或者数量超过一定限制，那么编码就是 OBJ_ENCODING_HT hash table 了
    当 type 是 OBJ_ZSET 时，是个有序集合，它底层有可能使用的是 OBJ_ENCODING_ZIPLIST 或者 OBJ_ENCODING_SKIPLIST
    当 type 是 OBJ_HASH 时，一开始也是 OBJ_ENCODING_ZIPLIST，然后当数据量大于 hash_max_ziplist_entries 时会转成 OBJ_ENCODING_HT
    • -
-]]> - - Redis - 数据结构 + redis数据结构介绍二-第二部分 跳表 + /2020/01/04/redis%E6%95%B0%E6%8D%AE%E7%BB%93%E6%9E%84%E4%BB%8B%E7%BB%8D%E4%BA%8C/ + 跳表 skiplist

跳表是个在我们日常的代码中不太常用到的数据结构，相对来讲就没有像数组，链表，字典，散列，树等结构那么熟悉，所以就从头开始分析下，首先是链表，跳表跟链表都有个表字（太硬扯了我🤦‍♀️），注意这是个有序链表

如上图，在这个链表里如果我要找到 23，是不是我需要从3，5，9开始一直往后找直到找到 23，也就是说时间复杂度是 O(N),N 的一次幂复杂度，那么我们来看看第二个

这个结构跟原先有点不一样，它给链表中偶数位的节点又加了一个指针把它们链接起来，这样子当我们要寻找 23 的时候就可以从原来的一个个往下找变成跳着找，先找到 5，然后是 10，接着是 19，然后是 28，这时候发现 28 比 23 大了，那我在退回到 19，然后从下一层原来的链表往前找，

这里毛估估是不是前面的节点我就少找了一半,有那么点二分法的意思。
前面的其实是跳表的引子，真正的跳表其实不是这样，因为上面的其实有个比较大的问题，就是插入一个元素后需要调整每个元素的指针，在 redis 中的跳表其实是做了个随机层数的优化，因为沿着前面的例子，其实当数据量很大的时候，是不是层数越多，其查询效率越高，但是随着层数变多，要保持这种严格的层数规则其实也会增大处理复杂度，所以 redis 插入每个元素的时候都是使用随机的方式，看一眼代码

+
/* ZSETs use a specialized version of Skiplists */
typedef struct zskiplistNode {
    sds ele;
    double score;
    struct zskiplistNode *backward;
    struct zskiplistLevel {
        struct zskiplistNode *forward;
        unsigned long span;
    } level[];
} zskiplistNode;

typedef struct zskiplist {
    struct zskiplistNode *header, *tail;
    unsigned long length;
    int level;
} zskiplist;

typedef struct zset {
    dict *dict;
    zskiplist *zsl;
} zset;
+

忘了说了，redis 是把 skiplist 跳表用在 zset 里，zset 是个有序的集合，可以看到 zskiplist 就是个跳表的结构，里面用 header 保存跳表的表头，tail 保存表尾，还有长度和最大层级，具体的跳表节点元素使用 zskiplistNode 表示，里面包含了 sds 类型的元素值，double 类型的分值，用来排序，一个 backward 后向指针和一个 zskiplistLevel 数组，每个 level 包含了一个前向指针，和一个 span，span 表示的是跳表前向指针的跨度，这里再补充一点，前面说了为了灵活这个跳表的新增修改，redis 使用了随机层高的方式插入新节点，但是如果所有节点都随机到很高的层级或者所有都很低的话，跳表的效率优势就会减小，所以 redis 使用了个小技巧，贴下代码

+
#define ZSKIPLIST_P 0.25      /* Skiplist P = 1/4 */
int zslRandomLevel(void) {
    int level = 1;
    while ((random()&0xFFFF) < (ZSKIPLIST_P * 0xFFFF))
        level += 1;
    return (level<ZSKIPLIST_MAXLEVEL) ? level : ZSKIPLIST_MAXLEVEL;
}
+

当随机值跟0xFFFF进行与操作小于ZSKIPLIST_P * 0xFFFF时才会增大 level 的值，因此保持了一个相对递减的概率
可以简单分析下，当 random() 的值小于 0xFFFF 的 1/4,才会 level + 1，就意味着当有 1 - 1/4也就是3/4的概率是直接跳出，所以一层的概率是3/4,也就是 1-P，二层的概率是 P*(1-P),三层的概率是 P² * (1-P) 依次递推。

+]]> + + Redis + 数据结构 C 源码 Redis @@ -3602,13 +3645,18 @@ - redis数据结构介绍二-第二部分 跳表 - /2020/01/04/redis%E6%95%B0%E6%8D%AE%E7%BB%93%E6%9E%84%E4%BB%8B%E7%BB%8D%E4%BA%8C/ - 跳表 skiplist

跳表是个在我们日常的代码中不太常用到的数据结构，相对来讲就没有像数组，链表，字典，散列，树等结构那么熟悉，所以就从头开始分析下，首先是链表，跳表跟链表都有个表字（太硬扯了我🤦‍♀️），注意这是个有序链表

如上图，在这个链表里如果我要找到 23，是不是我需要从3，5，9开始一直往后找直到找到 23，也就是说时间复杂度是 O(N),N 的一次幂复杂度，那么我们来看看第二个

这个结构跟原先有点不一样，它给链表中偶数位的节点又加了一个指针把它们链接起来，这样子当我们要寻找 23 的时候就可以从原来的一个个往下找变成跳着找，先找到 5，然后是 10，接着是 19，然后是 28，这时候发现 28 比 23 大了，那我在退回到 19，然后从下一层原来的链表往前找，

这里毛估估是不是前面的节点我就少找了一半,有那么点二分法的意思。
前面的其实是跳表的引子，真正的跳表其实不是这样，因为上面的其实有个比较大的问题，就是插入一个元素后需要调整每个元素的指针，在 redis 中的跳表其实是做了个随机层数的优化，因为沿着前面的例子，其实当数据量很大的时候，是不是层数越多，其查询效率越高，但是随着层数变多，要保持这种严格的层数规则其实也会增大处理复杂度，所以 redis 插入每个元素的时候都是使用随机的方式，看一眼代码

-
/* ZSETs use a specialized version of Skiplists */
typedef struct zskiplistNode {
    sds ele;
    double score;
    struct zskiplistNode *backward;
    struct zskiplistLevel {
        struct zskiplistNode *forward;
        unsigned long span;
    } level[];
} zskiplistNode;

typedef struct zskiplist {
    struct zskiplistNode *header, *tail;
    unsigned long length;
    int level;
} zskiplist;

typedef struct zset {
    dict *dict;
    zskiplist *zsl;
} zset;
-

忘了说了，redis 是把 skiplist 跳表用在 zset 里，zset 是个有序的集合，可以看到 zskiplist 就是个跳表的结构，里面用 header 保存跳表的表头，tail 保存表尾，还有长度和最大层级，具体的跳表节点元素使用 zskiplistNode 表示，里面包含了 sds 类型的元素值，double 类型的分值，用来排序，一个 backward 后向指针和一个 zskiplistLevel 数组，每个 level 包含了一个前向指针，和一个 span，span 表示的是跳表前向指针的跨度，这里再补充一点，前面说了为了灵活这个跳表的新增修改，redis 使用了随机层高的方式插入新节点，但是如果所有节点都随机到很高的层级或者所有都很低的话，跳表的效率优势就会减小，所以 redis 使用了个小技巧，贴下代码

-
#define ZSKIPLIST_P 0.25      /* Skiplist P = 1/4 */
int zslRandomLevel(void) {
    int level = 1;
    while ((random()&0xFFFF) < (ZSKIPLIST_P * 0xFFFF))
        level += 1;
    return (level<ZSKIPLIST_MAXLEVEL) ? level : ZSKIPLIST_MAXLEVEL;
}
-

当随机值跟0xFFFF进行与操作小于ZSKIPLIST_P * 0xFFFF时才会增大 level 的值，因此保持了一个相对递减的概率
可以简单分析下，当 random() 的值小于 0xFFFF 的 1/4,才会 level + 1，就意味着当有 1 - 1/4也就是3/4的概率是直接跳出，所以一层的概率是3/4,也就是 1-P，二层的概率是 P*(1-P),三层的概率是 P² * (1-P) 依次递推。

+ redis数据结构介绍五-第五部分 对象 + /2020/01/20/redis%E6%95%B0%E6%8D%AE%E7%BB%93%E6%9E%84%E4%BB%8B%E7%BB%8D%E4%BA%94/ + 前面说了这么些数据结构，其实大家对于 redis 最初的印象应该就是个 key-value 的缓存，类似于 memcache，redis 其实也是个 key-value，key 还是一样的字符串，或者说就是用 redis 自己的动态字符串实现，但是 value 其实就是前面说的那些数据结构，差不多快说完了，还有个 quicklist 后面还有一篇，这里先介绍下 redis 对于这些不同类型的 value 是怎么实现的，首先看下 redisObject 的源码头文件

+
/* The actual Redis Object */
#define OBJ_STRING 0    /* String object. */
#define OBJ_LIST 1      /* List object. */
#define OBJ_SET 2       /* Set object. */
#define OBJ_ZSET 3      /* Sorted set object. */
#define OBJ_HASH 4      /* Hash object. */
/*
 * Objects encoding. Some kind of objects like Strings and Hashes can be
 * internally represented in multiple ways. The 'encoding' field of the object
 * is set to one of this fields for this object. */
#define OBJ_ENCODING_RAW 0     /* Raw representation */
#define OBJ_ENCODING_INT 1     /* Encoded as integer */
#define OBJ_ENCODING_HT 2      /* Encoded as hash table */
#define OBJ_ENCODING_ZIPMAP 3  /* Encoded as zipmap */
#define OBJ_ENCODING_LINKEDLIST 4 /* No longer used: old list encoding. */
#define OBJ_ENCODING_ZIPLIST 5 /* Encoded as ziplist */
#define OBJ_ENCODING_INTSET 6  /* Encoded as intset */
#define OBJ_ENCODING_SKIPLIST 7  /* Encoded as skiplist */
#define OBJ_ENCODING_EMBSTR 8  /* Embedded sds string encoding */
#define OBJ_ENCODING_QUICKLIST 9 /* Encoded as linked list of ziplists */
#define OBJ_ENCODING_STREAM 10 /* Encoded as a radix tree of listpacks */

#define LRU_BITS 24
#define LRU_CLOCK_MAX ((1<<LRU_BITS)-1) /* Max value of obj->lru */
#define LRU_CLOCK_RESOLUTION 1000 /* LRU clock resolution in ms */

#define OBJ_SHARED_REFCOUNT INT_MAX
typedef struct redisObject {
    unsigned type:4;
    unsigned encoding:4;
    unsigned lru:LRU_BITS; /* LRU time (relative to global lru_clock) or
                            * LFU data (least significant 8 bits frequency
                            * and most significant 16 bits access time). */
    int refcount;
    void *ptr;
} robj;
+

主体结构就是这个 redisObject，

+
    +
  • type： 字段表示对象的类型，它对应的就是 redis 的对外暴露的，或者说用户可以使用的五种类型，OBJ_STRING, OBJ_LIST, OBJ_SET, OBJ_ZSET, OBJ_HASH
    • +
  • encoding： 字段表示这个对象在 redis 内部的编码方式，由OBJ_ENCODING_开头的 11 种
    • +
  • lru: 做LRU替换算法用，占24个bit
    • +
  • refcount: 引用计数。它允许robj对象在某些情况下被共享。
    • +
  • ptr: 指向底层实现数据结构的指针
    当 type 是 OBJ_STRING 时，表示类型是个 string，它的编码方式 encoding 可能有 OBJ_ENCODING_RAW，OBJ_ENCODING_INT，OBJ_ENCODING_EMBSTR 三种
    当 type 是 OBJ_LIST 时，表示类型是 list，它的编码方式 encoding 是 OBJ_ENCODING_QUICKLIST，对于早一些的版本，2.2这种可能还会使用 OBJ_ENCODING_ZIPLIST，OBJ_ENCODING_LINKEDLIST
    当 type 是 OBJ_SET 时，是个集合，但是得看具体元素的类型，有可能使用整数集合，OBJ_ENCODING_INTSET, 如果元素不全是整型或者数量超过一定限制，那么编码就是 OBJ_ENCODING_HT hash table 了
    当 type 是 OBJ_ZSET 时，是个有序集合，它底层有可能使用的是 OBJ_ENCODING_ZIPLIST 或者 OBJ_ENCODING_SKIPLIST
    当 type 是 OBJ_HASH 时，一开始也是 OBJ_ENCODING_ZIPLIST，然后当数据量大于 hash_max_ziplist_entries 时会转成 OBJ_ENCODING_HT
    • +
]]> Redis @@ -3664,54 +3712,6 @@ 源码 - - Leetcode 572 Subtree of Another Tree 题解分析 - /2024/01/28/Leetcode-572-Subtree-of-Another-Tree-%E9%A2%98%E8%A7%A3%E5%88%86%E6%9E%90/ - 题目介绍

Given the roots of two binary trees root and subRoot, return true if there is a subtree of root with the same structure and node values of subRoot and false otherwise.

-

A subtree of a binary tree tree is a tree that consists of a node in tree and all of this node’s descendants. The tree tree could also be considered as a subtree of itself.

-

示例 1

-
-

Input: root = [3,4,5,1,2], subRoot = [4,1,2]
Output: true

-
-

示例 2

-
-

Input: root = [3,4,5,1,2,null,null,null,null,0], subRoot = [4,1,2]
Output: false

-
-

解析

需要判断subRoot 为根节点的这棵树是不是 root 为根节点的这个树的子树，题应该不是特别难理解，只是需要注意，这里是子树，而不是一个子结构，也就是示例 2 的判断结果是 false，因为左边子树还有个 0，只能认为是左边的一部分，但不是子树，思路分析也不难，就是递归去判断，只不过是两种维度，第一种就是找到子树的根节点，也就是在 root 树找到 subRoot 的根节点相同的节点，这个就会用到递归，如果找到了一个，就开始递归的对比所有子节点，必须完全一样

-

代码

public boolean isSubtree(TreeNode root, TreeNode subRoot) {
       if (subRoot == null || root == null) {
           return false;
       }
       if (root.val == subRoot.val) {
           // 如果 root 节点跟 subRoot 节点相同，就开始递归对比所有的子节点
           if (isSameTree(root.left, subRoot.left) && isSameTree(root.right, subRoot.right)) {
               return true;
           }
       }
       // 如果 root 节点不同，就开始递归往下找与 subRoot 相同的起始节点，这里是或的关系，因为在左右子树任一找到一个就行
       return isSubtree(root.left, subRoot) || isSubtree(root.right, subRoot);
   }
   // 需要完全相同，也就是说不能像示例 2 那样多一个子节点这种，以及其他不同的情况，反正就是要完全一样
   public boolean isSameTree(TreeNode root, TreeNode subTree) {
       // 如果递归到这个节点都为空也认为是相同的
       if (root == null && subTree == null) {
           return true;
       }
       // 因为有前面的判断，这里就隐含了 subTree != null 这个条件
       if (root == null) {
           return false;
       }
       // 也因为有前面的判断，这里就隐含了  root != null 这个条件
       if (subTree == null) {
           return false;
       }
       // 两个都不为空，但是值不相同，也是 false
       if (root.val != subTree.val) {
           return false;
       }
       // 跟节点相同，就开始递归判断左右子树，必须两者都相同
       return isSameTree(root.left, subTree.left) && isSameTree(root.right, subTree.right);
   }
-]]> - - Java - leetcode - - - leetcode - java - 题解 - - - - rabbitmq-tips - /2017/04/25/rabbitmq-tips/ - rabbitmq 介绍

接触了一下rabbitmq，原来在选型的时候是在rabbitmq跟kafka之间做选择，网上搜了一下之后发现kafka的优势在于吞吐量，而rabbitmq相对注重可靠性，因为应用在im上，需要保证消息不能丢失所以就暂时选定rabbitmq，
Message Queue的需求由来已久，80年代最早在金融交易中，高盛等公司采用Teknekron公司的产品，当时的Message queuing软件叫做：the information bus（TIB）。 TIB被电信和通讯公司采用，路透社收购了Teknekron公司。之后，IBM开发了MQSeries，微软开发了Microsoft Message Queue（MSMQ）。这些商业MQ供应商的问题是厂商锁定，价格高昂。2001年，Java Message queuing试图解决锁定和交互性的问题，但对应用来说反而更加麻烦了。
RabbitMQ采用Erlang语言开发。Erlang语言由Ericson设计，专门为开发concurrent和distribution系统的一种语言，在电信领域使用广泛。OTP（Open Telecom Platform）作为Erlang语言的一部分，包含了很多基于Erlang开发的中间件／库／工具，如mnesia／SASL，极大方便了Erlang应用的开发。OTP就类似于Python语言中众多的module，用户借助这些module可以很方便的开发应用。
于是2004年，摩根大通和iMatrix开始着手Advanced Message Queuing Protocol （AMQP）开放标准的开发。2006年，AMQP规范发布。2007年，Rabbit技术公司基于AMQP标准开发的RabbitMQ 1.0 发布。所有主要的编程语言均有与代理接口通讯的客户端库。

-

简单的使用经验

通俗的理解

这里介绍下其中的一些概念，connection表示和队列服务器的连接，一般情况下是tcp连接， channel表示通道，可以在一个连接上建立多个通道，这里主要是节省了tcp连接握手的成本，exchange可以理解成一个路由器，将消息推送给对应的队列queue，其实是像一个订阅的模式。

-

集群经验

rabbitmqctl stop这个是关闭rabbitmq，在搭建集群时候先关闭服务，然后使用rabbitmq-server -detached静默启动，这时候使用rabbitmqctl cluster_status查看集群状态，因为还没将节点加入集群，所以只能看到类似

-
Cluster status of node rabbit@rabbit1 ...
[{nodes,[{disc,[rabbit@rabbit1,rabbit@rabbit2,rabbit@rabbit3]}]},
 {running_nodes,[rabbit@rabbit2,rabbit@rabbit1]}]
...done.
-

然后就可以把当前节点加入集群，

-
rabbit2$ rabbitmqctl stop_app #这个stop_app与stop的区别是前者停的是rabbitmq应用，保留erlang节点，
                              #后者是停止了rabbitmq和erlang节点
Stopping node rabbit@rabbit2 ...done.
rabbit2$ rabbitmqctl join_cluster rabbit@rabbit1 #这里可以用--ram指定将当前节点作为内存节点加入集群
Clustering node rabbit@rabbit2 with [rabbit@rabbit1] ...done.
rabbit2$ rabbitmqctl start_app
Starting node rabbit@rabbit2 ...done.
-

其他可以参考官方文档

-

一些坑

消息丢失

这里碰到过一个坑，对于使用exchange来做消息路由的，会有一个情况，就是在routing_key没被订阅的时候，会将该条找不到路由对应的queue的消息丢掉What happens if we break our contract and send a message with one or four words, like "orange" or "quick.orange.male.rabbit"? Well, these messages won't match any bindings and will be lost.对应链接,而当使用空的exchange时，会保留消息，当出现消费者的时候就可以将收到之前生产者所推送的消息对应链接,这里就是用了空的exchange。

-

集群搭建

集群搭建的时候有个erlang vm生成的random cookie，这个是用来做集群之间认证的，相同的cookie才能连接，但是如果通过vim打开复制后在其他几点新建文件写入会多一个换行，导致集群建立是报错，所以这里最好使用scp等传输命令直接传输cookie文件，同时要注意下cookie的文件权限。
另外在集群搭建的时候如果更改过hostname，那么要把rabbitmq的数据库删除，否则启动后会马上挂掉

-]]> - - php - - - php - mq - im - - redis数据结构介绍四-第四部分 压缩表 /2020/01/19/redis%E6%95%B0%E6%8D%AE%E7%BB%93%E6%9E%84%E4%BB%8B%E7%BB%8D%E5%9B%9B/ @@ -3727,33 +3727,6 @@

首先如果 encoding 的前两位是 00 的话代表这个元素是个 6 位的字符串，即直接将数据保存在 encoding 中，不消耗额外的<entry-data>，如果前两位是 01 的话表示是个 14 位的字符串，如果是 10 的话表示encoding 块之后的四个字节是存放字符串类型的数据，encoding 的剩余 6 位置 0。
如果 encoding 的前两位是 11 的话表示这是个整型，具体的如果后两位是00的话，表示后面是个2字节的 int16_t 类型，如果是01的话，后面是个4字节的int32_t,如果是10的话后面是8字节的int64_t,如果是 11 的话后面是 3 字节的有符号整型，这些都要最后 4 位都是 0 的情况噢
剩下当是11111110时，则表示是一个1 字节的有符号数，如果是 1111xxxx，其中xxxx在0000 到 1101 表示实际的 1 到 13，为啥呢，因为 0000 前面已经用过了，而 1110 跟 1111 也都有用了。
看个具体的例子(上下有点对不齐，将就看)

[0f 00 00 00] [0c 00 00 00] [02 00] [00 f3] [02 f6] [ff]
|**zlbytes***|  |***zltail***|  |*zllen*|  |entry1 entry2|  |zlend|

第一部分代表整个 ziplist 有 15 个字节，zlbytes 自己占了 4 个 zltail 表示最后一个元素的偏移量，第 13 个字节起，zllen 表示有 2 个元素，第一个元素是00f3,00表示前一个元素长度是 0，本来前面就没元素(不过不知道这个能不能优化这一字节)，然后是 f3，换成二进制就是11110011,对照上面的注释，是落在|1111xxxx|这个类型里，注意这个其实是用 0001 到 1101 也就是 1到 13 来表示 0到 12，所以 f3 应该就是 2，第一个元素是 2，第二个元素呢，02 代表前一个元素也就是刚才说的这个，占用 2 字节，f6 展开也是刚才的类型，实际是 5，ff 表示 ziplist 的结尾，所以这个 ziplist 里面是两个元素，2 跟 5

-]]> - - Redis - 数据结构 - C - 源码 - Redis - - - redis - 数据结构 - 源码 - - - - redis系列介绍七-过期策略 - /2020/04/12/redis%E7%B3%BB%E5%88%97%E4%BB%8B%E7%BB%8D%E4%B8%83/ - 这一篇不再是数据结构介绍了，大致的数据结构基本都介绍了，这一篇主要是查漏补缺，或者说讲一些重要且基本的概念，也可能是经常被忽略的，很多讲 redis 的系列文章可能都会忽略，学习 redis 的时候也会，因为觉得源码学习就是讲主要的数据结构和“算法”学习了就好了。
redis 的主要应用就是拿来作为高性能的缓存，那么缓存一般有些啥需要注意的，首先是访问速度，如果取得跟数据库一样快，那就没什么存在的意义，第二个是缓存的字面意思，我只是为了让数据读取快一些，通常大部分的场景这个是需要更新过期的，这里就把我要讲的第一点引出来了（真累，

-

redis过期策略

redis 是如何过期缓存的，可以猜测下，最无脑的就是每个设置了过期时间的 key 都设个定时器，过期了就删除，这种显然消耗太大，清理地最及时，还有的就是 redis 正在采用的懒汉清理策略和定期清理
懒汉策略就是在使用的时候去检查缓存是否过期，比如 get 操作时，先判断下这个 key 是否已经过期了，如果过期了就删掉，并且返回空，如果没过期则正常返回
主要代码是

-
/* This function is called when we are going to perform some operation
 * in a given key, but such key may be already logically expired even if
 * it still exists in the database. The main way this function is called
 * is via lookupKey*() family of functions.
 *
 * The behavior of the function depends on the replication role of the
 * instance, because slave instances do not expire keys, they wait
 * for DELs from the master for consistency matters. However even
 * slaves will try to have a coherent return value for the function,
 * so that read commands executed in the slave side will be able to
 * behave like if the key is expired even if still present (because the
 * master has yet to propagate the DEL).
 *
 * In masters as a side effect of finding a key which is expired, such
 * key will be evicted from the database. Also this may trigger the
 * propagation of a DEL/UNLINK command in AOF / replication stream.
 *
 * The return value of the function is 0 if the key is still valid,
 * otherwise the function returns 1 if the key is expired. */
int expireIfNeeded(redisDb *db, robj *key) {
    if (!keyIsExpired(db,key)) return 0;

    /* If we are running in the context of a slave, instead of
     * evicting the expired key from the database, we return ASAP:
     * the slave key expiration is controlled by the master that will
     * send us synthesized DEL operations for expired keys.
     *
     * Still we try to return the right information to the caller,
     * that is, 0 if we think the key should be still valid, 1 if
     * we think the key is expired at this time. */
    if (server.masterhost != NULL) return 1;

    /* Delete the key */
    server.stat_expiredkeys++;
    propagateExpire(db,key,server.lazyfree_lazy_expire);
    notifyKeyspaceEvent(NOTIFY_EXPIRED,
        "expired",key,db->id);
    return server.lazyfree_lazy_expire ? dbAsyncDelete(db,key) :
                                         dbSyncDelete(db,key);
}

/* Check if the key is expired. */
int keyIsExpired(redisDb *db, robj *key) {
    mstime_t when = getExpire(db,key);
    mstime_t now;

    if (when < 0) return 0; /* No expire for this key */

    /* Don't expire anything while loading. It will be done later. */
    if (server.loading) return 0;

    /* If we are in the context of a Lua script, we pretend that time is
     * blocked to when the Lua script started. This way a key can expire
     * only the first time it is accessed and not in the middle of the
     * script execution, making propagation to slaves / AOF consistent.
     * See issue #1525 on Github for more information. */
    if (server.lua_caller) {
        now = server.lua_time_start;
    }
    /* If we are in the middle of a command execution, we still want to use
     * a reference time that does not change: in that case we just use the
     * cached time, that we update before each call in the call() function.
     * This way we avoid that commands such as RPOPLPUSH or similar, that
     * may re-open the same key multiple times, can invalidate an already
     * open object in a next call, if the next call will see the key expired,
     * while the first did not. */
    else if (server.fixed_time_expire > 0) {
        now = server.mstime;
    }
    /* For the other cases, we want to use the most fresh time we have. */
    else {
        now = mstime();
    }

    /* The key expired if the current (virtual or real) time is greater
     * than the expire time of the key. */
    return now > when;
}
/* Return the expire time of the specified key, or -1 if no expire
 * is associated with this key (i.e. the key is non volatile) */
long long getExpire(redisDb *db, robj *key) {
    dictEntry *de;

    /* No expire? return ASAP */
    if (dictSize(db->expires) == 0 ||
       (de = dictFind(db->expires,key->ptr)) == NULL) return -1;

    /* The entry was found in the expire dict, this means it should also
     * be present in the main dict (safety check). */
    serverAssertWithInfo(NULL,key,dictFind(db->dict,key->ptr) != NULL);
    return dictGetSignedIntegerVal(de);
}
-

这里有几点要注意的，第一是当惰性删除时会根据lazyfree_lazy_expire这个参数去判断是执行同步删除还是异步删除，另外一点是对于 slave，是不需要执行的，因为会在 master 过期时向 slave 发送 del 指令。
光采用这个策略会有什么问题呢，假如一些key 一直未被访问，那这些 key 就不会过期了，导致一直被占用着内存，所以 redis 采取了懒汉式过期加定期过期策略，定期策略是怎么执行的呢

-
/* This function handles 'background' operations we are required to do
 * incrementally in Redis databases, such as active key expiring, resizing,
 * rehashing. */
void databasesCron(void) {
    /* Expire keys by random sampling. Not required for slaves
     * as master will synthesize DELs for us. */
    if (server.active_expire_enabled) {
        if (server.masterhost == NULL) {
            activeExpireCycle(ACTIVE_EXPIRE_CYCLE_SLOW);
        } else {
            expireSlaveKeys();
        }
    }

    /* Defrag keys gradually. */
    activeDefragCycle();

    /* Perform hash tables rehashing if needed, but only if there are no
     * other processes saving the DB on disk. Otherwise rehashing is bad
     * as will cause a lot of copy-on-write of memory pages. */
    if (!hasActiveChildProcess()) {
        /* We use global counters so if we stop the computation at a given
         * DB we'll be able to start from the successive in the next
         * cron loop iteration. */
        static unsigned int resize_db = 0;
        static unsigned int rehash_db = 0;
        int dbs_per_call = CRON_DBS_PER_CALL;
        int j;

        /* Don't test more DBs than we have. */
        if (dbs_per_call > server.dbnum) dbs_per_call = server.dbnum;

        /* Resize */
        for (j = 0; j < dbs_per_call; j++) {
            tryResizeHashTables(resize_db % server.dbnum);
            resize_db++;
        }

        /* Rehash */
        if (server.activerehashing) {
            for (j = 0; j < dbs_per_call; j++) {
                int work_done = incrementallyRehash(rehash_db);
                if (work_done) {
                    /* If the function did some work, stop here, we'll do
                     * more at the next cron loop. */
                    break;
                } else {
                    /* If this db didn't need rehash, we'll try the next one. */
                    rehash_db++;
                    rehash_db %= server.dbnum;
                }
            }
        }
    }
}
/* Try to expire a few timed out keys. The algorithm used is adaptive and
 * will use few CPU cycles if there are few expiring keys, otherwise
 * it will get more aggressive to avoid that too much memory is used by
 * keys that can be removed from the keyspace.
 *
 * Every expire cycle tests multiple databases: the next call will start
 * again from the next db, with the exception of exists for time limit: in that
 * case we restart again from the last database we were processing. Anyway
 * no more than CRON_DBS_PER_CALL databases are tested at every iteration.
 *
 * The function can perform more or less work, depending on the "type"
 * argument. It can execute a "fast cycle" or a "slow cycle". The slow
 * cycle is the main way we collect expired cycles: this happens with
 * the "server.hz" frequency (usually 10 hertz).
 *
 * However the slow cycle can exit for timeout, since it used too much time.
 * For this reason the function is also invoked to perform a fast cycle
 * at every event loop cycle, in the beforeSleep() function. The fast cycle
 * will try to perform less work, but will do it much more often.
 *
 * The following are the details of the two expire cycles and their stop
 * conditions:
 *
 * If type is ACTIVE_EXPIRE_CYCLE_FAST the function will try to run a
 * "fast" expire cycle that takes no longer than EXPIRE_FAST_CYCLE_DURATION
 * microseconds, and is not repeated again before the same amount of time.
 * The cycle will also refuse to run at all if the latest slow cycle did not
 * terminate because of a time limit condition.
 *
 * If type is ACTIVE_EXPIRE_CYCLE_SLOW, that normal expire cycle is
 * executed, where the time limit is a percentage of the REDIS_HZ period
 * as specified by the ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC define. In the
 * fast cycle, the check of every database is interrupted once the number
 * of already expired keys in the database is estimated to be lower than
 * a given percentage, in order to avoid doing too much work to gain too
 * little memory.
 *
 * The configured expire "effort" will modify the baseline parameters in
 * order to do more work in both the fast and slow expire cycles.
 */

#define ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP 20 /* Keys for each DB loop. */
#define ACTIVE_EXPIRE_CYCLE_FAST_DURATION 1000 /* Microseconds. */
#define ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC 25 /* Max % of CPU to use. */
#define ACTIVE_EXPIRE_CYCLE_ACCEPTABLE_STALE 10 /* % of stale keys after which
                                                   we do extra efforts. */
void activeExpireCycle(int type) {
    /* Adjust the running parameters according to the configured expire
     * effort. The default effort is 1, and the maximum configurable effort
     * is 10. */
    unsigned long
    effort = server.active_expire_effort-1, /* Rescale from 0 to 9. */
    config_keys_per_loop = ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP +
                           ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP/4*effort,
    config_cycle_fast_duration = ACTIVE_EXPIRE_CYCLE_FAST_DURATION +
                                 ACTIVE_EXPIRE_CYCLE_FAST_DURATION/4*effort,
    config_cycle_slow_time_perc = ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC +
                                  2*effort,
    config_cycle_acceptable_stale = ACTIVE_EXPIRE_CYCLE_ACCEPTABLE_STALE-
                                    effort;

    /* This function has some global state in order to continue the work
     * incrementally across calls. */
    static unsigned int current_db = 0; /* Last DB tested. */
    static int timelimit_exit = 0;      /* Time limit hit in previous call? */
    static long long last_fast_cycle = 0; /* When last fast cycle ran. */

    int j, iteration = 0;
    int dbs_per_call = CRON_DBS_PER_CALL;
    long long start = ustime(), timelimit, elapsed;

    /* When clients are paused the dataset should be static not just from the
     * POV of clients not being able to write, but also from the POV of
     * expires and evictions of keys not being performed. */
    if (clientsArePaused()) return;

    if (type == ACTIVE_EXPIRE_CYCLE_FAST) {
        /* Don't start a fast cycle if the previous cycle did not exit
         * for time limit, unless the percentage of estimated stale keys is
         * too high. Also never repeat a fast cycle for the same period
         * as the fast cycle total duration itself. */
        if (!timelimit_exit &&
            server.stat_expired_stale_perc < config_cycle_acceptable_stale)
            return;

        if (start < last_fast_cycle + (long long)config_cycle_fast_duration*2)
            return;

        last_fast_cycle = start;
    }

    /* We usually should test CRON_DBS_PER_CALL per iteration, with
     * two exceptions:
     *
     * 1) Don't test more DBs than we have.
     * 2) If last time we hit the time limit, we want to scan all DBs
     * in this iteration, as there is work to do in some DB and we don't want
     * expired keys to use memory for too much time. */
    if (dbs_per_call > server.dbnum || timelimit_exit)
        dbs_per_call = server.dbnum;

    /* We can use at max 'config_cycle_slow_time_perc' percentage of CPU
     * time per iteration. Since this function gets called with a frequency of
     * server.hz times per second, the following is the max amount of
     * microseconds we can spend in this function. */
    timelimit = config_cycle_slow_time_perc*1000000/server.hz/100;
    timelimit_exit = 0;
    if (timelimit <= 0) timelimit = 1;

    if (type == ACTIVE_EXPIRE_CYCLE_FAST)
        timelimit = config_cycle_fast_duration; /* in microseconds. */

    /* Accumulate some global stats as we expire keys, to have some idea
     * about the number of keys that are already logically expired, but still
     * existing inside the database. */
    long total_sampled = 0;
    long total_expired = 0;

    for (j = 0; j < dbs_per_call && timelimit_exit == 0; j++) {
        /* Expired and checked in a single loop. */
        unsigned long expired, sampled;

        redisDb *db = server.db+(current_db % server.dbnum);

        /* Increment the DB now so we are sure if we run out of time
         * in the current DB we'll restart from the next. This allows to
         * distribute the time evenly across DBs. */
        current_db++;

        /* Continue to expire if at the end of the cycle more than 25%
         * of the keys were expired. */
        do {
            unsigned long num, slots;
            long long now, ttl_sum;
            int ttl_samples;
            iteration++;

            /* If there is nothing to expire try next DB ASAP. */
            if ((num = dictSize(db->expires)) == 0) {
                db->avg_ttl = 0;
                break;
            }
            slots = dictSlots(db->expires);
            now = mstime();

            /* When there are less than 1% filled slots, sampling the key
             * space is expensive, so stop here waiting for better times...
             * The dictionary will be resized asap. */
            if (num && slots > DICT_HT_INITIAL_SIZE &&
                (num*100/slots < 1)) break;

            /* The main collection cycle. Sample random keys among keys
             * with an expire set, checking for expired ones. */
            expired = 0;
            sampled = 0;
            ttl_sum = 0;
            ttl_samples = 0;

            if (num > config_keys_per_loop)
                num = config_keys_per_loop;

            /* Here we access the low level representation of the hash table
             * for speed concerns: this makes this code coupled with dict.c,
             * but it hardly changed in ten years.
             *
             * Note that certain places of the hash table may be empty,
             * so we want also a stop condition about the number of
             * buckets that we scanned. However scanning for free buckets
             * is very fast: we are in the cache line scanning a sequential
             * array of NULL pointers, so we can scan a lot more buckets
             * than keys in the same time. */
            long max_buckets = num*20;
            long checked_buckets = 0;

            while (sampled < num && checked_buckets < max_buckets) {
                for (int table = 0; table < 2; table++) {
                    if (table == 1 && !dictIsRehashing(db->expires)) break;

                    unsigned long idx = db->expires_cursor;
                    idx &= db->expires->ht[table].sizemask;
                    dictEntry *de = db->expires->ht[table].table[idx];
                    long long ttl;

                    /* Scan the current bucket of the current table. */
                    checked_buckets++;
                    while(de) {
                        /* Get the next entry now since this entry may get
                         * deleted. */
                        dictEntry *e = de;
                        de = de->next;

                        ttl = dictGetSignedIntegerVal(e)-now;
                        if (activeExpireCycleTryExpire(db,e,now)) expired++;
                        if (ttl > 0) {
                            /* We want the average TTL of keys yet
                             * not expired. */
                            ttl_sum += ttl;
                            ttl_samples++;
                        }
                        sampled++;
                    }
                }
                db->expires_cursor++;
            }
            total_expired += expired;
            total_sampled += sampled;

            /* Update the average TTL stats for this database. */
            if (ttl_samples) {
                long long avg_ttl = ttl_sum/ttl_samples;

                /* Do a simple running average with a few samples.
                 * We just use the current estimate with a weight of 2%
                 * and the previous estimate with a weight of 98%. */
                if (db->avg_ttl == 0) db->avg_ttl = avg_ttl;
                db->avg_ttl = (db->avg_ttl/50)*49 + (avg_ttl/50);
            }

            /* We can't block forever here even if there are many keys to
             * expire. So after a given amount of milliseconds return to the
             * caller waiting for the other active expire cycle. */
            if ((iteration & 0xf) == 0) { /* check once every 16 iterations. */
                elapsed = ustime()-start;
                if (elapsed > timelimit) {
                    timelimit_exit = 1;
                    server.stat_expired_time_cap_reached_count++;
                    break;
                }
            }
            /* We don't repeat the cycle for the current database if there are
             * an acceptable amount of stale keys (logically expired but yet
             * not reclained). */
        } while ((expired*100/sampled) > config_cycle_acceptable_stale);
    }

    elapsed = ustime()-start;
    server.stat_expire_cycle_time_used += elapsed;
    latencyAddSampleIfNeeded("expire-cycle",elapsed/1000);

    /* Update our estimate of keys existing but yet to be expired.
     * Running average with this sample accounting for 5%. */
    double current_perc;
    if (total_sampled) {
        current_perc = (double)total_expired/total_sampled;
    } else
        current_perc = 0;
    server.stat_expired_stale_perc = (current_perc*0.05)+
                                     (server.stat_expired_stale_perc*0.95);
}
-

执行定期清除分成两种类型，快和慢，分别由beforeSleep和databasesCron调用，快版有两个限制，一个是执行时长由ACTIVE_EXPIRE_CYCLE_FAST_DURATION限制，另一个是执行间隔是 2 倍的ACTIVE_EXPIRE_CYCLE_FAST_DURATION，另外这还可以由配置的server.active_expire_effort参数来控制，默认是 1，最大是 10

-
onfig_cycle_fast_duration = ACTIVE_EXPIRE_CYCLE_FAST_DURATION +
                                 ACTIVE_EXPIRE_CYCLE_FAST_DURATION/4*effort
-

然后会从一定数量的 db 中找出一定数量的带过期时间的 key（保存在 expires中），这里的数量是由

-
config_keys_per_loop = ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP +
                           ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP/4*effort
```                                 
控制，慢速的执行时长是
```C
config_cycle_slow_time_perc = ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC +
                                  2*effort
timelimit = config_cycle_slow_time_perc*1000000/server.hz/100;
-

这里还有一个额外的退出条件，如果当前数据库的抽样结果已经达到我们所允许的过期 key 百分比，则下次不再处理当前 db，继续处理下个 db

]]> Redis @@ -3824,6 +3797,33 @@ Evict + + redis系列介绍七-过期策略 + /2020/04/12/redis%E7%B3%BB%E5%88%97%E4%BB%8B%E7%BB%8D%E4%B8%83/ + 这一篇不再是数据结构介绍了，大致的数据结构基本都介绍了，这一篇主要是查漏补缺，或者说讲一些重要且基本的概念，也可能是经常被忽略的，很多讲 redis 的系列文章可能都会忽略，学习 redis 的时候也会，因为觉得源码学习就是讲主要的数据结构和“算法”学习了就好了。
redis 的主要应用就是拿来作为高性能的缓存，那么缓存一般有些啥需要注意的，首先是访问速度，如果取得跟数据库一样快，那就没什么存在的意义，第二个是缓存的字面意思，我只是为了让数据读取快一些，通常大部分的场景这个是需要更新过期的，这里就把我要讲的第一点引出来了（真累，

+

redis过期策略

redis 是如何过期缓存的，可以猜测下，最无脑的就是每个设置了过期时间的 key 都设个定时器，过期了就删除，这种显然消耗太大，清理地最及时，还有的就是 redis 正在采用的懒汉清理策略和定期清理
懒汉策略就是在使用的时候去检查缓存是否过期，比如 get 操作时，先判断下这个 key 是否已经过期了，如果过期了就删掉，并且返回空，如果没过期则正常返回
主要代码是

+
/* This function is called when we are going to perform some operation
 * in a given key, but such key may be already logically expired even if
 * it still exists in the database. The main way this function is called
 * is via lookupKey*() family of functions.
 *
 * The behavior of the function depends on the replication role of the
 * instance, because slave instances do not expire keys, they wait
 * for DELs from the master for consistency matters. However even
 * slaves will try to have a coherent return value for the function,
 * so that read commands executed in the slave side will be able to
 * behave like if the key is expired even if still present (because the
 * master has yet to propagate the DEL).
 *
 * In masters as a side effect of finding a key which is expired, such
 * key will be evicted from the database. Also this may trigger the
 * propagation of a DEL/UNLINK command in AOF / replication stream.
 *
 * The return value of the function is 0 if the key is still valid,
 * otherwise the function returns 1 if the key is expired. */
int expireIfNeeded(redisDb *db, robj *key) {
    if (!keyIsExpired(db,key)) return 0;

    /* If we are running in the context of a slave, instead of
     * evicting the expired key from the database, we return ASAP:
     * the slave key expiration is controlled by the master that will
     * send us synthesized DEL operations for expired keys.
     *
     * Still we try to return the right information to the caller,
     * that is, 0 if we think the key should be still valid, 1 if
     * we think the key is expired at this time. */
    if (server.masterhost != NULL) return 1;

    /* Delete the key */
    server.stat_expiredkeys++;
    propagateExpire(db,key,server.lazyfree_lazy_expire);
    notifyKeyspaceEvent(NOTIFY_EXPIRED,
        "expired",key,db->id);
    return server.lazyfree_lazy_expire ? dbAsyncDelete(db,key) :
                                         dbSyncDelete(db,key);
}

/* Check if the key is expired. */
int keyIsExpired(redisDb *db, robj *key) {
    mstime_t when = getExpire(db,key);
    mstime_t now;

    if (when < 0) return 0; /* No expire for this key */

    /* Don't expire anything while loading. It will be done later. */
    if (server.loading) return 0;

    /* If we are in the context of a Lua script, we pretend that time is
     * blocked to when the Lua script started. This way a key can expire
     * only the first time it is accessed and not in the middle of the
     * script execution, making propagation to slaves / AOF consistent.
     * See issue #1525 on Github for more information. */
    if (server.lua_caller) {
        now = server.lua_time_start;
    }
    /* If we are in the middle of a command execution, we still want to use
     * a reference time that does not change: in that case we just use the
     * cached time, that we update before each call in the call() function.
     * This way we avoid that commands such as RPOPLPUSH or similar, that
     * may re-open the same key multiple times, can invalidate an already
     * open object in a next call, if the next call will see the key expired,
     * while the first did not. */
    else if (server.fixed_time_expire > 0) {
        now = server.mstime;
    }
    /* For the other cases, we want to use the most fresh time we have. */
    else {
        now = mstime();
    }

    /* The key expired if the current (virtual or real) time is greater
     * than the expire time of the key. */
    return now > when;
}
/* Return the expire time of the specified key, or -1 if no expire
 * is associated with this key (i.e. the key is non volatile) */
long long getExpire(redisDb *db, robj *key) {
    dictEntry *de;

    /* No expire? return ASAP */
    if (dictSize(db->expires) == 0 ||
       (de = dictFind(db->expires,key->ptr)) == NULL) return -1;

    /* The entry was found in the expire dict, this means it should also
     * be present in the main dict (safety check). */
    serverAssertWithInfo(NULL,key,dictFind(db->dict,key->ptr) != NULL);
    return dictGetSignedIntegerVal(de);
}
+

这里有几点要注意的，第一是当惰性删除时会根据lazyfree_lazy_expire这个参数去判断是执行同步删除还是异步删除，另外一点是对于 slave，是不需要执行的，因为会在 master 过期时向 slave 发送 del 指令。
光采用这个策略会有什么问题呢，假如一些key 一直未被访问，那这些 key 就不会过期了，导致一直被占用着内存，所以 redis 采取了懒汉式过期加定期过期策略，定期策略是怎么执行的呢

+
/* This function handles 'background' operations we are required to do
 * incrementally in Redis databases, such as active key expiring, resizing,
 * rehashing. */
void databasesCron(void) {
    /* Expire keys by random sampling. Not required for slaves
     * as master will synthesize DELs for us. */
    if (server.active_expire_enabled) {
        if (server.masterhost == NULL) {
            activeExpireCycle(ACTIVE_EXPIRE_CYCLE_SLOW);
        } else {
            expireSlaveKeys();
        }
    }

    /* Defrag keys gradually. */
    activeDefragCycle();

    /* Perform hash tables rehashing if needed, but only if there are no
     * other processes saving the DB on disk. Otherwise rehashing is bad
     * as will cause a lot of copy-on-write of memory pages. */
    if (!hasActiveChildProcess()) {
        /* We use global counters so if we stop the computation at a given
         * DB we'll be able to start from the successive in the next
         * cron loop iteration. */
        static unsigned int resize_db = 0;
        static unsigned int rehash_db = 0;
        int dbs_per_call = CRON_DBS_PER_CALL;
        int j;

        /* Don't test more DBs than we have. */
        if (dbs_per_call > server.dbnum) dbs_per_call = server.dbnum;

        /* Resize */
        for (j = 0; j < dbs_per_call; j++) {
            tryResizeHashTables(resize_db % server.dbnum);
            resize_db++;
        }

        /* Rehash */
        if (server.activerehashing) {
            for (j = 0; j < dbs_per_call; j++) {
                int work_done = incrementallyRehash(rehash_db);
                if (work_done) {
                    /* If the function did some work, stop here, we'll do
                     * more at the next cron loop. */
                    break;
                } else {
                    /* If this db didn't need rehash, we'll try the next one. */
                    rehash_db++;
                    rehash_db %= server.dbnum;
                }
            }
        }
    }
}
/* Try to expire a few timed out keys. The algorithm used is adaptive and
 * will use few CPU cycles if there are few expiring keys, otherwise
 * it will get more aggressive to avoid that too much memory is used by
 * keys that can be removed from the keyspace.
 *
 * Every expire cycle tests multiple databases: the next call will start
 * again from the next db, with the exception of exists for time limit: in that
 * case we restart again from the last database we were processing. Anyway
 * no more than CRON_DBS_PER_CALL databases are tested at every iteration.
 *
 * The function can perform more or less work, depending on the "type"
 * argument. It can execute a "fast cycle" or a "slow cycle". The slow
 * cycle is the main way we collect expired cycles: this happens with
 * the "server.hz" frequency (usually 10 hertz).
 *
 * However the slow cycle can exit for timeout, since it used too much time.
 * For this reason the function is also invoked to perform a fast cycle
 * at every event loop cycle, in the beforeSleep() function. The fast cycle
 * will try to perform less work, but will do it much more often.
 *
 * The following are the details of the two expire cycles and their stop
 * conditions:
 *
 * If type is ACTIVE_EXPIRE_CYCLE_FAST the function will try to run a
 * "fast" expire cycle that takes no longer than EXPIRE_FAST_CYCLE_DURATION
 * microseconds, and is not repeated again before the same amount of time.
 * The cycle will also refuse to run at all if the latest slow cycle did not
 * terminate because of a time limit condition.
 *
 * If type is ACTIVE_EXPIRE_CYCLE_SLOW, that normal expire cycle is
 * executed, where the time limit is a percentage of the REDIS_HZ period
 * as specified by the ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC define. In the
 * fast cycle, the check of every database is interrupted once the number
 * of already expired keys in the database is estimated to be lower than
 * a given percentage, in order to avoid doing too much work to gain too
 * little memory.
 *
 * The configured expire "effort" will modify the baseline parameters in
 * order to do more work in both the fast and slow expire cycles.
 */

#define ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP 20 /* Keys for each DB loop. */
#define ACTIVE_EXPIRE_CYCLE_FAST_DURATION 1000 /* Microseconds. */
#define ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC 25 /* Max % of CPU to use. */
#define ACTIVE_EXPIRE_CYCLE_ACCEPTABLE_STALE 10 /* % of stale keys after which
                                                   we do extra efforts. */
void activeExpireCycle(int type) {
    /* Adjust the running parameters according to the configured expire
     * effort. The default effort is 1, and the maximum configurable effort
     * is 10. */
    unsigned long
    effort = server.active_expire_effort-1, /* Rescale from 0 to 9. */
    config_keys_per_loop = ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP +
                           ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP/4*effort,
    config_cycle_fast_duration = ACTIVE_EXPIRE_CYCLE_FAST_DURATION +
                                 ACTIVE_EXPIRE_CYCLE_FAST_DURATION/4*effort,
    config_cycle_slow_time_perc = ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC +
                                  2*effort,
    config_cycle_acceptable_stale = ACTIVE_EXPIRE_CYCLE_ACCEPTABLE_STALE-
                                    effort;

    /* This function has some global state in order to continue the work
     * incrementally across calls. */
    static unsigned int current_db = 0; /* Last DB tested. */
    static int timelimit_exit = 0;      /* Time limit hit in previous call? */
    static long long last_fast_cycle = 0; /* When last fast cycle ran. */

    int j, iteration = 0;
    int dbs_per_call = CRON_DBS_PER_CALL;
    long long start = ustime(), timelimit, elapsed;

    /* When clients are paused the dataset should be static not just from the
     * POV of clients not being able to write, but also from the POV of
     * expires and evictions of keys not being performed. */
    if (clientsArePaused()) return;

    if (type == ACTIVE_EXPIRE_CYCLE_FAST) {
        /* Don't start a fast cycle if the previous cycle did not exit
         * for time limit, unless the percentage of estimated stale keys is
         * too high. Also never repeat a fast cycle for the same period
         * as the fast cycle total duration itself. */
        if (!timelimit_exit &&
            server.stat_expired_stale_perc < config_cycle_acceptable_stale)
            return;

        if (start < last_fast_cycle + (long long)config_cycle_fast_duration*2)
            return;

        last_fast_cycle = start;
    }

    /* We usually should test CRON_DBS_PER_CALL per iteration, with
     * two exceptions:
     *
     * 1) Don't test more DBs than we have.
     * 2) If last time we hit the time limit, we want to scan all DBs
     * in this iteration, as there is work to do in some DB and we don't want
     * expired keys to use memory for too much time. */
    if (dbs_per_call > server.dbnum || timelimit_exit)
        dbs_per_call = server.dbnum;

    /* We can use at max 'config_cycle_slow_time_perc' percentage of CPU
     * time per iteration. Since this function gets called with a frequency of
     * server.hz times per second, the following is the max amount of
     * microseconds we can spend in this function. */
    timelimit = config_cycle_slow_time_perc*1000000/server.hz/100;
    timelimit_exit = 0;
    if (timelimit <= 0) timelimit = 1;

    if (type == ACTIVE_EXPIRE_CYCLE_FAST)
        timelimit = config_cycle_fast_duration; /* in microseconds. */

    /* Accumulate some global stats as we expire keys, to have some idea
     * about the number of keys that are already logically expired, but still
     * existing inside the database. */
    long total_sampled = 0;
    long total_expired = 0;

    for (j = 0; j < dbs_per_call && timelimit_exit == 0; j++) {
        /* Expired and checked in a single loop. */
        unsigned long expired, sampled;

        redisDb *db = server.db+(current_db % server.dbnum);

        /* Increment the DB now so we are sure if we run out of time
         * in the current DB we'll restart from the next. This allows to
         * distribute the time evenly across DBs. */
        current_db++;

        /* Continue to expire if at the end of the cycle more than 25%
         * of the keys were expired. */
        do {
            unsigned long num, slots;
            long long now, ttl_sum;
            int ttl_samples;
            iteration++;

            /* If there is nothing to expire try next DB ASAP. */
            if ((num = dictSize(db->expires)) == 0) {
                db->avg_ttl = 0;
                break;
            }
            slots = dictSlots(db->expires);
            now = mstime();

            /* When there are less than 1% filled slots, sampling the key
             * space is expensive, so stop here waiting for better times...
             * The dictionary will be resized asap. */
            if (num && slots > DICT_HT_INITIAL_SIZE &&
                (num*100/slots < 1)) break;

            /* The main collection cycle. Sample random keys among keys
             * with an expire set, checking for expired ones. */
            expired = 0;
            sampled = 0;
            ttl_sum = 0;
            ttl_samples = 0;

            if (num > config_keys_per_loop)
                num = config_keys_per_loop;

            /* Here we access the low level representation of the hash table
             * for speed concerns: this makes this code coupled with dict.c,
             * but it hardly changed in ten years.
             *
             * Note that certain places of the hash table may be empty,
             * so we want also a stop condition about the number of
             * buckets that we scanned. However scanning for free buckets
             * is very fast: we are in the cache line scanning a sequential
             * array of NULL pointers, so we can scan a lot more buckets
             * than keys in the same time. */
            long max_buckets = num*20;
            long checked_buckets = 0;

            while (sampled < num && checked_buckets < max_buckets) {
                for (int table = 0; table < 2; table++) {
                    if (table == 1 && !dictIsRehashing(db->expires)) break;

                    unsigned long idx = db->expires_cursor;
                    idx &= db->expires->ht[table].sizemask;
                    dictEntry *de = db->expires->ht[table].table[idx];
                    long long ttl;

                    /* Scan the current bucket of the current table. */
                    checked_buckets++;
                    while(de) {
                        /* Get the next entry now since this entry may get
                         * deleted. */
                        dictEntry *e = de;
                        de = de->next;

                        ttl = dictGetSignedIntegerVal(e)-now;
                        if (activeExpireCycleTryExpire(db,e,now)) expired++;
                        if (ttl > 0) {
                            /* We want the average TTL of keys yet
                             * not expired. */
                            ttl_sum += ttl;
                            ttl_samples++;
                        }
                        sampled++;
                    }
                }
                db->expires_cursor++;
            }
            total_expired += expired;
            total_sampled += sampled;

            /* Update the average TTL stats for this database. */
            if (ttl_samples) {
                long long avg_ttl = ttl_sum/ttl_samples;

                /* Do a simple running average with a few samples.
                 * We just use the current estimate with a weight of 2%
                 * and the previous estimate with a weight of 98%. */
                if (db->avg_ttl == 0) db->avg_ttl = avg_ttl;
                db->avg_ttl = (db->avg_ttl/50)*49 + (avg_ttl/50);
            }

            /* We can't block forever here even if there are many keys to
             * expire. So after a given amount of milliseconds return to the
             * caller waiting for the other active expire cycle. */
            if ((iteration & 0xf) == 0) { /* check once every 16 iterations. */
                elapsed = ustime()-start;
                if (elapsed > timelimit) {
                    timelimit_exit = 1;
                    server.stat_expired_time_cap_reached_count++;
                    break;
                }
            }
            /* We don't repeat the cycle for the current database if there are
             * an acceptable amount of stale keys (logically expired but yet
             * not reclained). */
        } while ((expired*100/sampled) > config_cycle_acceptable_stale);
    }

    elapsed = ustime()-start;
    server.stat_expire_cycle_time_used += elapsed;
    latencyAddSampleIfNeeded("expire-cycle",elapsed/1000);

    /* Update our estimate of keys existing but yet to be expired.
     * Running average with this sample accounting for 5%. */
    double current_perc;
    if (total_sampled) {
        current_perc = (double)total_expired/total_sampled;
    } else
        current_perc = 0;
    server.stat_expired_stale_perc = (current_perc*0.05)+
                                     (server.stat_expired_stale_perc*0.95);
}
+

执行定期清除分成两种类型，快和慢，分别由beforeSleep和databasesCron调用，快版有两个限制，一个是执行时长由ACTIVE_EXPIRE_CYCLE_FAST_DURATION限制，另一个是执行间隔是 2 倍的ACTIVE_EXPIRE_CYCLE_FAST_DURATION，另外这还可以由配置的server.active_expire_effort参数来控制，默认是 1，最大是 10

+
onfig_cycle_fast_duration = ACTIVE_EXPIRE_CYCLE_FAST_DURATION +
                                 ACTIVE_EXPIRE_CYCLE_FAST_DURATION/4*effort
+

然后会从一定数量的 db 中找出一定数量的带过期时间的 key（保存在 expires中），这里的数量是由

+
config_keys_per_loop = ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP +
                           ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP/4*effort
```                                 
控制，慢速的执行时长是
```C
config_cycle_slow_time_perc = ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC +
                                  2*effort
timelimit = config_cycle_slow_time_perc*1000000/server.hz/100;
+

这里还有一个额外的退出条件，如果当前数据库的抽样结果已经达到我们所允许的过期 key 百分比，则下次不再处理当前 db，继续处理下个 db

+]]> + + Redis + 数据结构 + C + 源码 + Redis + + + redis + 数据结构 + 源码 + + redis系列介绍八-淘汰策略 /2020/04/18/redis%E7%B3%BB%E5%88%97%E4%BB%8B%E7%BB%8D%E5%85%AB/ @@ -3928,36 +3928,6 @@ 切片 - - rust学习笔记-所有权一 - /2021/04/18/rust%E5%AD%A6%E4%B9%A0%E7%AC%94%E8%AE%B0/ - 最近在看 《rust 权威指南》，还是难度比较大的，它里面的一些概念跟之前的用过的都有比较大的差别
比起有 gc 的虚拟机语言，跟像 C 和 C++这种主动释放内存的，rust 有他的独特点，主要是有三条

-
    -
  • Rust中的每一个值都有一个对应的变量作为它的所有者。
    • -
  • 在同一时间内，值有且只有一个所有者。
    • -
  • 当所有者离开自己的作用域时，它持有的值就会被释放掉。

    这里有两个重点：
    • -
  • s 在进入作用域后才变得有效
    • -
  • 它会保持自己的有效性直到自己离开作用域为止
    • -
-

然后看个案例

-
let x = 5;
let y = x;
-

这个其实有两种，一般可以认为比较多实现的会使用 copy on write 之类的，先让两个都指向同一个快 5 的存储，在发生变更后开始正式拷贝，但是涉及到内存处理的便利性，对于这类简单类型，可以直接拷贝
但是对于非基础类型

-
let s1 = String::from("hello");
let s2 = s1;

println!("{}, world!", s1);
-

有可能认为有两种内存分布可能
先看下 string 的内存结构

第一种可能是

第二种是

我们来尝试编译下

发现有这个错误，其实在 rust 中let y = x这个行为的实质是移动，在赋值给 y 之后 x 就无效了

这样子就不会造成脱离作用域时，对同一块内存区域的二次释放，如果需要复制，可以使用 clone 方法

-
let s1 = String::from("hello");
let s2 = s1.clone();

println!("s1 = {}, s2 = {}", s1, s2);
-

这里其实会有点疑惑，为什么前面的x, y 的行为跟 s1, s2 的不一样，其实主要是基本类型和 string 这类的不定大小的类型的内存分配方式不同，x, y这类整型可以直接确定大小，可以直接在栈上分配，而像 string 和其他的变体结构体，其大小都是不能在编译时确定，所以需要在堆上进行分配

-]]> - - 语言 - Rust - - - Rust - 所有权 - 内存分布 - 新语言 - - rust学习笔记-所有权二 /2021/04/18/rust%E5%AD%A6%E4%B9%A0%E7%AC%94%E8%AE%B0-%E6%89%80%E6%9C%89%E6%9D%83%E4%BA%8C/ @@ -4001,6 +3971,36 @@ 不可变引用 + + rust学习笔记-所有权一 + /2021/04/18/rust%E5%AD%A6%E4%B9%A0%E7%AC%94%E8%AE%B0/ + 最近在看 《rust 权威指南》，还是难度比较大的，它里面的一些概念跟之前的用过的都有比较大的差别
比起有 gc 的虚拟机语言，跟像 C 和 C++这种主动释放内存的，rust 有他的独特点，主要是有三条

+
    +
  • Rust中的每一个值都有一个对应的变量作为它的所有者。
    • +
  • 在同一时间内，值有且只有一个所有者。
    • +
  • 当所有者离开自己的作用域时，它持有的值就会被释放掉。

    这里有两个重点：
    • +
  • s 在进入作用域后才变得有效
    • +
  • 它会保持自己的有效性直到自己离开作用域为止
    • +
+

然后看个案例

+
let x = 5;
let y = x;
+

这个其实有两种，一般可以认为比较多实现的会使用 copy on write 之类的，先让两个都指向同一个快 5 的存储，在发生变更后开始正式拷贝，但是涉及到内存处理的便利性，对于这类简单类型，可以直接拷贝
但是对于非基础类型

+
let s1 = String::from("hello");
let s2 = s1;

println!("{}, world!", s1);
+

有可能认为有两种内存分布可能
先看下 string 的内存结构

第一种可能是

第二种是

我们来尝试编译下

发现有这个错误，其实在 rust 中let y = x这个行为的实质是移动，在赋值给 y 之后 x 就无效了

这样子就不会造成脱离作用域时，对同一块内存区域的二次释放，如果需要复制，可以使用 clone 方法

+
let s1 = String::from("hello");
let s2 = s1.clone();

println!("s1 = {}, s2 = {}", s1, s2);
+

这里其实会有点疑惑，为什么前面的x, y 的行为跟 s1, s2 的不一样，其实主要是基本类型和 string 这类的不定大小的类型的内存分配方式不同，x, y这类整型可以直接确定大小，可以直接在栈上分配，而像 string 和其他的变体结构体，其大小都是不能在编译时确定，所以需要在堆上进行分配

+]]> + + 语言 + Rust + + + Rust + 所有权 + 内存分布 + 新语言 + + spark-little-tips /2017/03/28/spark-little-tips/ @@ -4018,6 +4018,24 @@ python + + spring boot中的 http 接口返回 json 形式的小注意点 + /2023/06/25/spring-boot%E4%B8%AD%E7%9A%84-http-%E6%8E%A5%E5%8F%A3%E8%BF%94%E5%9B%9E-json-%E5%BD%A2%E5%BC%8F%E7%9A%84%E5%B0%8F%E6%B3%A8%E6%84%8F%E7%82%B9/ + 这个可能是个很简单的点，不过之前碰到了就记录下，我们常规的应用都是使用统一的请求响应转换器去处理请求和响应返回，但是对于有文件上传或者返回的是文件的情况，一般都是不使用统一的处理，但是在响应返回的时候可能会存在这样的情况，如果文件正常被处理那就返回文件，如果处理异常需要给前端返回 json类型的响应，里面能够取到响应码错误描述等

+

比如在请求中参数就使用 httpRequest(HttpServletRequest request, HttpServletResponse response)
然后在返回的时候就使用 response.getOutputStream().write(result)，而如果是要返回 json 形式的话就可以像这个文章说明的
链接

+
Employee employee = new Employee(1, "Karan", "IT", 5000);
String employeeJsonString = this.gson.toJson(employee);

PrintWriter out = response.getWriter();
response.setContentType("application/json");
response.setCharacterEncoding("UTF-8");
out.print(employeeJsonString);
out.flush();
+

一开始我也是这么一搜就用了，后来发现返回的一直是乱码，仔细看了下发现了个问题，就是这个 response 设置 contentType 是在getWriter之后的，这样自然就不会起作用了，所以要在设置 setContentType 和 setCharacterEncoding 之后再 getWriter，之后就可以正常返回了。

+]]> + + Java + SpringBoot + + + Java + Spring + SpringBoot + + spring event 介绍 /2022/01/30/spring-event-%E4%BB%8B%E7%BB%8D/ @@ -4051,24 +4069,6 @@ Spring Event - - spring boot中的 http 接口返回 json 形式的小注意点 - /2023/06/25/spring-boot%E4%B8%AD%E7%9A%84-http-%E6%8E%A5%E5%8F%A3%E8%BF%94%E5%9B%9E-json-%E5%BD%A2%E5%BC%8F%E7%9A%84%E5%B0%8F%E6%B3%A8%E6%84%8F%E7%82%B9/ - 这个可能是个很简单的点，不过之前碰到了就记录下，我们常规的应用都是使用统一的请求响应转换器去处理请求和响应返回，但是对于有文件上传或者返回的是文件的情况，一般都是不使用统一的处理，但是在响应返回的时候可能会存在这样的情况，如果文件正常被处理那就返回文件，如果处理异常需要给前端返回 json类型的响应，里面能够取到响应码错误描述等

-

比如在请求中参数就使用 httpRequest(HttpServletRequest request, HttpServletResponse response)
然后在返回的时候就使用 response.getOutputStream().write(result)，而如果是要返回 json 形式的话就可以像这个文章说明的
链接

-
Employee employee = new Employee(1, "Karan", "IT", 5000);
String employeeJsonString = this.gson.toJson(employee);

PrintWriter out = response.getWriter();
response.setContentType("application/json");
response.setCharacterEncoding("UTF-8");
out.print(employeeJsonString);
out.flush();
-

一开始我也是这么一搜就用了，后来发现返回的一直是乱码，仔细看了下发现了个问题，就是这个 response 设置 contentType 是在getWriter之后的，这样自然就不会起作用了，所以要在设置 setContentType 和 setCharacterEncoding 之后再 getWriter，之后就可以正常返回了。

-]]> - - Java - SpringBoot - - - Java - Spring - SpringBoot - - springboot mappings 注册逻辑 /2023/08/13/springboot-mappings-%E6%B3%A8%E5%86%8C%E9%80%BB%E8%BE%91/ @@ -4093,78 +4093,6 @@

最后是真的注册逻辑

public void register(T mapping, Object handler, Method method) {
			// Assert that the handler method is not a suspending one.
			if (KotlinDetector.isKotlinType(method.getDeclaringClass())) {
				Class<?>[] parameterTypes = method.getParameterTypes();
				if ((parameterTypes.length > 0) && "kotlin.coroutines.Continuation".equals(parameterTypes[parameterTypes.length - 1].getName())) {
					throw new IllegalStateException("Unsupported suspending handler method detected: " + method);
				}
			}
			this.readWriteLock.writeLock().lock();
			try {
				HandlerMethod handlerMethod = createHandlerMethod(handler, method);
				validateMethodMapping(handlerMethod, mapping);
				this.mappingLookup.put(mapping, handlerMethod);

				List<String> directUrls = getDirectUrls(mapping);
				for (String url : directUrls) {
					this.urlLookup.add(url, mapping);
				}

				String name = null;
				if (getNamingStrategy() != null) {
					name = getNamingStrategy().getName(handlerMethod, mapping);
					addMappingName(name, handlerMethod);
				}

				CorsConfiguration corsConfig = initCorsConfiguration(handler, method, mapping);
				if (corsConfig != null) {
					this.corsLookup.put(handlerMethod, corsConfig);
				}

				this.registry.put(mapping, new MappingRegistration<>(mapping, handlerMethod, directUrls, name));
			}
			finally {
				this.readWriteLock.writeLock().unlock();
			}
		}

底层的存储就是上一篇说的 mappingLookup 来存储信息

-]]> - - Java - SpringBoot - - - Java - SpringBoot - - - - springboot 处理请求的小分支-跳转 & cookie - /2023/09/03/springboot-%E5%A4%84%E7%90%86%E8%AF%B7%E6%B1%82%E7%9A%84%E5%B0%8F%E5%88%86%E6%94%AF-%E8%B7%B3%E8%BD%AC-cookie/ - 首先是跳转，应该说设置状态，其中跳转是其中一个状态，

-
@RequestMapping(value = "request1", method = RequestMethod.GET)
    public void request1(HttpServletRequest request, HttpServletResponse response) {
        response.setStatus(HttpServletResponse.SC_OK);
    }
-

200 状态就很简单，如果想做跳转可以使用 302 并设置 location

-
@RequestMapping(value = "request2", method = RequestMethod.GET)
public void request2(HttpServletRequest request, HttpServletResponse response) {
    response.setHeader("Location", "https://baidu.com");
    response.setStatus(HttpServletResponse.SC_MOVED_TEMPORARILY);
}
-

这里如果设置了 302，但没设置跳转 location，就是 302 found

-
int SC_MOVED_TEMPORARILY = 302;
int SC_FOUND = 302;
- -

而如果是 301 跳转，代表原地址不可用了，永久跳转

-
@RequestMapping(value = "request3", method = RequestMethod.GET)
    public void request3(HttpServletRequest request, HttpServletResponse response) {
        response.setHeader("Location", "https://baidu.com");
        response.setStatus(HttpServletResponse.SC_MOVED_PERMANENTLY);
    }
-

另一个问题是设置 cookie

@RequestMapping(value = "request4", method = RequestMethod.GET)
    public void request4(HttpServletRequest request, HttpServletResponse response) {
        Cookie cookie = new Cookie("a", "b");
        response.addCookie(cookie);
        response.setStatus(HttpServletResponse.SC_OK);
    }
-

这样的设置就能成功设定 cookie，而随着目前的浏览器 cookie 策略，如果要跳转后设置的话，估计是会越来越难，包括

-
response.addHeader("Set-Cookie", "a=b; domain=baidu.com; SameSite=none;Secure");
-

这样的方式也没法实现。

-]]> - - Java - SpringBoot - - - Java - SpringBoot - - - - springboot 请求响应处理流程 - /2023/08/27/springboot-%E8%AF%B7%E6%B1%82%E5%93%8D%E5%BA%94%E5%A4%84%E7%90%86%E6%B5%81%E7%A8%8B/ - Tomcat 会把请求委托到
org.springframework.web.servlet.DispatcherServlet#doService

-
protected void doService(HttpServletRequest request, HttpServletResponse response) throws Exception {
		logRequest(request);

        // 省略前面的代码
		try {
			doDispatch(request, response);
		}
-

然后就是调用
org.springframework.web.servlet.DispatcherServlet#doDispatch

-
protected void doDispatch(HttpServletRequest request, HttpServletResponse response) throws Exception {

	try {
		ModelAndView mv = null;
		Exception dispatchException = null;

		try {
			processedRequest = checkMultipart(request);
			multipartRequestParsed = (processedRequest != request);

               // 去获取处理器
			// Determine handler for the current request.
			mappedHandler = getHandler(processedRequest);
			if (mappedHandler == null) {
				noHandlerFound(processedRequest, response);
				return;
			}

			// Determine handler adapter for the current request.
			HandlerAdapter ha = getHandlerAdapter(mappedHandler.getHandler());

			// Process last-modified header, if supported by the handler.
			String method = request.getMethod();
			boolean isGet = HttpMethod.GET.matches(method);
			if (isGet || HttpMethod.HEAD.matches(method)) {
				long lastModified = ha.getLastModified(request, mappedHandler.getHandler());
				if (new ServletWebRequest(request, response).checkNotModified(lastModified) && isGet) {
					return;
				}
			}

			if (!mappedHandler.applyPreHandle(processedRequest, response)) {
				return;
			}

			// Actually invoke the handler.
			mv = ha.handle(processedRequest, response, mappedHandler.getHandler());

-

看下这里的逻辑

-
@Nullable
protected HandlerExecutionChain getHandler(HttpServletRequest request) throws Exception {
	if (this.handlerMappings != null) {
		for (HandlerMapping mapping : this.handlerMappings) {
			HandlerExecutionChain handler = mapping.getHandler(request);
			if (handler != null) {
				return handler;
			}
		}
	}
	return null;
}
-

可以看到有这些 HandlerMapping

而这里面就是前面提到过的
org.springframework.web.servlet.mvc.method.annotation.RequestMappingHandlerMapping
从这就能找到具体的 Handler
com.nicksxs.spbdemo.controller.DemoController#test()
这就是我简单的示例代码

-
@RequestMapping(value = "/test", method = RequestMethod.GET)
@ResponseBody
public DemoResponse test() {
    String item = "{\"id\": 1, \"name\": \"nick\"}";
    ParserConfig parserConfig = ParserConfig.getGlobalInstance();
    parserConfig.propertyNamingStrategy = PropertyNamingStrategy.SnakeCase;
    DemoResponse response = JSON.parseObject(item, DemoResponse.class, parserConfig);
    return response;
}
-

下一步是再获取处理器的适配器，
org.springframework.web.servlet.mvc.method.annotation.RequestMappingHandlerAdapter

-
protected HandlerAdapter getHandlerAdapter(Object handler) throws ServletException {
		if (this.handlerAdapters != null) {
			for (HandlerAdapter adapter : this.handlerAdapters) {
				if (adapter.supports(handler)) {
					return adapter;
				}
			}
		}
		throw new ServletException("No adapter for handler [" + handler +
				"]: The DispatcherServlet configuration needs to include a HandlerAdapter that supports this handler");
	}
-

正好这个适配器是调用的父类的 supports 方法

-
@Override
public final boolean supports(Object handler) {
	return (handler instanceof HandlerMethod && supportsInternal((HandlerMethod) handler));
}
-

而我这个com.nicksxs.spbdemo.controller.DemoController#test()
就是个包装好的 HandlerMethod
然后就是调用 ha 的 handle 方法，也是通过模板方法，实际调用的是
org.springframework.web.servlet.mvc.method.AbstractHandlerMethodAdapter#handle

-
@Override
@Nullable
public final ModelAndView handle(HttpServletRequest request, HttpServletResponse response, Object handler)
		throws Exception {

	return handleInternal(request, response, (HandlerMethod) handler);
}
-

然后调用
org.springframework.web.servlet.mvc.method.annotation.RequestMappingHandlerAdapter#handleInternal

-
@Override
	protected ModelAndView handleInternal(HttpServletRequest request,
			HttpServletResponse response, HandlerMethod handlerMethod) throws Exception {

		ModelAndView mav;
		checkRequest(request);

		// Execute invokeHandlerMethod in synchronized block if required.
		if (this.synchronizeOnSession) {
			HttpSession session = request.getSession(false);
			if (session != null) {
				Object mutex = WebUtils.getSessionMutex(session);
				synchronized (mutex) {
					mav = invokeHandlerMethod(request, response, handlerMethod);
				}
			}
			else {
				// No HttpSession available -> no mutex necessary
				mav = invokeHandlerMethod(request, response, handlerMethod);
			}
		}
		else {
            // 是否要锁定 session，否则走到这
			// No synchronization on session demanded at all...
			mav = invokeHandlerMethod(request, response, handlerMethod);
		}
- -

继续调用
org.springframework.web.servlet.mvc.method.annotation.RequestMappingHandlerAdapter#invokeHandlerMethod

-
@Nullable
	protected ModelAndView invokeHandlerMethod(HttpServletRequest request,
			HttpServletResponse response, HandlerMethod handlerMethod) throws Exception {

		ServletWebRequest webRequest = new ServletWebRequest(request, response);
		try {
			WebDataBinderFactory binderFactory = getDataBinderFactory(handlerMethod);
			ModelFactory modelFactory = getModelFactory(handlerMethod, binderFactory);

            // 包装调用方法，
			ServletInvocableHandlerMethod invocableMethod = createInvocableHandlerMethod(handlerMethod);
			// 省略一部分非本次关注核心代码
            // 然后是调用到这
			invocableMethod.invokeAndHandle(webRequest, mavContainer);
			if (asyncManager.isConcurrentHandlingStarted()) {
				return null;
			}

			return getModelAndView(mavContainer, modelFactory, webRequest);
		}
		finally {
			webRequest.requestCompleted();
		}
	}
-

稍微再看一眼
第一步是
org.springframework.web.servlet.mvc.method.annotation.RequestMappingHandlerAdapter#createInvocableHandlerMethod

-
protected ServletInvocableHandlerMethod createInvocableHandlerMethod(HandlerMethod handlerMethod) {
	return new ServletInvocableHandlerMethod(handlerMethod);
}
-

第二步是
org.springframework.web.servlet.mvc.method.annotation.ServletInvocableHandlerMethod#ServletInvocableHandlerMethod(org.springframework.web.method.HandlerMethod)

-
   public ServletInvocableHandlerMethod(HandlerMethod handlerMethod) {
	super(handlerMethod);
}
-

第三步是
org.springframework.web.method.support.InvocableHandlerMethod#InvocableHandlerMethod(org.springframework.web.method.HandlerMethod)

-
   public InvocableHandlerMethod(HandlerMethod handlerMethod) {
	super(handlerMethod);
}
-

第四步是
org.springframework.web.method.HandlerMethod#HandlerMethod(org.springframework.web.method.HandlerMethod)

-
protected HandlerMethod(HandlerMethod handlerMethod) {
	Assert.notNull(handlerMethod, "HandlerMethod is required");
	this.bean = handlerMethod.bean;
	this.beanFactory = handlerMethod.beanFactory;
	this.beanType = handlerMethod.beanType;
	this.method = handlerMethod.method;
	this.bridgedMethod = handlerMethod.bridgedMethod;
	this.parameters = handlerMethod.parameters;
	this.responseStatus = handlerMethod.responseStatus;
	this.responseStatusReason = handlerMethod.responseStatusReason;
	this.description = handlerMethod.description;
	this.resolvedFromHandlerMethod = handlerMethod.resolvedFromHandlerMethod;
}
-

这是个继承关系，一直调用到最顶层的父类的构造方法，其实就是拷贝，然后继续调用
org.springframework.web.servlet.mvc.method.annotation.ServletInvocableHandlerMethod#invokeAndHandle

-
public void invokeAndHandle(ServletWebRequest webRequest, ModelAndViewContainer mavContainer,
			Object... providedArgs) throws Exception {

        // 调用请求
		Object returnValue = invokeForRequest(webRequest, mavContainer, providedArgs);
		// 稍微忽略下后面的代码
	}
-

继续调用
org.springframework.web.method.support.InvocableHandlerMethod#invokeForRequest

-
@Nullable
public Object invokeForRequest(NativeWebRequest request, @Nullable ModelAndViewContainer mavContainer,
		Object... providedArgs) throws Exception {

	Object[] args = getMethodArgumentValues(request, mavContainer, providedArgs);
	if (logger.isTraceEnabled()) {
		logger.trace("Arguments: " + Arrays.toString(args));
	}
	return doInvoke(args);
}
-

来到了最核心处
org.springframework.web.method.support.InvocableHandlerMethod#doInvoke

-
@Nullable
protected Object doInvoke(Object... args) throws Exception {
	Method method = getBridgedMethod();
	ReflectionUtils.makeAccessible(method);
	try {
		if (KotlinDetector.isSuspendingFunction(method)) {
			return CoroutinesUtils.invokeSuspendingFunction(method, getBean(), args);
		}
           // 会走到这里，获取到 bean，而这个 bean 就是前面构造方法里赋值的，最开始被放在 handler 里面，然后调用方法
		return method.invoke(getBean(), args);
	}
]]> Java @@ -4198,6 +4126,32 @@

再调用里面的初始化方法，
org.springframework.boot.web.embedded.tomcat.TomcatWebServer#initialize

private void initialize() throws WebServerException {
		logger.info("Tomcat initialized with port(s): " + getPortsDescription(false));
		synchronized (this.monitor) {
			try {
				addInstanceIdToEngineName();

				Context context = findContext();
				context.addLifecycleListener((event) -> {
					if (context.equals(event.getSource()) && Lifecycle.START_EVENT.equals(event.getType())) {
						// Remove service connectors so that protocol binding doesn't
						// happen when the service is started.
						removeServiceConnectors();
					}
				});

				// Start the server to trigger initialization listeners
				this.tomcat.start();

				// We can re-throw failure exception directly in the main thread
				rethrowDeferredStartupExceptions();

				try {
					ContextBindings.bindClassLoader(context, context.getNamingToken(), getClass().getClassLoader());
				}
				catch (NamingException ex) {
					// Naming is not enabled. Continue
				}

				// Unlike Jetty, all Tomcat threads are daemon threads. We create a
				// blocking non-daemon to stop immediate shutdown
				startDaemonAwaitThread();
			}
			catch (Exception ex) {
				stopSilently();
				destroySilently();
				throw new WebServerException("Unable to start embedded Tomcat", ex);
			}
		}
	}
```  
这里就是继续调用 `org.apache.catalina.startup.Tomcat#start`
```java
    public void start() throws LifecycleException {
        this.getServer();
        this.server.start();
    }
```      
获取server, `org.apache.catalina.startup.Tomcat#getServer`
```java
public Server getServer() {
        if (this.server != null) {
            return this.server;
        } else {
            System.setProperty("catalina.useNaming", "false");
            this.server = new StandardServer();
            this.initBaseDir();
            ConfigFileLoader.setSource(new CatalinaBaseConfigurationSource(new File(this.basedir), (String)null));
            this.server.setPort(-1);
            Service service = new StandardService();
            service.setName("Tomcat");
            this.server.addService(service);
            return this.server;
        }
    }

然后就是启动 server，后面可以继续看这个启动 TomcatServer 内部的逻辑

+]]> + + Java + SpringBoot + + + Java + SpringBoot + + + + springboot 处理请求的小分支-跳转 & cookie + /2023/09/03/springboot-%E5%A4%84%E7%90%86%E8%AF%B7%E6%B1%82%E7%9A%84%E5%B0%8F%E5%88%86%E6%94%AF-%E8%B7%B3%E8%BD%AC-cookie/ + 首先是跳转，应该说设置状态，其中跳转是其中一个状态，

+
@RequestMapping(value = "request1", method = RequestMethod.GET)
    public void request1(HttpServletRequest request, HttpServletResponse response) {
        response.setStatus(HttpServletResponse.SC_OK);
    }
+

200 状态就很简单，如果想做跳转可以使用 302 并设置 location

+
@RequestMapping(value = "request2", method = RequestMethod.GET)
public void request2(HttpServletRequest request, HttpServletResponse response) {
    response.setHeader("Location", "https://baidu.com");
    response.setStatus(HttpServletResponse.SC_MOVED_TEMPORARILY);
}
+

这里如果设置了 302，但没设置跳转 location，就是 302 found

+
int SC_MOVED_TEMPORARILY = 302;
int SC_FOUND = 302;
+ +

而如果是 301 跳转，代表原地址不可用了，永久跳转

+
@RequestMapping(value = "request3", method = RequestMethod.GET)
    public void request3(HttpServletRequest request, HttpServletResponse response) {
        response.setHeader("Location", "https://baidu.com");
        response.setStatus(HttpServletResponse.SC_MOVED_PERMANENTLY);
    }
+

另一个问题是设置 cookie

@RequestMapping(value = "request4", method = RequestMethod.GET)
    public void request4(HttpServletRequest request, HttpServletResponse response) {
        Cookie cookie = new Cookie("a", "b");
        response.addCookie(cookie);
        response.setStatus(HttpServletResponse.SC_OK);
    }
+

这样的设置就能成功设定 cookie，而随着目前的浏览器 cookie 策略，如果要跳转后设置的话，估计是会越来越难，包括

+
response.addHeader("Set-Cookie", "a=b; domain=baidu.com; SameSite=none;Secure");
+

这样的方式也没法实现。

]]> Java @@ -4237,30 +4191,49 @@ - summary-ranges-228 - /2016/10/12/summary-ranges-228/ - problem

Given a sorted integer array without duplicates, return the summary of its ranges.

-

For example, given [0,1,2,4,5,7], return ["0->2","4->5","7"].

-

题解

每一个区间的起点nums[i]加上j是否等于nums[i+j]
参考

-

Code

class Solution {
public:
    vector<string> summaryRanges(vector<int>& nums) {
        int i = 0, j = 1, n;
        vector<string> res;
        n = nums.size();
        while(i < n){
            j = 1;
            while(j < n && nums[i+j] - nums[i] == j) j++;
            res.push_back(j <= 1 ? to_string(nums[i]) : to_string(nums[i]) + "->" + to_string(nums[i + j - 1]));
            i += j;
        }
        return res;
    }
};
]]> - - leetcode - - - leetcode - c++ - - - - win 下 vmware 虚拟机搭建黑裙 nas 的小思路 - /2023/06/04/win-%E4%B8%8B-vmware-%E8%99%9A%E6%8B%9F%E6%9C%BA%E6%90%AD%E5%BB%BA%E9%BB%91%E8%A3%99-nas-%E7%9A%84%E5%B0%8F%E6%80%9D%E8%B7%AF/ - 上次说 nas 的方案我是在 win10 下使用vmware workstation 搭建的黑裙虚拟机，采用 sata 物理磁盘直通的方式，算是跑通了黑裙的基础使用模式，但是后来发现的一个问题是之前没考虑到的，我买了不带 f 的处理器就是为了核显能做硬解，但是因为 cpu 是通过 vmware 虚拟的，目前看来是没法直通核显的，我是使用的 jellyfin 套件，一开始使用是默认的刮削方式，而且把电视剧当成了电影在刮削，所以基本不能看，后面使用了 tmm 作为刮削工具，可以手动填写 imdb 的id 来进行搜索，一般比较正式的剧都可以在豆瓣上找到的，然后让 jellyfin 只作为媒体管理器，但是前面的问题还是没解决，所以考虑了下可以在win10 下直接运行 jellyfin，媒体目录使用挂载在 nas 里的盘，这样 jellyfin 就能直接调用核显了，也算是把 win10 本身给利用起来了，并且文件的管理还是在黑裙中。
现在想来其实我这个方案还是不太合理，cpu 性能有点过剩想通过虚拟机的形式进行隔离使用，但是购买带核显的 cpu 最大的目的却没有实现，如果是直接裸机部署黑裙的话，真的是觉得 cpu 有点太浪费了，毕竟 passmark评分有 1w3 的cpu，只用来跑黑裙，所以网上的很多建议也是合理的，不过我可能是 win10 用的比较多了，还是习惯有 win 的环境。

+ springboot 请求响应处理流程 + /2023/08/27/springboot-%E8%AF%B7%E6%B1%82%E5%93%8D%E5%BA%94%E5%A4%84%E7%90%86%E6%B5%81%E7%A8%8B/ + Tomcat 会把请求委托到
org.springframework.web.servlet.DispatcherServlet#doService

+
protected void doService(HttpServletRequest request, HttpServletResponse response) throws Exception {
		logRequest(request);

        // 省略前面的代码
		try {
			doDispatch(request, response);
		}
+

然后就是调用
org.springframework.web.servlet.DispatcherServlet#doDispatch

+
protected void doDispatch(HttpServletRequest request, HttpServletResponse response) throws Exception {

	try {
		ModelAndView mv = null;
		Exception dispatchException = null;

		try {
			processedRequest = checkMultipart(request);
			multipartRequestParsed = (processedRequest != request);

               // 去获取处理器
			// Determine handler for the current request.
			mappedHandler = getHandler(processedRequest);
			if (mappedHandler == null) {
				noHandlerFound(processedRequest, response);
				return;
			}

			// Determine handler adapter for the current request.
			HandlerAdapter ha = getHandlerAdapter(mappedHandler.getHandler());

			// Process last-modified header, if supported by the handler.
			String method = request.getMethod();
			boolean isGet = HttpMethod.GET.matches(method);
			if (isGet || HttpMethod.HEAD.matches(method)) {
				long lastModified = ha.getLastModified(request, mappedHandler.getHandler());
				if (new ServletWebRequest(request, response).checkNotModified(lastModified) && isGet) {
					return;
				}
			}

			if (!mappedHandler.applyPreHandle(processedRequest, response)) {
				return;
			}

			// Actually invoke the handler.
			mv = ha.handle(processedRequest, response, mappedHandler.getHandler());

+

看下这里的逻辑

+
@Nullable
protected HandlerExecutionChain getHandler(HttpServletRequest request) throws Exception {
	if (this.handlerMappings != null) {
		for (HandlerMapping mapping : this.handlerMappings) {
			HandlerExecutionChain handler = mapping.getHandler(request);
			if (handler != null) {
				return handler;
			}
		}
	}
	return null;
}
+

可以看到有这些 HandlerMapping

而这里面就是前面提到过的
org.springframework.web.servlet.mvc.method.annotation.RequestMappingHandlerMapping
从这就能找到具体的 Handler
com.nicksxs.spbdemo.controller.DemoController#test()
这就是我简单的示例代码

+
@RequestMapping(value = "/test", method = RequestMethod.GET)
@ResponseBody
public DemoResponse test() {
    String item = "{\"id\": 1, \"name\": \"nick\"}";
    ParserConfig parserConfig = ParserConfig.getGlobalInstance();
    parserConfig.propertyNamingStrategy = PropertyNamingStrategy.SnakeCase;
    DemoResponse response = JSON.parseObject(item, DemoResponse.class, parserConfig);
    return response;
}
+

下一步是再获取处理器的适配器，
org.springframework.web.servlet.mvc.method.annotation.RequestMappingHandlerAdapter

+
protected HandlerAdapter getHandlerAdapter(Object handler) throws ServletException {
		if (this.handlerAdapters != null) {
			for (HandlerAdapter adapter : this.handlerAdapters) {
				if (adapter.supports(handler)) {
					return adapter;
				}
			}
		}
		throw new ServletException("No adapter for handler [" + handler +
				"]: The DispatcherServlet configuration needs to include a HandlerAdapter that supports this handler");
	}
+

正好这个适配器是调用的父类的 supports 方法

+
@Override
public final boolean supports(Object handler) {
	return (handler instanceof HandlerMethod && supportsInternal((HandlerMethod) handler));
}
+

而我这个com.nicksxs.spbdemo.controller.DemoController#test()
就是个包装好的 HandlerMethod
然后就是调用 ha 的 handle 方法，也是通过模板方法，实际调用的是
org.springframework.web.servlet.mvc.method.AbstractHandlerMethodAdapter#handle

+
@Override
@Nullable
public final ModelAndView handle(HttpServletRequest request, HttpServletResponse response, Object handler)
		throws Exception {

	return handleInternal(request, response, (HandlerMethod) handler);
}
+

然后调用
org.springframework.web.servlet.mvc.method.annotation.RequestMappingHandlerAdapter#handleInternal

+
@Override
	protected ModelAndView handleInternal(HttpServletRequest request,
			HttpServletResponse response, HandlerMethod handlerMethod) throws Exception {

		ModelAndView mav;
		checkRequest(request);

		// Execute invokeHandlerMethod in synchronized block if required.
		if (this.synchronizeOnSession) {
			HttpSession session = request.getSession(false);
			if (session != null) {
				Object mutex = WebUtils.getSessionMutex(session);
				synchronized (mutex) {
					mav = invokeHandlerMethod(request, response, handlerMethod);
				}
			}
			else {
				// No HttpSession available -> no mutex necessary
				mav = invokeHandlerMethod(request, response, handlerMethod);
			}
		}
		else {
            // 是否要锁定 session，否则走到这
			// No synchronization on session demanded at all...
			mav = invokeHandlerMethod(request, response, handlerMethod);
		}
+ +

继续调用
org.springframework.web.servlet.mvc.method.annotation.RequestMappingHandlerAdapter#invokeHandlerMethod

+
@Nullable
	protected ModelAndView invokeHandlerMethod(HttpServletRequest request,
			HttpServletResponse response, HandlerMethod handlerMethod) throws Exception {

		ServletWebRequest webRequest = new ServletWebRequest(request, response);
		try {
			WebDataBinderFactory binderFactory = getDataBinderFactory(handlerMethod);
			ModelFactory modelFactory = getModelFactory(handlerMethod, binderFactory);

            // 包装调用方法，
			ServletInvocableHandlerMethod invocableMethod = createInvocableHandlerMethod(handlerMethod);
			// 省略一部分非本次关注核心代码
            // 然后是调用到这
			invocableMethod.invokeAndHandle(webRequest, mavContainer);
			if (asyncManager.isConcurrentHandlingStarted()) {
				return null;
			}

			return getModelAndView(mavContainer, modelFactory, webRequest);
		}
		finally {
			webRequest.requestCompleted();
		}
	}
+

稍微再看一眼
第一步是
org.springframework.web.servlet.mvc.method.annotation.RequestMappingHandlerAdapter#createInvocableHandlerMethod

+
protected ServletInvocableHandlerMethod createInvocableHandlerMethod(HandlerMethod handlerMethod) {
	return new ServletInvocableHandlerMethod(handlerMethod);
}
+

第二步是
org.springframework.web.servlet.mvc.method.annotation.ServletInvocableHandlerMethod#ServletInvocableHandlerMethod(org.springframework.web.method.HandlerMethod)

+
   public ServletInvocableHandlerMethod(HandlerMethod handlerMethod) {
	super(handlerMethod);
}
+

第三步是
org.springframework.web.method.support.InvocableHandlerMethod#InvocableHandlerMethod(org.springframework.web.method.HandlerMethod)

+
   public InvocableHandlerMethod(HandlerMethod handlerMethod) {
	super(handlerMethod);
}
+

第四步是
org.springframework.web.method.HandlerMethod#HandlerMethod(org.springframework.web.method.HandlerMethod)

+
protected HandlerMethod(HandlerMethod handlerMethod) {
	Assert.notNull(handlerMethod, "HandlerMethod is required");
	this.bean = handlerMethod.bean;
	this.beanFactory = handlerMethod.beanFactory;
	this.beanType = handlerMethod.beanType;
	this.method = handlerMethod.method;
	this.bridgedMethod = handlerMethod.bridgedMethod;
	this.parameters = handlerMethod.parameters;
	this.responseStatus = handlerMethod.responseStatus;
	this.responseStatusReason = handlerMethod.responseStatusReason;
	this.description = handlerMethod.description;
	this.resolvedFromHandlerMethod = handlerMethod.resolvedFromHandlerMethod;
}
+

这是个继承关系，一直调用到最顶层的父类的构造方法，其实就是拷贝，然后继续调用
org.springframework.web.servlet.mvc.method.annotation.ServletInvocableHandlerMethod#invokeAndHandle

+
public void invokeAndHandle(ServletWebRequest webRequest, ModelAndViewContainer mavContainer,
			Object... providedArgs) throws Exception {

        // 调用请求
		Object returnValue = invokeForRequest(webRequest, mavContainer, providedArgs);
		// 稍微忽略下后面的代码
	}
+

继续调用
org.springframework.web.method.support.InvocableHandlerMethod#invokeForRequest

+
@Nullable
public Object invokeForRequest(NativeWebRequest request, @Nullable ModelAndViewContainer mavContainer,
		Object... providedArgs) throws Exception {

	Object[] args = getMethodArgumentValues(request, mavContainer, providedArgs);
	if (logger.isTraceEnabled()) {
		logger.trace("Arguments: " + Arrays.toString(args));
	}
	return doInvoke(args);
}
+

来到了最核心处
org.springframework.web.method.support.InvocableHandlerMethod#doInvoke

+
@Nullable
protected Object doInvoke(Object... args) throws Exception {
	Method method = getBridgedMethod();
	ReflectionUtils.makeAccessible(method);
	try {
		if (KotlinDetector.isSuspendingFunction(method)) {
			return CoroutinesUtils.invokeSuspendingFunction(method, getBean(), args);
		}
           // 会走到这里，获取到 bean，而这个 bean 就是前面构造方法里赋值的，最开始被放在 handler 里面，然后调用方法
		return method.invoke(getBean(), args);
	}
]]> - nas + Java + SpringBoot - nas + Java + SpringBoot @@ -4287,6 +4260,21 @@ 端口转发 + + summary-ranges-228 + /2016/10/12/summary-ranges-228/ + problem

Given a sorted integer array without duplicates, return the summary of its ranges.

+

For example, given [0,1,2,4,5,7], return ["0->2","4->5","7"].

+

题解

每一个区间的起点nums[i]加上j是否等于nums[i+j]
参考

+

Code

class Solution {
public:
    vector<string> summaryRanges(vector<int>& nums) {
        int i = 0, j = 1, n;
        vector<string> res;
        n = nums.size();
        while(i < n){
            j = 1;
            while(j < n && nums[i+j] - nums[i] == j) j++;
            res.push_back(j <= 1 ? to_string(nums[i]) : to_string(nums[i]) + "->" + to_string(nums[i + j - 1]));
            i += j;
        }
        return res;
    }
};
]]> + + leetcode + + + leetcode + c++ + + swoole-websocket-test /2016/07/13/swoole-websocket-test/ @@ -4326,6 +4314,18 @@ user3: swoole + + win 下 vmware 虚拟机搭建黑裙 nas 的小思路 + /2023/06/04/win-%E4%B8%8B-vmware-%E8%99%9A%E6%8B%9F%E6%9C%BA%E6%90%AD%E5%BB%BA%E9%BB%91%E8%A3%99-nas-%E7%9A%84%E5%B0%8F%E6%80%9D%E8%B7%AF/ + 上次说 nas 的方案我是在 win10 下使用vmware workstation 搭建的黑裙虚拟机，采用 sata 物理磁盘直通的方式，算是跑通了黑裙的基础使用模式，但是后来发现的一个问题是之前没考虑到的，我买了不带 f 的处理器就是为了核显能做硬解，但是因为 cpu 是通过 vmware 虚拟的，目前看来是没法直通核显的，我是使用的 jellyfin 套件，一开始使用是默认的刮削方式，而且把电视剧当成了电影在刮削，所以基本不能看，后面使用了 tmm 作为刮削工具，可以手动填写 imdb 的id 来进行搜索，一般比较正式的剧都可以在豆瓣上找到的，然后让 jellyfin 只作为媒体管理器，但是前面的问题还是没解决，所以考虑了下可以在win10 下直接运行 jellyfin，媒体目录使用挂载在 nas 里的盘，这样 jellyfin 就能直接调用核显了，也算是把 win10 本身给利用起来了，并且文件的管理还是在黑裙中。
现在想来其实我这个方案还是不太合理，cpu 性能有点过剩想通过虚拟机的形式进行隔离使用，但是购买带核显的 cpu 最大的目的却没有实现，如果是直接裸机部署黑裙的话，真的是觉得 cpu 有点太浪费了，毕竟 passmark评分有 1w3 的cpu，只用来跑黑裙，所以网上的很多建议也是合理的，不过我可能是 win10 用的比较多了，还是习惯有 win 的环境。

+]]> + + nas + + + nas + + wordpress 忘记密码的一种解决方法 /2021/12/05/wordpress-%E5%BF%98%E8%AE%B0%E5%AF%86%E7%A0%81%E7%9A%84%E4%B8%80%E7%A7%8D%E8%A7%A3%E5%86%B3%E6%96%B9%E6%B3%95/ @@ -4364,6 +4364,19 @@ user3: jvm + + 《寻羊历险记》读后感 + /2023/07/23/%E3%80%8A%E5%AF%BB%E7%BE%8A%E5%8E%86%E9%99%A9%E8%AE%B0%E3%80%8B%E8%AF%BB%E5%90%8E%E6%84%9F/ + 最近本来是在读《舞舞舞》，然后看到有介绍说，这个跟《寻羊历险记》是有情节上的关联，所以就先去看了《寻羊历险记》，《寻羊历险记》也是村上春树的第一本成规模的长篇小说，也可以认为是《舞舞舞》的前篇。
最开始这个情节跟之前的刺杀骑士团长还是哪本有点类似，都有跟老婆离婚了，主角应该是个跟朋友一起开翻译社的，后面也开始做广告相关的，做到了经济收益还不错的阶段，也有一些挺哲学的对话，朋友觉得这么赚钱不地道（可能也是觉得这样忘了初心），在离婚以后又结交了一个耳朵很好看的女友，这个女友也是个比较抽象的存在，描述中给人感觉是一个外貌很普通的女孩，但是耳朵漂亮的惊为天人，不知道是不是有什么隐喻，感觉现实中没见过这样的人，女友平时把耳朵遮起来不轻易露出来，只有在跟主角做爱的时候才露出来
主体剧情是因为男主在广告中用了一张一位叫“鼠”的朋友寄给他的一张包含一只特殊的羊的照片，就有个政界大佬的秘书找过来，逼迫主角要找到照片上的羊，这只羊背上有星纹，基本不可能属于在日本当时可能存在的羊的品种，因为这位政界大佬快病危了，所以要求主角必须在一个月内找到这只羊，因为这里把这只神秘的羊塑造成神一样的存在，这位政界大佬在年轻时被这只羊上身，后面就开始在政治事业上大展宏图，就基本成了能左右整个日本走向的巨佬，但近期随着巨佬，身体状态慢慢变差，这只羊就从他身上消失了，所以秘书要主角必须找到这只羊，不然基本会让主角的翻译社完蛋，这样主角就会面临破产赔偿等严重后果，只是说主角本来也一直是这种丧气存在，再说这么茫茫人海找个人都难，还要找这么一只玄乎的不太可能真实存在的羊，所以基本是想要放弃的，结果刚才说的耳朵很漂亮的女友却有着神乎其神的直觉，就觉得能找到，然后他们就踏上了巡羊的旅程，一开始到了札幌，寻找一无所获，然后神奇的是女友推荐一定要住的海豚宾馆，恰恰是一切线索的源头，宾馆老板的父亲正好是羊博士，在年轻的时候被羊上身过，后面离开后就去了那位巨佬身上，让巨佬成了真正控制日本的地下帝国的王，跟羊博士咨询后知道羊可能在十二瀑镇的牧场出现过，所以一路找寻，发现其实这个牧场中有个别墅正好是主角朋友“鼠”的，到了别墅后出现了个神秘的羊男，这个羊男真的不太明白是怎么个存在，就是让主角的女友回去了，然后最后一个肉体承载着“鼠”的灵魂跟主角有了一次接触，主角呆在这个别墅过着百无聊赖的生活，在才到有一次羊男来跟他交流的时候其实是承载着鼠的灵魂，就觉得是不是一切都是在忽悠他，离一个月期限也越来越近了，而在发怒之后，“鼠”真的出现后，但是不是真的“鼠”，而是只有他的灵魂，因为“鼠”已经死了，因为不想被“羊”附身，成为羊壳，并且让主角设定好时钟后的装置后尽快下山，第二天主角离开上了火车后山上牧场就传来爆炸声，“鼠”已经跟羊同归于尽了，免得再有其他人被羊附身，主角也很难过，回到故乡在四周大海已经被填掉了的旧防波堤上大哭悼念逝去的“鼠”。
其实对于没什么时代概念或者对村上一直以来的观念不是特别敏感的，对这本书讲了啥有点云里雾里，后面看了一些简单的解释就是羊其实代表日本帝国主义和资本主义，可能是村上本人反帝国主义，军国主义和资本主义的一个表征，想来也有些道理，不然“鼠”的牺牲就感觉比较没意义，但是另一方面我的理解也可能是对自由的向往的表达，被羊控制，虽然可以成就“伟大”的事业，但是也丧失了自我。

+]]> + + 读后感 + 生活 + + + 读后感 + + 《长安的荔枝》读后感 /2022/07/17/%E3%80%8A%E9%95%BF%E5%AE%89%E7%9A%84%E8%8D%94%E6%9E%9D%E3%80%8B%E8%AF%BB%E5%90%8E%E6%84%9F/ @@ -4374,8 +4387,8 @@ user3: 生活 - 生活 读后感 + 生活 @@ -4395,6 +4408,19 @@ user3: nginx + + 上次的其他 外行聊国足 + /2022/03/06/%E4%B8%8A%E6%AC%A1%E7%9A%84%E5%85%B6%E4%BB%96-%E5%A4%96%E8%A1%8C%E8%81%8A%E5%9B%BD%E8%B6%B3/ + 上次本来想在换车牌后面聊下这个话题，为啥要聊这个话题呢，也很简单，在地铁上看到一对猜测是情侣或者比较关系好的男女同学在聊，因为是这位男同学是大学学的工科，然后自己爱好设计绘画相关的，可能还以此赚了点钱，在地铁上讨论男的要不要好好努力把大学课程完成好，大致的观点是没必要，本来就不适合，这一段我就不说了，恋爱人的嘴，信你个鬼。
后面男的说在家里又跟他爹吵了关于男足的，估计是那次输了越南，实话说我不是个足球迷，对各方面技术相关也不熟，只是对包括这个人的解释和网上一些观点的看法，纯主观，这次地铁上这位说的大概意思是足球这个训练什么的很难的，要想赢越南也很难的，不是我们能嘴炮的；在网上看到一个赞同数很多的一个回答，说什么中国是个体育弱国，但是由于有一些乒乓球，跳水等小众项目比较厉害，让民众给误解了，首先我先来反驳下这个偷换概念的观点，第一所谓的体育弱国，跟我们觉得足球不应该这么差没半毛钱关系，因为体育弱国，我们的足球本来就不是顶尖的，也并不是去跟顶尖的球队去争，以足球为例，跟巴西，阿根廷，英国，德国，西班牙，意大利，法国这些足球强国，去比较，我相信没有一个足球迷会这么去做对比，因为我们足球历史最高排名是 1998 年的 37 名，最差是 100 名，把能数出来的强队都数完，估计都还不会到 37，所以根本没有跟强队去做对比，第二体育弱国，我们的体育投入是在逐年降低吗，我们是因战乱没法好好训练踢球？还是这帮傻逼就不争气，前面也说了我们足球世界排名最高 37，最低 100，那么前阵子我们输的越南是第几，目前我们的排名 77 名，越南 92 名，看明白了么，轮排名我们都不至于输越南，然后就是这个排名，这也是我想回应那位地铁上的兄弟，我觉得除了造核弹这种高精尖技术，绝大部分包含足球这类运动，遵循类二八原则，比如满分是 100 分，从 80 提到 90 分或者 90 分提到 100 分非常难，30 分提到 40 分，50 分提到 60 分我觉得都是可以凭后天努力达成的，基本不受天赋限制，这里可以以篮球来类比下，相对足球的确篮球没有那么火，或者行业市值没法比，但是也算是相对大众了，中国在篮球方面相对比较好一点，在 08 年奥运会冲进过八强，那也不是唯一的巅峰，但是我说这个其实是想说明两方面的事情，第一，像篮球一样，状态是有起起伏伏，排名也会变动，但是我觉得至少能维持一个相对稳定的总体排名和持平或者上升的趋势，这恰恰是我们这种所谓的“体育弱国”应该走的路线，第二就是去支持我的类二八原则的，可以看到我们的篮球这两年也很垃圾，排名跌到 29 了，那问题我觉得跟足球是一样的，就是不能脚踏实地，如斯科拉说的，中国篮球太缺少竞争，打得好不好都是这些人打，打输了还是照样拿钱，相对足球，篮球的技术我还是懂一些的，对比 08 年的中国男篮，的确像姚明跟王治郅这样的天赋型+努力型球员少了以后竞争力下降在所难免，但是去对比下基本功，传球，投篮，罚球稳定性，也完全不是一个水平的，这些就是我说的，可以通过努力训练拿 80 分的，只要拿到 80 分，甚至只要拿到 60 分，我觉得应该就还算对得起球迷了，就像 NBA 里球队也会有核心球员的更替，战绩起起伏伏，但是基本功这东西，防守积极性，我觉得不随核心球员的变化而变化，就像姚明这样的天赋，其实他应该还有一些先天缺陷，大脚趾较长等，但是他从 CBA 到 NBA，在 NBA 适应并且打成顶尖中锋，离不开刻苦训练，任何的成功都不是纯天赋的，必须要付出足够的努力。
说回足球，如果像前面那么洗地（体育弱国），那能给我维持住一个稳定的排名我也能接受，问题是我们的经济物质资源比 2000 年前应该有了质的变化，身体素质也越来越好，即使是体育弱国，这么继续走下坡路，半死不活的，不觉得是打了自己的脸么。足球也需要基本功，基本的体能，力量这些，看看现在这些国足运动员的体型，对比下女足，说实话，如果男足这些运动员都练得不错的体脂率，耐力等，成绩即使不好，也不会比现在更差。
纯主观吐槽，勿喷。

+]]> + + 生活 + 运动 + + + 生活 + + 介绍一下 RocketMQ /2020/06/21/%E4%BB%8B%E7%BB%8D%E4%B8%80%E4%B8%8B-RocketMQ/ @@ -4465,29 +4491,23 @@ user3: - 上次的其他 外行聊国足 - /2022/03/06/%E4%B8%8A%E6%AC%A1%E7%9A%84%E5%85%B6%E4%BB%96-%E5%A4%96%E8%A1%8C%E8%81%8A%E5%9B%BD%E8%B6%B3/ - 上次本来想在换车牌后面聊下这个话题，为啥要聊这个话题呢，也很简单，在地铁上看到一对猜测是情侣或者比较关系好的男女同学在聊，因为是这位男同学是大学学的工科，然后自己爱好设计绘画相关的，可能还以此赚了点钱，在地铁上讨论男的要不要好好努力把大学课程完成好，大致的观点是没必要，本来就不适合，这一段我就不说了，恋爱人的嘴，信你个鬼。
后面男的说在家里又跟他爹吵了关于男足的，估计是那次输了越南，实话说我不是个足球迷，对各方面技术相关也不熟，只是对包括这个人的解释和网上一些观点的看法，纯主观，这次地铁上这位说的大概意思是足球这个训练什么的很难的，要想赢越南也很难的，不是我们能嘴炮的；在网上看到一个赞同数很多的一个回答，说什么中国是个体育弱国，但是由于有一些乒乓球，跳水等小众项目比较厉害，让民众给误解了，首先我先来反驳下这个偷换概念的观点，第一所谓的体育弱国，跟我们觉得足球不应该这么差没半毛钱关系，因为体育弱国，我们的足球本来就不是顶尖的，也并不是去跟顶尖的球队去争，以足球为例，跟巴西，阿根廷，英国，德国，西班牙，意大利，法国这些足球强国，去比较，我相信没有一个足球迷会这么去做对比，因为我们足球历史最高排名是 1998 年的 37 名，最差是 100 名，把能数出来的强队都数完，估计都还不会到 37，所以根本没有跟强队去做对比，第二体育弱国，我们的体育投入是在逐年降低吗，我们是因战乱没法好好训练踢球？还是这帮傻逼就不争气，前面也说了我们足球世界排名最高 37，最低 100，那么前阵子我们输的越南是第几，目前我们的排名 77 名，越南 92 名，看明白了么，轮排名我们都不至于输越南，然后就是这个排名，这也是我想回应那位地铁上的兄弟，我觉得除了造核弹这种高精尖技术，绝大部分包含足球这类运动，遵循类二八原则，比如满分是 100 分，从 80 提到 90 分或者 90 分提到 100 分非常难，30 分提到 40 分，50 分提到 60 分我觉得都是可以凭后天努力达成的，基本不受天赋限制，这里可以以篮球来类比下，相对足球的确篮球没有那么火，或者行业市值没法比，但是也算是相对大众了，中国在篮球方面相对比较好一点，在 08 年奥运会冲进过八强，那也不是唯一的巅峰，但是我说这个其实是想说明两方面的事情，第一，像篮球一样，状态是有起起伏伏，排名也会变动，但是我觉得至少能维持一个相对稳定的总体排名和持平或者上升的趋势，这恰恰是我们这种所谓的“体育弱国”应该走的路线，第二就是去支持我的类二八原则的，可以看到我们的篮球这两年也很垃圾，排名跌到 29 了，那问题我觉得跟足球是一样的，就是不能脚踏实地，如斯科拉说的，中国篮球太缺少竞争，打得好不好都是这些人打，打输了还是照样拿钱，相对足球，篮球的技术我还是懂一些的，对比 08 年的中国男篮，的确像姚明跟王治郅这样的天赋型+努力型球员少了以后竞争力下降在所难免，但是去对比下基本功，传球，投篮，罚球稳定性，也完全不是一个水平的，这些就是我说的，可以通过努力训练拿 80 分的，只要拿到 80 分，甚至只要拿到 60 分，我觉得应该就还算对得起球迷了，就像 NBA 里球队也会有核心球员的更替，战绩起起伏伏，但是基本功这东西，防守积极性，我觉得不随核心球员的变化而变化，就像姚明这样的天赋，其实他应该还有一些先天缺陷，大脚趾较长等，但是他从 CBA 到 NBA，在 NBA 适应并且打成顶尖中锋，离不开刻苦训练，任何的成功都不是纯天赋的，必须要付出足够的努力。
说回足球，如果像前面那么洗地（体育弱国），那能给我维持住一个稳定的排名我也能接受，问题是我们的经济物质资源比 2000 年前应该有了质的变化，身体素质也越来越好，即使是体育弱国，这么继续走下坡路，半死不活的，不觉得是打了自己的脸么。足球也需要基本功，基本的体能，力量这些，看看现在这些国足运动员的体型，对比下女足，说实话，如果男足这些运动员都练得不错的体脂率，耐力等，成绩即使不好，也不会比现在更差。
纯主观吐槽，勿喷。

-]]> - - 生活 - 运动 - - - 生活 - - - - 《寻羊历险记》读后感 - /2023/07/23/%E3%80%8A%E5%AF%BB%E7%BE%8A%E5%8E%86%E9%99%A9%E8%AE%B0%E3%80%8B%E8%AF%BB%E5%90%8E%E6%84%9F/ - 最近本来是在读《舞舞舞》，然后看到有介绍说，这个跟《寻羊历险记》是有情节上的关联，所以就先去看了《寻羊历险记》，《寻羊历险记》也是村上春树的第一本成规模的长篇小说，也可以认为是《舞舞舞》的前篇。
最开始这个情节跟之前的刺杀骑士团长还是哪本有点类似，都有跟老婆离婚了，主角应该是个跟朋友一起开翻译社的，后面也开始做广告相关的，做到了经济收益还不错的阶段，也有一些挺哲学的对话，朋友觉得这么赚钱不地道（可能也是觉得这样忘了初心），在离婚以后又结交了一个耳朵很好看的女友，这个女友也是个比较抽象的存在，描述中给人感觉是一个外貌很普通的女孩，但是耳朵漂亮的惊为天人，不知道是不是有什么隐喻，感觉现实中没见过这样的人，女友平时把耳朵遮起来不轻易露出来，只有在跟主角做爱的时候才露出来
主体剧情是因为男主在广告中用了一张一位叫“鼠”的朋友寄给他的一张包含一只特殊的羊的照片，就有个政界大佬的秘书找过来，逼迫主角要找到照片上的羊，这只羊背上有星纹，基本不可能属于在日本当时可能存在的羊的品种，因为这位政界大佬快病危了，所以要求主角必须在一个月内找到这只羊，因为这里把这只神秘的羊塑造成神一样的存在，这位政界大佬在年轻时被这只羊上身，后面就开始在政治事业上大展宏图，就基本成了能左右整个日本走向的巨佬，但近期随着巨佬，身体状态慢慢变差，这只羊就从他身上消失了，所以秘书要主角必须找到这只羊，不然基本会让主角的翻译社完蛋，这样主角就会面临破产赔偿等严重后果，只是说主角本来也一直是这种丧气存在，再说这么茫茫人海找个人都难，还要找这么一只玄乎的不太可能真实存在的羊，所以基本是想要放弃的，结果刚才说的耳朵很漂亮的女友却有着神乎其神的直觉，就觉得能找到，然后他们就踏上了巡羊的旅程，一开始到了札幌，寻找一无所获，然后神奇的是女友推荐一定要住的海豚宾馆，恰恰是一切线索的源头，宾馆老板的父亲正好是羊博士，在年轻的时候被羊上身过，后面离开后就去了那位巨佬身上，让巨佬成了真正控制日本的地下帝国的王，跟羊博士咨询后知道羊可能在十二瀑镇的牧场出现过，所以一路找寻，发现其实这个牧场中有个别墅正好是主角朋友“鼠”的，到了别墅后出现了个神秘的羊男，这个羊男真的不太明白是怎么个存在，就是让主角的女友回去了，然后最后一个肉体承载着“鼠”的灵魂跟主角有了一次接触，主角呆在这个别墅过着百无聊赖的生活，在才到有一次羊男来跟他交流的时候其实是承载着鼠的灵魂，就觉得是不是一切都是在忽悠他，离一个月期限也越来越近了，而在发怒之后，“鼠”真的出现后，但是不是真的“鼠”，而是只有他的灵魂，因为“鼠”已经死了，因为不想被“羊”附身，成为羊壳，并且让主角设定好时钟后的装置后尽快下山，第二天主角离开上了火车后山上牧场就传来爆炸声，“鼠”已经跟羊同归于尽了，免得再有其他人被羊附身，主角也很难过，回到故乡在四周大海已经被填掉了的旧防波堤上大哭悼念逝去的“鼠”。
其实对于没什么时代概念或者对村上一直以来的观念不是特别敏感的，对这本书讲了啥有点云里雾里，后面看了一些简单的解释就是羊其实代表日本帝国主义和资本主义，可能是村上本人反帝国主义，军国主义和资本主义的一个表征，想来也有些道理，不然“鼠”的牺牲就感觉比较没意义，但是另一方面我的理解也可能是对自由的向往的表达，被羊控制，虽然可以成就“伟大”的事业，但是也丧失了自我。

+ 介绍下最近比较实用的端口转发 + /2021/11/14/%E4%BB%8B%E7%BB%8D%E4%B8%8B%E6%9C%80%E8%BF%91%E6%AF%94%E8%BE%83%E5%AE%9E%E7%94%A8%E7%9A%84%E7%AB%AF%E5%8F%A3%E8%BD%AC%E5%8F%91/ + vscode 扩展转发

在日常使用云服务器的时候，如果要访问上面自建的 mysql，一般要不直接开对应的端口，然后需要对本地 ip 进行授权，但是这个方案会有比较多的限制，比如本地 ip 变了，比如是非固定出口 ip 的家用宽带，或者要在家里跟公司都要访问，如果对所有 ip 都授权的话会不安全，这个时候其实是用 ssh 端口转发是个比较安全方便的方式。
原来在这个之前其实对这块内容不太了解，后面是听朋友说的，vscode 的 Remote - SSH 扩展可以很方便的使用端口转发，在使用该扩展的时候，会在控制台位置里都出现一个”端口” tab

如图中所示，我就是将一个服务器上的 mysql 的 3306 端口转发到本地的 3307 端口，至于为什么不用 3306 是因为本地我也有个 mysql 已经使用了 3306 端口，这个方法是使用的 vscode 的这个扩展，

+

ssh 命令转发

还有个方式是直接使用 ssh 命令
命令可以如此

+
ssh -CfNg -L 3307:127.0.0.1:3306 user1@199.199.199.199
+

简单介绍下这个命令
-C 表示的是压缩数据包
-f 表示后台执行命令
-N 是表示不执行具体命令只用于端口转发
-g 表示允许远程主机连接本地转发端口
-L 则是具体端口转发的映射配置
上面的命令就是将远程主机的 127.0.0.1:3306 对应转发到本地 3307
而后面的用户则就是登录主机的用户名user1和ip地址199.199.199.199，当然这个配置也不是唯一的

+

ssh config 配置转发

还可以在ssh 的 config 配置中加对应的配置

+
Host host1
  HostName 199.199.199.199
  User user1
  IdentityFile  /Users/user1/.ssh/id_rsa
  ServerAliveInterval 60
  LocalForward 3310 127.0.0.1:3306
+

然后通过 ssh host1 连接服务器的时候就能顺带做端口转发

]]> - 读后感 - 生活 + ssh + 技巧 - 读后感 + ssh + 端口转发 @@ -4511,23 +4531,23 @@ user3: - 介绍下最近比较实用的端口转发 - /2021/11/14/%E4%BB%8B%E7%BB%8D%E4%B8%8B%E6%9C%80%E8%BF%91%E6%AF%94%E8%BE%83%E5%AE%9E%E7%94%A8%E7%9A%84%E7%AB%AF%E5%8F%A3%E8%BD%AC%E5%8F%91/ - vscode 扩展转发

在日常使用云服务器的时候，如果要访问上面自建的 mysql，一般要不直接开对应的端口，然后需要对本地 ip 进行授权，但是这个方案会有比较多的限制，比如本地 ip 变了，比如是非固定出口 ip 的家用宽带，或者要在家里跟公司都要访问，如果对所有 ip 都授权的话会不安全，这个时候其实是用 ssh 端口转发是个比较安全方便的方式。
原来在这个之前其实对这块内容不太了解，后面是听朋友说的，vscode 的 Remote - SSH 扩展可以很方便的使用端口转发，在使用该扩展的时候，会在控制台位置里都出现一个”端口” tab

如图中所示，我就是将一个服务器上的 mysql 的 3306 端口转发到本地的 3307 端口，至于为什么不用 3306 是因为本地我也有个 mysql 已经使用了 3306 端口，这个方法是使用的 vscode 的这个扩展，

-

ssh 命令转发

还有个方式是直接使用 ssh 命令
命令可以如此

-
ssh -CfNg -L 3307:127.0.0.1:3306 user1@199.199.199.199
-

简单介绍下这个命令
-C 表示的是压缩数据包
-f 表示后台执行命令
-N 是表示不执行具体命令只用于端口转发
-g 表示允许远程主机连接本地转发端口
-L 则是具体端口转发的映射配置
上面的命令就是将远程主机的 127.0.0.1:3306 对应转发到本地 3307
而后面的用户则就是登录主机的用户名user1和ip地址199.199.199.199，当然这个配置也不是唯一的

-

ssh config 配置转发

还可以在ssh 的 config 配置中加对应的配置

-
Host host1
  HostName 199.199.199.199
  User user1
  IdentityFile  /Users/user1/.ssh/id_rsa
  ServerAliveInterval 60
  LocalForward 3310 127.0.0.1:3306
-

然后通过 ssh host1 连接服务器的时候就能顺带做端口转发

+ 从清华美院学姐聊聊我们身边的恶人 + /2020/11/29/%E4%BB%8E%E6%B8%85%E5%8D%8E%E7%BE%8E%E9%99%A2%E5%AD%A6%E5%A7%90%E8%81%8A%E8%81%8A%E6%88%91%E4%BB%AC%E8%BA%AB%E8%BE%B9%E7%9A%84%E6%81%B6%E4%BA%BA/ + 前几天清华美院学姐的热点火了，然后仔细看了下，其实是个学姐诬陷以为其貌不扬的男同学摸她屁股

然后还在朋友圈发文想让他社死，我也是挺晚才知道这个词什么意思，然后后面我看到了这个图片，挺有意思的

本来其实也没什么想聊这个的，是在 B 站看了个吐槽这个的，然后刚好晚上乘公交的时候又碰到了有点类似的问题
故事描述下，我们从始发站做了公交，这辆公交司机上次碰到过一回，就是会比较关注乘客的佩戴情况，主要考虑到目前国内疫情，然后这次在差不多人都坐满的情况下，可能在提示了三次让车内乘客戴好口罩，但是他指的那个中年女性还是没有反应，司机就转头比较大声指着这个乘客（中年女性）让戴好口罩，然后这个乘客（中年女性）就大声的说“我口罩是滑下来了，你指着我干嘛，你态度这么差，要吃了我一样，我要投诉你”等等，然后可能跟她一块的一个中年女性也是这么帮腔指责司机，比较基本的理解，车子里这么多乘客，假如是处于这位乘客口罩滑下来了而不自知的情况下，司机在提示了三次以后回头指着她说，我想的是没什么问题的，但是这位却反而指责这位司机指着她，并且说是态度差，要吃了她，完全是不可理喻的，并且一直喋喋不休说她口罩滑掉了有什么错，要投诉这个司机，让他可以提前退休了，在其他乘客的劝说下司机准备继续开车时，又口吐芬芳“你个傻，你来打我呀”，真的是让我再次体会到了所谓的恶人先告状的又一完美呈现，后面还有个乘客还是表示要打死司机这个傻，让我有点不明所以，俗话说有人是得理不饶人，前提是得理，这种理亏不饶人真的是挺让人长见识的，试想下，司机在提示三次后，这位乘客还是没有把口罩戴好，如何在不指着这位乘客的情况下能准确的提示到她呢，并且觉得语气态度不好，司机要载着一车的人，因为你这一个乘客不戴好口罩而不能正常出发，有些着急应该很正常吧，可能是平时自己在家里耀武扬威的使唤别人习惯了吧，别人不敢这么大声跟她说话，其实想想这位中年女性应该年纪不会很大，还比较时髦的吧，像一些常见的中年杭州本地人可能是不会说傻*这个词的吧。
杭州的公交可能是在二月份疫情还比较严重的时候是要求上车出示健康码，后面比较缓和以后只要求佩戴好口罩，但是在我们小绍兴，目前还是一律要求检验健康码和佩戴口罩，对于疫情中，并且目前阶段国内也时有报出小范围的疫情的情况下，司机尽职要求佩戴好口罩其实也是为了乘客着想，另一种情况如果司机不严格要求，万一车上有个感染者，这位中年女性被传染了，如果能找到这个司机的话，是不是想“打死”这个司机，竟然让感染者上了车，反正她自己是不可能有错的，上来就是对方态度差，要投诉，自己不戴好口罩啥都没错，我就想知道如果因为自己没戴好口罩被感染了，是不是也是司机的错，毕竟没有像仆人那样点头哈腰求着她戴好口罩。
再说回来，整个车就她一个人没戴好口罩，并且还有个细节，其实这个乘客是上了车之后就没戴好了，本来上车的时候是戴好的，这种比较有可能是觉得上车的时候司机那看一眼就好了，如果好好戴着口罩，一点事情都没有，唉，纯粹是太气愤了，调理逻辑什么的就忽略吧

]]> - ssh - 技巧 + 生活 + 吐槽 + 疫情 + 口罩 - ssh - 端口转发 + 生活 + 吐槽 + 疫情 + 公交车 + 口罩 + 杀人诛心 @@ -4561,23 +4581,25 @@ user3: - 从清华美院学姐聊聊我们身边的恶人 - /2020/11/29/%E4%BB%8E%E6%B8%85%E5%8D%8E%E7%BE%8E%E9%99%A2%E5%AD%A6%E5%A7%90%E8%81%8A%E8%81%8A%E6%88%91%E4%BB%AC%E8%BA%AB%E8%BE%B9%E7%9A%84%E6%81%B6%E4%BA%BA/ - 前几天清华美院学姐的热点火了，然后仔细看了下，其实是个学姐诬陷以为其貌不扬的男同学摸她屁股

然后还在朋友圈发文想让他社死，我也是挺晚才知道这个词什么意思，然后后面我看到了这个图片，挺有意思的

本来其实也没什么想聊这个的，是在 B 站看了个吐槽这个的，然后刚好晚上乘公交的时候又碰到了有点类似的问题
故事描述下，我们从始发站做了公交，这辆公交司机上次碰到过一回，就是会比较关注乘客的佩戴情况，主要考虑到目前国内疫情，然后这次在差不多人都坐满的情况下，可能在提示了三次让车内乘客戴好口罩，但是他指的那个中年女性还是没有反应，司机就转头比较大声指着这个乘客（中年女性）让戴好口罩，然后这个乘客（中年女性）就大声的说“我口罩是滑下来了，你指着我干嘛，你态度这么差，要吃了我一样，我要投诉你”等等，然后可能跟她一块的一个中年女性也是这么帮腔指责司机，比较基本的理解，车子里这么多乘客，假如是处于这位乘客口罩滑下来了而不自知的情况下，司机在提示了三次以后回头指着她说，我想的是没什么问题的，但是这位却反而指责这位司机指着她，并且说是态度差，要吃了她，完全是不可理喻的，并且一直喋喋不休说她口罩滑掉了有什么错，要投诉这个司机，让他可以提前退休了，在其他乘客的劝说下司机准备继续开车时，又口吐芬芳“你个傻，你来打我呀”，真的是让我再次体会到了所谓的恶人先告状的又一完美呈现，后面还有个乘客还是表示要打死司机这个傻，让我有点不明所以，俗话说有人是得理不饶人，前提是得理，这种理亏不饶人真的是挺让人长见识的，试想下，司机在提示三次后，这位乘客还是没有把口罩戴好，如何在不指着这位乘客的情况下能准确的提示到她呢，并且觉得语气态度不好，司机要载着一车的人，因为你这一个乘客不戴好口罩而不能正常出发，有些着急应该很正常吧，可能是平时自己在家里耀武扬威的使唤别人习惯了吧，别人不敢这么大声跟她说话，其实想想这位中年女性应该年纪不会很大，还比较时髦的吧，像一些常见的中年杭州本地人可能是不会说傻*这个词的吧。
杭州的公交可能是在二月份疫情还比较严重的时候是要求上车出示健康码，后面比较缓和以后只要求佩戴好口罩，但是在我们小绍兴，目前还是一律要求检验健康码和佩戴口罩，对于疫情中，并且目前阶段国内也时有报出小范围的疫情的情况下，司机尽职要求佩戴好口罩其实也是为了乘客着想，另一种情况如果司机不严格要求，万一车上有个感染者，这位中年女性被传染了，如果能找到这个司机的话，是不是想“打死”这个司机，竟然让感染者上了车，反正她自己是不可能有错的，上来就是对方态度差，要投诉，自己不戴好口罩啥都没错，我就想知道如果因为自己没戴好口罩被感染了，是不是也是司机的错，毕竟没有像仆人那样点头哈腰求着她戴好口罩。
再说回来，整个车就她一个人没戴好口罩，并且还有个细节，其实这个乘客是上了车之后就没戴好了，本来上车的时候是戴好的，这种比较有可能是觉得上车的时候司机那看一眼就好了，如果好好戴着口罩，一点事情都没有，唉，纯粹是太气愤了，调理逻辑什么的就忽略吧

+ 关于公共交通再吐个槽 + /2021/03/21/%E5%85%B3%E4%BA%8E%E5%85%AC%E5%85%B1%E4%BA%A4%E9%80%9A%E5%86%8D%E5%90%90%E4%B8%AA%E6%A7%BD/ + 事情源于周末来回家发生的两件事情，先是回去的时候从高铁下车要坐公交，现在算是有个比较好的临时候车点了，但是可能由于疫情好转，晚上都不用检查健康码就可以进候车点，但是上公交的时候还是需要看健康码，一般情况下从高铁下来的，各个地方的人都有，而且也不太清楚这边上公交车需要查验健康码，我的一个看法是候车的时候就应该放个横幅告示，或者再配合喇叭循环播放，请提前准备好健康码，上车前需要查验，因为像这周的情况，我乘坐的那辆车是间隔时间比较长，而且终点是工业开发区，可能是比较多外来务工人员的目的地，正好这部分人可能对于操作手机检验健康码这个事情不太熟悉，所以结果就是头上几个不知道怎么搞出来健康码，然后让几乎有满满一整车的人在后面堵着，司机又非常厌烦那些没有提前出示健康码的，有位乘客搞得久了点，还被误以为没刷卡买票，差点吵起来，其实公共交通或者高铁站负责的在公交指引路线上多写一句上车前需要查验健康码，可能就能改善比较多，还有就是那个积水的路，这个吐槽起来就一大坨了，整个绍兴像 dayuejin 一样到处都是破路。
第二个就是来杭州的时候，经过人行横道，远处车道的公交车停下来等我们了，为了少添麻烦总想快点穿过去，但是这时靠近我们的车道（晚上光线较暗，可见度不佳）有一辆从远处来的奥迪 A4 还是 A5 这种的车反而想加速冲过去，如果少看一下可能我已经残了，交规考的靠近人行道要减速好像基本都是个摆设了，杭州也只有公交车因为一些考核指标原因会主动礼让，人其实需要有同理心，虽然可能有些人是开车多于骑车走路的，但是总也不可能永远不穿人行道吧，甚至这些人可能还会在人行道红灯的时候走过去。这个事情不是吐槽公共交通的，只是也有些许关系，想起来还有一件事也是刚才来杭州的时候看到的，等公交的时候看到有辆路虎要加塞，而目标车道刚好是辆大货车，大货车看到按了喇叭，路虎犹豫了下还是挤进去了，可能是对路虎的扛撞性能非常自信吧，反正我是挺后怕的，这种级别的车，被撞了的话估计还是鸡蛋撞石头，吨位惯性在那，这里再延伸下，挺多开豪车的人好像都觉得这路上路权更大一些，谁谁都得让着他，可能实际吃亏的不多，所以越加巩固了这种思维，当真的碰到不管的可能就会明白了，路权这个事情在天朝也基本没啥人重视，也没想说个结论，就到这吧

]]> 生活 - 吐槽 - 疫情 - 口罩 + 公交 生活 - 吐槽 - 疫情 - 公交车 - 口罩 - 杀人诛心 + 开车 + 加塞 + 糟心事 + 规则 + 公交 + 路政规划 + 基础设施 + 杭州 + 健康码 @@ -4586,8 +4608,8 @@ user3: 最近群里大佬发起了一个读书打卡活动，需要每天读一会书，在群里打卡分享感悟，争取一个月能读完一本书，说实话一天十分钟的读书时间倒是问题不大，不过每天都要打卡，而且一个月要读完一本书，其实难度还是有点大的，不过也想试试看。
之前某某老大给自己立了个 flag，说要读一百本书，这对我来说挺难实现的，一则我也不喜欢书只读一小半，二则感觉对于喜欢看的内容范围还是比较有限制，可能也算是比较矫情，不爱追热门的各类东西，因为往往会有一些跟大众不一致的观点看法，显得格格不入。所以还是这个打卡活动可能会比较适合我，书是人类进步的阶梯。
到现在是打卡了三天了，读的主要是白岩松的《幸福了吗》，对于白岩松，我们这一代人是比较熟悉，并且整体印象比较不错的一个央视主持人，从《焦点访谈》开始，到疫情期间的各类一线节目，可能对我来说是个三观比较正，敢于说一些真话的主持人，这中间其实是有个空档期，没怎么看电视，也不太关注了，只是在疫情期间的节目，还是一如既往地给人一种可靠的感觉，正好有一次偶然微信读书推荐了白岩松的这本书，就看了一部分，正好这次继续往下看，因为相对来讲不会很晦涩，并且从这位知名央视主持人的角度分享他的过往和想法看法，还是比较有意思的。
从对汶川地震，08 年奥运等往事的回忆和一些细节的呈现，也让我了解比较多当时所不知道的，特别是汶川地震，那时的我还在读高中，真的是看着电视，作为“猛男”都忍不住泪目了，共和国之殇，多难兴邦，但是这对于当事人来说，都是一场醒不过来的噩梦。
然后是对于足球的热爱，其实光这个就能掰扯很多，因为我不爱足球，只爱篮球，其中原因有的没的也挺多可以说的，但是看了他的书，才能比较深入的了解一个足球迷，对足球，对中国足球，对世界杯，对阿根廷的感情。
接下去还是想能继续坚持下去，加油！

]]> - 生活 读后感 + 生活 白岩松 幸福了吗 @@ -4599,28 +4621,6 @@ user3: 足球 - - 关于公共交通再吐个槽 - /2021/03/21/%E5%85%B3%E4%BA%8E%E5%85%AC%E5%85%B1%E4%BA%A4%E9%80%9A%E5%86%8D%E5%90%90%E4%B8%AA%E6%A7%BD/ - 事情源于周末来回家发生的两件事情，先是回去的时候从高铁下车要坐公交，现在算是有个比较好的临时候车点了，但是可能由于疫情好转，晚上都不用检查健康码就可以进候车点，但是上公交的时候还是需要看健康码，一般情况下从高铁下来的，各个地方的人都有，而且也不太清楚这边上公交车需要查验健康码，我的一个看法是候车的时候就应该放个横幅告示，或者再配合喇叭循环播放，请提前准备好健康码，上车前需要查验，因为像这周的情况，我乘坐的那辆车是间隔时间比较长，而且终点是工业开发区，可能是比较多外来务工人员的目的地，正好这部分人可能对于操作手机检验健康码这个事情不太熟悉，所以结果就是头上几个不知道怎么搞出来健康码，然后让几乎有满满一整车的人在后面堵着，司机又非常厌烦那些没有提前出示健康码的，有位乘客搞得久了点，还被误以为没刷卡买票，差点吵起来，其实公共交通或者高铁站负责的在公交指引路线上多写一句上车前需要查验健康码，可能就能改善比较多，还有就是那个积水的路，这个吐槽起来就一大坨了，整个绍兴像 dayuejin 一样到处都是破路。
第二个就是来杭州的时候，经过人行横道，远处车道的公交车停下来等我们了，为了少添麻烦总想快点穿过去，但是这时靠近我们的车道（晚上光线较暗，可见度不佳）有一辆从远处来的奥迪 A4 还是 A5 这种的车反而想加速冲过去，如果少看一下可能我已经残了，交规考的靠近人行道要减速好像基本都是个摆设了，杭州也只有公交车因为一些考核指标原因会主动礼让，人其实需要有同理心，虽然可能有些人是开车多于骑车走路的，但是总也不可能永远不穿人行道吧，甚至这些人可能还会在人行道红灯的时候走过去。这个事情不是吐槽公共交通的，只是也有些许关系，想起来还有一件事也是刚才来杭州的时候看到的，等公交的时候看到有辆路虎要加塞，而目标车道刚好是辆大货车，大货车看到按了喇叭，路虎犹豫了下还是挤进去了，可能是对路虎的扛撞性能非常自信吧，反正我是挺后怕的，这种级别的车，被撞了的话估计还是鸡蛋撞石头，吨位惯性在那，这里再延伸下，挺多开豪车的人好像都觉得这路上路权更大一些，谁谁都得让着他，可能实际吃亏的不多，所以越加巩固了这种思维，当真的碰到不管的可能就会明白了，路权这个事情在天朝也基本没啥人重视，也没想说个结论，就到这吧

-]]> - - 生活 - 公交 - - - 生活 - 开车 - 加塞 - 糟心事 - 规则 - 公交 - 路政规划 - 基础设施 - 杭州 - 健康码 - - 分享一次折腾老旧笔记本的体验-续篇 /2023/02/12/%E5%88%86%E4%BA%AB%E4%B8%80%E6%AC%A1%E6%8A%98%E8%85%BE%E8%80%81%E6%97%A7%E7%AC%94%E8%AE%B0%E6%9C%AC%E7%9A%84%E4%BD%93%E9%AA%8C-%E7%BB%AD%E7%AF%87/ @@ -4635,9 +4635,9 @@ user3: - 分享一次折腾老旧笔记本的体验 - /2023/02/05/%E5%88%86%E4%BA%AB%E4%B8%80%E6%AC%A1%E6%8A%98%E8%85%BE%E8%80%81%E6%97%A7%E7%AC%94%E8%AE%B0%E6%9C%AC%E7%9A%84%E4%BD%93%E9%AA%8C/ - 上大学的时候买了第一个笔记本，是联想的小y，y460，配置应该是 i5+2g 内存，500g 硬盘，ati 5650 的显卡，那时候还是比较时髦的带有集显和独显切换的，一些人也觉得它算是一代“神机”，陪我度过了大学四年，还有毕业后的第一年，记得中间还用的比较曲折，差不多第一学期末的时候硬盘感觉有时候会文件操作卡住，去售后看了下，果然硬盘出问题了，还在当场把硬盘的东西都拷贝到新买的移动硬盘里，不过联想的售后还是比较不错的，在保内可以直接免费换，如果出保了估计就要修不起了，后面出了个很大的问题，就是屏幕花屏了，而且它的花屏是横着的会有那种上升的变化，一开始感觉跟湿度还有温度有点关系，天气冷了就很容易出现，天气热了就好一点，出现的概率小一点，而且是合盖后再开会好，过一会又会上升，只是这么度过了保修期，去售后问了下，修一下要两千多，后来是在玉泉学校里面的维修店，好像是花了六百多，省是省了很多，但是后面使用的时候发现有点漏光，而且两三个亮点，总归还是给我那不富裕的经济条件带来了一个正常屏幕，不过是挺影响使用，严格来说都没法用了，后面基本是大半个屏幕花掉，接近整个屏幕花掉，至此大学就是这么用过去了。
噢对了，中间在大二的时候加了一条 2g 的内存，因为像操作系统课需要用虚拟机，2g 内存不太够，不过那会用的都是 32 位的 win7 系统，实际使用用不到 4g 内存，得使用破解补丁才能识别到，后来在大学毕业后由于收入也低，想换其他电脑，特别是 mac，买不起，电脑在那会还会玩玩 DNF，但是风扇声很大，也想优化下，就买了个 msata 的固态硬盘，因为刚好有个口子留着，在那之前一直搜到的是把光驱位拆掉换上 sata 固态硬盘，这对于那会的我来说操作难度实在有点大，换上了msata 固态之后还是有比较大的提升的，把操作系统装到固态硬盘后其他盘就只放数据了，后面还装过黑苹果，只是不小心被室友强制关机了，之后就起不来了，也不知道啥原因，后续想继续按原来的操作装，也没成功，再往后就配了一台台式机，这个笔记本就放在那没啥用了，后面偶尔会拿出来用一下，特别是疫情那会充当了 LD 的临时使用机器。
最近一次就是想把行车记录仪里的视频导出来，结果上传的时候我点了下 win10 的更新，重启后这个机器就起不来了，一开始以为顶多是个重装系统，结果重装也不行，就进不去，插着 U 盘也起不来，一开始还能进 BIOS，后面就直接进不去了，像内存条脏了，擦下金手指什么的，都没搞定，想着也只可能是主板上的部件坏了，所以就开始了这趟半作死之旅，买了块主板来换，拆这个笔记本是真的够难的，开机键那一条是真的拆不开，后面还把两个扣子扳坏了，里面的排线插口还几个也拔坏了，幸好用买来的主板装上还能用，但是后面就很奇怪了，因为这个电脑装了 Ubuntu 跟 win10 的双系统，Ubuntu 能正常起来，但是 win10 就是起不来，插上老毛桃或者 win10 的启动盘都是起不来，老毛桃是能起来，但是进不了 pe，插启动盘又报 0xc00000e9 错误码，现在想着是不是这个固态硬盘有点问题或者还是内存问题，只能后续再看了，拆机的时候也找不到视频，机器实在是太老了，后面再试试看。

+ 分享一次折腾老旧笔记本的体验-续续篇 + /2023/02/26/%E5%88%86%E4%BA%AB%E4%B8%80%E6%AC%A1%E6%8A%98%E8%85%BE%E8%80%81%E6%97%A7%E7%AC%94%E8%AE%B0%E6%9C%AC%E7%9A%84%E4%BD%93%E9%AA%8C-%E7%BB%AD%E7%BB%AD%E7%AF%87/ + 上周因为一些事情没回去，买好了内存条这周才回去用，结果不知道是 U 盘的问题还是什么其他原因原来装的那个系统起不来，然后想用之前一直用的 LD 的笔记本，结果 LD 的老笔记本也起不来了，一直卡在启动界面，猜测可能是本身也比较老了，用的机械硬盘会不会被我一直动而损坏了，所以就想搞个老毛桃跟新搞一个启动盘，结果这周最大的坑就在这了，在我的 15 寸 mbp 上用etcher做了个 win10 的启动盘，可能是分区表格式是 GUID，不是 MBR 的，老电脑不能识别，就像装个虚拟机来做启动盘，结果像老毛桃不支持这种用虚拟机的，需要本地磁盘，然后我就有用 bootcamp 安装了个 win10，又没网络，查了下网络需要用 bootcamp 下载 Windows Support 软件，下了好久一直没下完，后来又提示连不上苹果服务器，好不容易下完了，开启 win10 后，安装到一半就蓝屏了，真的是够操蛋的，在这个时候真的很需要有一个 Windows 机器的支持，LD 的那个笔记本也跟我差不多老了，虽然比较慢但之前好歹也还可以用，结果这下也被我弄坏了，家里就没有其他机器可以支持了，有点巧妇难为无米之炊的赶脚，而且还是想再折腾下我的老电脑，后面看看打算做几个 U 盘，分工职责明确，一个老毛桃的PE 盘，老毛桃的虽然不是很纯净的，但是是我一直以来用过内置工具比较全，修复启动功能比较强大的一个 pe，没用过 winpe，后续可以考虑使用下，一个 win7 的启动盘，因为是老电脑，如果后面是新的电脑可以考虑是 win10，一个 win to go 盘，这样我的 mbp 就可以直接用 win10 了，不过想来也还是要有一台 win 机器才比较好，不然很多时候都是在折腾工具，工欲善其事必先利其器，后面也可以考虑能够更深入的去了解主板的一些问题，我原来的那个主板可能是一些小的电阻等问题，如果能自己学习解决就更好了，有时候研究下还是有意思的。

]]> Windows @@ -4648,9 +4648,9 @@ user3: - 分享一次折腾老旧笔记本的体验-续续篇 - /2023/02/26/%E5%88%86%E4%BA%AB%E4%B8%80%E6%AC%A1%E6%8A%98%E8%85%BE%E8%80%81%E6%97%A7%E7%AC%94%E8%AE%B0%E6%9C%AC%E7%9A%84%E4%BD%93%E9%AA%8C-%E7%BB%AD%E7%BB%AD%E7%AF%87/ - 上周因为一些事情没回去，买好了内存条这周才回去用，结果不知道是 U 盘的问题还是什么其他原因原来装的那个系统起不来，然后想用之前一直用的 LD 的笔记本，结果 LD 的老笔记本也起不来了，一直卡在启动界面，猜测可能是本身也比较老了，用的机械硬盘会不会被我一直动而损坏了，所以就想搞个老毛桃跟新搞一个启动盘，结果这周最大的坑就在这了，在我的 15 寸 mbp 上用etcher做了个 win10 的启动盘，可能是分区表格式是 GUID，不是 MBR 的，老电脑不能识别，就像装个虚拟机来做启动盘，结果像老毛桃不支持这种用虚拟机的，需要本地磁盘，然后我就有用 bootcamp 安装了个 win10，又没网络，查了下网络需要用 bootcamp 下载 Windows Support 软件，下了好久一直没下完，后来又提示连不上苹果服务器，好不容易下完了，开启 win10 后，安装到一半就蓝屏了，真的是够操蛋的，在这个时候真的很需要有一个 Windows 机器的支持，LD 的那个笔记本也跟我差不多老了，虽然比较慢但之前好歹也还可以用，结果这下也被我弄坏了，家里就没有其他机器可以支持了，有点巧妇难为无米之炊的赶脚，而且还是想再折腾下我的老电脑，后面看看打算做几个 U 盘，分工职责明确，一个老毛桃的PE 盘，老毛桃的虽然不是很纯净的，但是是我一直以来用过内置工具比较全，修复启动功能比较强大的一个 pe，没用过 winpe，后续可以考虑使用下，一个 win7 的启动盘，因为是老电脑，如果后面是新的电脑可以考虑是 win10，一个 win to go 盘，这样我的 mbp 就可以直接用 win10 了，不过想来也还是要有一台 win 机器才比较好，不然很多时候都是在折腾工具，工欲善其事必先利其器，后面也可以考虑能够更深入的去了解主板的一些问题，我原来的那个主板可能是一些小的电阻等问题，如果能自己学习解决就更好了，有时候研究下还是有意思的。

+ 分享一次折腾老旧笔记本的体验 + /2023/02/05/%E5%88%86%E4%BA%AB%E4%B8%80%E6%AC%A1%E6%8A%98%E8%85%BE%E8%80%81%E6%97%A7%E7%AC%94%E8%AE%B0%E6%9C%AC%E7%9A%84%E4%BD%93%E9%AA%8C/ + 上大学的时候买了第一个笔记本，是联想的小y，y460，配置应该是 i5+2g 内存，500g 硬盘，ati 5650 的显卡，那时候还是比较时髦的带有集显和独显切换的，一些人也觉得它算是一代“神机”，陪我度过了大学四年，还有毕业后的第一年，记得中间还用的比较曲折，差不多第一学期末的时候硬盘感觉有时候会文件操作卡住，去售后看了下，果然硬盘出问题了，还在当场把硬盘的东西都拷贝到新买的移动硬盘里，不过联想的售后还是比较不错的，在保内可以直接免费换，如果出保了估计就要修不起了，后面出了个很大的问题，就是屏幕花屏了，而且它的花屏是横着的会有那种上升的变化，一开始感觉跟湿度还有温度有点关系，天气冷了就很容易出现，天气热了就好一点，出现的概率小一点，而且是合盖后再开会好，过一会又会上升，只是这么度过了保修期，去售后问了下，修一下要两千多，后来是在玉泉学校里面的维修店，好像是花了六百多，省是省了很多，但是后面使用的时候发现有点漏光，而且两三个亮点，总归还是给我那不富裕的经济条件带来了一个正常屏幕，不过是挺影响使用，严格来说都没法用了，后面基本是大半个屏幕花掉，接近整个屏幕花掉，至此大学就是这么用过去了。
噢对了，中间在大二的时候加了一条 2g 的内存，因为像操作系统课需要用虚拟机，2g 内存不太够，不过那会用的都是 32 位的 win7 系统，实际使用用不到 4g 内存，得使用破解补丁才能识别到，后来在大学毕业后由于收入也低，想换其他电脑，特别是 mac，买不起，电脑在那会还会玩玩 DNF，但是风扇声很大，也想优化下，就买了个 msata 的固态硬盘，因为刚好有个口子留着，在那之前一直搜到的是把光驱位拆掉换上 sata 固态硬盘，这对于那会的我来说操作难度实在有点大，换上了msata 固态之后还是有比较大的提升的，把操作系统装到固态硬盘后其他盘就只放数据了，后面还装过黑苹果，只是不小心被室友强制关机了，之后就起不来了，也不知道啥原因，后续想继续按原来的操作装，也没成功，再往后就配了一台台式机，这个笔记本就放在那没啥用了，后面偶尔会拿出来用一下，特别是疫情那会充当了 LD 的临时使用机器。
最近一次就是想把行车记录仪里的视频导出来，结果上传的时候我点了下 win10 的更新，重启后这个机器就起不来了，一开始以为顶多是个重装系统，结果重装也不行，就进不去，插着 U 盘也起不来，一开始还能进 BIOS，后面就直接进不去了，像内存条脏了，擦下金手指什么的，都没搞定，想着也只可能是主板上的部件坏了，所以就开始了这趟半作死之旅，买了块主板来换，拆这个笔记本是真的够难的，开机键那一条是真的拆不开，后面还把两个扣子扳坏了，里面的排线插口还几个也拔坏了，幸好用买来的主板装上还能用，但是后面就很奇怪了，因为这个电脑装了 Ubuntu 跟 win10 的双系统，Ubuntu 能正常起来，但是 win10 就是起不来，插上老毛桃或者 win10 的启动盘都是起不来，老毛桃是能起来，但是进不了 pe，插启动盘又报 0xc00000e9 错误码，现在想着是不是这个固态硬盘有点问题或者还是内存问题，只能后续再看了，拆机的时候也找不到视频，机器实在是太老了，后面再试试看。

]]> Windows @@ -4695,25 +4695,6 @@ user3: git - - 分享记录一下一个 scp 操作方法 - /2022/02/06/%E5%88%86%E4%BA%AB%E8%AE%B0%E5%BD%95%E4%B8%80%E4%B8%8B%E4%B8%80%E4%B8%AA-scp-%E6%93%8D%E4%BD%9C%E6%96%B9%E6%B3%95/ - scp 是个在服务器之间拷贝文件的一个常用命令，有时候有个场景是比如我们需要拷贝一些带有共同前缀的文件，但是有一个问题是比如我们有使用 zsh 的话，会出现一个报错，

-
zsh: no matches found: root@100.100.100.100://root/prefix*
-

这里就比较奇怪了，这个前缀的文件肯定是有的，这里其实是由于 zsh 会对 * 进行展开，这个可以在例如 ls 命令在使用中就可以发现 zsh 有这个特性
需要使用双引号或单引号将路径包起来或者在*之前加反斜杠\来阻止对*展开和转义

-
scp root@100.100.100.100://root/prefix* .
-

通过使用双引号"进行转义

-
scp root@100.100.100.100:"//root/prefix*" .
-

或者可以将 shell 从 zsh 切换成 bash

-]]> - - shell - 小技巧 - - - scp - - 周末我在老丈人家打了天小工 /2020/08/16/%E5%91%A8%E6%9C%AB%E6%88%91%E5%9C%A8%E8%80%81%E4%B8%88%E4%BA%BA%E5%AE%B6%E6%89%93%E4%BA%86%E5%A4%A9%E5%B0%8F%E5%B7%A5/ @@ -4762,9 +4743,28 @@ user3: - 在老丈人家的小工记三 - /2020/09/13/%E5%9C%A8%E8%80%81%E4%B8%88%E4%BA%BA%E5%AE%B6%E7%9A%84%E5%B0%8F%E5%B7%A5%E8%AE%B0%E4%B8%89/ - 小工记三

前面这两周周末也都去老丈人家帮忙了，上上周周六先是去了那个在装修的旧房子那，把三楼收拾了下，因为要搬进来住，来不及等二楼装修好，就要把三楼里的东西都整理干净，这个活感觉是比较 easy，原来是就准备把三楼当放东西仓储的地方了，我们乡下大部分三层楼都是这么用的，这次也是没办法，之前搬进来的木头什么的都搬出去，主要是这上面灰尘太多，后面清理鼻孔的时候都是黑色的了，把东西都搬出去以后主要是地还是很脏，就扫了地拖了地，因为是水泥地，灰尘又太多了，拖起来都是会灰尘扬起来，整个脱完了的确干净很多，然而这会就出了个大乌龙，我们清理的是三楼的西边一间，结果老丈人上来说要住东边那间的🤦‍♂️，不过其实西边的也得清理，因为还是要放被子什么的，不算是白费功夫，接着清理东边那间，之前这个房子做过群租房，里面有个高低铺的床，当时觉得可以用在放被子什么的就没扔，只是拆掉了放旁边，我们就把它擦干净了又装好，发现螺丝🔩少了几个，亘古不变的真理，拆了以后装要不就多几个要不就少几个，不是很牢靠，不过用来放放被子省得放地上总还是可以的，对了前面还做了个事情就是铺地毯，其实也不是地毯，就是类似于墙布雨篷布那种，别人不用了送给我们的，三楼水泥地也不会铺瓷砖地板了就放一下，干净好看点，不过大小不合适要裁一下，那把剪刀是真的太难用了，我手都要抽筋了，它就是刀口只有一小个点是能剪下来的，其他都是钝的，后来还是用刀片直接裁，铺好以后，真的感觉也不太一样了，焕然一新的感觉
差不多中午了就去吃饭了，之前两次是去了一家小饭店，还是还比较干净，但是店里菜不好吃，还死贵，这次去了一家小快餐店，口味好，便宜，味道是真的不错，带鱼跟黄鱼都好吃，一点都不腥，我对这类比较腥的鱼真的是很挑剔的，基本上除了家里做的很少吃外面的，那天抱着试试的态度吃了下，真的还不错，后来丈母娘说好像这家老板是给别人结婚喜事酒席当厨师的，怪不得做的好吃，其实本来是有一点小抗拒，怕不干净什么的，后来发现菜很好吃，而且可能是老丈人跟干活的师傅去吃的比较多，老板很客气，我们吃完饭，还给我们买了葡萄吃，不过这家店有一个槽点，就是饭比较不好吃，有时候会夹生，不过后面聊起来其实是这种小菜馆饭点的通病，烧的太早太多容易多出来浪费，烧的迟了不够吃，而且大的电饭锅比较不容易烧好。
下午前面还是在处理三楼的，窗户上各种钉子，实在是太多了，我后面在走廊上排了一排🤦‍♂️，有些是直接断了，有些是就撬了出来，感觉我在杭州租房也没有这样子各种钉钉子，挂下衣服什么的也不用这么多吧，比较不能理解，搞得到处都是钉子。那天我爸也去帮忙了，主要是在卫生间里做白缝，其实也是个技术活，印象中好像我小时候自己家里也做过这个事情，但是比较模糊了，后面我们三楼搞完了就去帮我爸了，前面是我老婆二爹在那先刷上白缝，这里叫白缝，有些考究的也叫美缝，就是瓷砖铺完之后的缝，如果不去弄的话，里面水泥的颜色就露出来了，而且容易渗水，所以就要用白水泥加胶水搅拌之后糊在缝上，但是也不是直接糊，先要把缝抠一抠，因为铺瓷砖的还不会仔细到每个缝里的水泥都是一样满，而且也需要一些空间糊上去，不然就太表面的一层很容易被水直接冲掉了，然后这次其实也不是用的白水泥，而是直接现成买来就已经配好的用来填缝的，兑水搅拌均匀就好了，后面就主要是我跟我爸在搞，那个时候真的觉得我实在是太胖了，蹲下去真的没一会就受不了了，膝盖什么的太难受了，后面我跪着刷，然后膝盖又疼，也是比较不容易，不过我爸动作很快，我中间跪累了休息一会，我爸就能搞一大片，后面其实我也没做多少（谦虚一下），总体来讲这次不是很累，就是蹲着跪着腿有点受不了，是应该好好减肥了。

+ 分享记录一下一个 scp 操作方法 + /2022/02/06/%E5%88%86%E4%BA%AB%E8%AE%B0%E5%BD%95%E4%B8%80%E4%B8%8B%E4%B8%80%E4%B8%AA-scp-%E6%93%8D%E4%BD%9C%E6%96%B9%E6%B3%95/ + scp 是个在服务器之间拷贝文件的一个常用命令，有时候有个场景是比如我们需要拷贝一些带有共同前缀的文件，但是有一个问题是比如我们有使用 zsh 的话，会出现一个报错，

+
zsh: no matches found: root@100.100.100.100://root/prefix*
+

这里就比较奇怪了，这个前缀的文件肯定是有的，这里其实是由于 zsh 会对 * 进行展开，这个可以在例如 ls 命令在使用中就可以发现 zsh 有这个特性
需要使用双引号或单引号将路径包起来或者在*之前加反斜杠\来阻止对*展开和转义

+
scp root@100.100.100.100://root/prefix* .
+

通过使用双引号"进行转义

+
scp root@100.100.100.100:"//root/prefix*" .
+

或者可以将 shell 从 zsh 切换成 bash

+]]> + + shell + 小技巧 + + + scp + + + + 在老丈人家的小工记五 + /2020/10/18/%E5%9C%A8%E8%80%81%E4%B8%88%E4%BA%BA%E5%AE%B6%E7%9A%84%E5%B0%8F%E5%B7%A5%E8%AE%B0%E4%BA%94/ + 终于回忆起来了，年纪大了写这种东西真的要立马写，不然很容易想不起来，那天应该是 9 月 12 日，也就是上周六，因为我爸也去了，而且娘亲（丈母娘，LD 这么叫，我也就随了她这么叫，当然是背后，当面就叫妈）也在那，早上一到那二爹就给我爸指挥了活，要挖一条院子的出水道，自己想出来的词，因为觉得下水道是竖的，在那稍稍帮了一会会忙，然后我还是比较惯例的跟着 LD 还有娘亲去住的家里，主要是老丈人可能也不太想让我干太累的活，因为上次已经差不多把三楼都整理干净了，然后就是二楼了，二楼说实话我也帮不上什么忙，主要是衣服被子什么的，正好是有张以前小孩子睡过的那种摇篮床，看上去虽然有一些破损，整体还是不错的，所以打算拿过去，我就负责把它拆掉了，比较简单的是只要拧螺丝就行了，但是其实是用了好多好多工具才搞定的，一开始只要螺丝刀就行了，但是因为年代久了，后面的螺帽也有点锈住或者本身就会串着会一起动，所以拿来了个扳手，大部分的其实都被这两个工具给搞定了，但是后期大概还剩下四分之一的时候，有一颗完全锈住，并且螺纹跟之前那些都不一样，但是这个已经是最大的螺丝刀了，也没办法换个大的了，所以又去找来个一字的，因为十字的不是也可以用一字的拧嘛，结果可能是我买的工具箱里的一字螺丝刀太新了，口子那很锋利，直接把螺丝花纹给划掉了，大的小的都划掉，然后真的变成凹进去一个圆柱体了，然后就想能不能隔一层布去拧，然而因为的确是已经变成圆柱体了，布也不太给力，不放弃的我又去找来了个老虎钳，妄图把划掉的螺丝用老虎钳钳住，另一端用扳手拧开螺帽，但是这个螺丝跟螺帽真的是生锈的太严重了，外加上钳不太牢，完全是两边一起转，实在是没办法了，在征得同意之后，直接掰断了，火死了，一颗螺丝折腾得比我拆一张床还久，那天因为早上去的也比较晚了，然后就快吃午饭了，正好想着带一点东西过去，就把一些脸盆，泡脚桶啥的拿过去了，先是去吃了饭，还是在那家快餐店，菜的口味还是依然不错，就是人比较多，我爸旁边都是素菜，都没怎么吃远一点的荤菜，下次要早点去，把荤菜放我爸旁边😄（PS：他们家饭还是依然尴尬，需要等），吃完就开到在修的房子那把东西拿了出来，我爸已经动作很快的打了一小半的地沟了，说实话那玩意真的是很重，我之前把它从三楼拿下来，就觉得这个太重了，这次还要用起来，感觉我的手会分分钟废掉，不过一开始我还是跟着LD去了住的家里，惯例睡了午觉，那天睡得比较踏实，竟然睡了一个小时，醒了想了下，其实LD她们收拾也用不上我（没啥力气活），我还是去帮我爸他们，跟LD说了下就去了在修的老房子那，两位老爹在一起钻地，看着就很累，我连忙上去想换一会他们，因为刚好是钻到混凝土地线，特别难，力道不够就会滑开，用蛮力就是钻进去拔不出来，原理是因为本身浇的时候就是很紧实的，需要边钻边动，那家伙实在是太重了，真的是汗如雨下，基本是三个人轮流来，我是个添乱的，经常卡住，然后把地线，其实就是一条混凝土横梁，里面还有14跟18的钢筋，需要割断，这个割断也是很有技巧，钢筋本身在里面是受到挤压的，直接用切割的，到快断掉的时候就会崩一下，非常危险，还是老丈人比较有经验，要留一点点，然后直接用榔头敲断就好了，本来以为这个是最难的了，结果下面是一块非常大的青基石，而且也是石头跟石头挤一块，边上一点点打钻有点杯水车薪，后来是用那种螺旋的钻，钻四个洞，相对位置大概是个长方形，这样子把中间这个长方形钻出来就比较容易地能拿出来了，后面的也容易搞出来了，后面的其实难度不是特别大了，主要是地沟打好之后得看看高低是不是符合要求的，不能本来是往外排水的反而外面高，这个怎么看就又很有技巧了，一般在地上的只要侧着看一下就好了，考究点就用下水平尺，但是在地下的，不用水平尺，其实可以借助于地沟里正要放进去的水管，放点水进去，看水往哪流就行了，铺好水管后，就剩填埋的活了，不是太麻烦了，那天真的是累到了，打那个混凝土的时候我真的是把我整个人压上去了，不过也挺爽的，有点把平时无处发泄的蛮力发泄出去了。

]]> 生活 @@ -4782,9 +4782,9 @@ user3: - 在老丈人家的小工记五 - /2020/10/18/%E5%9C%A8%E8%80%81%E4%B8%88%E4%BA%BA%E5%AE%B6%E7%9A%84%E5%B0%8F%E5%B7%A5%E8%AE%B0%E4%BA%94/ - 终于回忆起来了，年纪大了写这种东西真的要立马写，不然很容易想不起来，那天应该是 9 月 12 日，也就是上周六，因为我爸也去了，而且娘亲（丈母娘，LD 这么叫，我也就随了她这么叫，当然是背后，当面就叫妈）也在那，早上一到那二爹就给我爸指挥了活，要挖一条院子的出水道，自己想出来的词，因为觉得下水道是竖的，在那稍稍帮了一会会忙，然后我还是比较惯例的跟着 LD 还有娘亲去住的家里，主要是老丈人可能也不太想让我干太累的活，因为上次已经差不多把三楼都整理干净了，然后就是二楼了，二楼说实话我也帮不上什么忙，主要是衣服被子什么的，正好是有张以前小孩子睡过的那种摇篮床，看上去虽然有一些破损，整体还是不错的，所以打算拿过去，我就负责把它拆掉了，比较简单的是只要拧螺丝就行了，但是其实是用了好多好多工具才搞定的，一开始只要螺丝刀就行了，但是因为年代久了，后面的螺帽也有点锈住或者本身就会串着会一起动，所以拿来了个扳手，大部分的其实都被这两个工具给搞定了，但是后期大概还剩下四分之一的时候，有一颗完全锈住，并且螺纹跟之前那些都不一样，但是这个已经是最大的螺丝刀了，也没办法换个大的了，所以又去找来个一字的，因为十字的不是也可以用一字的拧嘛，结果可能是我买的工具箱里的一字螺丝刀太新了，口子那很锋利，直接把螺丝花纹给划掉了，大的小的都划掉，然后真的变成凹进去一个圆柱体了，然后就想能不能隔一层布去拧，然而因为的确是已经变成圆柱体了，布也不太给力，不放弃的我又去找来了个老虎钳，妄图把划掉的螺丝用老虎钳钳住，另一端用扳手拧开螺帽，但是这个螺丝跟螺帽真的是生锈的太严重了，外加上钳不太牢，完全是两边一起转，实在是没办法了，在征得同意之后，直接掰断了，火死了，一颗螺丝折腾得比我拆一张床还久，那天因为早上去的也比较晚了，然后就快吃午饭了，正好想着带一点东西过去，就把一些脸盆，泡脚桶啥的拿过去了，先是去吃了饭，还是在那家快餐店，菜的口味还是依然不错，就是人比较多，我爸旁边都是素菜，都没怎么吃远一点的荤菜，下次要早点去，把荤菜放我爸旁边😄（PS：他们家饭还是依然尴尬，需要等），吃完就开到在修的房子那把东西拿了出来，我爸已经动作很快的打了一小半的地沟了，说实话那玩意真的是很重，我之前把它从三楼拿下来，就觉得这个太重了，这次还要用起来，感觉我的手会分分钟废掉，不过一开始我还是跟着LD去了住的家里，惯例睡了午觉，那天睡得比较踏实，竟然睡了一个小时，醒了想了下，其实LD她们收拾也用不上我（没啥力气活），我还是去帮我爸他们，跟LD说了下就去了在修的老房子那，两位老爹在一起钻地，看着就很累，我连忙上去想换一会他们，因为刚好是钻到混凝土地线，特别难，力道不够就会滑开，用蛮力就是钻进去拔不出来，原理是因为本身浇的时候就是很紧实的，需要边钻边动，那家伙实在是太重了，真的是汗如雨下，基本是三个人轮流来，我是个添乱的，经常卡住，然后把地线，其实就是一条混凝土横梁，里面还有14跟18的钢筋，需要割断，这个割断也是很有技巧，钢筋本身在里面是受到挤压的，直接用切割的，到快断掉的时候就会崩一下，非常危险，还是老丈人比较有经验，要留一点点，然后直接用榔头敲断就好了，本来以为这个是最难的了，结果下面是一块非常大的青基石，而且也是石头跟石头挤一块，边上一点点打钻有点杯水车薪，后来是用那种螺旋的钻，钻四个洞，相对位置大概是个长方形，这样子把中间这个长方形钻出来就比较容易地能拿出来了，后面的也容易搞出来了，后面的其实难度不是特别大了，主要是地沟打好之后得看看高低是不是符合要求的，不能本来是往外排水的反而外面高，这个怎么看就又很有技巧了，一般在地上的只要侧着看一下就好了，考究点就用下水平尺，但是在地下的，不用水平尺，其实可以借助于地沟里正要放进去的水管，放点水进去，看水往哪流就行了，铺好水管后，就剩填埋的活了，不是太麻烦了，那天真的是累到了，打那个混凝土的时候我真的是把我整个人压上去了，不过也挺爽的，有点把平时无处发泄的蛮力发泄出去了。

+ 在老丈人家的小工记三 + /2020/09/13/%E5%9C%A8%E8%80%81%E4%B8%88%E4%BA%BA%E5%AE%B6%E7%9A%84%E5%B0%8F%E5%B7%A5%E8%AE%B0%E4%B8%89/ + 小工记三

前面这两周周末也都去老丈人家帮忙了，上上周周六先是去了那个在装修的旧房子那，把三楼收拾了下，因为要搬进来住，来不及等二楼装修好，就要把三楼里的东西都整理干净，这个活感觉是比较 easy，原来是就准备把三楼当放东西仓储的地方了，我们乡下大部分三层楼都是这么用的，这次也是没办法，之前搬进来的木头什么的都搬出去，主要是这上面灰尘太多，后面清理鼻孔的时候都是黑色的了，把东西都搬出去以后主要是地还是很脏，就扫了地拖了地，因为是水泥地，灰尘又太多了，拖起来都是会灰尘扬起来，整个脱完了的确干净很多，然而这会就出了个大乌龙，我们清理的是三楼的西边一间，结果老丈人上来说要住东边那间的🤦‍♂️，不过其实西边的也得清理，因为还是要放被子什么的，不算是白费功夫，接着清理东边那间，之前这个房子做过群租房，里面有个高低铺的床，当时觉得可以用在放被子什么的就没扔，只是拆掉了放旁边，我们就把它擦干净了又装好，发现螺丝🔩少了几个，亘古不变的真理，拆了以后装要不就多几个要不就少几个，不是很牢靠，不过用来放放被子省得放地上总还是可以的，对了前面还做了个事情就是铺地毯，其实也不是地毯，就是类似于墙布雨篷布那种，别人不用了送给我们的，三楼水泥地也不会铺瓷砖地板了就放一下，干净好看点，不过大小不合适要裁一下，那把剪刀是真的太难用了，我手都要抽筋了，它就是刀口只有一小个点是能剪下来的，其他都是钝的，后来还是用刀片直接裁，铺好以后，真的感觉也不太一样了，焕然一新的感觉
差不多中午了就去吃饭了，之前两次是去了一家小饭店，还是还比较干净，但是店里菜不好吃，还死贵，这次去了一家小快餐店，口味好，便宜，味道是真的不错，带鱼跟黄鱼都好吃，一点都不腥，我对这类比较腥的鱼真的是很挑剔的，基本上除了家里做的很少吃外面的，那天抱着试试的态度吃了下，真的还不错，后来丈母娘说好像这家老板是给别人结婚喜事酒席当厨师的，怪不得做的好吃，其实本来是有一点小抗拒，怕不干净什么的，后来发现菜很好吃，而且可能是老丈人跟干活的师傅去吃的比较多，老板很客气，我们吃完饭，还给我们买了葡萄吃，不过这家店有一个槽点，就是饭比较不好吃，有时候会夹生，不过后面聊起来其实是这种小菜馆饭点的通病，烧的太早太多容易多出来浪费，烧的迟了不够吃，而且大的电饭锅比较不容易烧好。
下午前面还是在处理三楼的，窗户上各种钉子，实在是太多了，我后面在走廊上排了一排🤦‍♂️，有些是直接断了，有些是就撬了出来，感觉我在杭州租房也没有这样子各种钉钉子，挂下衣服什么的也不用这么多吧，比较不能理解，搞得到处都是钉子。那天我爸也去帮忙了，主要是在卫生间里做白缝，其实也是个技术活，印象中好像我小时候自己家里也做过这个事情，但是比较模糊了，后面我们三楼搞完了就去帮我爸了，前面是我老婆二爹在那先刷上白缝，这里叫白缝，有些考究的也叫美缝，就是瓷砖铺完之后的缝，如果不去弄的话，里面水泥的颜色就露出来了，而且容易渗水，所以就要用白水泥加胶水搅拌之后糊在缝上，但是也不是直接糊，先要把缝抠一抠，因为铺瓷砖的还不会仔细到每个缝里的水泥都是一样满，而且也需要一些空间糊上去，不然就太表面的一层很容易被水直接冲掉了，然后这次其实也不是用的白水泥，而是直接现成买来就已经配好的用来填缝的，兑水搅拌均匀就好了，后面就主要是我跟我爸在搞，那个时候真的觉得我实在是太胖了，蹲下去真的没一会就受不了了，膝盖什么的太难受了，后面我跪着刷，然后膝盖又疼，也是比较不容易，不过我爸动作很快，我中间跪累了休息一会，我爸就能搞一大片，后面其实我也没做多少（谦虚一下），总体来讲这次不是很累，就是蹲着跪着腿有点受不了，是应该好好减肥了。

]]> 生活 @@ -4802,12 +4802,15 @@ user3: - 小工周记一 - /2023/03/05/%E5%B0%8F%E5%B7%A5%E5%91%A8%E8%AE%B0%E4%B8%80/ - 开始修老房子又可以更新这个系列了，比较无聊，就是帮着干点零活的记录，这次过去起的比较早，前几天是在翻新瓦片，到这次周六是收尾了，到了的时候先是继续筛了沙子，上周也筛了，就是只筛了一点点，筛沙子的那个像纱窗一样的还是用一扇中空的中间有一根竖档的门钉上铁丝网做的，就是沙子一直放在外面，原来是有袋子装好的，后来是风吹雨打在上面的都已经破掉，还夹杂了很多树叶什么的，需要过下筛，并且前面都是下雨天，沙子都是湿的，不太像我以前看村里有人造房子筛沙子那样，用铲子铲上去就自己都下去的，湿的就是会在一坨，所以需要铲得比较少，然后撒的比较开，这个需要一点经验，然后如果有人一起的话就可以用扫把按住扫一下，这样就会筛得比较有效，不至于都滑下去，沙子本来大部分是可以筛出来的，还有一点就是这种情况网筛需要放得坡度小一点，不然就更容易直接往下调，袋子没破的就不用过筛了，只是湿掉了的是真的重，筛完了那些破掉了的袋子里的沙子，就没有特别的事情要做了，看到大工在那打墙，有一些敲下来的好的砖头就留着，需要削一下上面的混凝土，据大工说现在砖头要七八毛一块了，后面能够重新利用还是挺值钱的，我跟 LD 就用泥刀和铁锹的在那慢慢削，砖头上的泥灰有的比较牢固有的就像直接是沙子，泥刀刮一下就下来了，有的就结合得比较牢固，不过据说以前的砖头工艺上还比较落后，这个房子差不多是三十年前了的，砖头表面都是有点不平，甚至变形，那时候可能砖头是手工烧制的，现在的砖头比较工艺可好多了，不过可能也贵了很多，后来老丈人也过来了，指导了我们拌泥灰，就是水泥和黄沙混合，以前小时候可喜欢玩这个了，可是就也搞不清楚这个是怎么搅拌的，只看见是水泥跟黄沙围城一圈，中间放水，然后一点点搬进去，首先需要先把干的水泥跟黄沙进行混合，具体的比例是老丈人说的，拌的方式有点像堆沙堆，把水泥黄沙铲起来堆起来，就一直要往这个混合堆的尖尖上堆，这样子它自己滑下来能更好地混合，来回两趟就基本混合均匀了，然后就是跟以前看过的，中间扒拉出一个空间放水，然后慢慢把周围的混合好的泥沙推进去，需要注意不要太着急，旁边的推进去太多太快就会漏水出来，一个是会把旁边的地给弄脏，另一个也铲不回水，然后就是推完所有的都混合水了，就铲起来倒一下，再将铲子翻过来捣几下，后面我们就去吃饭了，去了一家叫金记的，又贵又不太好吃的店，就是离得比较近，六七个人只有六七个菜，吃完要四百多，也是有点离谱了。
下午是重头戏，其实本来倒没啥事，就说帮忙搞下靠背（就是踢脚线上面到窗台附近的用木头还有其他材料的装饰性的），都撬撬掉，但是真的是有点离谱了，首先是撬棒真的很重，20 斤的重量（网上查的，没有真的查过），抡起来还要用力地铲进去，因为就是破坏性的要把整个都撬掉，对于我这种又没技巧又没力气的非专业选手，抡起撬棍铲两下手就开始痛了，只是也比较犟，不想刚开始弄就说太重了要休息，后面都完全靠的一点倔强劲撑着，看着里面的工艺感觉也是不容易的，直着横着的木条有好多，竖的一整条，每隔三五十公分，横着的就是三五十公分，每根都要用钉子钉起来，然后外层好像是贴上去，在同一个面的开了头之后就能靠着蛮力往下撬，但是到了转角就又要重新开头，而且最上面一根横条跟紧邻的那一块，大概十几公分，是横着的三条钉在一起，真的是大力都出不了奇迹了，用撬棍的一头用力地敲打都很震手，要从下面往上铲进去撬开一点，然后再从上面往下敲打，这里比较重要的是要小心钉子，我这次运气比较好，踩下去已经扎到了，不过正好在脚趾缝里，没有扎到脚，还是要小心的，做完这个我的手真的是差不多废了，上臂的疼痛已经动一下就受不了了，后面有撬下了最下面当踢脚线的小瓷砖，这个房子估计中间修过一次，两批水泥糊的，新的那批粘的特别牢，敲敲打打了半天才下来一点点，锤子敲上去跟一整块石头一样，震手又没有进展，整个搞完，楼上又在敲墙了，下面的灰尘也是从没见过，我一直在那洒水都完全没有缓解，就上去跟 LD 一起拣砖头，手痛到只能抬两块砖头都会痛了。
回到家里开始越来越痛，两个手就完全没法动了，应该也是肌肉拉伤了，我这样是没足够的力气也不会什么技巧，像大工说的，他们也累也难，只是为了赚钱，不过他们有了经验跟技巧，会注意怎么使力不容易受伤，怎么样比较省力，还有一点就是即使这么累，他们一般也下午五点半就下班了，真的很累了，至少还有不少时间可以回家休息，而我们的职业呢，就像 LD 说的回家就像住酒店，就只是来洗澡睡个觉，希望能改善吧

+ 在老丈人家的小工记四 + /2020/09/26/%E5%9C%A8%E8%80%81%E4%B8%88%E4%BA%BA%E5%AE%B6%E7%9A%84%E5%B0%8F%E5%B7%A5%E8%AE%B0%E5%9B%9B/ + 小工记四

第四周去的时候让我们去了现在在住的房子里，去三楼整理东西了，蛮多的东西需要收拾整理，有些需要丢一下，以前往往是把不太要用的东西就放三楼了，但是后面就不会再去收拾整理，LD 跟丈母娘负责收拾，我不太知道哪些还要的，哪些不要了，而且本来也不擅长这种收拾🤦‍♂️，然后就变成她们收拾出来废纸箱，我负责拆掉，压平，这时候终于觉得体重还算是有点作用，总体来说这个事情我其实也不擅长，不擅长的主要是捆起来，可能我总是小题大做，因为纸箱大小不一，如果不做一下分类，然后把大的折小一些的话，直接绑起来，容易拎起来就散掉了，而且一些鞋盒子这种小件的纸盒会比较薄，冰箱这种大件的比较厚，厚的比较不容易变形，需要大力踩踏，而且扎的时候需要用体重压住捆实了之后那样子才是真的捆实的，不然待会又是松松垮垮容易滑出来散架，因为压住了捆好后，下来了之后箱子就会弹开了把绳子崩紧实，感觉又是掌握到生活小技巧了😃，我这里其实比较单调无聊，然后 LD 那可以说非常厉害了，一共理出来 11 把旧电扇，还有好多没用过全新的不锈钢脸盆大大小小的，感觉比店里在卖的还多，还有是有比较多小时候的东西，特别多小时候的衣服，其实这种对我来说最难了，可能需要读一下断舍离，蛮多东西都舍不得扔，但是其实是没啥用了，然后还占地方，这天应该算是比较轻松的一天了，上午主要是把收拾出来要的和不要的搬下楼，然后下午要去把纸板给卖掉。中午还是去小快餐店吃的，在住的家里理东西还有个好处就是中午吃完饭可以小憩一下，因为我个人是非常依赖午休的，不然下午完全没精神，而且心态也会比较烦躁，一方面是客观的的确比较疲惫，另一方面应该主观心理作用也有点影响，就像上班的时候也是觉得不午睡就会很难受，心理作用也有一点，不过总之能睡还是睡一会，真的没办法就心态好点，吃完午饭之后我们就推着小平板车去收废品的地方卖掉了上午我收拾捆起来的纸板，好像卖了一百多，都是直接过地磅了，不用一捆一捆地称，不过有个小插曲，那里另外一个大爷在倒他的三轮车的时候撞了我一下，还好车速慢，屁股上肉垫后，接下来就比较麻烦了，是LD 她们两姐妹从小到大的书，也要去卖掉，小平板车就载不下了，而且着实也不太好推，轮子不太平，导致推着很累，书有好多箱，本来是想去亲戚家借电动三轮车，因为不会开摩托的那种，摩托的那种 LD 邻居家就有，可是到了那发现那个也是很大，而且刹车是用脚踩的那种，俺爹不太放心，就说第二天周日他有空会帮忙去载了卖掉的，然后比较搞笑的来了，丈母娘看错了时间，以为已经快五点了，就让我们顺便在车里带点东西去在修的房子，放到那边三楼去，到了那还跟老丈人说已经这么迟了要赶紧去菜场买菜了，结果我们回来以后才发现看错了一个小时🤦‍♂️。
前面可以没提，前三周去的我们一般就周六去一天，然后周日因为要早点回杭州，而且可能想让我们周日能休息下，但是这周就因为周日的时候我爸要去帮忙载书，然后 LD 姐姐也会过来收拾东西，我们周日就又去整理收拾了，周日由于俺爹去的很早，我过去的时候书已经木有了，主要是去收拾东西了，把一些有用没用的继续整理，基本上三楼的就处理完毕了，舒了一大口气，毕竟让丈母娘一个人收拾实在是太累了，但是要扔掉的衣服比较棘手，附近知道的青蛙回收桶被推倒了，其他地方也不知道哪里有，我们就先载了一些东西去在修的房子那，然后去找青蛙桶，结果一个小区可以进，但是已经满了，另一个不让进，后来只能让 LD 姐姐带去她们小区扔了，塞了满满一车。因为要赶回杭州的车就没有等我爸一起回来，他还在那帮忙搞卫生间的墙缝。
虽然这两天不太热，活也不算很吃力，不过我这个体重和易出汗的体质，还是让短袖不知道湿透了多少次，灌了好多水和冰红茶（下午能提提神），回来周一早上称体重也比较喜人，差一点就达到阶段目标，可以想想去哪里吃之前想好的烤肉跟火锅了（估计吃完立马回到解放前）。

]]> 生活 + 运动 + 跑步 + 干活 生活 @@ -4853,73 +4856,41 @@ user3: - 我是如何走上跑步这条不归路的 - /2020/07/26/%E6%88%91%E6%98%AF%E5%A6%82%E4%BD%95%E8%B5%B0%E4%B8%8A%E8%B7%91%E6%AD%A5%E8%BF%99%E6%9D%A1%E4%B8%8D%E5%BD%92%E8%B7%AF%E7%9A%84/ - 这周因为没有准备技术方面的内容加之之前有想分享下我和跑步的一些事情，我从小学开始就是个体育渣，因为体重大非常胖，小学的时候要做仰卧起坐，基本是一个都起不来，然后那时候跑步也是要我命那种，跟另外一个比较胖的同学在跑步队尾苟延残喘，只有立定跳远还行。

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时光飞逝，我在初中高中的时候因为爱打篮球，以为自己体质已经有了质的变化，所以在体育课跑步的时候妄图跟一位体育非常好的同学一起跑，结果跟的快断气了，最终还是确认了自己是个体育渣，特别是到了大学的第一次体测跑一千米，跑完直接吐了，一则是大学太宅不运动，二则的确是底子不好。那么怎么会去跑步了呢，其实也没什么特殊的原因，就是工作以后因为运动得更少，体质差，而且越来越胖，所以就想运动下，加之跑步也是我觉得成本最低的运动了，刚好那时候17 年租的地方附近小区周围的路车不太多，一圈刚好一公里多，就觉得开始跑跑看，其实想想以前觉得一千米是非常远的，学校塑胶跑道才 400 米，一千米要两圈半，太难了，但是后来在这个小区周围跑的时候好像跑了一圈以后还能再跑一点，最后跑了两圈，可把自己牛坏了，我都能跑两千米了，哈哈，这是个什么概念呢，大学里最让我绝望的两项体育相关的内容就是一千米和十二分钟跑，一千米把我跑吐了，十二分钟跑及格五圈半也能让我跑完花一周时间恢复以及提前一周心理压力爆炸，虽然我那时候跑的不快，但是已经能跑两千米了，瞬间让自己自信心爆炸，并且跑完步出完汗的感觉是非常棒的，毕竟吃奶茶鸡排都能心安理得了，谁叫我跑步了呢😄，其实现在回去看，那时候跑得还算快的，因为还比较瘦，现在要跑得那么快心跳就太快了，关于心跳什么的后面说，开始建立起自信心之后，对跑步这件事就开始不那么排斥跟害怕了，毕竟我能跑两千米了，然后试试三公里，哇，也可以了呢，三公里是什么概念呢，我大学里跑过最多的一次是十二分钟跑五圈半还是六圈，也就是两公里多，不到三公里，几乎是生涯最长了，一时间产生了一些我可能是个被埋没的运动天才的错觉，其实细想下也能明白，只是速度足够慢了就能跑多一点，毕竟提测一千米是要跑进四分钟才及格，自己跑的时候一千米跑六分多钟已经算不慢了（对我自己来说），但是即使是这样还是对把跑步坚持下去这件事有了很大的正面激励作用，并且由于那时候上下班骑车，整个体重控制的比较理想，导致一时间误会跑步就能非常快的减肥（其实这是我跑步历程中比较大的误区之一），因为会在跑步前后称下体重，如果跑个五公里（后面可以跑五公里了），可能体重就能降 0.5 千克，但实际上这只是这五公里跑步身体流失的水分，喝杯水就回来了，那时候能控制体重主要是骑车跟跑步一起的作用，并且工作压力相对来讲比较小，没有过劳肥。

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后面其实跑步慢慢变得一个比较习惯的运动了，从三公里，到五公里，到七公里，再到十公里，十公里差不多对我来说是个坎，一直还不能比较轻松的跑十公里，可能近一两年好了一些（原谅我只是跟自己比较，跟那些大神比差得不知道多远），其实对我来说每次都是个突破，因为其实与他人比较没有特别大意义，比较顶尖的差得太远，比较普通的也不行，都会打击自信心，比较比我差的就更没意义了，所以其实能挑战自己，能把自己的上限提高才是最有意义的，这也是我看着朋友圈里的一些大神的速度除了佩服赞叹之外没什么其他的惭愧或者说嫌弃自己的感觉（阿 Q 精神😄）。

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一直感性地觉得，跑步能解压，跑完浑身汗，有种把身体的负能量都排出去的感觉，也把吃太多的罪恶感排解掉了🤦‍♂️，之前朋友有看一本书，书名差不多叫越跑越接近自己，这个也是我觉得挺准确的一句话，当跑到接近极限了，还想再继续再跑一点，再跑一点就能突破自己上一次的最远记录了，再跑一点就能又一次突破自己了，成人以后，毕业以后，进入社会以后，世事总是难以件件顺遂，磕磕绊绊的往前走，总觉得要崩溃了，但是还是得坚持，再熬一下，再拼一下，可能还是失败，但人生呢，运气好的人和事总是小概率的，唯有面对挫折，还是日拱一卒，来日方长，我们再坚持下，没准下一次，没准再跑一会，就能突破自己，达到新的境界。

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另外个人后期对跑步的一些知识和理解也变得深入一些，比如伤膝盖，其实跑步的确伤膝盖，需要做一些准备和防护，最好的是适合自己的跑鞋和比较好的路（最好的是塑胶跑道了），也要注意热身跟跑后的拉伸（虽然我做的很差），还有就是注意心率，每个人有自己的适宜心率，我这就不冒充科普达人了，可以自行搜索关键字，先说到这吧~

+ 小工周记一 + /2023/03/05/%E5%B0%8F%E5%B7%A5%E5%91%A8%E8%AE%B0%E4%B8%80/ + 开始修老房子又可以更新这个系列了，比较无聊，就是帮着干点零活的记录，这次过去起的比较早，前几天是在翻新瓦片，到这次周六是收尾了，到了的时候先是继续筛了沙子，上周也筛了，就是只筛了一点点，筛沙子的那个像纱窗一样的还是用一扇中空的中间有一根竖档的门钉上铁丝网做的，就是沙子一直放在外面，原来是有袋子装好的，后来是风吹雨打在上面的都已经破掉，还夹杂了很多树叶什么的，需要过下筛，并且前面都是下雨天，沙子都是湿的，不太像我以前看村里有人造房子筛沙子那样，用铲子铲上去就自己都下去的，湿的就是会在一坨，所以需要铲得比较少，然后撒的比较开，这个需要一点经验，然后如果有人一起的话就可以用扫把按住扫一下，这样就会筛得比较有效，不至于都滑下去，沙子本来大部分是可以筛出来的，还有一点就是这种情况网筛需要放得坡度小一点，不然就更容易直接往下调，袋子没破的就不用过筛了，只是湿掉了的是真的重，筛完了那些破掉了的袋子里的沙子，就没有特别的事情要做了，看到大工在那打墙，有一些敲下来的好的砖头就留着，需要削一下上面的混凝土，据大工说现在砖头要七八毛一块了，后面能够重新利用还是挺值钱的，我跟 LD 就用泥刀和铁锹的在那慢慢削，砖头上的泥灰有的比较牢固有的就像直接是沙子，泥刀刮一下就下来了，有的就结合得比较牢固，不过据说以前的砖头工艺上还比较落后，这个房子差不多是三十年前了的，砖头表面都是有点不平，甚至变形，那时候可能砖头是手工烧制的，现在的砖头比较工艺可好多了，不过可能也贵了很多，后来老丈人也过来了，指导了我们拌泥灰，就是水泥和黄沙混合，以前小时候可喜欢玩这个了，可是就也搞不清楚这个是怎么搅拌的，只看见是水泥跟黄沙围城一圈，中间放水，然后一点点搬进去，首先需要先把干的水泥跟黄沙进行混合，具体的比例是老丈人说的，拌的方式有点像堆沙堆，把水泥黄沙铲起来堆起来，就一直要往这个混合堆的尖尖上堆，这样子它自己滑下来能更好地混合，来回两趟就基本混合均匀了，然后就是跟以前看过的，中间扒拉出一个空间放水，然后慢慢把周围的混合好的泥沙推进去，需要注意不要太着急，旁边的推进去太多太快就会漏水出来，一个是会把旁边的地给弄脏，另一个也铲不回水，然后就是推完所有的都混合水了，就铲起来倒一下，再将铲子翻过来捣几下，后面我们就去吃饭了，去了一家叫金记的，又贵又不太好吃的店，就是离得比较近，六七个人只有六七个菜，吃完要四百多，也是有点离谱了。
下午是重头戏，其实本来倒没啥事，就说帮忙搞下靠背（就是踢脚线上面到窗台附近的用木头还有其他材料的装饰性的），都撬撬掉，但是真的是有点离谱了，首先是撬棒真的很重，20 斤的重量（网上查的，没有真的查过），抡起来还要用力地铲进去，因为就是破坏性的要把整个都撬掉，对于我这种又没技巧又没力气的非专业选手，抡起撬棍铲两下手就开始痛了，只是也比较犟，不想刚开始弄就说太重了要休息，后面都完全靠的一点倔强劲撑着，看着里面的工艺感觉也是不容易的，直着横着的木条有好多，竖的一整条，每隔三五十公分，横着的就是三五十公分，每根都要用钉子钉起来，然后外层好像是贴上去，在同一个面的开了头之后就能靠着蛮力往下撬，但是到了转角就又要重新开头，而且最上面一根横条跟紧邻的那一块，大概十几公分，是横着的三条钉在一起，真的是大力都出不了奇迹了，用撬棍的一头用力地敲打都很震手，要从下面往上铲进去撬开一点，然后再从上面往下敲打，这里比较重要的是要小心钉子，我这次运气比较好，踩下去已经扎到了，不过正好在脚趾缝里，没有扎到脚，还是要小心的，做完这个我的手真的是差不多废了，上臂的疼痛已经动一下就受不了了，后面有撬下了最下面当踢脚线的小瓷砖，这个房子估计中间修过一次，两批水泥糊的，新的那批粘的特别牢，敲敲打打了半天才下来一点点，锤子敲上去跟一整块石头一样，震手又没有进展，整个搞完，楼上又在敲墙了，下面的灰尘也是从没见过，我一直在那洒水都完全没有缓解，就上去跟 LD 一起拣砖头，手痛到只能抬两块砖头都会痛了。
回到家里开始越来越痛，两个手就完全没法动了，应该也是肌肉拉伤了，我这样是没足够的力气也不会什么技巧，像大工说的，他们也累也难，只是为了赚钱，不过他们有了经验跟技巧，会注意怎么使力不容易受伤，怎么样比较省力，还有一点就是即使这么累，他们一般也下午五点半就下班了，真的很累了，至少还有不少时间可以回家休息，而我们的职业呢，就像 LD 说的回家就像住酒店，就只是来洗澡睡个觉，希望能改善吧

]]> 生活 - 运动 - 跑步 生活 + 小技巧 运动 减肥 跑步 + 干活 - 用 ollama 本地运行谷歌开源大模型 Gemma - /2024/03/24/%E7%94%A8-ollama-%E6%9C%AC%E5%9C%B0%E8%BF%90%E8%A1%8C%E5%A4%A7%E6%A8%A1%E5%9E%8B/ - 原先在 23 年初的时候调研过一些国产的大模型，包括复旦开源的 MOSS 和清华的 ChatGLM，那时候还是早期版本，需要在 Linux 上，并且有比较好的显卡，而且一般来讲都得是 N 卡，过程中需要安装 pytorch和比较多依赖，并且当时的效果也还比较差，所以后面就没有长期使用。
最近看到谷歌在 2 月份开源了大模型 Gemma ，gemma 的博客在这里，想要在本地运行这个模型在现在这个阶段也变得简单很多，因为我们有了 ollama 工具

可以通过这个工具来运行大模型，并且已经支持了谷歌开源的 Gemma

我这边本地是 MacBook Pro 14 寸的，m3 pro 的处理器，18g 内存，刚好可以用 7b 量化的模型

这里有推荐的模型和内存推荐匹配规则，16g 可以运行 13B 及以下模型
下载安装完后我们可以用以下命令

-
ollama run gemma:7b
-

这里需要拉取模型，约5.2g 大小，考虑网络原因可能会比较慢

我们可以简单来试试问个问题


看出来回答的还是比较丰富的，谷歌出品还是比较有水平的，不至于像 ChatGLM 最初版本的在不做调优的情况下甚至有点前言不搭后语
对于想使用 chatgpt 但是没条件，这也算是个低配平替了, 并且已经是个比较可用的了，同时也方便进行学习调优等
如果想要类似于 chatgpt 那样的网页版，可以安装 open-webui
可以通过 webui 访问 ollama 运行的大模型，
用 docker 启动的命令也贴一下

-
docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main
-


这里有一个小区别，Gemma 在多轮会话的时候会在前面的答案基础上再完善。

-

补充一个在 windows 环境下，cpu 跑模型的也是可行的

现在是大模型可以深入千家万户了，大家都可以尝试下，如果对日常的工作学习有一些效率上的提升也是好的

-]]> - - LLM - - - LLM - - - - 是何原因竟让两人深夜奔袭十公里 - /2022/06/05/%E6%98%AF%E4%BD%95%E5%8E%9F%E5%9B%A0%E7%AB%9F%E8%AE%A9%E4%B8%A4%E4%BA%BA%E6%B7%B1%E5%A4%9C%E5%A5%94%E8%A2%AD%E5%8D%81%E5%85%AC%E9%87%8C/ - 偶尔来个标题党，不过也是一次比较神奇的经历
上周五下班后跟 LD 约好去吃牛蛙，某个朋友好像对这类都不太能接受，我以前小时候也不常吃，但是这类其实都是口味比较重，没有那种肉本身的腥味，而且肉质比较特殊，吃过几次以后就有点爱上了，这次刚好是 LD 买的新店开业券，比较优惠（我们俩都是有点勤俭持家的，想着小电驴还有三格电，这家店又有点远，骑车单趟大概要 10 公里左右，有点担心，LD 说应该可以的，就一起骑了过去（跟她轮换着骑电驴和共享单车），结果大概离吃牛蛙的店还有一辆公里的时候，电量就报警了，只有最后一个红色的了，一共是五格，最后一格是红色的，提示我们该充电了，这样子是真的有点慌了，之前开了几个月都是还有一两格电的时候就充电了，没有试验过究竟这最后一格电能开多远，总之先到了再说。
这家牛蛙没想到还挺热闹的，我们到那已经快八点了，还有十几个排队的，有个人还想插队（向来是不惯着这种，一边去），旁边刚好是有些商店就逛了下，就跟常规的商业中心差不多，开业的比较早也算是这一边比较核心的商业综合体了，各种品牌都有，而且还有彩票售卖点的，只是不太理解现在的彩票都是兑图案的，而且要 10 块钱一张，我的概念里还是以前 2 块钱一张的双色球，偶尔能中个五块十块的。排队还剩四五个的时候我们就去门口坐着等了，又等了大概二十分钟才排到我们，靠近我们等的里面的位置，好像好几个小女生在那还叫了外卖奶茶，然后各种拍照，小朋友的生活还是丰富多彩的，我们到了就点了蒜蓉的，没有点传说中紫苏的，菜单上画了 N 个🌶，LD 还是想体验下说下次人多点可以试试，我们俩吃怕太辣了吃不消，口味还是不错的，这家貌似是 LD 闺蜜推荐的，口碑有保证。两个人光吃一个蛙锅就差不多了，本来还想再点个其他的，后面实在吃不下了就没点，吃完还是惯例点了个奶茶，不过是真的不好找，太大了。
本来是就回个家的事了，结果就因为前面铺垫的小电驴已经只有一格电了，标题的深夜奔袭十公里就出现了，这个电驴估计续航也虚标挺严重的，电量也是这样，骑的时候显示只有一格电，关掉再开起来又有三格，然后我们回去骑了没一公里就没电了，这下是真的完球了，觉得车子也比较新，直接停外面也不放心，就开始了深夜的十公里推电驴奔袭，LD 看我太累还帮我中间推了一段，虽然是跑过十公里的，但是推着个没电的电驴，还是着实不容易的，LD 也是陪我推着车走，中间好几次说我们把电驴停着打车回去，把电池带回去充满了明天再过来骑车，可能是心态已经转变了，这应该算是一次很特殊的体验，从我们吃完出来大概十点，到最后我们推到小区，大概是过了两个小时的样子，说句深夜也不太过分，把这次这么推车看成了一种意志力的考验，很多事情也都是怕坚持，或者说怕不能坚持，想走得远，没有持续的努力坚持肯定是不行的，所以还是坚持着把车推回来（好吧，我其实主要是怕车被偷，毕竟刚来杭州上学没多久就被偷了自行车留下了阴影），中间感谢 LD，跟我轮着推了一段路，有些下坡的时候还在那坐着用脚蹬一下，离家里大概还有一公里的时候，有个骑电瓶车的大叔还停下来问我们是车破了还是没电了，应该是出于好意吧，最后快到的时候真的非常渴，买了2.5 升的水被我一口气喝了大半瓶，奶茶已经不能起到解渴的作用了，本来以为这样能消耗很多，结果第二天一称还重了，（我的称一定有问题 233

-]]> - - 生活 - - - 生活 - - - - 在老丈人家的小工记四 - /2020/09/26/%E5%9C%A8%E8%80%81%E4%B8%88%E4%BA%BA%E5%AE%B6%E7%9A%84%E5%B0%8F%E5%B7%A5%E8%AE%B0%E5%9B%9B/ - 小工记四

第四周去的时候让我们去了现在在住的房子里，去三楼整理东西了，蛮多的东西需要收拾整理，有些需要丢一下，以前往往是把不太要用的东西就放三楼了，但是后面就不会再去收拾整理，LD 跟丈母娘负责收拾，我不太知道哪些还要的，哪些不要了，而且本来也不擅长这种收拾🤦‍♂️，然后就变成她们收拾出来废纸箱，我负责拆掉，压平，这时候终于觉得体重还算是有点作用，总体来说这个事情我其实也不擅长，不擅长的主要是捆起来，可能我总是小题大做，因为纸箱大小不一，如果不做一下分类，然后把大的折小一些的话，直接绑起来，容易拎起来就散掉了，而且一些鞋盒子这种小件的纸盒会比较薄，冰箱这种大件的比较厚，厚的比较不容易变形，需要大力踩踏，而且扎的时候需要用体重压住捆实了之后那样子才是真的捆实的，不然待会又是松松垮垮容易滑出来散架，因为压住了捆好后，下来了之后箱子就会弹开了把绳子崩紧实，感觉又是掌握到生活小技巧了😃，我这里其实比较单调无聊，然后 LD 那可以说非常厉害了，一共理出来 11 把旧电扇，还有好多没用过全新的不锈钢脸盆大大小小的，感觉比店里在卖的还多，还有是有比较多小时候的东西，特别多小时候的衣服，其实这种对我来说最难了，可能需要读一下断舍离，蛮多东西都舍不得扔，但是其实是没啥用了，然后还占地方，这天应该算是比较轻松的一天了，上午主要是把收拾出来要的和不要的搬下楼，然后下午要去把纸板给卖掉。中午还是去小快餐店吃的，在住的家里理东西还有个好处就是中午吃完饭可以小憩一下，因为我个人是非常依赖午休的，不然下午完全没精神，而且心态也会比较烦躁，一方面是客观的的确比较疲惫，另一方面应该主观心理作用也有点影响，就像上班的时候也是觉得不午睡就会很难受，心理作用也有一点，不过总之能睡还是睡一会，真的没办法就心态好点，吃完午饭之后我们就推着小平板车去收废品的地方卖掉了上午我收拾捆起来的纸板，好像卖了一百多，都是直接过地磅了，不用一捆一捆地称，不过有个小插曲，那里另外一个大爷在倒他的三轮车的时候撞了我一下，还好车速慢，屁股上肉垫后，接下来就比较麻烦了，是LD 她们两姐妹从小到大的书，也要去卖掉，小平板车就载不下了，而且着实也不太好推，轮子不太平，导致推着很累，书有好多箱，本来是想去亲戚家借电动三轮车，因为不会开摩托的那种，摩托的那种 LD 邻居家就有，可是到了那发现那个也是很大，而且刹车是用脚踩的那种，俺爹不太放心，就说第二天周日他有空会帮忙去载了卖掉的，然后比较搞笑的来了，丈母娘看错了时间，以为已经快五点了，就让我们顺便在车里带点东西去在修的房子，放到那边三楼去，到了那还跟老丈人说已经这么迟了要赶紧去菜场买菜了，结果我们回来以后才发现看错了一个小时🤦‍♂️。
前面可以没提，前三周去的我们一般就周六去一天，然后周日因为要早点回杭州，而且可能想让我们周日能休息下，但是这周就因为周日的时候我爸要去帮忙载书，然后 LD 姐姐也会过来收拾东西，我们周日就又去整理收拾了，周日由于俺爹去的很早，我过去的时候书已经木有了，主要是去收拾东西了，把一些有用没用的继续整理，基本上三楼的就处理完毕了，舒了一大口气，毕竟让丈母娘一个人收拾实在是太累了，但是要扔掉的衣服比较棘手，附近知道的青蛙回收桶被推倒了，其他地方也不知道哪里有，我们就先载了一些东西去在修的房子那，然后去找青蛙桶，结果一个小区可以进，但是已经满了，另一个不让进，后来只能让 LD 姐姐带去她们小区扔了，塞了满满一车。因为要赶回杭州的车就没有等我爸一起回来，他还在那帮忙搞卫生间的墙缝。
虽然这两天不太热，活也不算很吃力，不过我这个体重和易出汗的体质，还是让短袖不知道湿透了多少次，灌了好多水和冰红茶（下午能提提神），回来周一早上称体重也比较喜人，差一点就达到阶段目标，可以想想去哪里吃之前想好的烤肉跟火锅了（估计吃完立马回到解放前）。

+ 我是如何走上跑步这条不归路的 + /2020/07/26/%E6%88%91%E6%98%AF%E5%A6%82%E4%BD%95%E8%B5%B0%E4%B8%8A%E8%B7%91%E6%AD%A5%E8%BF%99%E6%9D%A1%E4%B8%8D%E5%BD%92%E8%B7%AF%E7%9A%84/ + 这周因为没有准备技术方面的内容加之之前有想分享下我和跑步的一些事情，我从小学开始就是个体育渣，因为体重大非常胖，小学的时候要做仰卧起坐，基本是一个都起不来，然后那时候跑步也是要我命那种，跟另外一个比较胖的同学在跑步队尾苟延残喘，只有立定跳远还行。

+

时光飞逝，我在初中高中的时候因为爱打篮球，以为自己体质已经有了质的变化，所以在体育课跑步的时候妄图跟一位体育非常好的同学一起跑，结果跟的快断气了，最终还是确认了自己是个体育渣，特别是到了大学的第一次体测跑一千米，跑完直接吐了，一则是大学太宅不运动，二则的确是底子不好。那么怎么会去跑步了呢，其实也没什么特殊的原因，就是工作以后因为运动得更少，体质差，而且越来越胖，所以就想运动下，加之跑步也是我觉得成本最低的运动了，刚好那时候17 年租的地方附近小区周围的路车不太多，一圈刚好一公里多，就觉得开始跑跑看，其实想想以前觉得一千米是非常远的，学校塑胶跑道才 400 米，一千米要两圈半，太难了，但是后来在这个小区周围跑的时候好像跑了一圈以后还能再跑一点，最后跑了两圈，可把自己牛坏了，我都能跑两千米了，哈哈，这是个什么概念呢，大学里最让我绝望的两项体育相关的内容就是一千米和十二分钟跑，一千米把我跑吐了，十二分钟跑及格五圈半也能让我跑完花一周时间恢复以及提前一周心理压力爆炸，虽然我那时候跑的不快，但是已经能跑两千米了，瞬间让自己自信心爆炸，并且跑完步出完汗的感觉是非常棒的，毕竟吃奶茶鸡排都能心安理得了，谁叫我跑步了呢😄，其实现在回去看，那时候跑得还算快的，因为还比较瘦，现在要跑得那么快心跳就太快了，关于心跳什么的后面说，开始建立起自信心之后，对跑步这件事就开始不那么排斥跟害怕了，毕竟我能跑两千米了，然后试试三公里，哇，也可以了呢，三公里是什么概念呢，我大学里跑过最多的一次是十二分钟跑五圈半还是六圈，也就是两公里多，不到三公里，几乎是生涯最长了，一时间产生了一些我可能是个被埋没的运动天才的错觉，其实细想下也能明白，只是速度足够慢了就能跑多一点，毕竟提测一千米是要跑进四分钟才及格，自己跑的时候一千米跑六分多钟已经算不慢了（对我自己来说），但是即使是这样还是对把跑步坚持下去这件事有了很大的正面激励作用，并且由于那时候上下班骑车，整个体重控制的比较理想，导致一时间误会跑步就能非常快的减肥（其实这是我跑步历程中比较大的误区之一），因为会在跑步前后称下体重，如果跑个五公里（后面可以跑五公里了），可能体重就能降 0.5 千克，但实际上这只是这五公里跑步身体流失的水分，喝杯水就回来了，那时候能控制体重主要是骑车跟跑步一起的作用，并且工作压力相对来讲比较小，没有过劳肥。

+

后面其实跑步慢慢变得一个比较习惯的运动了，从三公里，到五公里，到七公里，再到十公里，十公里差不多对我来说是个坎，一直还不能比较轻松的跑十公里，可能近一两年好了一些（原谅我只是跟自己比较，跟那些大神比差得不知道多远），其实对我来说每次都是个突破，因为其实与他人比较没有特别大意义，比较顶尖的差得太远，比较普通的也不行，都会打击自信心，比较比我差的就更没意义了，所以其实能挑战自己，能把自己的上限提高才是最有意义的，这也是我看着朋友圈里的一些大神的速度除了佩服赞叹之外没什么其他的惭愧或者说嫌弃自己的感觉（阿 Q 精神😄）。

+

一直感性地觉得，跑步能解压，跑完浑身汗，有种把身体的负能量都排出去的感觉，也把吃太多的罪恶感排解掉了🤦‍♂️，之前朋友有看一本书，书名差不多叫越跑越接近自己，这个也是我觉得挺准确的一句话，当跑到接近极限了，还想再继续再跑一点，再跑一点就能突破自己上一次的最远记录了，再跑一点就能又一次突破自己了，成人以后，毕业以后，进入社会以后，世事总是难以件件顺遂，磕磕绊绊的往前走，总觉得要崩溃了，但是还是得坚持，再熬一下，再拼一下，可能还是失败，但人生呢，运气好的人和事总是小概率的，唯有面对挫折，还是日拱一卒，来日方长，我们再坚持下，没准下一次，没准再跑一会，就能突破自己，达到新的境界。

+

另外个人后期对跑步的一些知识和理解也变得深入一些，比如伤膝盖，其实跑步的确伤膝盖，需要做一些准备和防护，最好的是适合自己的跑鞋和比较好的路（最好的是塑胶跑道了），也要注意热身跟跑后的拉伸（虽然我做的很差），还有就是注意心率，每个人有自己的适宜心率，我这就不冒充科普达人了，可以自行搜索关键字，先说到这吧~

]]> 生活 运动 跑步 - 干活 生活 - 小技巧 运动 减肥 跑步 - 干活 @@ -5010,6 +4981,18 @@ user3: utf8mb4_general_ci + + 是何原因竟让两人深夜奔袭十公里 + /2022/06/05/%E6%98%AF%E4%BD%95%E5%8E%9F%E5%9B%A0%E7%AB%9F%E8%AE%A9%E4%B8%A4%E4%BA%BA%E6%B7%B1%E5%A4%9C%E5%A5%94%E8%A2%AD%E5%8D%81%E5%85%AC%E9%87%8C/ + 偶尔来个标题党，不过也是一次比较神奇的经历
上周五下班后跟 LD 约好去吃牛蛙，某个朋友好像对这类都不太能接受，我以前小时候也不常吃，但是这类其实都是口味比较重，没有那种肉本身的腥味，而且肉质比较特殊，吃过几次以后就有点爱上了，这次刚好是 LD 买的新店开业券，比较优惠（我们俩都是有点勤俭持家的，想着小电驴还有三格电，这家店又有点远，骑车单趟大概要 10 公里左右，有点担心，LD 说应该可以的，就一起骑了过去（跟她轮换着骑电驴和共享单车），结果大概离吃牛蛙的店还有一辆公里的时候，电量就报警了，只有最后一个红色的了，一共是五格，最后一格是红色的，提示我们该充电了，这样子是真的有点慌了，之前开了几个月都是还有一两格电的时候就充电了，没有试验过究竟这最后一格电能开多远，总之先到了再说。
这家牛蛙没想到还挺热闹的，我们到那已经快八点了，还有十几个排队的，有个人还想插队（向来是不惯着这种，一边去），旁边刚好是有些商店就逛了下，就跟常规的商业中心差不多，开业的比较早也算是这一边比较核心的商业综合体了，各种品牌都有，而且还有彩票售卖点的，只是不太理解现在的彩票都是兑图案的，而且要 10 块钱一张，我的概念里还是以前 2 块钱一张的双色球，偶尔能中个五块十块的。排队还剩四五个的时候我们就去门口坐着等了，又等了大概二十分钟才排到我们，靠近我们等的里面的位置，好像好几个小女生在那还叫了外卖奶茶，然后各种拍照，小朋友的生活还是丰富多彩的，我们到了就点了蒜蓉的，没有点传说中紫苏的，菜单上画了 N 个🌶，LD 还是想体验下说下次人多点可以试试，我们俩吃怕太辣了吃不消，口味还是不错的，这家貌似是 LD 闺蜜推荐的，口碑有保证。两个人光吃一个蛙锅就差不多了，本来还想再点个其他的，后面实在吃不下了就没点，吃完还是惯例点了个奶茶，不过是真的不好找，太大了。
本来是就回个家的事了，结果就因为前面铺垫的小电驴已经只有一格电了，标题的深夜奔袭十公里就出现了，这个电驴估计续航也虚标挺严重的，电量也是这样，骑的时候显示只有一格电，关掉再开起来又有三格，然后我们回去骑了没一公里就没电了，这下是真的完球了，觉得车子也比较新，直接停外面也不放心，就开始了深夜的十公里推电驴奔袭，LD 看我太累还帮我中间推了一段，虽然是跑过十公里的，但是推着个没电的电驴，还是着实不容易的，LD 也是陪我推着车走，中间好几次说我们把电驴停着打车回去，把电池带回去充满了明天再过来骑车，可能是心态已经转变了，这应该算是一次很特殊的体验，从我们吃完出来大概十点，到最后我们推到小区，大概是过了两个小时的样子，说句深夜也不太过分，把这次这么推车看成了一种意志力的考验，很多事情也都是怕坚持，或者说怕不能坚持，想走得远，没有持续的努力坚持肯定是不行的，所以还是坚持着把车推回来（好吧，我其实主要是怕车被偷，毕竟刚来杭州上学没多久就被偷了自行车留下了阴影），中间感谢 LD，跟我轮着推了一段路，有些下坡的时候还在那坐着用脚蹬一下，离家里大概还有一公里的时候，有个骑电瓶车的大叔还停下来问我们是车破了还是没电了，应该是出于好意吧，最后快到的时候真的非常渴，买了2.5 升的水被我一口气喝了大半瓶，奶茶已经不能起到解渴的作用了，本来以为这样能消耗很多，结果第二天一称还重了，（我的称一定有问题 233

+]]> + + 生活 + + + 生活 + + 深度学习入门初认识 /2023/04/30/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E5%85%A5%E9%97%A8%E5%88%9D%E8%AE%A4%E8%AF%86/ @@ -5022,6 +5005,25 @@ user3: 深度学习 + + 用 ollama 本地运行谷歌开源大模型 Gemma + /2024/03/24/%E7%94%A8-ollama-%E6%9C%AC%E5%9C%B0%E8%BF%90%E8%A1%8C%E5%A4%A7%E6%A8%A1%E5%9E%8B/ + 原先在 23 年初的时候调研过一些国产的大模型，包括复旦开源的 MOSS 和清华的 ChatGLM，那时候还是早期版本，需要在 Linux 上，并且有比较好的显卡，而且一般来讲都得是 N 卡，过程中需要安装 pytorch和比较多依赖，并且当时的效果也还比较差，所以后面就没有长期使用。
最近看到谷歌在 2 月份开源了大模型 Gemma ，gemma 的博客在这里，想要在本地运行这个模型在现在这个阶段也变得简单很多，因为我们有了 ollama 工具

可以通过这个工具来运行大模型，并且已经支持了谷歌开源的 Gemma

我这边本地是 MacBook Pro 14 寸的，m3 pro 的处理器，18g 内存，刚好可以用 7b 量化的模型

这里有推荐的模型和内存推荐匹配规则，16g 可以运行 13B 及以下模型
下载安装完后我们可以用以下命令

+
ollama run gemma:7b
+

这里需要拉取模型，约5.2g 大小，考虑网络原因可能会比较慢

我们可以简单来试试问个问题


看出来回答的还是比较丰富的，谷歌出品还是比较有水平的，不至于像 ChatGLM 最初版本的在不做调优的情况下甚至有点前言不搭后语
对于想使用 chatgpt 但是没条件，这也算是个低配平替了, 并且已经是个比较可用的了，同时也方便进行学习调优等
如果想要类似于 chatgpt 那样的网页版，可以安装 open-webui
可以通过 webui 访问 ollama 运行的大模型，
用 docker 启动的命令也贴一下

+
docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main
+

不过有个小问题就是 docker 镜像拉取会有点慢，可以添加下国内镜像加速

+
{
    "registry-mirrors": [
        "https://dockerproxy.com",
        "https://docker.mirrors.ustc.edu.cn",
        "https://docker.nju.edu.cn"
    ]
}
+


这里有一个小区别，Gemma 在多轮会话的时候会在前面的答案基础上再完善。

+

补充一个在 windows 环境下，cpu 跑模型的也是可行的

现在是大模型可以深入千家万户了，大家都可以尝试下，如果对日常的工作学习有一些效率上的提升也是好的

+]]> + + LLM + + + LLM + + 看完了扫黑风暴,聊聊感想 /2021/10/24/%E7%9C%8B%E5%AE%8C%E4%BA%86%E6%89%AB%E9%BB%91%E9%A3%8E%E6%9A%B4-%E8%81%8A%E8%81%8A%E6%84%9F%E6%83%B3/ @@ -5038,6 +5040,20 @@ user3: 影评 + + 给小电驴上牌 + /2022/03/20/%E7%BB%99%E5%B0%8F%E7%94%B5%E9%A9%B4%E4%B8%8A%E7%89%8C/ + 三八节活动的时候下决心买了个小电驴，主要是上下班路上现在通勤条件越来越恶劣了，之前都是觉得坐公交就行了，实际路程就比较短，但是现在或者说大概是年前那两个月差不多就开始了，基本是堵一路，个人感觉是天目山路那边在修地铁，而且蚂蚁的几个空间都在那，上班的时间点都差不多，前一个修地铁感觉挺久了，机动车保有量也越来越多，总体是古墩路就越来越堵，还有个原因就是早上上班的点共享单车都被骑走了，有时候整整走一路都没一辆，有时候孤零零地有一辆基本都是破的；走路其实也是一种选择，但是因为要赶着上班，走得太慢就要很久，可能要 45 分钟这样，走得比较快就一身汗挺难受的。所以考虑自行车和电动车，这里还有一点就是不管是乘公交还是骑共享单车，其实都要从楼下走出去蛮远，公司回来也是，也就是这种通勤方式在准备阶段就花了比较多时间，比如总的从下班到到家的时间是半小时，可能在骑共享单车和公交车上的时间都不到十分钟，就比较难受。觉得这种比例太浪费时间，如果能有这种比较点对点的方式，估计能省时省力不少，前面说的骑共享单车的方式其实在之前是比较可行的，但是后来越来越少车，基本都是每周的前几天，周一到周三都是没有车，走路到公司再冷的天都是走出一身的汗，下雨天就更难受，本来下雨天应该是优先选择坐公交，但是一般下雨天堵车会更严重，而且车子到我上车的那个站，下雨天就挤得不行，总体说下来感觉事情都不打，但是几年下来，还是会挺不爽的。

+

电驴看的比较草率，主要是考虑续航，然后锂电池外加 48v 和 24AH，这样一般来讲还是价格比较高的，只是原来没预料到这个限速，以为现在的车子都比较快，但是现在的新国标车子都是 25km/h 的限速，然后 15km/h 都是会要提醒，虽然说有一些特殊的解除限速的方法，但是解了也就 35km/h ，差距不是特别大，而且现在的车子都是比较小，也不太能载东西，特别是上下班路程也不远的情况下，其实不是那么需要速度，就像我朋友说的，可能骑车的时间还不如等红绿灯多，所以就还好，也不打算解除限速，只是品牌上也仔细看，后来选了绿源，目前大部分还是雅迪，爱玛，台羚，绿源，小牛等，路上看的话还是雅迪比较多，不过价格也比较贵一点，还有就是小牛了，是比较新兴的品牌，手机 App 什么的做得比较好，而且也比较贵，最后以相对比较便宜的价格买了个锂电 48V24AH 的小车子，后来发现还是有点不方便的点就是没有比较大的筐，也不好装，这样就是下雨天雨衣什么的比较不方便放。

+

聊回来主题上牌这个事情，这个事情也是颇费心力，提车的时候店里的让我跟他早上一起去，但是因为不确定时间，也比较远就没跟着去，因为我是线上买的，线下自提，线下的店可能没啥利润可以拿，就不肯帮忙代上牌，朋友说在线下店里买是可以代上的，自己上牌过程也比较曲折，一开始是头盔没到，然后是等开发票，主要的东西就是需要骑着车子去车管所，不能只自己去，然后需要预约，附近比较近的都是提前一周就预约完了号了，要提前在支付宝上进行预约，比较空的就是店里推荐的景区大队，但是随之而来就是比较蛋疼的，这个景区大队太远了，看下骑车距离有十几公里，所以就有点拖延症，但是总归要上的，不然一直不能开是白买了，上牌的材料主要是车辆合格证，发票，然后车子上的浙品码，在车架上和电池上，然后车架号什么的都要跟合格证上完全对应，整体车子要跟合格证上一毛一样，如果有额外的反光镜，后面副座都需要拆掉，脚踏板要装上，到了那其实还比较顺利，就是十几公里外加那天比较冷，吹得头疼。

+]]> + + 生活 + + + 生活 + + 聊一下 Java 的日志系列一 /2024/01/07/%E8%81%8A%E4%B8%80%E4%B8%8B-Java-%E7%9A%84%E6%97%A5%E5%BF%97%E7%B3%BB%E5%88%97%E4%B8%80/ @@ -5078,34 +5094,125 @@ user3: - 给小电驴上牌 - /2022/03/20/%E7%BB%99%E5%B0%8F%E7%94%B5%E9%A9%B4%E4%B8%8A%E7%89%8C/ - 三八节活动的时候下决心买了个小电驴，主要是上下班路上现在通勤条件越来越恶劣了，之前都是觉得坐公交就行了，实际路程就比较短，但是现在或者说大概是年前那两个月差不多就开始了，基本是堵一路，个人感觉是天目山路那边在修地铁，而且蚂蚁的几个空间都在那，上班的时间点都差不多，前一个修地铁感觉挺久了，机动车保有量也越来越多，总体是古墩路就越来越堵，还有个原因就是早上上班的点共享单车都被骑走了，有时候整整走一路都没一辆，有时候孤零零地有一辆基本都是破的；走路其实也是一种选择，但是因为要赶着上班，走得太慢就要很久，可能要 45 分钟这样，走得比较快就一身汗挺难受的。所以考虑自行车和电动车，这里还有一点就是不管是乘公交还是骑共享单车，其实都要从楼下走出去蛮远，公司回来也是，也就是这种通勤方式在准备阶段就花了比较多时间，比如总的从下班到到家的时间是半小时，可能在骑共享单车和公交车上的时间都不到十分钟，就比较难受。觉得这种比例太浪费时间，如果能有这种比较点对点的方式，估计能省时省力不少，前面说的骑共享单车的方式其实在之前是比较可行的，但是后来越来越少车，基本都是每周的前几天，周一到周三都是没有车，走路到公司再冷的天都是走出一身的汗，下雨天就更难受，本来下雨天应该是优先选择坐公交，但是一般下雨天堵车会更严重，而且车子到我上车的那个站，下雨天就挤得不行，总体说下来感觉事情都不打，但是几年下来，还是会挺不爽的。

-

电驴看的比较草率，主要是考虑续航，然后锂电池外加 48v 和 24AH，这样一般来讲还是价格比较高的，只是原来没预料到这个限速，以为现在的车子都比较快，但是现在的新国标车子都是 25km/h 的限速，然后 15km/h 都是会要提醒，虽然说有一些特殊的解除限速的方法，但是解了也就 35km/h ，差距不是特别大，而且现在的车子都是比较小，也不太能载东西，特别是上下班路程也不远的情况下，其实不是那么需要速度，就像我朋友说的，可能骑车的时间还不如等红绿灯多，所以就还好，也不打算解除限速，只是品牌上也仔细看，后来选了绿源，目前大部分还是雅迪，爱玛，台羚，绿源，小牛等，路上看的话还是雅迪比较多，不过价格也比较贵一点，还有就是小牛了，是比较新兴的品牌，手机 App 什么的做得比较好，而且也比较贵，最后以相对比较便宜的价格买了个锂电 48V24AH 的小车子，后来发现还是有点不方便的点就是没有比较大的筐，也不好装，这样就是下雨天雨衣什么的比较不方便放。

-

聊回来主题上牌这个事情，这个事情也是颇费心力，提车的时候店里的让我跟他早上一起去，但是因为不确定时间，也比较远就没跟着去，因为我是线上买的，线下自提，线下的店可能没啥利润可以拿，就不肯帮忙代上牌，朋友说在线下店里买是可以代上的，自己上牌过程也比较曲折，一开始是头盔没到，然后是等开发票，主要的东西就是需要骑着车子去车管所，不能只自己去，然后需要预约，附近比较近的都是提前一周就预约完了号了，要提前在支付宝上进行预约，比较空的就是店里推荐的景区大队，但是随之而来就是比较蛋疼的，这个景区大队太远了，看下骑车距离有十几公里，所以就有点拖延症，但是总归要上的，不然一直不能开是白买了，上牌的材料主要是车辆合格证，发票，然后车子上的浙品码，在车架上和电池上，然后车架号什么的都要跟合格证上完全对应，整体车子要跟合格证上一毛一样，如果有额外的反光镜，后面副座都需要拆掉，脚踏板要装上，到了那其实还比较顺利，就是十几公里外加那天比较冷，吹得头疼。

+ 聊一下 Java 的日志系列三 + /2024/01/21/%E8%81%8A%E4%B8%80%E4%B8%8B-Java-%E7%9A%84%E6%97%A5%E5%BF%97%E7%B3%BB%E5%88%97%E4%B8%89/ + 上周因为一些事情没有更新在这里，是因为新电脑还没到，手头没有把移动硬盘里的 time machine 恢复出来的机器，所以单独更了一篇在新建的一个 cloudflare page 服务上，总体体验还可以，就是有个小点后面可以讲一下，继续完善下 Java 的这个日志，或者说主要讲的是 logback
前面讲了logback 的初始化逻辑，后面就是我最开始来看这个的逻辑，日志的滚动策略的触发逻辑
我们常规的记录日志的方式比如

+
logger.info("log some thing and biz info: {}",biz);
+

这里就调用了
ch.qos.logback.classic.Logger#info(java.lang.String, java.lang.Object)

+
public void info(String format, Object arg) {
    filterAndLog_1(FQCN, null, Level.INFO, format, arg, null);
}
+

这里的 FQCN 就是这个类的全限定名

+
public static final String FQCN = ch.qos.logback.classic.Logger.class.getName();
+

这个具体的 filterAndLog_1 方法还是在同一个 Logger 类里的
ch.qos.logback.classic.Logger#filterAndLog_1

+
private void filterAndLog_1(final String localFQCN, final Marker marker, final Level level, final String msg, final Object param, final Throwable t) {

    final FilterReply decision = loggerContext.getTurboFilterChainDecision_1(marker, this, level, msg, param, t);

    if (decision == FilterReply.NEUTRAL) {
        if (effectiveLevelInt > level.levelInt) {
            return;
        }
    } else if (decision == FilterReply.DENY) {
        return;
    }

    buildLoggingEventAndAppend(localFQCN, marker, level, msg, new Object[] { param }, t);
}
+

这里面先是走过滤器逻辑，如果是拒绝的，那就不往下执行，也就不执行下面的写日志逻辑了，如果是中性的，那就判断日志级别是否符合，如果直接是拒绝就 return 了，如果是 ACCEPT 就往下执行了

+
public enum FilterReply {
    DENY, NEUTRAL, ACCEPT;
}
+

然后继续调用同样的类的方法
ch.qos.logback.classic.Logger#buildLoggingEventAndAppend

+
private void buildLoggingEventAndAppend(final String localFQCN, final Marker marker, final Level level, final String msg, final Object[] params,
                final Throwable t) {
    LoggingEvent le = new LoggingEvent(localFQCN, this, level, msg, t, params);
    le.setMarker(marker);
    callAppenders(le);
}
+

先把日志包装成 LoggingEvent ，然后调用
ch.qos.logback.classic.Logger#callAppenders

+
public void callAppenders(ILoggingEvent event) {
    int writes = 0;
    for (Logger l = this; l != null; l = l.parent) {
        writes += l.appendLoopOnAppenders(event);
        if (!l.additive) {
            break;
        }
    }
    // No appenders in hierarchy
    if (writes == 0) {
        loggerContext.noAppenderDefinedWarning(this);
    }
}
+

这里会按 Logger 调用 appendLoopOnAppenders

+
private int appendLoopOnAppenders(ILoggingEvent event) {
    if (aai != null) {
        return aai.appendLoopOnAppenders(event);
    } else {
        return 0;
    }
+

继续调用事件的
ch.qos.logback.core.spi.AppenderAttachableImpl#appendLoopOnAppenders

+
public int appendLoopOnAppenders(E e) {
    int size = 0;
    final Appender<E>[] appenderArray = appenderList.asTypedArray();
    final int len = appenderArray.length;
    for (int i = 0; i < len; i++) {
        appenderArray[i].doAppend(e);
        size++;
    }
    return size;
}
+

因为 Logger 里有关联 appender，就具体调用关联的 appender 来添加日志
然后就接着调用
ch.qos.logback.core.UnsynchronizedAppenderBase#doAppend 方法

+
public void doAppend(E eventObject) {
        // WARNING: The guard check MUST be the first statement in the
        // doAppend() method.

        // prevent re-entry.
        if (Boolean.TRUE.equals(guard.get())) {
            return;
        }

        try {
            guard.set(Boolean.TRUE);

            if (!this.started) {
                if (statusRepeatCount++ < ALLOWED_REPEATS) {
                    addStatus(new WarnStatus("Attempted to append to non started appender [" + name + "].", this));
                }
                return;
            }

            if (getFilterChainDecision(eventObject) == FilterReply.DENY) {
                return;
            }

            // ok, we now invoke derived class' implementation of append
            this.append(eventObject);

        } catch (Exception e) {
            if (exceptionCount++ < ALLOWED_REPEATS) {
                addError("Appender [" + name + "] failed to append.", e);
            }
        } finally {
            guard.set(Boolean.FALSE);
        }
    }
+

这里先判断了 guard 的状态，guard 是个 ThreadLocal，是为了拦截异常的无限循环调用，这里有些疑惑的，看了一圈可能相关的是前面的 Logger 会往父级查找，然后如果不同层级的 Logger 关联了相同的 appender 的话，或者这个 doAppend 又被其他 appender 调用了，就可能会出现循环调用，然后会在开始实际的 append的之前先设置 guard 状态，
然后再执行 append，这里会走到
ch.qos.logback.core.OutputStreamAppender#append

+
@Override
protected void append(E eventObject) {
    if (!isStarted()) {
        return;
    }

    subAppend(eventObject);
}
+

忘了补充下，我们这里使用的是
ch.qos.logback.core.rolling.RollingFileAppender
接下去就是调用的 RollingFileAppender 的 subAppend 方法

+
@Override
protected void subAppend(E event) {
    // The roll-over check must precede actual writing. This is the
    // only correct behavior for time driven triggers.

    // We need to synchronize on triggeringPolicy so that only one rollover
    // occurs at a time
    synchronized (triggeringPolicy) {
        if (triggeringPolicy.isTriggeringEvent(currentlyActiveFile, event)) {
            rollover();
        }
    }

    super.subAppend(event);
}
+

这里就会先判断是否触发事件，
而这里就是主要的逻辑，看是否需要走 rollover，也就是具体的滚动逻辑

+
@Override
    public boolean isTriggeringEvent(File activeFile, final E event) {

        long time = getCurrentTime();

        // first check for roll-over based on time
        if (time >= nextCheck) {
            Date dateInElapsedPeriod = dateInCurrentPeriod;
            elapsedPeriodsFileName = tbrp.fileNamePatternWithoutCompSuffix.convertMultipleArguments(dateInElapsedPeriod, currentPeriodsCounter);
            currentPeriodsCounter = 0;
            setDateInCurrentPeriod(time);
            computeNextCheck();
            return true;
        }

        // next check for roll-over based on size
        if (invocationGate.isTooSoon(time)) {
            return false;
        }

        if (activeFile == null) {
            addWarn("activeFile == null");
            return false;
        }
        if (maxFileSize == null) {
            addWarn("maxFileSize = null");
            return false;
        }
        if (activeFile.length() >= maxFileSize.getSize()) {

            elapsedPeriodsFileName = tbrp.fileNamePatternWithoutCompSuffix.convertMultipleArguments(dateInCurrentPeriod, currentPeriodsCounter);
            currentPeriodsCounter++;
            return true;
        }

        return false;
    }
+

这里主要就用到了 nextCheck 判断，如果通过判断就可以执行滚动了，然后就是后面的判断，是否太快了，也就是 isTooSoon 然后再看当前的活跃日志以及最大文件大小是否设置，然后如果当前的活跃日志的大小超过了配置也会触发滚动

]]> - 生活 + Java - 生活 + Java - 聊一下 RocketMQ 的 DefaultMQPushConsumer 源码 - /2020/06/26/%E8%81%8A%E4%B8%80%E4%B8%8B-RocketMQ-%E7%9A%84-Consumer/ - 首先看下官方的小 demo

-
public static void main(String[] args) throws InterruptedException, MQClientException {

        /*
         * Instantiate with specified consumer group name.
         * 首先是new 一个对象出来，然后指定 Consumer 的 Group
         * 同一类Consumer的集合，这类Consumer通常消费同一类消息且消费逻辑一致。消费者组使得在消息消费方面，实现负载均衡和容错的目标变得非常容易。要注意的是，消费者组的消费者实例必须订阅完全相同的Topic。RocketMQ 支持两种消息模式：集群消费（Clustering）和广播消费（Broadcasting）。
         */
        DefaultMQPushConsumer consumer = new DefaultMQPushConsumer("please_rename_unique_group_name_4");

        /*
         * Specify name server addresses.
         * <p/>
         * 这里可以通知指定环境变量或者设置对象参数的形式指定名字空间服务的地址
         *
         * Alternatively, you may specify name server addresses via exporting environmental variable: NAMESRV_ADDR
         * <pre>
         * {@code
         * consumer.setNamesrvAddr("name-server1-ip:9876;name-server2-ip:9876");
         * }
         * </pre>
         */

        /*
         * Specify where to start in case the specified consumer group is a brand new one.
         * 指定消费起始点
         */
        consumer.setConsumeFromWhere(ConsumeFromWhere.CONSUME_FROM_FIRST_OFFSET);

        /*
         * Subscribe one more more topics to consume.
         * 指定订阅的 topic 跟 tag，注意后面的是个表达式，可以以 tag1 || tag2 || tag3 传入
         */
        consumer.subscribe("TopicTest", "*");

        /*
         *  Register callback to execute on arrival of messages fetched from brokers.
         *  注册具体获得消息后的处理方法
         */
        consumer.registerMessageListener(new MessageListenerConcurrently() {

            @Override
            public ConsumeConcurrentlyStatus consumeMessage(List<MessageExt> msgs,
                ConsumeConcurrentlyContext context) {
                System.out.printf("%s Receive New Messages: %s %n", Thread.currentThread().getName(), msgs);
                return ConsumeConcurrentlyStatus.CONSUME_SUCCESS;
            }
        });

        /*
         *  Launch the consumer instance.
         * 启动消费者
         */
        consumer.start();

        System.out.printf("Consumer Started.%n");
    }
- -

然后就是看看 start 的过程了

-
/**
     * This method gets internal infrastructure readily to serve. Instances must call this method after configuration.
     *
     * @throws MQClientException if there is any client error.
     */
    @Override
    public void start() throws MQClientException {
        setConsumerGroup(NamespaceUtil.wrapNamespace(this.getNamespace(), this.consumerGroup));
        this.defaultMQPushConsumerImpl.start();
        if (null != traceDispatcher) {
            try {
                traceDispatcher.start(this.getNamesrvAddr(), this.getAccessChannel());
            } catch (MQClientException e) {
                log.warn("trace dispatcher start failed ", e);
            }
        }
    }
-

具体的逻辑在this.defaultMQPushConsumerImpl.start()，这个 defaultMQPushConsumerImpl 就是

-
/**
     * Internal implementation. Most of the functions herein are delegated to it.
     */
    protected final transient DefaultMQPushConsumerImpl defaultMQPushConsumerImpl;
- -
public synchronized void start() throws MQClientException {
        switch (this.serviceState) {
            case CREATE_JUST:
                log.info("the consumer [{}] start beginning. messageModel={}, isUnitMode={}", this.defaultMQPushConsumer.getConsumerGroup(),
                    this.defaultMQPushConsumer.getMessageModel(), this.defaultMQPushConsumer.isUnitMode());
                // 这里比较巧妙，相当于想设立了个屏障，防止并发启动，不过这里并不是悲观锁，也不算个严格的乐观锁
                this.serviceState = ServiceState.START_FAILED;

                this.checkConfig();

                this.copySubscription();

                if (this.defaultMQPushConsumer.getMessageModel() == MessageModel.CLUSTERING) {
                    this.defaultMQPushConsumer.changeInstanceNameToPID();
                }

                // 这个mQClientFactory，负责管理client（consumer、producer），并提供多中功能接口供各个Service（Rebalance、PullMessage等）调用；大部分逻辑均在这个类中完成
                this.mQClientFactory = MQClientManager.getInstance().getOrCreateMQClientInstance(this.defaultMQPushConsumer, this.rpcHook);

                // 这个 rebalanceImpl 主要负责决定，当前的consumer应该从哪些Queue中消费消息；
                this.rebalanceImpl.setConsumerGroup(this.defaultMQPushConsumer.getConsumerGroup());
                this.rebalanceImpl.setMessageModel(this.defaultMQPushConsumer.getMessageModel());
                this.rebalanceImpl.setAllocateMessageQueueStrategy(this.defaultMQPushConsumer.getAllocateMessageQueueStrategy());
                this.rebalanceImpl.setmQClientFactory(this.mQClientFactory);

                // 长连接，负责从broker处拉取消息，然后利用ConsumeMessageService回调用户的Listener执行消息消费逻辑
                this.pullAPIWrapper = new PullAPIWrapper(
                    mQClientFactory,
                    this.defaultMQPushConsumer.getConsumerGroup(), isUnitMode());
                this.pullAPIWrapper.registerFilterMessageHook(filterMessageHookList);

                if (this.defaultMQPushConsumer.getOffsetStore() != null) {
                    this.offsetStore = this.defaultMQPushConsumer.getOffsetStore();
                } else {
                    switch (this.defaultMQPushConsumer.getMessageModel()) {
                        case BROADCASTING:
                            this.offsetStore = new LocalFileOffsetStore(this.mQClientFactory, this.defaultMQPushConsumer.getConsumerGroup());
                            break;
                        case CLUSTERING:
                            this.offsetStore = new RemoteBrokerOffsetStore(this.mQClientFactory, this.defaultMQPushConsumer.getConsumerGroup());
                            break;
                        default:
                            break;
                    }
                    this.defaultMQPushConsumer.setOffsetStore(this.offsetStore);
                }
                // offsetStore 维护当前consumer的消费记录（offset）；有两种实现，Local和Rmote，Local存储在本地磁盘上，适用于BROADCASTING广播消费模式；而Remote则将消费进度存储在Broker上，适用于CLUSTERING集群消费模式；
                this.offsetStore.load();

                if (this.getMessageListenerInner() instanceof MessageListenerOrderly) {
                    this.consumeOrderly = true;
                    this.consumeMessageService =
                        new ConsumeMessageOrderlyService(this, (MessageListenerOrderly) this.getMessageListenerInner());
                } else if (this.getMessageListenerInner() instanceof MessageListenerConcurrently) {
                    this.consumeOrderly = false;
                    this.consumeMessageService =
                        new ConsumeMessageConcurrentlyService(this, (MessageListenerConcurrently) this.getMessageListenerInner());
                }

                // 实现所谓的"Push-被动"消费机制；从Broker拉取的消息后，封装成ConsumeRequest提交给ConsumeMessageSerivce，此service负责回调用户的Listener消费消息；
                this.consumeMessageService.start();

                boolean registerOK = mQClientFactory.registerConsumer(this.defaultMQPushConsumer.getConsumerGroup(), this);
                if (!registerOK) {
                    this.serviceState = ServiceState.CREATE_JUST;
                    this.consumeMessageService.shutdown();
                    throw new MQClientException("The consumer group[" + this.defaultMQPushConsumer.getConsumerGroup()
                        + "] has been created before, specify another name please." + FAQUrl.suggestTodo(FAQUrl.GROUP_NAME_DUPLICATE_URL),
                        null);
                }

                mQClientFactory.start();
                log.info("the consumer [{}] start OK.", this.defaultMQPushConsumer.getConsumerGroup());
                this.serviceState = ServiceState.RUNNING;
                break;
            case RUNNING:
            case START_FAILED:
            case SHUTDOWN_ALREADY:
                throw new MQClientException("The PushConsumer service state not OK, maybe started once, "
                    + this.serviceState
                    + FAQUrl.suggestTodo(FAQUrl.CLIENT_SERVICE_NOT_OK),
                    null);
            default:
                break;
        }

        this.updateTopicSubscribeInfoWhenSubscriptionChanged();
        this.mQClientFactory.checkClientInBroker();
        this.mQClientFactory.sendHeartbeatToAllBrokerWithLock();
        this.mQClientFactory.rebalanceImmediately();
    }
-

然后我们往下看主要的目光聚焦mQClientFactory.start()

-
public void start() throws MQClientException {

        synchronized (this) {
            switch (this.serviceState) {
                case CREATE_JUST:
                    this.serviceState = ServiceState.START_FAILED;
                    // If not specified,looking address from name server
                    if (null == this.clientConfig.getNamesrvAddr()) {
                        this.mQClientAPIImpl.fetchNameServerAddr();
                    }
                    // Start request-response channel
                    // 这里主要是初始化了个网络客户端
                    this.mQClientAPIImpl.start();
                    // Start various schedule tasks
                    // 定时任务
                    this.startScheduledTask();
                    // Start pull service
                    // 这里重点说下
                    this.pullMessageService.start();
                    // Start rebalance service
                    this.rebalanceService.start();
                    // Start push service
                    this.defaultMQProducer.getDefaultMQProducerImpl().start(false);
                    log.info("the client factory [{}] start OK", this.clientId);
                    this.serviceState = ServiceState.RUNNING;
                    break;
                case START_FAILED:
                    throw new MQClientException("The Factory object[" + this.getClientId() + "] has been created before, and failed.", null);
                default:
                    break;
            }
        }
    }
-

我们来看下这个 pullMessageService，org.apache.rocketmq.client.impl.consumer.PullMessageService，

实现了 runnable 接口，
然后可以看到 run 方法

+ 聊一下 Java 的日志系列二 + /2024/01/14/%E8%81%8A%E4%B8%80%E4%B8%8B-Java-%E7%9A%84%E6%97%A5%E5%BF%97%E7%B3%BB%E5%88%97%E4%BA%8C/ + log 初始化过程，首先是在启动类里会获取 logger

+
private static final Log logger = LogFactory.getLog(SpringApplication.class);
+

然后是

+
public static Log getLog(Class clazz) throws LogConfigurationException {
        return getFactory().getInstance(clazz);
    }
+

继续下去是
org.apache.commons.logging.impl.SLF4JLogFactory#getInstance(java.lang.Class)

+
public Log getInstance(Class clazz) throws LogConfigurationException {
    return this.getInstance(clazz.getName());
}
public Log getInstance(String name) throws LogConfigurationException {
    Log instance = (Log)this.loggerMap.get(name);
    if (instance != null) {
        return instance;
    } else {
        Logger slf4jLogger = LoggerFactory.getLogger(name);
        Object newInstance;
        if (slf4jLogger instanceof LocationAwareLogger) {
            newInstance = new SLF4JLocationAwareLog((LocationAwareLogger)slf4jLogger);
        } else {
            newInstance = new SLF4JLog(slf4jLogger);
        }

        Log oldInstance = (Log)this.loggerMap.putIfAbsent(name, newInstance);
        return (Log)(oldInstance == null ? newInstance : oldInstance);
    }
}
+

然后再往下处理就是 LoggerFactory.getLogger(name); 了，跟普通的获取 logger 一样

+
public static Logger getLogger(String name) {
    ILoggerFactory iLoggerFactory = getILoggerFactory();
    return iLoggerFactory.getLogger(name);
}
+

继续下去会先判断是否已初始化

+
public static ILoggerFactory getILoggerFactory() {
        if (INITIALIZATION_STATE == UNINITIALIZED) {
            synchronized (LoggerFactory.class) {
                if (INITIALIZATION_STATE == UNINITIALIZED) {
                    INITIALIZATION_STATE = ONGOING_INITIALIZATION;
                    performInitialization();
                }
            }
        }
        switch (INITIALIZATION_STATE) {
        case SUCCESSFUL_INITIALIZATION:
            return StaticLoggerBinder.getSingleton().getLoggerFactory();
        case NOP_FALLBACK_INITIALIZATION:
            return NOP_FALLBACK_FACTORY;
        case FAILED_INITIALIZATION:
            throw new IllegalStateException(UNSUCCESSFUL_INIT_MSG);
        case ONGOING_INITIALIZATION:
            // support re-entrant behavior.
            // See also http://jira.qos.ch/browse/SLF4J-97
            return SUBST_FACTORY;
        }
        throw new IllegalStateException("Unreachable code");
    }
+

第一次调用的话就会走到 org.slf4j.LoggerFactory#performInitialization 里面是先调用绑定，这也是 slf4j 门面模式的特点

+
private final static void performInitialization() {
    bind();
    if (INITIALIZATION_STATE == SUCCESSFUL_INITIALIZATION) {
        versionSanityCheck();
    }
}
+ + +
private final static void bind() {
        try {
            Set<URL> staticLoggerBinderPathSet = null;
            // skip check under android, see also
            // http://jira.qos.ch/browse/SLF4J-328
            if (!isAndroid()) {
                staticLoggerBinderPathSet = findPossibleStaticLoggerBinderPathSet();
                reportMultipleBindingAmbiguity(staticLoggerBinderPathSet);
            }
            // the next line does the binding
            StaticLoggerBinder.getSingleton();
            INITIALIZATION_STATE = SUCCESSFUL_INITIALIZATION;
            reportActualBinding(staticLoggerBinderPathSet);
            fixSubstituteLoggers();
            replayEvents();
            // release all resources in SUBST_FACTORY
            SUBST_FACTORY.clear();
        } catch (NoClassDefFoundError ncde) {
            String msg = ncde.getMessage();
            if (messageContainsOrgSlf4jImplStaticLoggerBinder(msg)) {
                INITIALIZATION_STATE = NOP_FALLBACK_INITIALIZATION;
                Util.report("Failed to load class \"org.slf4j.impl.StaticLoggerBinder\".");
                Util.report("Defaulting to no-operation (NOP) logger implementation");
                Util.report("See " + NO_STATICLOGGERBINDER_URL + " for further details.");
            } else {
                failedBinding(ncde);
                throw ncde;
            }
        } catch (java.lang.NoSuchMethodError nsme) {
            String msg = nsme.getMessage();
            if (msg != null && msg.contains("org.slf4j.impl.StaticLoggerBinder.getSingleton()")) {
                INITIALIZATION_STATE = FAILED_INITIALIZATION;
                Util.report("slf4j-api 1.6.x (or later) is incompatible with this binding.");
                Util.report("Your binding is version 1.5.5 or earlier.");
                Util.report("Upgrade your binding to version 1.6.x.");
            }
            throw nsme;
        } catch (Exception e) {
            failedBinding(e);
            throw new IllegalStateException("Unexpected initialization failure", e);
        }
    }
+

非安卓环境会进入第一个 if 逻辑，先要去找static_logger_binder

+
static Set<URL> findPossibleStaticLoggerBinderPathSet() {
        // use Set instead of list in order to deal with bug #138
        // LinkedHashSet appropriate here because it preserves insertion order
        // during iteration
        Set<URL> staticLoggerBinderPathSet = new LinkedHashSet<URL>();
        try {
            ClassLoader loggerFactoryClassLoader = LoggerFactory.class.getClassLoader();
            Enumeration<URL> paths;
            if (loggerFactoryClassLoader == null) {
                paths = ClassLoader.getSystemResources(STATIC_LOGGER_BINDER_PATH);
            } else {
                paths = loggerFactoryClassLoader.getResources(STATIC_LOGGER_BINDER_PATH);
            }
            while (paths.hasMoreElements()) {
                URL path = paths.nextElement();
                staticLoggerBinderPathSet.add(path);
            }
        } catch (IOException ioe) {
            Util.report("Error getting resources from path", ioe);
        }
        return staticLoggerBinderPathSet;
    }
+

上面的 STATIC_LOGGER_BINDER_PATH
就是 org/slf4j/impl/StaticLoggerBinder.class 如果找不到在外层方法就会抛出 NoSuchMethodError 错误，然后就是通过 StaticLoggerBinder.getSingleton(); 获取 StaticLoggerBinder 实例了

+
public static StaticLoggerBinder getSingleton() {
    return SINGLETON;
}
private static StaticLoggerBinder SINGLETON = new StaticLoggerBinder();
+

比较重要的是这里的 static 代码块还有一个逻辑，就是下面这个初始化逻辑

+
static {
    SINGLETON.init();
}
void init() {
    try {
        try {
            new ContextInitializer(defaultLoggerContext).autoConfig();
        } catch (JoranException je) {
            Util.report("Failed to auto configure default logger context", je);
        }
        // logback-292
        if (!StatusUtil.contextHasStatusListener(defaultLoggerContext)) {
            StatusPrinter.printInCaseOfErrorsOrWarnings(defaultLoggerContext);
        }
        contextSelectorBinder.init(defaultLoggerContext, KEY);
        initialized = true;
    } catch (Exception t) { // see LOGBACK-1159
        Util.report("Failed to instantiate [" + LoggerContext.class.getName() + "]", t);
    }
}
+

上面的 defaultLoggerContext 也是通过静态代码块处理的

+
private LoggerContext defaultLoggerContext = new LoggerContext();
+

然后是调用 ch.qos.logback.classic.util.ContextInitializer#autoConfig 方法

+
public void autoConfig() throws JoranException {
        StatusListenerConfigHelper.installIfAsked(loggerContext);
        URL url = findURLOfDefaultConfigurationFile(true);
        if (url != null) {
            configureByResource(url);
        } else {
            Configurator c = EnvUtil.loadFromServiceLoader(Configurator.class);
            if (c != null) {
                try {
                    c.setContext(loggerContext);
                    c.configure(loggerContext);
                } catch (Exception e) {
                    throw new LogbackException(String.format("Failed to initialize Configurator: %s using ServiceLoader", c != null ? c.getClass()
                                    .getCanonicalName() : "null"), e);
                }
            } else {
                BasicConfigurator basicConfigurator = new BasicConfigurator();
                basicConfigurator.setContext(loggerContext);
                basicConfigurator.configure(loggerContext);
            }
        }
    }
+

前面会先查找配置文件路径
URL url = findURLOfDefaultConfigurationFile(true); 还是调用这个类内的 ch.qos.logback.classic.util.ContextInitializer#findURLOfDefaultConfigurationFile 方法

+
public URL findURLOfDefaultConfigurationFile(boolean updateStatus) {
    ClassLoader myClassLoader = Loader.getClassLoaderOfObject(this);
    URL url = findConfigFileURLFromSystemProperties(myClassLoader, updateStatus);
    if (url != null) {
        return url;
    }

    url = getResource(TEST_AUTOCONFIG_FILE, myClassLoader, updateStatus);
    if (url != null) {
        return url;
    }

    url = getResource(GROOVY_AUTOCONFIG_FILE, myClassLoader, updateStatus);
    if (url != null) {
        return url;
    }

    return getResource(AUTOCONFIG_FILE, myClassLoader, updateStatus);
}
+

才发现原来这里也是硬编码了文件名

+
public class ContextInitializer {

    final public static String GROOVY_AUTOCONFIG_FILE = "logback.groovy";
    final public static String AUTOCONFIG_FILE = "logback.xml";
    final public static String TEST_AUTOCONFIG_FILE = "logback-test.xml";
    final public static String CONFIG_FILE_PROPERTY = "logback.configurationFile";

+

如果不为空就调用了
ch.qos.logback.classic.util.ContextInitializer#configureByResource 这边是根据后缀判断处理方法

+
public void configureByResource(URL url) throws JoranException {
        if (url == null) {
            throw new IllegalArgumentException("URL argument cannot be null");
        }
        final String urlString = url.toString();
        if (urlString.endsWith("groovy")) {
            if (EnvUtil.isGroovyAvailable()) {
                // avoid directly referring to GafferConfigurator so as to avoid
                // loading groovy.lang.GroovyObject . See also http://jira.qos.ch/browse/LBCLASSIC-214
                GafferUtil.runGafferConfiguratorOn(loggerContext, this, url);
            } else {
                StatusManager sm = loggerContext.getStatusManager();
                sm.add(new ErrorStatus("Groovy classes are not available on the class path. ABORTING INITIALIZATION.", loggerContext));
            }
        } else if (urlString.endsWith("xml")) {
            JoranConfigurator configurator = new JoranConfigurator();
            configurator.setContext(loggerContext);
            configurator.doConfigure(url);
        } else {
            throw new LogbackException("Unexpected filename extension of file [" + url.toString() + "]. Should be either .groovy or .xml");
        }
    }
+

因为我们找到的是 logback.xml，所以走的是
ch.qos.logback.classic.joran.JoranConfigurator ，
然后调用了
ch.qos.logback.core.joran.GenericConfigurator#doConfigure(java.net.URL)
这个 GenericConfigurator 是 JoranConfigurator 的父类

+
public final void doConfigure(URL url) throws JoranException {
        InputStream in = null;
        try {
            informContextOfURLUsedForConfiguration(getContext(), url);
            URLConnection urlConnection = url.openConnection();
            // per http://jira.qos.ch/browse/LBCORE-105
            // per http://jira.qos.ch/browse/LBCORE-127
            urlConnection.setUseCaches(false);

            in = urlConnection.getInputStream();
            doConfigure(in, url.toExternalForm());
        } catch (IOException ioe) {
            String errMsg = "Could not open URL [" + url + "].";
            addError(errMsg, ioe);
            throw new JoranException(errMsg, ioe);
        } finally {
            if (in != null) {
                try {
                    in.close();
                } catch (IOException ioe) {
                    String errMsg = "Could not close input stream";
                    addError(errMsg, ioe);
                    throw new JoranException(errMsg, ioe);
                }
            }
        }
    }
+

然后继续调用
ch.qos.logback.core.joran.GenericConfigurator#doConfigure(java.io.InputStream, java.lang.String) 处理具体的内容，前面处理了内容获取，因为如果是走的 url 文件就需要从网络获取文件流，

+
public final void doConfigure(InputStream inputStream, String systemId) throws JoranException {
    InputSource inputSource = new InputSource(inputStream);
    inputSource.setSystemId(systemId);
    doConfigure(inputSource);
}
+

而实际的处理 xml 内容则是在
ch.qos.logback.core.joran.GenericConfigurator#doConfigure(org.xml.sax.InputSource)

+
public final void doConfigure(final InputSource inputSource) throws JoranException {

    long threshold = System.currentTimeMillis();
    // if (!ConfigurationWatchListUtil.wasConfigurationWatchListReset(context)) {
    // informContextOfURLUsedForConfiguration(getContext(), null);
    // }
    SaxEventRecorder recorder = new SaxEventRecorder(context);
    recorder.recordEvents(inputSource);
    doConfigure(recorder.saxEventList);
    // no exceptions a this level
    StatusUtil statusUtil = new StatusUtil(context);
    if (statusUtil.noXMLParsingErrorsOccurred(threshold)) {
        addInfo("Registering current configuration as safe fallback point");
        registerSafeConfiguration(recorder.saxEventList);
    }
}
+

需要解析 xml 了，先是调用 buildInterpreter 构建了 Interpreter

+
public void doConfigure(final List<SaxEvent> eventList) throws JoranException {
    buildInterpreter();
    // disallow simultaneous configurations of the same context
    synchronized (context.getConfigurationLock()) {
        interpreter.getEventPlayer().play(eventList);
    }
}
+

build 里还有一些逻辑，就是匹配后面要处理的规则集，就是要确认那些标签要处理

+
protected void buildInterpreter() {
        RuleStore rs = new SimpleRuleStore(context);
        addInstanceRules(rs);
        this.interpreter = new Interpreter(context, rs, initialElementPath());
        InterpretationContext interpretationContext = interpreter.getInterpretationContext();
        interpretationContext.setContext(context);
        addImplicitRules(interpreter);
        addDefaultNestedComponentRegistryRules(interpretationContext.getDefaultNestedComponentRegistry());
    }
+

第一步就是先 new 一个 ch.qos.logback.core.joran.spi.SimpleRuleStore 然后调用了 ch.qos.logback.classic.joran.JoranConfigurator#addInstanceRules 来添加规则，就是下面的，可以看到对于 logger,appender 这些的配置，其中前面点的父类也又一些规则 ,ch.qos.logback.core.joran.JoranConfiguratorBase 逻辑类似就不展开了，这里的规则就对应了后面的各种 Action，就是对应的处理逻辑

+
public void addInstanceRules(RuleStore rs) {
    // parent rules already added
    super.addInstanceRules(rs);

    rs.addRule(new ElementSelector("configuration"), new ConfigurationAction());

    rs.addRule(new ElementSelector("configuration/contextName"), new ContextNameAction());
    rs.addRule(new ElementSelector("configuration/contextListener"), new LoggerContextListenerAction());
    rs.addRule(new ElementSelector("configuration/insertFromJNDI"), new InsertFromJNDIAction());
    rs.addRule(new ElementSelector("configuration/evaluator"), new EvaluatorAction());

    rs.addRule(new ElementSelector("configuration/appender/sift"), new SiftAction());
    rs.addRule(new ElementSelector("configuration/appender/sift/*"), new NOPAction());

    rs.addRule(new ElementSelector("configuration/logger"), new LoggerAction());
    rs.addRule(new ElementSelector("configuration/logger/level"), new LevelAction());

    rs.addRule(new ElementSelector("configuration/root"), new RootLoggerAction());
    rs.addRule(new ElementSelector("configuration/root/level"), new LevelAction());
    rs.addRule(new ElementSelector("configuration/logger/appender-ref"), new AppenderRefAction<ILoggingEvent>());
    rs.addRule(new ElementSelector("configuration/root/appender-ref"), new AppenderRefAction<ILoggingEvent>());

    // add if-then-else support
    rs.addRule(new ElementSelector("*/if"), new IfAction());
    rs.addRule(new ElementSelector("*/if/then"), new ThenAction());
    rs.addRule(new ElementSelector("*/if/then/*"), new NOPAction());
    rs.addRule(new ElementSelector("*/if/else"), new ElseAction());
    rs.addRule(new ElementSelector("*/if/else/*"), new NOPAction());

    // add jmxConfigurator only if we have JMX available.
    // If running under JDK 1.4 (retrotranslateed logback) then we
    // might not have JMX.
    if (PlatformInfo.hasJMXObjectName()) {
        rs.addRule(new ElementSelector("configuration/jmxConfigurator"), new JMXConfiguratorAction());
    }
    rs.addRule(new ElementSelector("configuration/include"), new IncludeAction());

    rs.addRule(new ElementSelector("configuration/consolePlugin"), new ConsolePluginAction());

    rs.addRule(new ElementSelector("configuration/receiver"), new ReceiverAction());

}
+

然后调用了 interpreter 的 eventPlayer 处理 xml 的各个标签

+
public void play(List<SaxEvent> aSaxEventList) {
        eventList = aSaxEventList;
        SaxEvent se;
        for (currentIndex = 0; currentIndex < eventList.size(); currentIndex++) {
            se = eventList.get(currentIndex);

            if (se instanceof StartEvent) {
                interpreter.startElement((StartEvent) se);
                // invoke fireInPlay after startElement processing
                interpreter.getInterpretationContext().fireInPlay(se);
            }
            if (se instanceof BodyEvent) {
                // invoke fireInPlay before characters processing
                interpreter.getInterpretationContext().fireInPlay(se);
                interpreter.characters((BodyEvent) se);
            }
            if (se instanceof EndEvent) {
                // invoke fireInPlay before endElement processing
                interpreter.getInterpretationContext().fireInPlay(se);
                interpreter.endElement((EndEvent) se);
            }

        }
    }
+

接下去就在 startElement 中调用会先获取 getApplicableActionList 适配的 Action， callBeginAction

+
private void startElement(String namespaceURI, String localName, String qName, Attributes atts) {

        String tagName = getTagName(localName, qName);
        elementPath.push(tagName);

        if (skip != null) {
            // every startElement pushes an action list
            pushEmptyActionList();
            return;
        }

        List<Action> applicableActionList = getApplicableActionList(elementPath, atts);
        if (applicableActionList != null) {
            actionListStack.add(applicableActionList);
            callBeginAction(applicableActionList, tagName, atts);
        } else {
            // every startElement pushes an action list
            pushEmptyActionList();
            String errMsg = "no applicable action for [" + tagName + "], current ElementPath  is [" + elementPath + "]";
            cai.addError(errMsg);
        }
    }
+

里面就是用了 ruleStore 来判断是否适配，并且取出对应的 Action

+
List<Action> getApplicableActionList(ElementPath elementPath, Attributes attributes) {
    List<Action> applicableActionList = ruleStore.matchActions(elementPath);

    // logger.debug("set of applicable patterns: " + applicableActionList);
    if (applicableActionList == null) {
        applicableActionList = lookupImplicitAction(elementPath, attributes, interpretationContext);
    }

    return applicableActionList;
}
+

比如我这边往下处理，通过规则匹配拿到了 LoggerAction, 然后调用 Action.begin 方法

+
void callBeginAction(List<Action> applicableActionList, String tagName, Attributes atts) {
        if (applicableActionList == null) {
            return;
        }

        Iterator<Action> i = applicableActionList.iterator();
        while (i.hasNext()) {
            Action action = (Action) i.next();
            // now let us invoke the action. We catch and report any eventual
            // exceptions
            try {
                action.begin(interpretationContext, tagName, atts);
            } catch (ActionException e) {
                skip = elementPath.duplicate();
                cai.addError("ActionException in Action for tag [" + tagName + "]", e);
            } catch (RuntimeException e) {
                skip = elementPath.duplicate();
                cai.addError("RuntimeException in Action for tag [" + tagName + "]", e);
            }
        }
    }
+

就是下面这个

+
public void begin(InterpretationContext ec, String name, Attributes attributes) {
        // Let us forget about previous errors (in this object)
        inError = false;
        logger = null;

        LoggerContext loggerContext = (LoggerContext) this.context;

        String loggerName = ec.subst(attributes.getValue(NAME_ATTRIBUTE));

        if (OptionHelper.isEmpty(loggerName)) {
            inError = true;
            String aroundLine = getLineColStr(ec);
            String errorMsg = "No 'name' attribute in element " + name + ", around " + aroundLine;
            addError(errorMsg);
            return;
        }

        logger = loggerContext.getLogger(loggerName);

        String levelStr = ec.subst(attributes.getValue(LEVEL_ATTRIBUTE));

        if (!OptionHelper.isEmpty(levelStr)) {
            if (ActionConst.INHERITED.equalsIgnoreCase(levelStr) || ActionConst.NULL.equalsIgnoreCase(levelStr)) {
                addInfo("Setting level of logger [" + loggerName + "] to null, i.e. INHERITED");
                logger.setLevel(null);
            } else {
                Level level = Level.toLevel(levelStr);
                addInfo("Setting level of logger [" + loggerName + "] to " + level);
                logger.setLevel(level);
            }
        }

        String additivityStr = ec.subst(attributes.getValue(ActionConst.ADDITIVITY_ATTRIBUTE));
        if (!OptionHelper.isEmpty(additivityStr)) {
            boolean additive = OptionHelper.toBoolean(additivityStr, true);
            addInfo("Setting additivity of logger [" + loggerName + "] to " + additive);
            logger.setAdditive(additive);
        }
        ec.pushObject(logger);
    }
+

这里就会处理 logger 获取逻辑

+
public final Logger getLogger(final String name) {

        if (name == null) {
            throw new IllegalArgumentException("name argument cannot be null");
        }

        // if we are asking for the root logger, then let us return it without
        // wasting time
        if (Logger.ROOT_LOGGER_NAME.equalsIgnoreCase(name)) {
            return root;
        }

        int i = 0;
        Logger logger = root;

        // check if the desired logger exists, if it does, return it
        // without further ado.
        Logger childLogger = (Logger) loggerCache.get(name);
        // if we have the child, then let us return it without wasting time
        if (childLogger != null) {
            return childLogger;
        }

        // if the desired logger does not exist, them create all the loggers
        // in between as well (if they don't already exist)
        String childName;
        while (true) {
            int h = LoggerNameUtil.getSeparatorIndexOf(name, i);
            if (h == -1) {
                childName = name;
            } else {
                childName = name.substring(0, h);
            }
            // move i left of the last point
            i = h + 1;
            synchronized (logger) {
                childLogger = logger.getChildByName(childName);
                if (childLogger == null) {
                    childLogger = logger.createChildByName(childName);
                    loggerCache.put(childName, childLogger);
                    incSize();
                }
            }
            logger = childLogger;
            if (h == -1) {
                return childLogger;
            }
        }
    }
+

如果从 loggerCache 中能取到就直接获取，如果不能就会去创建

+]]> + + Java + + + Java + + + + 聊一下 RocketMQ 的 DefaultMQPushConsumer 源码 + /2020/06/26/%E8%81%8A%E4%B8%80%E4%B8%8B-RocketMQ-%E7%9A%84-Consumer/ + 首先看下官方的小 demo

+
public static void main(String[] args) throws InterruptedException, MQClientException {

        /*
         * Instantiate with specified consumer group name.
         * 首先是new 一个对象出来，然后指定 Consumer 的 Group
         * 同一类Consumer的集合，这类Consumer通常消费同一类消息且消费逻辑一致。消费者组使得在消息消费方面，实现负载均衡和容错的目标变得非常容易。要注意的是，消费者组的消费者实例必须订阅完全相同的Topic。RocketMQ 支持两种消息模式：集群消费（Clustering）和广播消费（Broadcasting）。
         */
        DefaultMQPushConsumer consumer = new DefaultMQPushConsumer("please_rename_unique_group_name_4");

        /*
         * Specify name server addresses.
         * <p/>
         * 这里可以通知指定环境变量或者设置对象参数的形式指定名字空间服务的地址
         *
         * Alternatively, you may specify name server addresses via exporting environmental variable: NAMESRV_ADDR
         * <pre>
         * {@code
         * consumer.setNamesrvAddr("name-server1-ip:9876;name-server2-ip:9876");
         * }
         * </pre>
         */

        /*
         * Specify where to start in case the specified consumer group is a brand new one.
         * 指定消费起始点
         */
        consumer.setConsumeFromWhere(ConsumeFromWhere.CONSUME_FROM_FIRST_OFFSET);

        /*
         * Subscribe one more more topics to consume.
         * 指定订阅的 topic 跟 tag，注意后面的是个表达式，可以以 tag1 || tag2 || tag3 传入
         */
        consumer.subscribe("TopicTest", "*");

        /*
         *  Register callback to execute on arrival of messages fetched from brokers.
         *  注册具体获得消息后的处理方法
         */
        consumer.registerMessageListener(new MessageListenerConcurrently() {

            @Override
            public ConsumeConcurrentlyStatus consumeMessage(List<MessageExt> msgs,
                ConsumeConcurrentlyContext context) {
                System.out.printf("%s Receive New Messages: %s %n", Thread.currentThread().getName(), msgs);
                return ConsumeConcurrentlyStatus.CONSUME_SUCCESS;
            }
        });

        /*
         *  Launch the consumer instance.
         * 启动消费者
         */
        consumer.start();

        System.out.printf("Consumer Started.%n");
    }
+ +

然后就是看看 start 的过程了

+
/**
     * This method gets internal infrastructure readily to serve. Instances must call this method after configuration.
     *
     * @throws MQClientException if there is any client error.
     */
    @Override
    public void start() throws MQClientException {
        setConsumerGroup(NamespaceUtil.wrapNamespace(this.getNamespace(), this.consumerGroup));
        this.defaultMQPushConsumerImpl.start();
        if (null != traceDispatcher) {
            try {
                traceDispatcher.start(this.getNamesrvAddr(), this.getAccessChannel());
            } catch (MQClientException e) {
                log.warn("trace dispatcher start failed ", e);
            }
        }
    }
+

具体的逻辑在this.defaultMQPushConsumerImpl.start()，这个 defaultMQPushConsumerImpl 就是

+
/**
     * Internal implementation. Most of the functions herein are delegated to it.
     */
    protected final transient DefaultMQPushConsumerImpl defaultMQPushConsumerImpl;
+ +
public synchronized void start() throws MQClientException {
        switch (this.serviceState) {
            case CREATE_JUST:
                log.info("the consumer [{}] start beginning. messageModel={}, isUnitMode={}", this.defaultMQPushConsumer.getConsumerGroup(),
                    this.defaultMQPushConsumer.getMessageModel(), this.defaultMQPushConsumer.isUnitMode());
                // 这里比较巧妙，相当于想设立了个屏障，防止并发启动，不过这里并不是悲观锁，也不算个严格的乐观锁
                this.serviceState = ServiceState.START_FAILED;

                this.checkConfig();

                this.copySubscription();

                if (this.defaultMQPushConsumer.getMessageModel() == MessageModel.CLUSTERING) {
                    this.defaultMQPushConsumer.changeInstanceNameToPID();
                }

                // 这个mQClientFactory，负责管理client（consumer、producer），并提供多中功能接口供各个Service（Rebalance、PullMessage等）调用；大部分逻辑均在这个类中完成
                this.mQClientFactory = MQClientManager.getInstance().getOrCreateMQClientInstance(this.defaultMQPushConsumer, this.rpcHook);

                // 这个 rebalanceImpl 主要负责决定，当前的consumer应该从哪些Queue中消费消息；
                this.rebalanceImpl.setConsumerGroup(this.defaultMQPushConsumer.getConsumerGroup());
                this.rebalanceImpl.setMessageModel(this.defaultMQPushConsumer.getMessageModel());
                this.rebalanceImpl.setAllocateMessageQueueStrategy(this.defaultMQPushConsumer.getAllocateMessageQueueStrategy());
                this.rebalanceImpl.setmQClientFactory(this.mQClientFactory);

                // 长连接，负责从broker处拉取消息，然后利用ConsumeMessageService回调用户的Listener执行消息消费逻辑
                this.pullAPIWrapper = new PullAPIWrapper(
                    mQClientFactory,
                    this.defaultMQPushConsumer.getConsumerGroup(), isUnitMode());
                this.pullAPIWrapper.registerFilterMessageHook(filterMessageHookList);

                if (this.defaultMQPushConsumer.getOffsetStore() != null) {
                    this.offsetStore = this.defaultMQPushConsumer.getOffsetStore();
                } else {
                    switch (this.defaultMQPushConsumer.getMessageModel()) {
                        case BROADCASTING:
                            this.offsetStore = new LocalFileOffsetStore(this.mQClientFactory, this.defaultMQPushConsumer.getConsumerGroup());
                            break;
                        case CLUSTERING:
                            this.offsetStore = new RemoteBrokerOffsetStore(this.mQClientFactory, this.defaultMQPushConsumer.getConsumerGroup());
                            break;
                        default:
                            break;
                    }
                    this.defaultMQPushConsumer.setOffsetStore(this.offsetStore);
                }
                // offsetStore 维护当前consumer的消费记录（offset）；有两种实现，Local和Rmote，Local存储在本地磁盘上，适用于BROADCASTING广播消费模式；而Remote则将消费进度存储在Broker上，适用于CLUSTERING集群消费模式；
                this.offsetStore.load();

                if (this.getMessageListenerInner() instanceof MessageListenerOrderly) {
                    this.consumeOrderly = true;
                    this.consumeMessageService =
                        new ConsumeMessageOrderlyService(this, (MessageListenerOrderly) this.getMessageListenerInner());
                } else if (this.getMessageListenerInner() instanceof MessageListenerConcurrently) {
                    this.consumeOrderly = false;
                    this.consumeMessageService =
                        new ConsumeMessageConcurrentlyService(this, (MessageListenerConcurrently) this.getMessageListenerInner());
                }

                // 实现所谓的"Push-被动"消费机制；从Broker拉取的消息后，封装成ConsumeRequest提交给ConsumeMessageSerivce，此service负责回调用户的Listener消费消息；
                this.consumeMessageService.start();

                boolean registerOK = mQClientFactory.registerConsumer(this.defaultMQPushConsumer.getConsumerGroup(), this);
                if (!registerOK) {
                    this.serviceState = ServiceState.CREATE_JUST;
                    this.consumeMessageService.shutdown();
                    throw new MQClientException("The consumer group[" + this.defaultMQPushConsumer.getConsumerGroup()
                        + "] has been created before, specify another name please." + FAQUrl.suggestTodo(FAQUrl.GROUP_NAME_DUPLICATE_URL),
                        null);
                }

                mQClientFactory.start();
                log.info("the consumer [{}] start OK.", this.defaultMQPushConsumer.getConsumerGroup());
                this.serviceState = ServiceState.RUNNING;
                break;
            case RUNNING:
            case START_FAILED:
            case SHUTDOWN_ALREADY:
                throw new MQClientException("The PushConsumer service state not OK, maybe started once, "
                    + this.serviceState
                    + FAQUrl.suggestTodo(FAQUrl.CLIENT_SERVICE_NOT_OK),
                    null);
            default:
                break;
        }

        this.updateTopicSubscribeInfoWhenSubscriptionChanged();
        this.mQClientFactory.checkClientInBroker();
        this.mQClientFactory.sendHeartbeatToAllBrokerWithLock();
        this.mQClientFactory.rebalanceImmediately();
    }
+

然后我们往下看主要的目光聚焦mQClientFactory.start()

+
public void start() throws MQClientException {

        synchronized (this) {
            switch (this.serviceState) {
                case CREATE_JUST:
                    this.serviceState = ServiceState.START_FAILED;
                    // If not specified,looking address from name server
                    if (null == this.clientConfig.getNamesrvAddr()) {
                        this.mQClientAPIImpl.fetchNameServerAddr();
                    }
                    // Start request-response channel
                    // 这里主要是初始化了个网络客户端
                    this.mQClientAPIImpl.start();
                    // Start various schedule tasks
                    // 定时任务
                    this.startScheduledTask();
                    // Start pull service
                    // 这里重点说下
                    this.pullMessageService.start();
                    // Start rebalance service
                    this.rebalanceService.start();
                    // Start push service
                    this.defaultMQProducer.getDefaultMQProducerImpl().start(false);
                    log.info("the client factory [{}] start OK", this.clientId);
                    this.serviceState = ServiceState.RUNNING;
                    break;
                case START_FAILED:
                    throw new MQClientException("The Factory object[" + this.getClientId() + "] has been created before, and failed.", null);
                default:
                    break;
            }
        }
    }
+

我们来看下这个 pullMessageService，org.apache.rocketmq.client.impl.consumer.PullMessageService，

实现了 runnable 接口，
然后可以看到 run 方法

public void run() {
        log.info(this.getServiceName() + " service started");

        while (!this.isStopped()) {
            try {
                PullRequest pullRequest = this.pullRequestQueue.take();
                this.pullMessage(pullRequest);
            } catch (InterruptedException ignored) {
            } catch (Exception e) {
                log.error("Pull Message Service Run Method exception", e);
            }
        }

        log.info(this.getServiceName() + " service end");
    }

接着在看 pullMessage 方法

private void pullMessage(final PullRequest pullRequest) {
        final MQConsumerInner consumer = this.mQClientFactory.selectConsumer(pullRequest.getConsumerGroup());
        if (consumer != null) {
            DefaultMQPushConsumerImpl impl = (DefaultMQPushConsumerImpl) consumer;
            impl.pullMessage(pullRequest);
        } else {
            log.warn("No matched consumer for the PullRequest {}, drop it", pullRequest);
        }
    }
@@ -5215,44 +5322,6 @@ user3:

这里也可以看到 ConsumeQueue 的存储格式，

AA6Tve

偏移量，消息大小，跟 tag 的 hashCode

-]]> - - MQ - RocketMQ - 消息队列 - - - MQ - 消息队列 - RocketMQ - - - - 聊一下 RocketMQ 的消息存储二 - /2021/09/12/%E8%81%8A%E4%B8%80%E4%B8%8B-RocketMQ-%E7%9A%84%E6%B6%88%E6%81%AF%E5%AD%98%E5%82%A8%E4%BA%8C/ - CommitLog 结构

CommitLog 是 rocketmq 的服务端，也就是 broker 存储消息的的文件，跟 kafka 一样，也是顺序写入，当然消息是变长的，生成的规则是每个文件的默认1G =1024 * 1024 * 1024，commitlog的文件名fileName，名字长度为20位，左边补零，剩余为起始偏移量；比如00000000000000000000代表了第一个文件，起始偏移量为0，文件大小为1G=1 073 741 824Byte；当这个文件满了，第二个文件名字为00000000001073741824，起始偏移量为1073741824, 消息存储的时候会顺序写入文件，当文件满了则写入下一个文件，代码中的定义

-
// CommitLog file size,default is 1G
private int mapedFileSizeCommitLog = 1024 * 1024 * 1024;
- -

kLahwW

-

本地跑个 demo 验证下，也是这样，这里奇妙有几个比较巧妙的点（个人观点），首先文件就刚好是 1G，并且按照大小偏移量去生成下一个文件，这样获取消息的时候按大小算一下就知道在哪个文件里了，

-

代码中写入 CommitLog 的逻辑可以从这开始看

-
public PutMessageResult putMessage(final MessageExtBrokerInner msg) {
        // Set the storage time
        msg.setStoreTimestamp(System.currentTimeMillis());
        // Set the message body BODY CRC (consider the most appropriate setting
        // on the client)
        msg.setBodyCRC(UtilAll.crc32(msg.getBody()));
        // Back to Results
        AppendMessageResult result = null;

        StoreStatsService storeStatsService = this.defaultMessageStore.getStoreStatsService();

        String topic = msg.getTopic();
        int queueId = msg.getQueueId();

        final int tranType = MessageSysFlag.getTransactionValue(msg.getSysFlag());
        if (tranType == MessageSysFlag.TRANSACTION_NOT_TYPE
            || tranType == MessageSysFlag.TRANSACTION_COMMIT_TYPE) {
            // Delay Delivery
            if (msg.getDelayTimeLevel() > 0) {
                if (msg.getDelayTimeLevel() > this.defaultMessageStore.getScheduleMessageService().getMaxDelayLevel()) {
                    msg.setDelayTimeLevel(this.defaultMessageStore.getScheduleMessageService().getMaxDelayLevel());
                }

                topic = ScheduleMessageService.SCHEDULE_TOPIC;
                queueId = ScheduleMessageService.delayLevel2QueueId(msg.getDelayTimeLevel());

                // Backup real topic, queueId
                MessageAccessor.putProperty(msg, MessageConst.PROPERTY_REAL_TOPIC, msg.getTopic());
                MessageAccessor.putProperty(msg, MessageConst.PROPERTY_REAL_QUEUE_ID, String.valueOf(msg.getQueueId()));
                msg.setPropertiesString(MessageDecoder.messageProperties2String(msg.getProperties()));

                msg.setTopic(topic);
                msg.setQueueId(queueId);
            }
        }

        long eclipseTimeInLock = 0;
        MappedFile unlockMappedFile = null;
        MappedFile mappedFile = this.mappedFileQueue.getLastMappedFile();

        putMessageLock.lock(); //spin or ReentrantLock ,depending on store config
        try {
            long beginLockTimestamp = this.defaultMessageStore.getSystemClock().now();
            this.beginTimeInLock = beginLockTimestamp;

            // Here settings are stored timestamp, in order to ensure an orderly
            // global
            msg.setStoreTimestamp(beginLockTimestamp);

            if (null == mappedFile || mappedFile.isFull()) {
                mappedFile = this.mappedFileQueue.getLastMappedFile(0); // Mark: NewFile may be cause noise
            }
            if (null == mappedFile) {
                log.error("create mapped file1 error, topic: " + msg.getTopic() + " clientAddr: " + msg.getBornHostString());
                beginTimeInLock = 0;
                return new PutMessageResult(PutMessageStatus.CREATE_MAPEDFILE_FAILED, null);
            }

            result = mappedFile.appendMessage(msg, this.appendMessageCallback);
            switch (result.getStatus()) {
                case PUT_OK:
                    break;
                case END_OF_FILE:
                    unlockMappedFile = mappedFile;
                    // Create a new file, re-write the message
                    mappedFile = this.mappedFileQueue.getLastMappedFile(0);
                    if (null == mappedFile) {
                        // XXX: warn and notify me
                        log.error("create mapped file2 error, topic: " + msg.getTopic() + " clientAddr: " + msg.getBornHostString());
                        beginTimeInLock = 0;
                        return new PutMessageResult(PutMessageStatus.CREATE_MAPEDFILE_FAILED, result);
                    }
                    result = mappedFile.appendMessage(msg, this.appendMessageCallback);
                    break;
                case MESSAGE_SIZE_EXCEEDED:
                case PROPERTIES_SIZE_EXCEEDED:
                    beginTimeInLock = 0;
                    return new PutMessageResult(PutMessageStatus.MESSAGE_ILLEGAL, result);
                case UNKNOWN_ERROR:
                    beginTimeInLock = 0;
                    return new PutMessageResult(PutMessageStatus.UNKNOWN_ERROR, result);
                default:
                    beginTimeInLock = 0;
                    return new PutMessageResult(PutMessageStatus.UNKNOWN_ERROR, result);
            }

            eclipseTimeInLock = this.defaultMessageStore.getSystemClock().now() - beginLockTimestamp;
            beginTimeInLock = 0;
        } finally {
            putMessageLock.unlock();
        }

        if (eclipseTimeInLock > 500) {
            log.warn("[NOTIFYME]putMessage in lock cost time(ms)={}, bodyLength={} AppendMessageResult={}", eclipseTimeInLock, msg.getBody().length, result);
        }

        if (null != unlockMappedFile && this.defaultMessageStore.getMessageStoreConfig().isWarmMapedFileEnable()) {
            this.defaultMessageStore.unlockMappedFile(unlockMappedFile);
        }

        PutMessageResult putMessageResult = new PutMessageResult(PutMessageStatus.PUT_OK, result);

        // Statistics
        storeStatsService.getSinglePutMessageTopicTimesTotal(msg.getTopic()).incrementAndGet();
        storeStatsService.getSinglePutMessageTopicSizeTotal(topic).addAndGet(result.getWroteBytes());

        handleDiskFlush(result, putMessageResult, msg);
        handleHA(result, putMessageResult, msg);

        return putMessageResult;
    }
- -

前面也看到在CommitLog 目录下是有大小为 1G 的文件组成，在实现逻辑中，其实是通过 org.apache.rocketmq.store.MappedFileQueue ，内部是存的一个MappedFile的队列，对于写入的场景每次都是通过org.apache.rocketmq.store.MappedFileQueue#getLastMappedFile() 获取最后一个文件，如果还没有创建，或者最后这个文件已经满了，那就调用 org.apache.rocketmq.store.MappedFileQueue#getLastMappedFile(long)

-
public MappedFile getLastMappedFile(final long startOffset, boolean needCreate) {
        long createOffset = -1;
  			// 调用前面的方法，只是从 mappedFileQueue 获取最后一个
        MappedFile mappedFileLast = getLastMappedFile();

        // 如果为空，计算下创建的偏移量
        if (mappedFileLast == null) {
            createOffset = startOffset - (startOffset % this.mappedFileSize);
        }
  
				// 如果不为空，但是当前的文件写满了
        if (mappedFileLast != null && mappedFileLast.isFull()) {
            // 前一个的偏移量加上单个文件的偏移量，也就是 1G
            createOffset = mappedFileLast.getFileFromOffset() + this.mappedFileSize;
        }

        if (createOffset != -1 && needCreate) {
            // 根据 createOffset 转换成文件名进行创建
            String nextFilePath = this.storePath + File.separator + UtilAll.offset2FileName(createOffset);
            String nextNextFilePath = this.storePath + File.separator
                + UtilAll.offset2FileName(createOffset + this.mappedFileSize);
            MappedFile mappedFile = null;

          	// 这里如果allocateMappedFileService 存在，就提交请求
            if (this.allocateMappedFileService != null) {
                mappedFile = this.allocateMappedFileService.putRequestAndReturnMappedFile(nextFilePath,
                    nextNextFilePath, this.mappedFileSize);
            } else {
                try {
                  // 否则就直接创建
                    mappedFile = new MappedFile(nextFilePath, this.mappedFileSize);
                } catch (IOException e) {
                    log.error("create mappedFile exception", e);
                }
            }

            if (mappedFile != null) {
                if (this.mappedFiles.isEmpty()) {
                    mappedFile.setFirstCreateInQueue(true);
                }
                this.mappedFiles.add(mappedFile);
            }

            return mappedFile;
        }

        return mappedFileLast;
    }
- -

首先看下直接创建的，

-
public MappedFile(final String fileName, final int fileSize) throws IOException {
        init(fileName, fileSize);
    }
private void init(final String fileName, final int fileSize) throws IOException {
        this.fileName = fileName;
        this.fileSize = fileSize;
        this.file = new File(fileName);
        this.fileFromOffset = Long.parseLong(this.file.getName());
        boolean ok = false;

        ensureDirOK(this.file.getParent());

        try {
          // 通过 RandomAccessFile 创建 fileChannel
            this.fileChannel = new RandomAccessFile(this.file, "rw").getChannel();
          // 做 mmap 映射
            this.mappedByteBuffer = this.fileChannel.map(MapMode.READ_WRITE, 0, fileSize);
            TOTAL_MAPPED_VIRTUAL_MEMORY.addAndGet(fileSize);
            TOTAL_MAPPED_FILES.incrementAndGet();
            ok = true;
        } catch (FileNotFoundException e) {
            log.error("create file channel " + this.fileName + " Failed. ", e);
            throw e;
        } catch (IOException e) {
            log.error("map file " + this.fileName + " Failed. ", e);
            throw e;
        } finally {
            if (!ok && this.fileChannel != null) {
                this.fileChannel.close();
            }
        }
    }
- -

如果是提交给AllocateMappedFileService的话就用到了一些异步操作

-
public MappedFile putRequestAndReturnMappedFile(String nextFilePath, String nextNextFilePath, int fileSize) {
        int canSubmitRequests = 2;
        if (this.messageStore.getMessageStoreConfig().isTransientStorePoolEnable()) {
            if (this.messageStore.getMessageStoreConfig().isFastFailIfNoBufferInStorePool()
                && BrokerRole.SLAVE != this.messageStore.getMessageStoreConfig().getBrokerRole()) { //if broker is slave, don't fast fail even no buffer in pool
                canSubmitRequests = this.messageStore.getTransientStorePool().remainBufferNumbs() - this.requestQueue.size();
            }
        }
				// 将请求放在 requestTable 中
        AllocateRequest nextReq = new AllocateRequest(nextFilePath, fileSize);
        boolean nextPutOK = this.requestTable.putIfAbsent(nextFilePath, nextReq) == null;
        // requestTable 使用了 concurrentHashMap，用文件名作为 key，防止并发
        if (nextPutOK) {
            // 这里判断了是否可以提交到 TransientStorePool，涉及读写分离，后面再细聊
            if (canSubmitRequests <= 0) {
                log.warn("[NOTIFYME]TransientStorePool is not enough, so create mapped file error, " +
                    "RequestQueueSize : {}, StorePoolSize: {}", this.requestQueue.size(), this.messageStore.getTransientStorePool().remainBufferNumbs());
                this.requestTable.remove(nextFilePath);
                return null;
            }
          // 塞到阻塞队列中
            boolean offerOK = this.requestQueue.offer(nextReq);
            if (!offerOK) {
                log.warn("never expected here, add a request to preallocate queue failed");
            }
            canSubmitRequests--;
        }

        // 这里的两个提交我猜测是为了多生成一个 CommitLog，
        AllocateRequest nextNextReq = new AllocateRequest(nextNextFilePath, fileSize);
        boolean nextNextPutOK = this.requestTable.putIfAbsent(nextNextFilePath, nextNextReq) == null;
        if (nextNextPutOK) {
            if (canSubmitRequests <= 0) {
                log.warn("[NOTIFYME]TransientStorePool is not enough, so skip preallocate mapped file, " +
                    "RequestQueueSize : {}, StorePoolSize: {}", this.requestQueue.size(), this.messageStore.getTransientStorePool().remainBufferNumbs());
                this.requestTable.remove(nextNextFilePath);
            } else {
                boolean offerOK = this.requestQueue.offer(nextNextReq);
                if (!offerOK) {
                    log.warn("never expected here, add a request to preallocate queue failed");
                }
            }
        }

        if (hasException) {
            log.warn(this.getServiceName() + " service has exception. so return null");
            return null;
        }

        AllocateRequest result = this.requestTable.get(nextFilePath);
        try {
          // 这里就异步等着
            if (result != null) {
                boolean waitOK = result.getCountDownLatch().await(waitTimeOut, TimeUnit.MILLISECONDS);
                if (!waitOK) {
                    log.warn("create mmap timeout " + result.getFilePath() + " " + result.getFileSize());
                    return null;
                } else {
                    this.requestTable.remove(nextFilePath);
                    return result.getMappedFile();
                }
            } else {
                log.error("find preallocate mmap failed, this never happen");
            }
        } catch (InterruptedException e) {
            log.warn(this.getServiceName() + " service has exception. ", e);
        }

        return null;
    }
- -

而真正去执行文件操作的就是 AllocateMappedFileService的 run 方法

-
public void run() {
        log.info(this.getServiceName() + " service started");

        while (!this.isStopped() && this.mmapOperation()) {

        }
        log.info(this.getServiceName() + " service end");
    }
private boolean mmapOperation() {
        boolean isSuccess = false;
        AllocateRequest req = null;
        try {
          // 从阻塞队列里获取请求
            req = this.requestQueue.take();
            AllocateRequest expectedRequest = this.requestTable.get(req.getFilePath());
            if (null == expectedRequest) {
                log.warn("this mmap request expired, maybe cause timeout " + req.getFilePath() + " "
                    + req.getFileSize());
                return true;
            }
            if (expectedRequest != req) {
                log.warn("never expected here,  maybe cause timeout " + req.getFilePath() + " "
                    + req.getFileSize() + ", req:" + req + ", expectedRequest:" + expectedRequest);
                return true;
            }

            if (req.getMappedFile() == null) {
                long beginTime = System.currentTimeMillis();

                MappedFile mappedFile;
                if (messageStore.getMessageStoreConfig().isTransientStorePoolEnable()) {
                    try {
                      // 通过 transientStorePool 创建
                        mappedFile = ServiceLoader.load(MappedFile.class).iterator().next();
                        mappedFile.init(req.getFilePath(), req.getFileSize(), messageStore.getTransientStorePool());
                    } catch (RuntimeException e) {
                        log.warn("Use default implementation.");
                      // 默认创建
                        mappedFile = new MappedFile(req.getFilePath(), req.getFileSize(), messageStore.getTransientStorePool());
                    }
                } else {
                  // 默认创建
                    mappedFile = new MappedFile(req.getFilePath(), req.getFileSize());
                }

                long eclipseTime = UtilAll.computeEclipseTimeMilliseconds(beginTime);
                if (eclipseTime > 10) {
                    int queueSize = this.requestQueue.size();
                    log.warn("create mappedFile spent time(ms) " + eclipseTime + " queue size " + queueSize
                        + " " + req.getFilePath() + " " + req.getFileSize());
                }

                // pre write mappedFile
                if (mappedFile.getFileSize() >= this.messageStore.getMessageStoreConfig()
                    .getMapedFileSizeCommitLog()
                    &&
                    this.messageStore.getMessageStoreConfig().isWarmMapedFileEnable()) {
                    mappedFile.warmMappedFile(this.messageStore.getMessageStoreConfig().getFlushDiskType(),
                        this.messageStore.getMessageStoreConfig().getFlushLeastPagesWhenWarmMapedFile());
                }

                req.setMappedFile(mappedFile);
                this.hasException = false;
                isSuccess = true;
            }
        } catch (InterruptedException e) {
            log.warn(this.getServiceName() + " interrupted, possibly by shutdown.");
            this.hasException = true;
            return false;
        } catch (IOException e) {
            log.warn(this.getServiceName() + " service has exception. ", e);
            this.hasException = true;
            if (null != req) {
                requestQueue.offer(req);
                try {
                    Thread.sleep(1);
                } catch (InterruptedException ignored) {
                }
            }
        } finally {
            if (req != null && isSuccess)
              // 通知前面等待的
                req.getCountDownLatch().countDown();
        }
        return true;
    }
- - - - ]]> MQ @@ -5327,6 +5396,108 @@ user3: NameServer + + 聊一下 RocketMQ 的消息存储二 + /2021/09/12/%E8%81%8A%E4%B8%80%E4%B8%8B-RocketMQ-%E7%9A%84%E6%B6%88%E6%81%AF%E5%AD%98%E5%82%A8%E4%BA%8C/ + CommitLog 结构

CommitLog 是 rocketmq 的服务端，也就是 broker 存储消息的的文件，跟 kafka 一样，也是顺序写入，当然消息是变长的，生成的规则是每个文件的默认1G =1024 * 1024 * 1024，commitlog的文件名fileName，名字长度为20位，左边补零，剩余为起始偏移量；比如00000000000000000000代表了第一个文件，起始偏移量为0，文件大小为1G=1 073 741 824Byte；当这个文件满了，第二个文件名字为00000000001073741824，起始偏移量为1073741824, 消息存储的时候会顺序写入文件，当文件满了则写入下一个文件，代码中的定义

+
// CommitLog file size,default is 1G
private int mapedFileSizeCommitLog = 1024 * 1024 * 1024;
+ +

kLahwW

+

本地跑个 demo 验证下，也是这样，这里奇妙有几个比较巧妙的点（个人观点），首先文件就刚好是 1G，并且按照大小偏移量去生成下一个文件，这样获取消息的时候按大小算一下就知道在哪个文件里了，

+

代码中写入 CommitLog 的逻辑可以从这开始看

+
public PutMessageResult putMessage(final MessageExtBrokerInner msg) {
        // Set the storage time
        msg.setStoreTimestamp(System.currentTimeMillis());
        // Set the message body BODY CRC (consider the most appropriate setting
        // on the client)
        msg.setBodyCRC(UtilAll.crc32(msg.getBody()));
        // Back to Results
        AppendMessageResult result = null;

        StoreStatsService storeStatsService = this.defaultMessageStore.getStoreStatsService();

        String topic = msg.getTopic();
        int queueId = msg.getQueueId();

        final int tranType = MessageSysFlag.getTransactionValue(msg.getSysFlag());
        if (tranType == MessageSysFlag.TRANSACTION_NOT_TYPE
            || tranType == MessageSysFlag.TRANSACTION_COMMIT_TYPE) {
            // Delay Delivery
            if (msg.getDelayTimeLevel() > 0) {
                if (msg.getDelayTimeLevel() > this.defaultMessageStore.getScheduleMessageService().getMaxDelayLevel()) {
                    msg.setDelayTimeLevel(this.defaultMessageStore.getScheduleMessageService().getMaxDelayLevel());
                }

                topic = ScheduleMessageService.SCHEDULE_TOPIC;
                queueId = ScheduleMessageService.delayLevel2QueueId(msg.getDelayTimeLevel());

                // Backup real topic, queueId
                MessageAccessor.putProperty(msg, MessageConst.PROPERTY_REAL_TOPIC, msg.getTopic());
                MessageAccessor.putProperty(msg, MessageConst.PROPERTY_REAL_QUEUE_ID, String.valueOf(msg.getQueueId()));
                msg.setPropertiesString(MessageDecoder.messageProperties2String(msg.getProperties()));

                msg.setTopic(topic);
                msg.setQueueId(queueId);
            }
        }

        long eclipseTimeInLock = 0;
        MappedFile unlockMappedFile = null;
        MappedFile mappedFile = this.mappedFileQueue.getLastMappedFile();

        putMessageLock.lock(); //spin or ReentrantLock ,depending on store config
        try {
            long beginLockTimestamp = this.defaultMessageStore.getSystemClock().now();
            this.beginTimeInLock = beginLockTimestamp;

            // Here settings are stored timestamp, in order to ensure an orderly
            // global
            msg.setStoreTimestamp(beginLockTimestamp);

            if (null == mappedFile || mappedFile.isFull()) {
                mappedFile = this.mappedFileQueue.getLastMappedFile(0); // Mark: NewFile may be cause noise
            }
            if (null == mappedFile) {
                log.error("create mapped file1 error, topic: " + msg.getTopic() + " clientAddr: " + msg.getBornHostString());
                beginTimeInLock = 0;
                return new PutMessageResult(PutMessageStatus.CREATE_MAPEDFILE_FAILED, null);
            }

            result = mappedFile.appendMessage(msg, this.appendMessageCallback);
            switch (result.getStatus()) {
                case PUT_OK:
                    break;
                case END_OF_FILE:
                    unlockMappedFile = mappedFile;
                    // Create a new file, re-write the message
                    mappedFile = this.mappedFileQueue.getLastMappedFile(0);
                    if (null == mappedFile) {
                        // XXX: warn and notify me
                        log.error("create mapped file2 error, topic: " + msg.getTopic() + " clientAddr: " + msg.getBornHostString());
                        beginTimeInLock = 0;
                        return new PutMessageResult(PutMessageStatus.CREATE_MAPEDFILE_FAILED, result);
                    }
                    result = mappedFile.appendMessage(msg, this.appendMessageCallback);
                    break;
                case MESSAGE_SIZE_EXCEEDED:
                case PROPERTIES_SIZE_EXCEEDED:
                    beginTimeInLock = 0;
                    return new PutMessageResult(PutMessageStatus.MESSAGE_ILLEGAL, result);
                case UNKNOWN_ERROR:
                    beginTimeInLock = 0;
                    return new PutMessageResult(PutMessageStatus.UNKNOWN_ERROR, result);
                default:
                    beginTimeInLock = 0;
                    return new PutMessageResult(PutMessageStatus.UNKNOWN_ERROR, result);
            }

            eclipseTimeInLock = this.defaultMessageStore.getSystemClock().now() - beginLockTimestamp;
            beginTimeInLock = 0;
        } finally {
            putMessageLock.unlock();
        }

        if (eclipseTimeInLock > 500) {
            log.warn("[NOTIFYME]putMessage in lock cost time(ms)={}, bodyLength={} AppendMessageResult={}", eclipseTimeInLock, msg.getBody().length, result);
        }

        if (null != unlockMappedFile && this.defaultMessageStore.getMessageStoreConfig().isWarmMapedFileEnable()) {
            this.defaultMessageStore.unlockMappedFile(unlockMappedFile);
        }

        PutMessageResult putMessageResult = new PutMessageResult(PutMessageStatus.PUT_OK, result);

        // Statistics
        storeStatsService.getSinglePutMessageTopicTimesTotal(msg.getTopic()).incrementAndGet();
        storeStatsService.getSinglePutMessageTopicSizeTotal(topic).addAndGet(result.getWroteBytes());

        handleDiskFlush(result, putMessageResult, msg);
        handleHA(result, putMessageResult, msg);

        return putMessageResult;
    }
+ +

前面也看到在CommitLog 目录下是有大小为 1G 的文件组成，在实现逻辑中，其实是通过 org.apache.rocketmq.store.MappedFileQueue ，内部是存的一个MappedFile的队列，对于写入的场景每次都是通过org.apache.rocketmq.store.MappedFileQueue#getLastMappedFile() 获取最后一个文件，如果还没有创建，或者最后这个文件已经满了，那就调用 org.apache.rocketmq.store.MappedFileQueue#getLastMappedFile(long)

+
public MappedFile getLastMappedFile(final long startOffset, boolean needCreate) {
        long createOffset = -1;
  			// 调用前面的方法，只是从 mappedFileQueue 获取最后一个
        MappedFile mappedFileLast = getLastMappedFile();

        // 如果为空，计算下创建的偏移量
        if (mappedFileLast == null) {
            createOffset = startOffset - (startOffset % this.mappedFileSize);
        }
  
				// 如果不为空，但是当前的文件写满了
        if (mappedFileLast != null && mappedFileLast.isFull()) {
            // 前一个的偏移量加上单个文件的偏移量，也就是 1G
            createOffset = mappedFileLast.getFileFromOffset() + this.mappedFileSize;
        }

        if (createOffset != -1 && needCreate) {
            // 根据 createOffset 转换成文件名进行创建
            String nextFilePath = this.storePath + File.separator + UtilAll.offset2FileName(createOffset);
            String nextNextFilePath = this.storePath + File.separator
                + UtilAll.offset2FileName(createOffset + this.mappedFileSize);
            MappedFile mappedFile = null;

          	// 这里如果allocateMappedFileService 存在，就提交请求
            if (this.allocateMappedFileService != null) {
                mappedFile = this.allocateMappedFileService.putRequestAndReturnMappedFile(nextFilePath,
                    nextNextFilePath, this.mappedFileSize);
            } else {
                try {
                  // 否则就直接创建
                    mappedFile = new MappedFile(nextFilePath, this.mappedFileSize);
                } catch (IOException e) {
                    log.error("create mappedFile exception", e);
                }
            }

            if (mappedFile != null) {
                if (this.mappedFiles.isEmpty()) {
                    mappedFile.setFirstCreateInQueue(true);
                }
                this.mappedFiles.add(mappedFile);
            }

            return mappedFile;
        }

        return mappedFileLast;
    }
+ +

首先看下直接创建的，

+
public MappedFile(final String fileName, final int fileSize) throws IOException {
        init(fileName, fileSize);
    }
private void init(final String fileName, final int fileSize) throws IOException {
        this.fileName = fileName;
        this.fileSize = fileSize;
        this.file = new File(fileName);
        this.fileFromOffset = Long.parseLong(this.file.getName());
        boolean ok = false;

        ensureDirOK(this.file.getParent());

        try {
          // 通过 RandomAccessFile 创建 fileChannel
            this.fileChannel = new RandomAccessFile(this.file, "rw").getChannel();
          // 做 mmap 映射
            this.mappedByteBuffer = this.fileChannel.map(MapMode.READ_WRITE, 0, fileSize);
            TOTAL_MAPPED_VIRTUAL_MEMORY.addAndGet(fileSize);
            TOTAL_MAPPED_FILES.incrementAndGet();
            ok = true;
        } catch (FileNotFoundException e) {
            log.error("create file channel " + this.fileName + " Failed. ", e);
            throw e;
        } catch (IOException e) {
            log.error("map file " + this.fileName + " Failed. ", e);
            throw e;
        } finally {
            if (!ok && this.fileChannel != null) {
                this.fileChannel.close();
            }
        }
    }
+ +

如果是提交给AllocateMappedFileService的话就用到了一些异步操作

+
public MappedFile putRequestAndReturnMappedFile(String nextFilePath, String nextNextFilePath, int fileSize) {
        int canSubmitRequests = 2;
        if (this.messageStore.getMessageStoreConfig().isTransientStorePoolEnable()) {
            if (this.messageStore.getMessageStoreConfig().isFastFailIfNoBufferInStorePool()
                && BrokerRole.SLAVE != this.messageStore.getMessageStoreConfig().getBrokerRole()) { //if broker is slave, don't fast fail even no buffer in pool
                canSubmitRequests = this.messageStore.getTransientStorePool().remainBufferNumbs() - this.requestQueue.size();
            }
        }
				// 将请求放在 requestTable 中
        AllocateRequest nextReq = new AllocateRequest(nextFilePath, fileSize);
        boolean nextPutOK = this.requestTable.putIfAbsent(nextFilePath, nextReq) == null;
        // requestTable 使用了 concurrentHashMap，用文件名作为 key，防止并发
        if (nextPutOK) {
            // 这里判断了是否可以提交到 TransientStorePool，涉及读写分离，后面再细聊
            if (canSubmitRequests <= 0) {
                log.warn("[NOTIFYME]TransientStorePool is not enough, so create mapped file error, " +
                    "RequestQueueSize : {}, StorePoolSize: {}", this.requestQueue.size(), this.messageStore.getTransientStorePool().remainBufferNumbs());
                this.requestTable.remove(nextFilePath);
                return null;
            }
          // 塞到阻塞队列中
            boolean offerOK = this.requestQueue.offer(nextReq);
            if (!offerOK) {
                log.warn("never expected here, add a request to preallocate queue failed");
            }
            canSubmitRequests--;
        }

        // 这里的两个提交我猜测是为了多生成一个 CommitLog，
        AllocateRequest nextNextReq = new AllocateRequest(nextNextFilePath, fileSize);
        boolean nextNextPutOK = this.requestTable.putIfAbsent(nextNextFilePath, nextNextReq) == null;
        if (nextNextPutOK) {
            if (canSubmitRequests <= 0) {
                log.warn("[NOTIFYME]TransientStorePool is not enough, so skip preallocate mapped file, " +
                    "RequestQueueSize : {}, StorePoolSize: {}", this.requestQueue.size(), this.messageStore.getTransientStorePool().remainBufferNumbs());
                this.requestTable.remove(nextNextFilePath);
            } else {
                boolean offerOK = this.requestQueue.offer(nextNextReq);
                if (!offerOK) {
                    log.warn("never expected here, add a request to preallocate queue failed");
                }
            }
        }

        if (hasException) {
            log.warn(this.getServiceName() + " service has exception. so return null");
            return null;
        }

        AllocateRequest result = this.requestTable.get(nextFilePath);
        try {
          // 这里就异步等着
            if (result != null) {
                boolean waitOK = result.getCountDownLatch().await(waitTimeOut, TimeUnit.MILLISECONDS);
                if (!waitOK) {
                    log.warn("create mmap timeout " + result.getFilePath() + " " + result.getFileSize());
                    return null;
                } else {
                    this.requestTable.remove(nextFilePath);
                    return result.getMappedFile();
                }
            } else {
                log.error("find preallocate mmap failed, this never happen");
            }
        } catch (InterruptedException e) {
            log.warn(this.getServiceName() + " service has exception. ", e);
        }

        return null;
    }
+ +

而真正去执行文件操作的就是 AllocateMappedFileService的 run 方法

+
public void run() {
        log.info(this.getServiceName() + " service started");

        while (!this.isStopped() && this.mmapOperation()) {

        }
        log.info(this.getServiceName() + " service end");
    }
private boolean mmapOperation() {
        boolean isSuccess = false;
        AllocateRequest req = null;
        try {
          // 从阻塞队列里获取请求
            req = this.requestQueue.take();
            AllocateRequest expectedRequest = this.requestTable.get(req.getFilePath());
            if (null == expectedRequest) {
                log.warn("this mmap request expired, maybe cause timeout " + req.getFilePath() + " "
                    + req.getFileSize());
                return true;
            }
            if (expectedRequest != req) {
                log.warn("never expected here,  maybe cause timeout " + req.getFilePath() + " "
                    + req.getFileSize() + ", req:" + req + ", expectedRequest:" + expectedRequest);
                return true;
            }

            if (req.getMappedFile() == null) {
                long beginTime = System.currentTimeMillis();

                MappedFile mappedFile;
                if (messageStore.getMessageStoreConfig().isTransientStorePoolEnable()) {
                    try {
                      // 通过 transientStorePool 创建
                        mappedFile = ServiceLoader.load(MappedFile.class).iterator().next();
                        mappedFile.init(req.getFilePath(), req.getFileSize(), messageStore.getTransientStorePool());
                    } catch (RuntimeException e) {
                        log.warn("Use default implementation.");
                      // 默认创建
                        mappedFile = new MappedFile(req.getFilePath(), req.getFileSize(), messageStore.getTransientStorePool());
                    }
                } else {
                  // 默认创建
                    mappedFile = new MappedFile(req.getFilePath(), req.getFileSize());
                }

                long eclipseTime = UtilAll.computeEclipseTimeMilliseconds(beginTime);
                if (eclipseTime > 10) {
                    int queueSize = this.requestQueue.size();
                    log.warn("create mappedFile spent time(ms) " + eclipseTime + " queue size " + queueSize
                        + " " + req.getFilePath() + " " + req.getFileSize());
                }

                // pre write mappedFile
                if (mappedFile.getFileSize() >= this.messageStore.getMessageStoreConfig()
                    .getMapedFileSizeCommitLog()
                    &&
                    this.messageStore.getMessageStoreConfig().isWarmMapedFileEnable()) {
                    mappedFile.warmMappedFile(this.messageStore.getMessageStoreConfig().getFlushDiskType(),
                        this.messageStore.getMessageStoreConfig().getFlushLeastPagesWhenWarmMapedFile());
                }

                req.setMappedFile(mappedFile);
                this.hasException = false;
                isSuccess = true;
            }
        } catch (InterruptedException e) {
            log.warn(this.getServiceName() + " interrupted, possibly by shutdown.");
            this.hasException = true;
            return false;
        } catch (IOException e) {
            log.warn(this.getServiceName() + " service has exception. ", e);
            this.hasException = true;
            if (null != req) {
                requestQueue.offer(req);
                try {
                    Thread.sleep(1);
                } catch (InterruptedException ignored) {
                }
            }
        } finally {
            if (req != null && isSuccess)
              // 通知前面等待的
                req.getCountDownLatch().countDown();
        }
        return true;
    }
+ + + + +]]> + + MQ + RocketMQ + 消息队列 + + + MQ + 消息队列 + RocketMQ + + + + 聊一下 RocketMQ 的消息存储四 + /2021/10/17/%E8%81%8A%E4%B8%80%E4%B8%8B-RocketMQ-%E7%9A%84%E6%B6%88%E6%81%AF%E5%AD%98%E5%82%A8%E5%9B%9B/ + IndexFile 结构 hash 结构能够通过 key 寻找到对应在 CommitLog 中的位置

+

IndexFile 的构建则是分发给这个进行处理

+
class CommitLogDispatcherBuildIndex implements CommitLogDispatcher {

    @Override
    public void dispatch(DispatchRequest request) {
        if (DefaultMessageStore.this.messageStoreConfig.isMessageIndexEnable()) {
            DefaultMessageStore.this.indexService.buildIndex(request);
        }
    }
}
public void buildIndex(DispatchRequest req) {
        IndexFile indexFile = retryGetAndCreateIndexFile();
        if (indexFile != null) {
            long endPhyOffset = indexFile.getEndPhyOffset();
            DispatchRequest msg = req;
            String topic = msg.getTopic();
            String keys = msg.getKeys();
            if (msg.getCommitLogOffset() < endPhyOffset) {
                return;
            }

            final int tranType = MessageSysFlag.getTransactionValue(msg.getSysFlag());
            switch (tranType) {
                case MessageSysFlag.TRANSACTION_NOT_TYPE:
                case MessageSysFlag.TRANSACTION_PREPARED_TYPE:
                case MessageSysFlag.TRANSACTION_COMMIT_TYPE:
                    break;
                case MessageSysFlag.TRANSACTION_ROLLBACK_TYPE:
                    return;
            }

            if (req.getUniqKey() != null) {
                indexFile = putKey(indexFile, msg, buildKey(topic, req.getUniqKey()));
                if (indexFile == null) {
                    log.error("putKey error commitlog {} uniqkey {}", req.getCommitLogOffset(), req.getUniqKey());
                    return;
                }
            }

            if (keys != null && keys.length() > 0) {
                String[] keyset = keys.split(MessageConst.KEY_SEPARATOR);
                for (int i = 0; i < keyset.length; i++) {
                    String key = keyset[i];
                    if (key.length() > 0) {
                        indexFile = putKey(indexFile, msg, buildKey(topic, key));
                        if (indexFile == null) {
                            log.error("putKey error commitlog {} uniqkey {}", req.getCommitLogOffset(), req.getUniqKey());
                            return;
                        }
                    }
                }
            }
        } else {
            log.error("build index error, stop building index");
        }
    }
+ +

配置的数量

+
private boolean messageIndexEnable = true;
private int maxHashSlotNum = 5000000;
private int maxIndexNum = 5000000 * 4;
+ +

最核心的其实是 IndexFile 的结构和如何写入

+
public boolean putKey(final String key, final long phyOffset, final long storeTimestamp) {
        if (this.indexHeader.getIndexCount() < this.indexNum) {
          // 获取 key 的 hash
            int keyHash = indexKeyHashMethod(key);
          // 计算属于哪个 slot
            int slotPos = keyHash % this.hashSlotNum;
          // 计算 slot 位置 因为结构是有个 indexHead，主要是分为三段 header，slot 和 index
            int absSlotPos = IndexHeader.INDEX_HEADER_SIZE + slotPos * hashSlotSize;

            FileLock fileLock = null;

            try {

                // fileLock = this.fileChannel.lock(absSlotPos, hashSlotSize,
                // false);
                int slotValue = this.mappedByteBuffer.getInt(absSlotPos);
                if (slotValue <= invalidIndex || slotValue > this.indexHeader.getIndexCount()) {
                    slotValue = invalidIndex;
                }

                long timeDiff = storeTimestamp - this.indexHeader.getBeginTimestamp();

                timeDiff = timeDiff / 1000;

                if (this.indexHeader.getBeginTimestamp() <= 0) {
                    timeDiff = 0;
                } else if (timeDiff > Integer.MAX_VALUE) {
                    timeDiff = Integer.MAX_VALUE;
                } else if (timeDiff < 0) {
                    timeDiff = 0;
                }

              // 计算索引存放位置，头部 + slot 数量 * slot 大小 + 已有的 index 数量 + index 大小
                int absIndexPos =
                    IndexHeader.INDEX_HEADER_SIZE + this.hashSlotNum * hashSlotSize
                        + this.indexHeader.getIndexCount() * indexSize;
							
                this.mappedByteBuffer.putInt(absIndexPos, keyHash);
                this.mappedByteBuffer.putLong(absIndexPos + 4, phyOffset);
                this.mappedByteBuffer.putInt(absIndexPos + 4 + 8, (int) timeDiff);
                this.mappedByteBuffer.putInt(absIndexPos + 4 + 8 + 4, slotValue);

              // 存放的是数量位移，不是绝对位置
                this.mappedByteBuffer.putInt(absSlotPos, this.indexHeader.getIndexCount());

                if (this.indexHeader.getIndexCount() <= 1) {
                    this.indexHeader.setBeginPhyOffset(phyOffset);
                    this.indexHeader.setBeginTimestamp(storeTimestamp);
                }

                this.indexHeader.incHashSlotCount();
                this.indexHeader.incIndexCount();
                this.indexHeader.setEndPhyOffset(phyOffset);
                this.indexHeader.setEndTimestamp(storeTimestamp);

                return true;
            } catch (Exception e) {
                log.error("putKey exception, Key: " + key + " KeyHashCode: " + key.hashCode(), e);
            } finally {
                if (fileLock != null) {
                    try {
                        fileLock.release();
                    } catch (IOException e) {
                        log.error("Failed to release the lock", e);
                    }
                }
            }
        } else {
            log.warn("Over index file capacity: index count = " + this.indexHeader.getIndexCount()
                + "; index max num = " + this.indexNum);
        }

        return false;
    }
+ +

具体可以看一下这个简略的示意图

+]]> + + MQ + RocketMQ + 消息队列 + + + MQ + 消息队列 + RocketMQ + + + + 聊一下 RocketMQ 的顺序消息 + /2021/08/29/%E8%81%8A%E4%B8%80%E4%B8%8B-RocketMQ-%E7%9A%84%E9%A1%BA%E5%BA%8F%E6%B6%88%E6%81%AF/ + rocketmq 里有一种比较特殊的用法，就是顺序消息，比如订单的生命周期里，在创建，支付，签收等状态轮转中，会发出来对应的消息，这里面就比较需要去保证他们的顺序，当然在处理的业务代码也可以做对应的处理，结合消息重投，但是如果这里消息就能保证顺序性了，那么业务代码就能更好的关注业务代码的处理。

+

首先有一种情况是全局的有序，比如对于一个 topic 里就得发送线程保证只有一个，内部的 queue 也只有一个，消费线程也只有一个，这样就能比较容易的保证全局顺序性了，但是这里的问题就是完全限制了性能，不是很现实，在真实场景里很多都是比如对于同一个订单，需要去保证状态的轮转是按照预期的顺序来，而不必要全局的有序性。

+

对于这类的有序性，需要在发送和接收方都有对应的处理，在发送消息中，需要去指定 selector，即MessageQueueSelector，能够以固定的方式是分配到对应的 MessageQueue

+

比如像 RocketMQ 中的示例

+
SendResult sendResult = producer.send(msg, new MessageQueueSelector() {
                @Override
                public MessageQueue select(List<MessageQueue> mqs, Message msg, Object arg) {
                    Long id = (Long) arg;  //message queue is selected by #salesOrderID
                    long index = id % mqs.size();
                    return mqs.get((int) index);
                }
            }, orderList.get(i).getOrderId());
+ +

而在消费侧有几个点比较重要，首先我们要保证一个 MessageQueue只被一个消费者消费，消费队列存在broker端，要保证 MessageQueue 只被一个消费者消费，那么消费者在进行消息拉取消费时就必须向mq服务器申请队列锁，消费者申请队列锁的代码存在于RebalanceService消息队列负载的实现代码中。

+
List<PullRequest> pullRequestList = new ArrayList<PullRequest>();
        for (MessageQueue mq : mqSet) {
            if (!this.processQueueTable.containsKey(mq)) {
              // 判断是否顺序，如果是顺序消费的，则需要加锁
                if (isOrder && !this.lock(mq)) {
                    log.warn("doRebalance, {}, add a new mq failed, {}, because lock failed", consumerGroup, mq);
                    continue;
                }

                this.removeDirtyOffset(mq);
                ProcessQueue pq = new ProcessQueue();
                long nextOffset = this.computePullFromWhere(mq);
                if (nextOffset >= 0) {
                    ProcessQueue pre = this.processQueueTable.putIfAbsent(mq, pq);
                    if (pre != null) {
                        log.info("doRebalance, {}, mq already exists, {}", consumerGroup, mq);
                    } else {
                        log.info("doRebalance, {}, add a new mq, {}", consumerGroup, mq);
                        PullRequest pullRequest = new PullRequest();
                        pullRequest.setConsumerGroup(consumerGroup);
                        pullRequest.setNextOffset(nextOffset);
                        pullRequest.setMessageQueue(mq);
                        pullRequest.setProcessQueue(pq);
                        pullRequestList.add(pullRequest);
                        changed = true;
                    }
                } else {
                    log.warn("doRebalance, {}, add new mq failed, {}", consumerGroup, mq);
                }
            }
        }
+ +

在申请到锁之后会创建 pullRequest 进行消息拉取，消息拉取部分的代码实现在PullMessageService中，

+
@Override
    public void run() {
        log.info(this.getServiceName() + " service started");

        while (!this.isStopped()) {
            try {
                PullRequest pullRequest = this.pullRequestQueue.take();
                this.pullMessage(pullRequest);
            } catch (InterruptedException ignored) {
            } catch (Exception e) {
                log.error("Pull Message Service Run Method exception", e);
            }
        }

        log.info(this.getServiceName() + " service end");
    }
+ +

消息拉取完后，需要提交到ConsumeMessageService中进行消费，顺序消费的实现为ConsumeMessageOrderlyService，提交消息进行消费的方法为ConsumeMessageOrderlyService#submitConsumeRequest，具体实现如下：

+
@Override
public void submitConsumeRequest(
    final List<MessageExt> msgs,
    final ProcessQueue processQueue,
    final MessageQueue messageQueue,
    final boolean dispathToConsume) {
    if (dispathToConsume) {
        ConsumeRequest consumeRequest = new ConsumeRequest(processQueue, messageQueue);
        this.consumeExecutor.submit(consumeRequest);
    }
}
+ +

构建了一个ConsumeRequest对象，它是个实现了 runnable 接口的类，并提交给了线程池来并行消费，看下顺序消费的ConsumeRequest的run方法实现：

+
@Override
        public void run() {
            if (this.processQueue.isDropped()) {
                log.warn("run, the message queue not be able to consume, because it's dropped. {}", this.messageQueue);
                return;
            }
						// 获得 Consumer 消息队列锁，即单个线程独占
            final Object objLock = messageQueueLock.fetchLockObject(this.messageQueue);
            synchronized (objLock) {
              // (广播模式) 或者 (集群模式 && Broker消息队列锁有效)
                if (MessageModel.BROADCASTING.equals(ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.messageModel())
                    || (this.processQueue.isLocked() && !this.processQueue.isLockExpired())) {
                    final long beginTime = System.currentTimeMillis();
                  // 循环
                    for (boolean continueConsume = true; continueConsume; ) {
                        if (this.processQueue.isDropped()) {
                            log.warn("the message queue not be able to consume, because it's dropped. {}", this.messageQueue);
                            break;
                        }

                      // 消息队列分布式锁未锁定，提交延迟获得锁并消费请求
                        if (MessageModel.CLUSTERING.equals(ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.messageModel())
                            && !this.processQueue.isLocked()) {
                            log.warn("the message queue not locked, so consume later, {}", this.messageQueue);
                            ConsumeMessageOrderlyService.this.tryLockLaterAndReconsume(this.messageQueue, this.processQueue, 10);
                            break;
                        }

                      // 消息队列分布式锁已经过期，提交延迟获得锁并消费请求
                        if (MessageModel.CLUSTERING.equals(ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.messageModel())
                            && this.processQueue.isLockExpired()) {
                            log.warn("the message queue lock expired, so consume later, {}", this.messageQueue);
                            ConsumeMessageOrderlyService.this.tryLockLaterAndReconsume(this.messageQueue, this.processQueue, 10);
                            break;
                        }
												// 当前周期消费时间超过连续时长，默认：60s，提交延迟消费请求。默认情况下，每消费1分钟休息10ms。
                        long interval = System.currentTimeMillis() - beginTime;
                        if (interval > MAX_TIME_CONSUME_CONTINUOUSLY) {
                            ConsumeMessageOrderlyService.this.submitConsumeRequestLater(processQueue, messageQueue, 10);
                            break;
                        }
												// 获取消费消息。此处和并发消息请求不同，并发消息请求已经带了消费哪些消息。
                        final int consumeBatchSize =
                            ConsumeMessageOrderlyService.this.defaultMQPushConsumer.getConsumeMessageBatchMaxSize();

                        List<MessageExt> msgs = this.processQueue.takeMessags(consumeBatchSize);
                        defaultMQPushConsumerImpl.resetRetryAndNamespace(msgs, defaultMQPushConsumer.getConsumerGroup());
                        if (!msgs.isEmpty()) {
                            final ConsumeOrderlyContext context = new ConsumeOrderlyContext(this.messageQueue);

                            ConsumeOrderlyStatus status = null;

                            ConsumeMessageContext consumeMessageContext = null;
                            if (ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.hasHook()) {
                                consumeMessageContext = new ConsumeMessageContext();
                                consumeMessageContext
                                    .setConsumerGroup(ConsumeMessageOrderlyService.this.defaultMQPushConsumer.getConsumerGroup());
                                consumeMessageContext.setNamespace(defaultMQPushConsumer.getNamespace());
                                consumeMessageContext.setMq(messageQueue);
                                consumeMessageContext.setMsgList(msgs);
                                consumeMessageContext.setSuccess(false);
                                // init the consume context type
                                consumeMessageContext.setProps(new HashMap<String, String>());
                                ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.executeHookBefore(consumeMessageContext);
                            }
														// 执行消费
                            long beginTimestamp = System.currentTimeMillis();
                            ConsumeReturnType returnType = ConsumeReturnType.SUCCESS;
                            boolean hasException = false;
                            try {
                                this.processQueue.getLockConsume().lock(); // 锁定处理队列
                                if (this.processQueue.isDropped()) {
                                    log.warn("consumeMessage, the message queue not be able to consume, because it's dropped. {}",
                                        this.messageQueue);
                                    break;
                                }

                                status = messageListener.consumeMessage(Collections.unmodifiableList(msgs), context);
                            } catch (Throwable e) {
                                log.warn("consumeMessage exception: {} Group: {} Msgs: {} MQ: {}",
                                    RemotingHelper.exceptionSimpleDesc(e),
                                    ConsumeMessageOrderlyService.this.consumerGroup,
                                    msgs,
                                    messageQueue);
                                hasException = true;
                            } finally {
                                this.processQueue.getLockConsume().unlock();  // 解锁
                            }

                            if (null == status
                                || ConsumeOrderlyStatus.ROLLBACK == status
                                || ConsumeOrderlyStatus.SUSPEND_CURRENT_QUEUE_A_MOMENT == status) {
                                log.warn("consumeMessage Orderly return not OK, Group: {} Msgs: {} MQ: {}",
                                    ConsumeMessageOrderlyService.this.consumerGroup,
                                    msgs,
                                    messageQueue);
                            }

                            long consumeRT = System.currentTimeMillis() - beginTimestamp;
                            if (null == status) {
                                if (hasException) {
                                    returnType = ConsumeReturnType.EXCEPTION;
                                } else {
                                    returnType = ConsumeReturnType.RETURNNULL;
                                }
                            } else if (consumeRT >= defaultMQPushConsumer.getConsumeTimeout() * 60 * 1000) {
                                returnType = ConsumeReturnType.TIME_OUT;
                            } else if (ConsumeOrderlyStatus.SUSPEND_CURRENT_QUEUE_A_MOMENT == status) {
                                returnType = ConsumeReturnType.FAILED;
                            } else if (ConsumeOrderlyStatus.SUCCESS == status) {
                                returnType = ConsumeReturnType.SUCCESS;
                            }

                            if (ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.hasHook()) {
                                consumeMessageContext.getProps().put(MixAll.CONSUME_CONTEXT_TYPE, returnType.name());
                            }

                            if (null == status) {
                                status = ConsumeOrderlyStatus.SUSPEND_CURRENT_QUEUE_A_MOMENT;
                            }

                            if (ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.hasHook()) {
                                consumeMessageContext.setStatus(status.toString());
                                consumeMessageContext
                                    .setSuccess(ConsumeOrderlyStatus.SUCCESS == status || ConsumeOrderlyStatus.COMMIT == status);
                                ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.executeHookAfter(consumeMessageContext);
                            }

                            ConsumeMessageOrderlyService.this.getConsumerStatsManager()
                                .incConsumeRT(ConsumeMessageOrderlyService.this.consumerGroup, messageQueue.getTopic(), consumeRT);

                            continueConsume = ConsumeMessageOrderlyService.this.processConsumeResult(msgs, status, context, this);
                        } else {
                            continueConsume = false;
                        }
                    }
                } else {
                    if (this.processQueue.isDropped()) {
                        log.warn("the message queue not be able to consume, because it's dropped. {}", this.messageQueue);
                        return;
                    }

                    ConsumeMessageOrderlyService.this.tryLockLaterAndReconsume(this.messageQueue, this.processQueue, 100);
                }
            }
        }
+ +

获取到锁对象后，使用synchronized尝试申请线程级独占锁。

+

如果加锁成功，同一时刻只有一个线程进行消息消费。

+

如果加锁失败，会延迟100ms重新尝试向broker端申请锁定messageQueue，锁定成功后重新提交消费请求

+

创建消息拉取任务时，消息客户端向broker端申请锁定MessageQueue，使得一个MessageQueue同一个时刻只能被一个消费客户端消费。

+

消息消费时，多线程针对同一个消息队列的消费先尝试使用synchronized申请独占锁，加锁成功才能进行消费，使得一个MessageQueue同一个时刻只能被一个消费客户端中一个线程消费。
这里其实还有很重要的一点是对processQueue的加锁，这里其实是保证了在 rebalance的过程中如果 processQueue 被分配给了另一个 consumer，但是当前已经被我这个 consumer 再消费，但是没提交，就有可能出现被两个消费者消费，所以得进行加锁保证不受 rebalance 影响。

+]]> + + MQ + RocketMQ + 消息队列 + + + MQ + 消息队列 + RocketMQ + + 聊一下 SpringBoot 中使用的 cglib 作为动态代理中的一个注意点 /2021/09/19/%E8%81%8A%E4%B8%80%E4%B8%8B-SpringBoot-%E4%B8%AD%E4%BD%BF%E7%94%A8%E7%9A%84-cglib-%E4%BD%9C%E4%B8%BA%E5%8A%A8%E6%80%81%E4%BB%A3%E7%90%86%E4%B8%AD%E7%9A%84%E4%B8%80%E4%B8%AA%E6%B3%A8%E6%84%8F%E7%82%B9/ @@ -5369,32 +5540,6 @@ user3: 事务 - - 聊一下 RocketMQ 的消息存储四 - /2021/10/17/%E8%81%8A%E4%B8%80%E4%B8%8B-RocketMQ-%E7%9A%84%E6%B6%88%E6%81%AF%E5%AD%98%E5%82%A8%E5%9B%9B/ - IndexFile 结构 hash 结构能够通过 key 寻找到对应在 CommitLog 中的位置

-

IndexFile 的构建则是分发给这个进行处理

-
class CommitLogDispatcherBuildIndex implements CommitLogDispatcher {

    @Override
    public void dispatch(DispatchRequest request) {
        if (DefaultMessageStore.this.messageStoreConfig.isMessageIndexEnable()) {
            DefaultMessageStore.this.indexService.buildIndex(request);
        }
    }
}
public void buildIndex(DispatchRequest req) {
        IndexFile indexFile = retryGetAndCreateIndexFile();
        if (indexFile != null) {
            long endPhyOffset = indexFile.getEndPhyOffset();
            DispatchRequest msg = req;
            String topic = msg.getTopic();
            String keys = msg.getKeys();
            if (msg.getCommitLogOffset() < endPhyOffset) {
                return;
            }

            final int tranType = MessageSysFlag.getTransactionValue(msg.getSysFlag());
            switch (tranType) {
                case MessageSysFlag.TRANSACTION_NOT_TYPE:
                case MessageSysFlag.TRANSACTION_PREPARED_TYPE:
                case MessageSysFlag.TRANSACTION_COMMIT_TYPE:
                    break;
                case MessageSysFlag.TRANSACTION_ROLLBACK_TYPE:
                    return;
            }

            if (req.getUniqKey() != null) {
                indexFile = putKey(indexFile, msg, buildKey(topic, req.getUniqKey()));
                if (indexFile == null) {
                    log.error("putKey error commitlog {} uniqkey {}", req.getCommitLogOffset(), req.getUniqKey());
                    return;
                }
            }

            if (keys != null && keys.length() > 0) {
                String[] keyset = keys.split(MessageConst.KEY_SEPARATOR);
                for (int i = 0; i < keyset.length; i++) {
                    String key = keyset[i];
                    if (key.length() > 0) {
                        indexFile = putKey(indexFile, msg, buildKey(topic, key));
                        if (indexFile == null) {
                            log.error("putKey error commitlog {} uniqkey {}", req.getCommitLogOffset(), req.getUniqKey());
                            return;
                        }
                    }
                }
            }
        } else {
            log.error("build index error, stop building index");
        }
    }
- -

配置的数量

-
private boolean messageIndexEnable = true;
private int maxHashSlotNum = 5000000;
private int maxIndexNum = 5000000 * 4;
- -

最核心的其实是 IndexFile 的结构和如何写入

-
public boolean putKey(final String key, final long phyOffset, final long storeTimestamp) {
        if (this.indexHeader.getIndexCount() < this.indexNum) {
          // 获取 key 的 hash
            int keyHash = indexKeyHashMethod(key);
          // 计算属于哪个 slot
            int slotPos = keyHash % this.hashSlotNum;
          // 计算 slot 位置 因为结构是有个 indexHead，主要是分为三段 header，slot 和 index
            int absSlotPos = IndexHeader.INDEX_HEADER_SIZE + slotPos * hashSlotSize;

            FileLock fileLock = null;

            try {

                // fileLock = this.fileChannel.lock(absSlotPos, hashSlotSize,
                // false);
                int slotValue = this.mappedByteBuffer.getInt(absSlotPos);
                if (slotValue <= invalidIndex || slotValue > this.indexHeader.getIndexCount()) {
                    slotValue = invalidIndex;
                }

                long timeDiff = storeTimestamp - this.indexHeader.getBeginTimestamp();

                timeDiff = timeDiff / 1000;

                if (this.indexHeader.getBeginTimestamp() <= 0) {
                    timeDiff = 0;
                } else if (timeDiff > Integer.MAX_VALUE) {
                    timeDiff = Integer.MAX_VALUE;
                } else if (timeDiff < 0) {
                    timeDiff = 0;
                }

              // 计算索引存放位置，头部 + slot 数量 * slot 大小 + 已有的 index 数量 + index 大小
                int absIndexPos =
                    IndexHeader.INDEX_HEADER_SIZE + this.hashSlotNum * hashSlotSize
                        + this.indexHeader.getIndexCount() * indexSize;
							
                this.mappedByteBuffer.putInt(absIndexPos, keyHash);
                this.mappedByteBuffer.putLong(absIndexPos + 4, phyOffset);
                this.mappedByteBuffer.putInt(absIndexPos + 4 + 8, (int) timeDiff);
                this.mappedByteBuffer.putInt(absIndexPos + 4 + 8 + 4, slotValue);

              // 存放的是数量位移，不是绝对位置
                this.mappedByteBuffer.putInt(absSlotPos, this.indexHeader.getIndexCount());

                if (this.indexHeader.getIndexCount() <= 1) {
                    this.indexHeader.setBeginPhyOffset(phyOffset);
                    this.indexHeader.setBeginTimestamp(storeTimestamp);
                }

                this.indexHeader.incHashSlotCount();
                this.indexHeader.incIndexCount();
                this.indexHeader.setEndPhyOffset(phyOffset);
                this.indexHeader.setEndTimestamp(storeTimestamp);

                return true;
            } catch (Exception e) {
                log.error("putKey exception, Key: " + key + " KeyHashCode: " + key.hashCode(), e);
            } finally {
                if (fileLock != null) {
                    try {
                        fileLock.release();
                    } catch (IOException e) {
                        log.error("Failed to release the lock", e);
                    }
                }
            }
        } else {
            log.warn("Over index file capacity: index count = " + this.indexHeader.getIndexCount()
                + "; index max num = " + this.indexNum);
        }

        return false;
    }
- -

具体可以看一下这个简略的示意图

-]]> - - MQ - RocketMQ - 消息队列 - - - MQ - 消息队列 - RocketMQ - - 聊一下 SpringBoot 中动态切换数据源的方法 /2021/09/26/%E8%81%8A%E4%B8%80%E4%B8%8B-SpringBoot-%E4%B8%AD%E5%8A%A8%E6%80%81%E5%88%87%E6%8D%A2%E6%95%B0%E6%8D%AE%E6%BA%90%E7%9A%84%E6%96%B9%E6%B3%95/ @@ -5444,18 +5589,6 @@ user3: 数据源动态切换 - - 聊一下关于怎么陪伴学习 - /2022/11/06/%E8%81%8A%E4%B8%80%E4%B8%8B%E5%85%B3%E4%BA%8E%E6%80%8E%E4%B9%88%E9%99%AA%E4%BC%B4%E5%AD%A6%E4%B9%A0/ - 这是一次开车过程中结合网上的一些微博想到的，开车是之前LD买了车后，陪领导练车，其实在一开始练车的时候，我们已经是找了相对很空的封闭路段，路上基本很少有车，偶尔有一辆车，但是LD还是很害怕，车速还只有十几的时候，还很远的对面来车的时候就觉得很慌了，这个时候如果以常理肯定会说这样子完全不用怕，如果克服恐惧真的这么容易的话，问题就不会那么纠结了，人生是很难完全感同身受的，唯有降低预设的基准让事情从头理清楚，害怕了我们就先休息，有车了我们就停下，先适应完全没车的情况，变得更慢一点，如果这时候着急一点，反而会起到反效果，比如只是说不要怕，接着开，甚至有点厌烦了，那基本这个练车也不太成得了了，而正好是有耐心的一起慢慢练习，还有就是第二件是切身体会，就是当道路本来是两条道，但是封了一条的时候，这时候开车如果是像我这样的新手，如果开车时左右边看着的话，车肯定开不好，因为那样会一直左右调整，反而更容易控制不好左右的距离，蹭到旁边的隔离栏，正确的方式应该是专注于正前方的路，这样才能保证左右边距离尽可能均匀，而不是顾左失右或者顾右失左，所以很多陪伴学习需要注意的是方式和耐心，能够识别到关键点那是最好的，但是有时候更需要的是耐心，纯靠耐心不一定能解决问题，但是可能会找到问题关键点。

-]]> - - 生活 - - - 生活 - - 聊一下 SpringBoot 设置非 web 应用的方法 /2022/07/31/%E8%81%8A%E4%B8%80%E4%B8%8B-SpringBoot-%E8%AE%BE%E7%BD%AE%E9%9D%9E-web-%E5%BA%94%E7%94%A8%E7%9A%84%E6%96%B9%E6%B3%95/ @@ -5483,75 +5616,115 @@ user3: - 聊一下 RocketMQ 的顺序消息 - /2021/08/29/%E8%81%8A%E4%B8%80%E4%B8%8B-RocketMQ-%E7%9A%84%E9%A1%BA%E5%BA%8F%E6%B6%88%E6%81%AF/ - rocketmq 里有一种比较特殊的用法，就是顺序消息，比如订单的生命周期里，在创建，支付，签收等状态轮转中，会发出来对应的消息，这里面就比较需要去保证他们的顺序，当然在处理的业务代码也可以做对应的处理，结合消息重投，但是如果这里消息就能保证顺序性了，那么业务代码就能更好的关注业务代码的处理。

-

首先有一种情况是全局的有序，比如对于一个 topic 里就得发送线程保证只有一个，内部的 queue 也只有一个，消费线程也只有一个，这样就能比较容易的保证全局顺序性了，但是这里的问题就是完全限制了性能，不是很现实，在真实场景里很多都是比如对于同一个订单，需要去保证状态的轮转是按照预期的顺序来，而不必要全局的有序性。

-

对于这类的有序性，需要在发送和接收方都有对应的处理，在发送消息中，需要去指定 selector，即MessageQueueSelector，能够以固定的方式是分配到对应的 MessageQueue

-

比如像 RocketMQ 中的示例

-
SendResult sendResult = producer.send(msg, new MessageQueueSelector() {
                @Override
                public MessageQueue select(List<MessageQueue> mqs, Message msg, Object arg) {
                    Long id = (Long) arg;  //message queue is selected by #salesOrderID
                    long index = id % mqs.size();
                    return mqs.get((int) index);
                }
            }, orderList.get(i).getOrderId());
- -

而在消费侧有几个点比较重要，首先我们要保证一个 MessageQueue只被一个消费者消费，消费队列存在broker端，要保证 MessageQueue 只被一个消费者消费，那么消费者在进行消息拉取消费时就必须向mq服务器申请队列锁，消费者申请队列锁的代码存在于RebalanceService消息队列负载的实现代码中。

-
List<PullRequest> pullRequestList = new ArrayList<PullRequest>();
        for (MessageQueue mq : mqSet) {
            if (!this.processQueueTable.containsKey(mq)) {
              // 判断是否顺序，如果是顺序消费的，则需要加锁
                if (isOrder && !this.lock(mq)) {
                    log.warn("doRebalance, {}, add a new mq failed, {}, because lock failed", consumerGroup, mq);
                    continue;
                }

                this.removeDirtyOffset(mq);
                ProcessQueue pq = new ProcessQueue();
                long nextOffset = this.computePullFromWhere(mq);
                if (nextOffset >= 0) {
                    ProcessQueue pre = this.processQueueTable.putIfAbsent(mq, pq);
                    if (pre != null) {
                        log.info("doRebalance, {}, mq already exists, {}", consumerGroup, mq);
                    } else {
                        log.info("doRebalance, {}, add a new mq, {}", consumerGroup, mq);
                        PullRequest pullRequest = new PullRequest();
                        pullRequest.setConsumerGroup(consumerGroup);
                        pullRequest.setNextOffset(nextOffset);
                        pullRequest.setMessageQueue(mq);
                        pullRequest.setProcessQueue(pq);
                        pullRequestList.add(pullRequest);
                        changed = true;
                    }
                } else {
                    log.warn("doRebalance, {}, add new mq failed, {}", consumerGroup, mq);
                }
            }
        }
- -

在申请到锁之后会创建 pullRequest 进行消息拉取，消息拉取部分的代码实现在PullMessageService中，

-
@Override
    public void run() {
        log.info(this.getServiceName() + " service started");

        while (!this.isStopped()) {
            try {
                PullRequest pullRequest = this.pullRequestQueue.take();
                this.pullMessage(pullRequest);
            } catch (InterruptedException ignored) {
            } catch (Exception e) {
                log.error("Pull Message Service Run Method exception", e);
            }
        }

        log.info(this.getServiceName() + " service end");
    }
- -

消息拉取完后，需要提交到ConsumeMessageService中进行消费，顺序消费的实现为ConsumeMessageOrderlyService，提交消息进行消费的方法为ConsumeMessageOrderlyService#submitConsumeRequest，具体实现如下：

-
@Override
public void submitConsumeRequest(
    final List<MessageExt> msgs,
    final ProcessQueue processQueue,
    final MessageQueue messageQueue,
    final boolean dispathToConsume) {
    if (dispathToConsume) {
        ConsumeRequest consumeRequest = new ConsumeRequest(processQueue, messageQueue);
        this.consumeExecutor.submit(consumeRequest);
    }
}
- -

构建了一个ConsumeRequest对象，它是个实现了 runnable 接口的类，并提交给了线程池来并行消费，看下顺序消费的ConsumeRequest的run方法实现：

-
@Override
        public void run() {
            if (this.processQueue.isDropped()) {
                log.warn("run, the message queue not be able to consume, because it's dropped. {}", this.messageQueue);
                return;
            }
						// 获得 Consumer 消息队列锁，即单个线程独占
            final Object objLock = messageQueueLock.fetchLockObject(this.messageQueue);
            synchronized (objLock) {
              // (广播模式) 或者 (集群模式 && Broker消息队列锁有效)
                if (MessageModel.BROADCASTING.equals(ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.messageModel())
                    || (this.processQueue.isLocked() && !this.processQueue.isLockExpired())) {
                    final long beginTime = System.currentTimeMillis();
                  // 循环
                    for (boolean continueConsume = true; continueConsume; ) {
                        if (this.processQueue.isDropped()) {
                            log.warn("the message queue not be able to consume, because it's dropped. {}", this.messageQueue);
                            break;
                        }

                      // 消息队列分布式锁未锁定，提交延迟获得锁并消费请求
                        if (MessageModel.CLUSTERING.equals(ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.messageModel())
                            && !this.processQueue.isLocked()) {
                            log.warn("the message queue not locked, so consume later, {}", this.messageQueue);
                            ConsumeMessageOrderlyService.this.tryLockLaterAndReconsume(this.messageQueue, this.processQueue, 10);
                            break;
                        }

                      // 消息队列分布式锁已经过期，提交延迟获得锁并消费请求
                        if (MessageModel.CLUSTERING.equals(ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.messageModel())
                            && this.processQueue.isLockExpired()) {
                            log.warn("the message queue lock expired, so consume later, {}", this.messageQueue);
                            ConsumeMessageOrderlyService.this.tryLockLaterAndReconsume(this.messageQueue, this.processQueue, 10);
                            break;
                        }
												// 当前周期消费时间超过连续时长，默认：60s，提交延迟消费请求。默认情况下，每消费1分钟休息10ms。
                        long interval = System.currentTimeMillis() - beginTime;
                        if (interval > MAX_TIME_CONSUME_CONTINUOUSLY) {
                            ConsumeMessageOrderlyService.this.submitConsumeRequestLater(processQueue, messageQueue, 10);
                            break;
                        }
												// 获取消费消息。此处和并发消息请求不同，并发消息请求已经带了消费哪些消息。
                        final int consumeBatchSize =
                            ConsumeMessageOrderlyService.this.defaultMQPushConsumer.getConsumeMessageBatchMaxSize();

                        List<MessageExt> msgs = this.processQueue.takeMessags(consumeBatchSize);
                        defaultMQPushConsumerImpl.resetRetryAndNamespace(msgs, defaultMQPushConsumer.getConsumerGroup());
                        if (!msgs.isEmpty()) {
                            final ConsumeOrderlyContext context = new ConsumeOrderlyContext(this.messageQueue);

                            ConsumeOrderlyStatus status = null;

                            ConsumeMessageContext consumeMessageContext = null;
                            if (ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.hasHook()) {
                                consumeMessageContext = new ConsumeMessageContext();
                                consumeMessageContext
                                    .setConsumerGroup(ConsumeMessageOrderlyService.this.defaultMQPushConsumer.getConsumerGroup());
                                consumeMessageContext.setNamespace(defaultMQPushConsumer.getNamespace());
                                consumeMessageContext.setMq(messageQueue);
                                consumeMessageContext.setMsgList(msgs);
                                consumeMessageContext.setSuccess(false);
                                // init the consume context type
                                consumeMessageContext.setProps(new HashMap<String, String>());
                                ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.executeHookBefore(consumeMessageContext);
                            }
														// 执行消费
                            long beginTimestamp = System.currentTimeMillis();
                            ConsumeReturnType returnType = ConsumeReturnType.SUCCESS;
                            boolean hasException = false;
                            try {
                                this.processQueue.getLockConsume().lock(); // 锁定处理队列
                                if (this.processQueue.isDropped()) {
                                    log.warn("consumeMessage, the message queue not be able to consume, because it's dropped. {}",
                                        this.messageQueue);
                                    break;
                                }

                                status = messageListener.consumeMessage(Collections.unmodifiableList(msgs), context);
                            } catch (Throwable e) {
                                log.warn("consumeMessage exception: {} Group: {} Msgs: {} MQ: {}",
                                    RemotingHelper.exceptionSimpleDesc(e),
                                    ConsumeMessageOrderlyService.this.consumerGroup,
                                    msgs,
                                    messageQueue);
                                hasException = true;
                            } finally {
                                this.processQueue.getLockConsume().unlock();  // 解锁
                            }

                            if (null == status
                                || ConsumeOrderlyStatus.ROLLBACK == status
                                || ConsumeOrderlyStatus.SUSPEND_CURRENT_QUEUE_A_MOMENT == status) {
                                log.warn("consumeMessage Orderly return not OK, Group: {} Msgs: {} MQ: {}",
                                    ConsumeMessageOrderlyService.this.consumerGroup,
                                    msgs,
                                    messageQueue);
                            }

                            long consumeRT = System.currentTimeMillis() - beginTimestamp;
                            if (null == status) {
                                if (hasException) {
                                    returnType = ConsumeReturnType.EXCEPTION;
                                } else {
                                    returnType = ConsumeReturnType.RETURNNULL;
                                }
                            } else if (consumeRT >= defaultMQPushConsumer.getConsumeTimeout() * 60 * 1000) {
                                returnType = ConsumeReturnType.TIME_OUT;
                            } else if (ConsumeOrderlyStatus.SUSPEND_CURRENT_QUEUE_A_MOMENT == status) {
                                returnType = ConsumeReturnType.FAILED;
                            } else if (ConsumeOrderlyStatus.SUCCESS == status) {
                                returnType = ConsumeReturnType.SUCCESS;
                            }

                            if (ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.hasHook()) {
                                consumeMessageContext.getProps().put(MixAll.CONSUME_CONTEXT_TYPE, returnType.name());
                            }

                            if (null == status) {
                                status = ConsumeOrderlyStatus.SUSPEND_CURRENT_QUEUE_A_MOMENT;
                            }

                            if (ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.hasHook()) {
                                consumeMessageContext.setStatus(status.toString());
                                consumeMessageContext
                                    .setSuccess(ConsumeOrderlyStatus.SUCCESS == status || ConsumeOrderlyStatus.COMMIT == status);
                                ConsumeMessageOrderlyService.this.defaultMQPushConsumerImpl.executeHookAfter(consumeMessageContext);
                            }

                            ConsumeMessageOrderlyService.this.getConsumerStatsManager()
                                .incConsumeRT(ConsumeMessageOrderlyService.this.consumerGroup, messageQueue.getTopic(), consumeRT);

                            continueConsume = ConsumeMessageOrderlyService.this.processConsumeResult(msgs, status, context, this);
                        } else {
                            continueConsume = false;
                        }
                    }
                } else {
                    if (this.processQueue.isDropped()) {
                        log.warn("the message queue not be able to consume, because it's dropped. {}", this.messageQueue);
                        return;
                    }

                    ConsumeMessageOrderlyService.this.tryLockLaterAndReconsume(this.messageQueue, this.processQueue, 100);
                }
            }
        }
- -

获取到锁对象后，使用synchronized尝试申请线程级独占锁。

-

如果加锁成功，同一时刻只有一个线程进行消息消费。

-

如果加锁失败，会延迟100ms重新尝试向broker端申请锁定messageQueue，锁定成功后重新提交消费请求

-

创建消息拉取任务时，消息客户端向broker端申请锁定MessageQueue，使得一个MessageQueue同一个时刻只能被一个消费客户端消费。

-

消息消费时，多线程针对同一个消息队列的消费先尝试使用synchronized申请独占锁，加锁成功才能进行消费，使得一个MessageQueue同一个时刻只能被一个消费客户端中一个线程消费。
这里其实还有很重要的一点是对processQueue的加锁，这里其实是保证了在 rebalance的过程中如果 processQueue 被分配给了另一个 consumer，但是当前已经被我这个 consumer 再消费，但是没提交，就有可能出现被两个消费者消费，所以得进行加锁保证不受 rebalance 影响。

+ 聊一下关于怎么陪伴学习 + /2022/11/06/%E8%81%8A%E4%B8%80%E4%B8%8B%E5%85%B3%E4%BA%8E%E6%80%8E%E4%B9%88%E9%99%AA%E4%BC%B4%E5%AD%A6%E4%B9%A0/ + 这是一次开车过程中结合网上的一些微博想到的，开车是之前LD买了车后，陪领导练车，其实在一开始练车的时候，我们已经是找了相对很空的封闭路段，路上基本很少有车，偶尔有一辆车，但是LD还是很害怕，车速还只有十几的时候，还很远的对面来车的时候就觉得很慌了，这个时候如果以常理肯定会说这样子完全不用怕，如果克服恐惧真的这么容易的话，问题就不会那么纠结了，人生是很难完全感同身受的，唯有降低预设的基准让事情从头理清楚，害怕了我们就先休息，有车了我们就停下，先适应完全没车的情况，变得更慢一点，如果这时候着急一点，反而会起到反效果，比如只是说不要怕，接着开，甚至有点厌烦了，那基本这个练车也不太成得了了，而正好是有耐心的一起慢慢练习，还有就是第二件是切身体会，就是当道路本来是两条道，但是封了一条的时候，这时候开车如果是像我这样的新手，如果开车时左右边看着的话，车肯定开不好，因为那样会一直左右调整，反而更容易控制不好左右的距离，蹭到旁边的隔离栏，正确的方式应该是专注于正前方的路，这样才能保证左右边距离尽可能均匀，而不是顾左失右或者顾右失左，所以很多陪伴学习需要注意的是方式和耐心，能够识别到关键点那是最好的，但是有时候更需要的是耐心，纯靠耐心不一定能解决问题，但是可能会找到问题关键点。

]]> - MQ - RocketMQ - 消息队列 + 生活 - MQ - 消息队列 - RocketMQ + 生活 - 聊聊 Dubbo 的 SPI 续之自适应拓展 - /2020/06/06/%E8%81%8A%E8%81%8A-Dubbo-%E7%9A%84-SPI-%E7%BB%AD%E4%B9%8B%E8%87%AA%E9%80%82%E5%BA%94%E6%8B%93%E5%B1%95/ - Adaptive

这个应该是 Dubbo SPI 里最玄妙的东西了，一开始没懂，自适应扩展点加载，
dubbo://123.123.123.123:1234/com.nicksxs.demo.service.HelloWorldService?anyhost=true&application=demo&default.loadbalance=random&default.service.filter=LoggerFilter&dubbo=2.5.3&interface=com.nicksxs.demo.service.HelloWorldService&logger=slf4j&methods=method1,method2,method3,method4&pid=4292&retries=0&side=provider&threadpool=fixed&threads=200&timeout=2000&timestamp=1590647155886
那我从比较能理解的角度或者说思路去讲讲我的理解，因为直接将原理如果脱离了使用，对于我这样的理解能力比较差的可能会比较吃力，从使用场景开始讲可能会比较舒服了，这里可以看到参数里有蛮多的，举个例子，比如这个 threadpool = fixed，说明线程池使用的是 fixed 对应的实现，也就是下图的这个

这样子似乎没啥问题了，反正就是用dubbo 的 spi 加载嘛，好像没啥问题，其实问题还是存在的，或者说不太优雅，比如要先判断我这个 fixed 对应的实现类是哪个，这里可能就有个 if-else 判断了，但是 dubbo 的开发人员似乎不太想这么做这个事情，

-

譬如我们在引用一个服务时，在ReferenceConfig 中的

-
private static final Protocol refprotocol = ExtensionLoader.getExtensionLoader(Protocol.class).getAdaptiveExtension();
- -

就获取了自适应拓展，

-
public T getAdaptiveExtension() {
        Object instance = cachedAdaptiveInstance.get();
        if (instance == null) {
            if (createAdaptiveInstanceError == null) {
                synchronized (cachedAdaptiveInstance) {
                    instance = cachedAdaptiveInstance.get();
                    if (instance == null) {
                        try {
                            instance = createAdaptiveExtension();
                            cachedAdaptiveInstance.set(instance);
                        } catch (Throwable t) {
                            createAdaptiveInstanceError = t;
                            throw new IllegalStateException("fail to create adaptive instance: " + t.toString(), t);
                        }
                    }
                }
            } else {
                throw new IllegalStateException("fail to create adaptive instance: " + createAdaptiveInstanceError.toString(), createAdaptiveInstanceError);
            }
        }

        return (T) instance;
    }
- -

这里也使用了 DCL，来锁cachedAdaptiveInstance，当缓存中没有时就去创建自适应拓展

-
private T createAdaptiveExtension() {
        try {
          // 获取自适应拓展类然后实例化
            return injectExtension((T) getAdaptiveExtensionClass().newInstance());
        } catch (Exception e) {
            throw new IllegalStateException("Can not create adaptive extension " + type + ", cause: " + e.getMessage(), e);
        }
    }

private Class<?> getAdaptiveExtensionClass() {
  			// 这里会获取拓展类，如果没有自适应的拓展类，那么就需要调用createAdaptiveExtensionClass
        getExtensionClasses();
        if (cachedAdaptiveClass != null) {
            return cachedAdaptiveClass;
        }
        return cachedAdaptiveClass = createAdaptiveExtensionClass();
    }
private Class<?> createAdaptiveExtensionClass() {
  			// 这里去生成了自适应拓展的代码，具体生成逻辑比较复杂先不展开讲
        String code = createAdaptiveExtensionClassCode();
        ClassLoader classLoader = findClassLoader();
        com.alibaba.dubbo.common.compiler.Compiler compiler = ExtensionLoader.getExtensionLoader(com.alibaba.dubbo.common.compiler.Compiler.class).getAdaptiveExtension();
        return compiler.compile(code, classLoader);
    }
- -

生成的代码像这样

-
package com.alibaba.dubbo.rpc;

import com.alibaba.dubbo.common.extension.ExtensionLoader;


public class Protocol$Adaptive implements com.alibaba.dubbo.rpc.Protocol {
    public void destroy() {
        throw new UnsupportedOperationException(
            "method public abstract void com.alibaba.dubbo.rpc.Protocol.destroy() of interface com.alibaba.dubbo.rpc.Protocol is not adaptive method!");
    }

    public int getDefaultPort() {
        throw new UnsupportedOperationException(
            "method public abstract int com.alibaba.dubbo.rpc.Protocol.getDefaultPort() of interface com.alibaba.dubbo.rpc.Protocol is not adaptive method!");
    }

    public com.alibaba.dubbo.rpc.Exporter export(
        com.alibaba.dubbo.rpc.Invoker arg0)
        throws com.alibaba.dubbo.rpc.RpcException {
        if (arg0 == null) {
            throw new IllegalArgumentException(
                "com.alibaba.dubbo.rpc.Invoker argument == null");
        }

        if (arg0.getUrl() == null) {
            throw new IllegalArgumentException(
                "com.alibaba.dubbo.rpc.Invoker argument getUrl() == null");
        }

        com.alibaba.dubbo.common.URL url = arg0.getUrl();
        String extName = ((url.getProtocol() == null) ? "dubbo"
                                                      : url.getProtocol());

        if (extName == null) {
            throw new IllegalStateException(
                "Fail to get extension(com.alibaba.dubbo.rpc.Protocol) name from url(" +
                url.toString() + ") use keys([protocol])");
        }

        com.alibaba.dubbo.rpc.Protocol extension = (com.alibaba.dubbo.rpc.Protocol) ExtensionLoader.getExtensionLoader(com.alibaba.dubbo.rpc.Protocol.class)
                                                                                                   .getExtension(extName);

        return extension.export(arg0);
    }

    public com.alibaba.dubbo.rpc.Invoker refer(java.lang.Class arg0,
        com.alibaba.dubbo.common.URL arg1)
        throws com.alibaba.dubbo.rpc.RpcException {
        if (arg1 == null) {
            throw new IllegalArgumentException("url == null");
        }

        com.alibaba.dubbo.common.URL url = arg1;
      // 其实前面所说的逻辑就在这里呈现了
        String extName = ((url.getProtocol() == null) ? "dubbo"
                                                      : url.getProtocol());

        if (extName == null) {
            throw new IllegalStateException(
                "Fail to get extension(com.alibaba.dubbo.rpc.Protocol) name from url(" +
                url.toString() + ") use keys([protocol])");
        }
				// 在这就是实际的通过dubbo 的 spi 去加载实际对应的扩展
        com.alibaba.dubbo.rpc.Protocol extension = (com.alibaba.dubbo.rpc.Protocol) ExtensionLoader.getExtensionLoader(com.alibaba.dubbo.rpc.Protocol.class)
                                                                                                   .getExtension(extName);

        return extension.refer(arg0, arg1);
    }
}

+ 聊一聊 https 的逻辑 + /2024/03/10/%E8%81%8A%E4%B8%80%E8%81%8A-https-%E7%9A%84%E9%80%BB%E8%BE%91/ + https 和 tls

https 我原本的理解来自于几个概念

+

第一个是非对称加密

+

也就是公钥可以公开在网上，然后用公钥加密，由私有的私钥进行解密，然后就对 https 有了初步的偏颇的概念，就是浏览器用公钥进行加密，服务器端用私钥进行解密，这里再仔细想想会延伸出来几个问题，也是逐步完善我的后续理解

+

第二个就是非对称加密以后的对称加密

+

因为对加密的理解是超大的质数（这个还来源于大学的数据结构老师）相乘后会很难做质因数分解，比如最大的质数2^82,589,933 − 1，用十进制表示有24,862,048位，用现在计算机来算也是非常难的，那如果一直采用非对称加密，这个效率也会比较低，所以在网上查了一番之后知道了是先采用非对称加密，然后再用对称加密，因为非对称加密先有了安全保证，后续的消息就可以用对称加密的方式来进行传输安全了

+

第三个是最近一次看到的

+

也是一直缺乏思考的问题，因为 https 我们在使用的时候都会购买证书或者使用免费的证书，那这个证书和前面说的公私钥是什么关系，好像一直是悬空的，没想过这中间的相关性，证书究竟是怎么起作用的

+

下面是摘自 cloudflare 的 tls 握手流程，把证书的使用方式说的比较明白了

+

TLS 握手是由客户端和服务器交换的一系列数据报或消息。TLS 握手涉及多个步骤，因为客户端和服务器要交换完成握手和进行进一步对话所需的信息。

+

TLS 握手中的确切步骤将根据所使用的密钥交换算法的种类和双方支持的密码套件而有所不同。RSA 密钥交换算法虽然现在被认为不安全，但曾在 1.3 之前的 TLS 版本中使用。大致如下：

+
    +
  1. “客户端问候（client hello）” 消息： 客户端通过向服务器发送“问候”消息来开始握手。该消息将包含客户端支持的 TLS 版本，支持的密码套件，以及称为一串称为“客户端随机数（client random）”的随机字节。
    2. +
  2. “服务器问候（server hello）”消息： 作为对 client hello 消息的回复，服务器发送一条消息，内含服务器的 SSL 证书、服务器选择的密码套件，以及“服务器随机数（server random）”，即由服务器生成的另一串随机字节。
    3. +
  3. 身份验证： 客户端使用颁发该证书的证书颁发机构验证服务器的 SSL 证书。此举确认服务器是其声称的身份，且客户端正在与该域的实际所有者进行交互。
    4. +
  4. 预主密钥： 客户端再发送一串随机字节，即“预主密钥（premaster secret）”。预主密钥是使用公钥加密的，只能使用服务器的私钥解密。（客户端从服务器的 SSL 证书中获得公钥。）
    5. +
  5. 私钥被使用：服务器对预主密钥进行解密。
    6. +
  6. 生成会话密钥：客户端和服务器均使用客户端随机数、服务器随机数和预主密钥生成会话密钥。双方应得到相同的结果。
    7. +
  7. 客户端就绪：客户端发送一条“已完成”消息，该消息用会话密钥加密。
    8. +
  8. 服务器就绪：服务器发送一条“已完成”消息，该消息用会话密钥加密。
    9. +
  9. 实现安全对称加密：已完成握手，并使用会话密钥继续进行通信。
    10. +
+

为了学习这个过程，我们尝试用 Chrome 的自带抓包工具，以往这是可以通过在 Chrome 地址栏中输入 chrome://net-internals/#events 来打开，现在变成了两部分，chrome://net-export/ 这里可以开始抓包，然后会记录下一个抓包日志文件里，

+

+

然后再打开

+

https://netlog-viewer.appspot.com/#events 来查看具体的日志

+

这里我们以打开百度为例，即在打开 chrome://net-export/ 并启动抓包后，再在一个新 tab 打开 baidu.com，然后关闭

+

将日志文件在 https://netlog-viewer.appspot.com/#events 打开

+

+

这里可以看到

+

+

--> type 1 表示现在 tls 握手进行到哪一步了, 对应的值表示不同的阶段

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
代码(type)释义
0HelloRequest
1ClientHello
2ServerHello
11Certificate
12ServerKeyExchange
13CertificateRequest
14ServerHelloDone
15CertificateVerify
16ClientKeyExchange
20Finished
+

具体的对应关系是在这边

+

比如 11 之后表示我们从服务端收到了证书

+

+

然后就要去验证证书的可靠性

+

+

后面是验证后的结果

+

+

+

最后就是交换对称会话秘钥然后完成握手

+

]]> - Java - Dubbo - RPC - SPI - Dubbo - SPI - Adaptive + 网络 - Java - Dubbo - RPC - SPI - Adaptive - 自适应拓展 + http @@ -5594,6 +5767,40 @@ user3: 跳水 + + 聊聊 Dubbo 的 SPI 续之自适应拓展 + /2020/06/06/%E8%81%8A%E8%81%8A-Dubbo-%E7%9A%84-SPI-%E7%BB%AD%E4%B9%8B%E8%87%AA%E9%80%82%E5%BA%94%E6%8B%93%E5%B1%95/ + Adaptive

这个应该是 Dubbo SPI 里最玄妙的东西了，一开始没懂，自适应扩展点加载，
dubbo://123.123.123.123:1234/com.nicksxs.demo.service.HelloWorldService?anyhost=true&application=demo&default.loadbalance=random&default.service.filter=LoggerFilter&dubbo=2.5.3&interface=com.nicksxs.demo.service.HelloWorldService&logger=slf4j&methods=method1,method2,method3,method4&pid=4292&retries=0&side=provider&threadpool=fixed&threads=200&timeout=2000&timestamp=1590647155886
那我从比较能理解的角度或者说思路去讲讲我的理解，因为直接将原理如果脱离了使用，对于我这样的理解能力比较差的可能会比较吃力，从使用场景开始讲可能会比较舒服了，这里可以看到参数里有蛮多的，举个例子，比如这个 threadpool = fixed，说明线程池使用的是 fixed 对应的实现，也就是下图的这个

这样子似乎没啥问题了，反正就是用dubbo 的 spi 加载嘛，好像没啥问题，其实问题还是存在的，或者说不太优雅，比如要先判断我这个 fixed 对应的实现类是哪个，这里可能就有个 if-else 判断了，但是 dubbo 的开发人员似乎不太想这么做这个事情，

+

譬如我们在引用一个服务时，在ReferenceConfig 中的

+
private static final Protocol refprotocol = ExtensionLoader.getExtensionLoader(Protocol.class).getAdaptiveExtension();
+ +

就获取了自适应拓展，

+
public T getAdaptiveExtension() {
        Object instance = cachedAdaptiveInstance.get();
        if (instance == null) {
            if (createAdaptiveInstanceError == null) {
                synchronized (cachedAdaptiveInstance) {
                    instance = cachedAdaptiveInstance.get();
                    if (instance == null) {
                        try {
                            instance = createAdaptiveExtension();
                            cachedAdaptiveInstance.set(instance);
                        } catch (Throwable t) {
                            createAdaptiveInstanceError = t;
                            throw new IllegalStateException("fail to create adaptive instance: " + t.toString(), t);
                        }
                    }
                }
            } else {
                throw new IllegalStateException("fail to create adaptive instance: " + createAdaptiveInstanceError.toString(), createAdaptiveInstanceError);
            }
        }

        return (T) instance;
    }
+ +

这里也使用了 DCL，来锁cachedAdaptiveInstance，当缓存中没有时就去创建自适应拓展

+
private T createAdaptiveExtension() {
        try {
          // 获取自适应拓展类然后实例化
            return injectExtension((T) getAdaptiveExtensionClass().newInstance());
        } catch (Exception e) {
            throw new IllegalStateException("Can not create adaptive extension " + type + ", cause: " + e.getMessage(), e);
        }
    }

private Class<?> getAdaptiveExtensionClass() {
  			// 这里会获取拓展类，如果没有自适应的拓展类，那么就需要调用createAdaptiveExtensionClass
        getExtensionClasses();
        if (cachedAdaptiveClass != null) {
            return cachedAdaptiveClass;
        }
        return cachedAdaptiveClass = createAdaptiveExtensionClass();
    }
private Class<?> createAdaptiveExtensionClass() {
  			// 这里去生成了自适应拓展的代码，具体生成逻辑比较复杂先不展开讲
        String code = createAdaptiveExtensionClassCode();
        ClassLoader classLoader = findClassLoader();
        com.alibaba.dubbo.common.compiler.Compiler compiler = ExtensionLoader.getExtensionLoader(com.alibaba.dubbo.common.compiler.Compiler.class).getAdaptiveExtension();
        return compiler.compile(code, classLoader);
    }
+ +

生成的代码像这样

+
package com.alibaba.dubbo.rpc;

import com.alibaba.dubbo.common.extension.ExtensionLoader;


public class Protocol$Adaptive implements com.alibaba.dubbo.rpc.Protocol {
    public void destroy() {
        throw new UnsupportedOperationException(
            "method public abstract void com.alibaba.dubbo.rpc.Protocol.destroy() of interface com.alibaba.dubbo.rpc.Protocol is not adaptive method!");
    }

    public int getDefaultPort() {
        throw new UnsupportedOperationException(
            "method public abstract int com.alibaba.dubbo.rpc.Protocol.getDefaultPort() of interface com.alibaba.dubbo.rpc.Protocol is not adaptive method!");
    }

    public com.alibaba.dubbo.rpc.Exporter export(
        com.alibaba.dubbo.rpc.Invoker arg0)
        throws com.alibaba.dubbo.rpc.RpcException {
        if (arg0 == null) {
            throw new IllegalArgumentException(
                "com.alibaba.dubbo.rpc.Invoker argument == null");
        }

        if (arg0.getUrl() == null) {
            throw new IllegalArgumentException(
                "com.alibaba.dubbo.rpc.Invoker argument getUrl() == null");
        }

        com.alibaba.dubbo.common.URL url = arg0.getUrl();
        String extName = ((url.getProtocol() == null) ? "dubbo"
                                                      : url.getProtocol());

        if (extName == null) {
            throw new IllegalStateException(
                "Fail to get extension(com.alibaba.dubbo.rpc.Protocol) name from url(" +
                url.toString() + ") use keys([protocol])");
        }

        com.alibaba.dubbo.rpc.Protocol extension = (com.alibaba.dubbo.rpc.Protocol) ExtensionLoader.getExtensionLoader(com.alibaba.dubbo.rpc.Protocol.class)
                                                                                                   .getExtension(extName);

        return extension.export(arg0);
    }

    public com.alibaba.dubbo.rpc.Invoker refer(java.lang.Class arg0,
        com.alibaba.dubbo.common.URL arg1)
        throws com.alibaba.dubbo.rpc.RpcException {
        if (arg1 == null) {
            throw new IllegalArgumentException("url == null");
        }

        com.alibaba.dubbo.common.URL url = arg1;
      // 其实前面所说的逻辑就在这里呈现了
        String extName = ((url.getProtocol() == null) ? "dubbo"
                                                      : url.getProtocol());

        if (extName == null) {
            throw new IllegalStateException(
                "Fail to get extension(com.alibaba.dubbo.rpc.Protocol) name from url(" +
                url.toString() + ") use keys([protocol])");
        }
				// 在这就是实际的通过dubbo 的 spi 去加载实际对应的扩展
        com.alibaba.dubbo.rpc.Protocol extension = (com.alibaba.dubbo.rpc.Protocol) ExtensionLoader.getExtensionLoader(com.alibaba.dubbo.rpc.Protocol.class)
                                                                                                   .getExtension(extName);

        return extension.refer(arg0, arg1);
    }
}

+]]> + + Java + Dubbo + RPC + SPI + Dubbo + SPI + Adaptive + + + Java + Dubbo + RPC + SPI + Adaptive + 自适应拓展 + + 聊聊 Dubbo 的 SPI /2020/05/31/%E8%81%8A%E8%81%8A-Dubbo-%E7%9A%84-SPI/ @@ -5666,22 +5873,6 @@ user3: 容错机制 - - 聊聊 Java 的 equals 和 hashCode 方法 - /2021/01/03/%E8%81%8A%E8%81%8A-Java-%E7%9A%84-equals-%E5%92%8C-hashCode-%E6%96%B9%E6%B3%95/ - Java 中的这个话题也是比较常遇到的，关于这块原先也是比较忽略的，但是仔细想想又有点遗忘了就在这里记一下
简单看下代码
java.lang.Object#equals

-
public boolean equals(Object obj) {
        return (this == obj);
    }
-

对于所有对象的父类，equals 方法其实对比的就是对象的地址，也就是是否是同一个对象，试想如果像 Integer 或者 String 这种，我们没有重写 equals，那其实就等于是在用==，可能就没法达到我们的目的，所以像 String 这种常用的 jdk 类都是默认重写了
java.lang.String#equals

-
public boolean equals(Object anObject) {
        if (this == anObject) {
            return true;
        }
        if (anObject instanceof String) {
            String anotherString = (String)anObject;
            int n = value.length;
            if (n == anotherString.value.length) {
                char v1[] = value;
                char v2[] = anotherString.value;
                int i = 0;
                while (n-- != 0) {
                    if (v1[i] != v2[i])
                        return false;
                    i++;
                }
                return true;
            }
        }
        return false;
    }
-

然后呢就是为啥一些书或者 effective java 中写了 equals 跟 hashCode 要一起重写，这里涉及到当对象作为 HashMap 的 key 的时候
首先 HashMap 会使用 hashCode 去判断是否在同一个槽里，然后在通过 equals 去判断是否是同一个 key，是的话就替换，不是的话就链表接下去，如果不重写 hashCode 的话，默认的 object 的hashCode 是 native 方法，根据对象的地址生成的，这样其实对象的值相同的话，因为地址不同，HashMap 也会出现异常，所以需要重写，同时也需要重写 equals 方法，才能确认是同一个 key，而不是落在同一个槽的不同 key.

-]]> - - java - - - java - - 聊聊 Java 中绕不开的 Synchronized 关键字-二 /2021/06/27/%E8%81%8A%E8%81%8A-Java-%E4%B8%AD%E7%BB%95%E4%B8%8D%E5%BC%80%E7%9A%84-Synchronized-%E5%85%B3%E9%94%AE%E5%AD%97-%E4%BA%8C/ @@ -5756,6 +5947,22 @@ user3: 自旋 + + 聊聊 Java 的 equals 和 hashCode 方法 + /2021/01/03/%E8%81%8A%E8%81%8A-Java-%E7%9A%84-equals-%E5%92%8C-hashCode-%E6%96%B9%E6%B3%95/ + Java 中的这个话题也是比较常遇到的，关于这块原先也是比较忽略的，但是仔细想想又有点遗忘了就在这里记一下
简单看下代码
java.lang.Object#equals

+
public boolean equals(Object obj) {
        return (this == obj);
    }
+

对于所有对象的父类，equals 方法其实对比的就是对象的地址，也就是是否是同一个对象，试想如果像 Integer 或者 String 这种，我们没有重写 equals，那其实就等于是在用==，可能就没法达到我们的目的，所以像 String 这种常用的 jdk 类都是默认重写了
java.lang.String#equals

+
public boolean equals(Object anObject) {
        if (this == anObject) {
            return true;
        }
        if (anObject instanceof String) {
            String anotherString = (String)anObject;
            int n = value.length;
            if (n == anotherString.value.length) {
                char v1[] = value;
                char v2[] = anotherString.value;
                int i = 0;
                while (n-- != 0) {
                    if (v1[i] != v2[i])
                        return false;
                    i++;
                }
                return true;
            }
        }
        return false;
    }
+

然后呢就是为啥一些书或者 effective java 中写了 equals 跟 hashCode 要一起重写，这里涉及到当对象作为 HashMap 的 key 的时候
首先 HashMap 会使用 hashCode 去判断是否在同一个槽里，然后在通过 equals 去判断是否是同一个 key，是的话就替换，不是的话就链表接下去，如果不重写 hashCode 的话，默认的 object 的hashCode 是 native 方法，根据对象的地址生成的，这样其实对象的值相同的话，因为地址不同，HashMap 也会出现异常，所以需要重写，同时也需要重写 equals 方法，才能确认是同一个 key，而不是落在同一个槽的不同 key.

+]]> + + java + + + java + + 聊聊 Java 的类加载机制一 /2020/11/08/%E8%81%8A%E8%81%8A-Java-%E7%9A%84%E7%B1%BB%E5%8A%A0%E8%BD%BD%E6%9C%BA%E5%88%B6/ @@ -5829,6 +6036,31 @@ user3: 双亲委派 + + 聊聊 Java 自带的那些*逆天*工具 + /2020/08/02/%E8%81%8A%E8%81%8A-Java-%E8%87%AA%E5%B8%A6%E7%9A%84%E9%82%A3%E4%BA%9B%E9%80%86%E5%A4%A9%E5%B7%A5%E5%85%B7/ + 原谅我的标题党，其实这些工具的确很厉害，之前其实介绍过一点相关的，是从我一次问题排查的过程中用到的，但是最近又有碰到一次排查问题，发现其实用 idea 直接 dump thread 是不现实的，毕竟服务器环境的没法这么操作，那就得用 Java 的那些工具了

+

jstack & jps

譬如 jstack，这个命令其实不能更简单了
看看 help 信息

用-l参数可以打出锁的额外信息，然后后面的 pid 就是进程 id 咯，机智的小伙伴会问了（就你这个小白才问这么蠢的问题🤦‍♂️），怎么看 Java 应用的进程呢
那就是 jps 了，命令也很简单，一般直接用 jps命令就好了，不过也可以 help 看一下

稍微解释下，-q是只显示进程 id，-m是输出给main 方法的参数，比如我在配置中加给参数

然后用 jps -m查看

-v加上小 v 的话就是打印 jvm 参数

还是有点东西，然后就继续介绍 jstack 了，然后我们看看 jstack 出来是啥，为了加点内容我加了个死锁

+
public static void main(String[] args) throws InterruptedException {
        SpringApplication.run(ThreadDumpDemoApplication.class, args);
        ReentrantLock lock1 = new ReentrantLock();
        ReentrantLock lock2 = new ReentrantLock();
        Thread t1 = new Thread() {
            @Override
            public void run() {
                try {
                    lock1.lock();
                    TimeUnit.SECONDS.sleep(1);
                    lock2.lock();
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            }
        };
        Thread t2 = new Thread() {
            @Override
            public void run() {
                try {
                    lock2.lock();
                    TimeUnit.SECONDS.sleep(1);
                    lock1.lock();
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            }
        };
        t1.setName("mythread1");
        t2.setName("mythread2");
        t1.start();
        t2.start();
        Thread.sleep(10000);
    }
+

然后看看出来时怎么样的

+
2020-08-02 21:50:32
Full thread dump Java HotSpot(TM) 64-Bit Server VM (25.201-b09 mixed mode):

"DestroyJavaVM" #147 prio=5 os_prio=31 tid=0x00007fc9dd807000 nid=0x2603 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"mythread2" #140 prio=5 os_prio=31 tid=0x00007fc9dd877000 nid=0x9903 waiting on condition [0x0000700006fb9000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$2.run(ThreadDumpDemoApplication.java:34)

   Locked ownable synchronizers:
        - <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)

"mythread1" #139 prio=5 os_prio=31 tid=0x00007fc9de873800 nid=0x9a03 waiting on condition [0x0000700006eb6000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$1.run(ThreadDumpDemoApplication.java:22)

   Locked ownable synchronizers:
        - <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)

"http-nio-8080-Acceptor" #137 daemon prio=5 os_prio=31 tid=0x00007fc9de1ac000 nid=0x9b03 runnable [0x0000700006db3000]
   java.lang.Thread.State: RUNNABLE
        at sun.nio.ch.ServerSocketChannelImpl.accept0(Native Method)
        at sun.nio.ch.ServerSocketChannelImpl.accept(ServerSocketChannelImpl.java:422)
        at sun.nio.ch.ServerSocketChannelImpl.accept(ServerSocketChannelImpl.java:250)
        - locked <0x000000076f1e4820> (a java.lang.Object)
        at org.apache.tomcat.util.net.NioEndpoint.serverSocketAccept(NioEndpoint.java:469)
        at org.apache.tomcat.util.net.NioEndpoint.serverSocketAccept(NioEndpoint.java:71)
        at org.apache.tomcat.util.net.Acceptor.run(Acceptor.java:95)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-ClientPoller" #136 daemon prio=5 os_prio=31 tid=0x00007fc9dd876800 nid=0x6503 runnable [0x0000700006cb0000]
   java.lang.Thread.State: RUNNABLE
        at sun.nio.ch.KQueueArrayWrapper.kevent0(Native Method)
        at sun.nio.ch.KQueueArrayWrapper.poll(KQueueArrayWrapper.java:198)
        at sun.nio.ch.KQueueSelectorImpl.doSelect(KQueueSelectorImpl.java:117)
        at sun.nio.ch.SelectorImpl.lockAndDoSelect(SelectorImpl.java:86)
        - locked <0x000000076f2978c8> (a sun.nio.ch.Util$3)
        - locked <0x000000076f2978b8> (a java.util.Collections$UnmodifiableSet)
        - locked <0x000000076f297798> (a sun.nio.ch.KQueueSelectorImpl)
        at sun.nio.ch.SelectorImpl.select(SelectorImpl.java:97)
        at org.apache.tomcat.util.net.NioEndpoint$Poller.run(NioEndpoint.java:709)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-10" #135 daemon prio=5 os_prio=31 tid=0x00007fc9de1af000 nid=0x9d03 waiting on condition [0x0000700006bad000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-9" #134 daemon prio=5 os_prio=31 tid=0x00007fc9de1ab800 nid=0x6403 waiting on condition [0x0000700006aaa000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-8" #133 daemon prio=5 os_prio=31 tid=0x00007fc9de873000 nid=0x9f03 waiting on condition [0x00007000069a7000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-7" #132 daemon prio=5 os_prio=31 tid=0x00007fc9df0a1800 nid=0xa103 waiting on condition [0x00007000068a4000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-6" #131 daemon prio=5 os_prio=31 tid=0x00007fc9df242800 nid=0x6103 waiting on condition [0x00007000067a1000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-5" #130 daemon prio=5 os_prio=31 tid=0x00007fc9de872000 nid=0x5f03 waiting on condition [0x000070000669e000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-4" #129 daemon prio=5 os_prio=31 tid=0x00007fc9de1a6000 nid=0x5e03 waiting on condition [0x000070000659b000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-3" #128 daemon prio=5 os_prio=31 tid=0x00007fc9de871800 nid=0x5c03 waiting on condition [0x0000700006498000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-2" #127 daemon prio=5 os_prio=31 tid=0x00007fc9dead9000 nid=0x5b03 waiting on condition [0x0000700006395000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-1" #126 daemon prio=5 os_prio=31 tid=0x00007fc9ddb00000 nid=0x5a03 waiting on condition [0x0000700006292000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-BlockPoller" #125 daemon prio=5 os_prio=31 tid=0x00007fc9df242000 nid=0xa503 runnable [0x000070000618f000]
   java.lang.Thread.State: RUNNABLE
        at sun.nio.ch.KQueueArrayWrapper.kevent0(Native Method)
        at sun.nio.ch.KQueueArrayWrapper.poll(KQueueArrayWrapper.java:198)
        at sun.nio.ch.KQueueSelectorImpl.doSelect(KQueueSelectorImpl.java:117)
        at sun.nio.ch.SelectorImpl.lockAndDoSelect(SelectorImpl.java:86)
        - locked <0x000000076f1eea30> (a sun.nio.ch.Util$3)
        - locked <0x000000076f1ee198> (a java.util.Collections$UnmodifiableSet)
        - locked <0x000000076f1ee010> (a sun.nio.ch.KQueueSelectorImpl)
        at sun.nio.ch.SelectorImpl.select(SelectorImpl.java:97)
        at org.apache.tomcat.util.net.NioBlockingSelector$BlockPoller.run(NioBlockingSelector.java:313)

   Locked ownable synchronizers:
        - None

"container-0" #124 prio=5 os_prio=31 tid=0x00007fc9df06a000 nid=0x5803 waiting on condition [0x000070000608c000]
   java.lang.Thread.State: TIMED_WAITING (sleeping)
        at java.lang.Thread.sleep(Native Method)
        at org.apache.catalina.core.StandardServer.await(StandardServer.java:570)
        at org.springframework.boot.web.embedded.tomcat.TomcatWebServer$1.run(TomcatWebServer.java:197)

   Locked ownable synchronizers:
        - None

"Catalina-utility-2" #123 prio=1 os_prio=31 tid=0x00007fc9de886000 nid=0xa80f waiting on condition [0x0000700005f89000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076c88ab58> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1088)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"Catalina-utility-1" #122 prio=1 os_prio=31 tid=0x00007fc9de884000 nid=0x5667 waiting on condition [0x0000700005e86000]
   java.lang.Thread.State: TIMED_WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076c88ab58> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:215)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:2078)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1093)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"RMI Scheduler(0)" #15 daemon prio=5 os_prio=31 tid=0x00007fc9de9ee000 nid=0x5503 waiting on condition [0x0000700005d83000]
   java.lang.Thread.State: TIMED_WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x00000006c0015410> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:215)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:2078)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1093)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"Attach Listener" #13 daemon prio=9 os_prio=31 tid=0x00007fc9df149800 nid=0x3c07 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"RMI TCP Accept-0" #11 daemon prio=5 os_prio=31 tid=0x00007fc9df100000 nid=0x4003 runnable [0x0000700005977000]
   java.lang.Thread.State: RUNNABLE
        at java.net.PlainSocketImpl.socketAccept(Native Method)
        at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:409)
        at java.net.ServerSocket.implAccept(ServerSocket.java:545)
        at java.net.ServerSocket.accept(ServerSocket.java:513)
        at sun.management.jmxremote.LocalRMIServerSocketFactory$1.accept(LocalRMIServerSocketFactory.java:52)
        at sun.rmi.transport.tcp.TCPTransport$AcceptLoop.executeAcceptLoop(TCPTransport.java:405)
        at sun.rmi.transport.tcp.TCPTransport$AcceptLoop.run(TCPTransport.java:377)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"Service Thread" #9 daemon prio=9 os_prio=31 tid=0x00007fc9df0ce800 nid=0x4103 runnable [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"C1 CompilerThread2" #8 daemon prio=9 os_prio=31 tid=0x00007fc9df0ce000 nid=0x4203 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"C2 CompilerThread1" #7 daemon prio=9 os_prio=31 tid=0x00007fc9de0a3800 nid=0x3503 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"C2 CompilerThread0" #6 daemon prio=9 os_prio=31 tid=0x00007fc9de89b000 nid=0x3403 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"Monitor Ctrl-Break" #5 daemon prio=5 os_prio=31 tid=0x00007fc9df0ca000 nid=0x3303 runnable [0x0000700005468000]
   java.lang.Thread.State: RUNNABLE
        at java.net.SocketInputStream.socketRead0(Native Method)
        at java.net.SocketInputStream.socketRead(SocketInputStream.java:116)
        at java.net.SocketInputStream.read(SocketInputStream.java:171)
        at java.net.SocketInputStream.read(SocketInputStream.java:141)
        at sun.nio.cs.StreamDecoder.readBytes(StreamDecoder.java:284)
        at sun.nio.cs.StreamDecoder.implRead(StreamDecoder.java:326)
        at sun.nio.cs.StreamDecoder.read(StreamDecoder.java:178)
        - locked <0x00000006c001b760> (a java.io.InputStreamReader)
        at java.io.InputStreamReader.read(InputStreamReader.java:184)
        at java.io.BufferedReader.fill(BufferedReader.java:161)
        at java.io.BufferedReader.readLine(BufferedReader.java:324)
        - locked <0x00000006c001b760> (a java.io.InputStreamReader)
        at java.io.BufferedReader.readLine(BufferedReader.java:389)
        at com.intellij.rt.execution.application.AppMainV2$1.run(AppMainV2.java:64)

   Locked ownable synchronizers:
        - None

"Signal Dispatcher" #4 daemon prio=9 os_prio=31 tid=0x00007fc9de824000 nid=0x4503 runnable [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"Finalizer" #3 daemon prio=8 os_prio=31 tid=0x00007fc9dd811800 nid=0x4f03 in Object.wait() [0x0000700005262000]
   java.lang.Thread.State: WAITING (on object monitor)
        at java.lang.Object.wait(Native Method)
        - waiting on <0x00000006c0008348> (a java.lang.ref.ReferenceQueue$Lock)
        at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:144)
        - locked <0x00000006c0008348> (a java.lang.ref.ReferenceQueue$Lock)
        at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:165)
        at java.lang.ref.Finalizer$FinalizerThread.run(Finalizer.java:216)

   Locked ownable synchronizers:
        - None

"Reference Handler" #2 daemon prio=10 os_prio=31 tid=0x00007fc9de02a000 nid=0x5003 in Object.wait() [0x000070000515f000]
   java.lang.Thread.State: WAITING (on object monitor)
        at java.lang.Object.wait(Native Method)
        - waiting on <0x00000006c001b940> (a java.lang.ref.Reference$Lock)
        at java.lang.Object.wait(Object.java:502)
        at java.lang.ref.Reference.tryHandlePending(Reference.java:191)
        - locked <0x00000006c001b940> (a java.lang.ref.Reference$Lock)
        at java.lang.ref.Reference$ReferenceHandler.run(Reference.java:153)

   Locked ownable synchronizers:
        - None

"VM Thread" os_prio=31 tid=0x00007fc9df00b800 nid=0x2c03 runnable 

"GC task thread#0 (ParallelGC)" os_prio=31 tid=0x00007fc9de805000 nid=0x1e07 runnable 

"GC task thread#1 (ParallelGC)" os_prio=31 tid=0x00007fc9de003800 nid=0x2a03 runnable 

"GC task thread#2 (ParallelGC)" os_prio=31 tid=0x00007fc9df002000 nid=0x5403 runnable 

"GC task thread#3 (ParallelGC)" os_prio=31 tid=0x00007fc9df002800 nid=0x5203 runnable 

"VM Periodic Task Thread" os_prio=31 tid=0x00007fc9df11a800 nid=0x3a03 waiting on condition 

JNI global references: 1087


Found one Java-level deadlock:
=============================
"mythread2":
  waiting for ownable synchronizer 0x000000076f5d4330, (a java.util.concurrent.locks.ReentrantLock$NonfairSync),
  which is held by "mythread1"
"mythread1":
  waiting for ownable synchronizer 0x000000076f5d4360, (a java.util.concurrent.locks.ReentrantLock$NonfairSync),
  which is held by "mythread2"

Java stack information for the threads listed above:
===================================================
"mythread2":
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$2.run(ThreadDumpDemoApplication.java:34)
"mythread1":
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$1.run(ThreadDumpDemoApplication.java:22)

Found 1 deadlock.
+

前面的信息其实上次就看过了，后面就可以发现有个死锁了，

上面比较长，把主要的截出来，就是这边的，这点就很强大了。

+

jmap

惯例还是看一下帮助信息

这个相对命令比较多，不过因为现在 dump 下来我们可能会用文件模式，然后将文件下载下来使用 mat 进行分析，所以可以使用
jmap -dump:live,format=b,file=heap.bin <pid>
命令照着上面看的就是打印活着的对象，然后以二进制格式，文件名叫 heap.bin 然后最后就是进程 id，打印出来以后可以用 mat 打开

这样就可以很清晰的看到应用里的各种信息，jmap 直接在命令中还可以看很多信息，比如使用jmap -histo <pid>打印对象的实例数和对象占用的内存

jmap -finalizerinfo <pid> 打印正在等候回收的对象

+

小tips

对于一些应用内存已经占满了，jstack 和 jmap 可能会连不上的情况，可以使用-F参数强制打印线程或者 dump 文件，但是要注意这两者使用的用户必须与 java 进程启动用户一致，并且使用的 jdk 也要一致

+]]> + + Java + Thread dump + 问题排查 + 工具 + + + Java + JPS + JStack + JMap + + 聊聊 Linux 下的 top 命令 /2021/03/28/%E8%81%8A%E8%81%8A-Linux-%E4%B8%8B%E7%9A%84-top-%E5%91%BD%E4%BB%A4/ @@ -5840,8 +6072,8 @@ user3: ]]> Linux - 命令 小技巧 + 命令 top top 排序 @@ -5853,138 +6085,6 @@ user3: top - - 聊聊 Sharding-Jdbc 分库分表下的分页方案 - /2022/01/09/%E8%81%8A%E8%81%8A-Sharding-Jdbc-%E5%88%86%E5%BA%93%E5%88%86%E8%A1%A8%E4%B8%8B%E7%9A%84%E5%88%86%E9%A1%B5%E6%96%B9%E6%A1%88/ - 前面在聊 Sharding-Jdbc 的时候看到了一篇文章，关于一个分页的查询，一直比较直接的想法就是分库分表下的分页是非常不合理的，一般我们的实操方案都是分表加上 ES 搜索做分页，或者通过合表读写分离的方案，因为对于 sharding-jdbc 如果没有带分表键，查询基本都是只能在所有分表都执行一遍，然后再加上分页，基本上是分页越大后续的查询越耗资源，但是仔细的去想这个细节还是这次，就简单说说
首先就是我的分表结构

-
CREATE TABLE `student_time_0` (
  `id` int(11) unsigned NOT NULL AUTO_INCREMENT,
  `user_id` int(11) NOT NULL,
  `name` varchar(200) COLLATE utf8_bin DEFAULT NULL,
  `age` tinyint(3) unsigned DEFAULT NULL,
  `create_time` bigint(20) DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=674 DEFAULT CHARSET=utf8 COLLATE=utf8_bin;
-

有这样的三个表，student_time_0, student_time_1, student_time_2, 以 user_id 作为分表键，根据表数量取模作为分表依据
这里先构造点数据，

-
insert into student_time (`name`, `user_id`, `age`, `create_time`) values (?, ?, ?, ?)
-

主要是为了保证 create_time 唯一比较好说明问题，

-
int i = 0;
try (
        Connection conn = dataSource.getConnection();
        PreparedStatement ps = conn.prepareStatement(insertSql)) {
    do {
        ps.setString(1, localName + new Random().nextInt(100));
        ps.setLong(2, 10086L + (new Random().nextInt(100)));
        ps.setInt(3, 18);
        ps.setLong(4, new Date().getTime());


        int result = ps.executeUpdate();
        LOGGER.info("current execute result: {}", result);
        Thread.sleep(new Random().nextInt(100));
        i++;
    } while (i <= 2000);
-

三个表的数据分别是 673，678，650，说明符合预期了，各个表数据不一样，接下来比如我们想要做一个这样的分页查询

-
select * from student_time ORDER BY create_time ASC limit 1000, 5;
-

student_time 对于我们使用的 sharding-jdbc 来说当然是逻辑表，首先从一无所知去想这个查询如果我们自己来处理应该是怎么做，
首先是不是可以每个表都从 333 开始取 5 条数据，类似于下面的查询，然后进行 15 条的合并重排序获取前面的 5 条

-
select * from student_time_0 ORDER BY create_time ASC limit 333, 5;
select * from student_time_1 ORDER BY create_time ASC limit 333, 5;
select * from student_time_2 ORDER BY create_time ASC limit 333, 5;
-

忽略前面 limit 差的 1，这个结果除非三个表的分布是绝对的均匀，否则结果肯定会出现一定的偏差，以为每个表的 333 这个位置对于其他表来说都不一定是一样的，这样对于最后整体的结果，就会出现偏差
因为一直在纠结怎么让这个更直观的表现出来，所以尝试画了个图

黑色的框代表我从每个表里按排序从 334 到 338 的 5 条数据， 他们在每个表里都是代表了各自正确的排序值，但是对于我们想要的其实是合表后的 1001，1005 这五条，然后我们假设总的排序值位于前 1000 的分布是第 0 个表是 320 条，第 1 个表是 340 条，第 2 个表是 340 条，那么可以明显地看出来我这么查的结果简单合并肯定是不对的。
那么 sharding-jdbc 是如何保证这个结果的呢，其实就是我在每个表里都查分页偏移量和分页大小那么多的数据，在我这个例子里就是对于 0，1，2 三个分表每个都查 1005 条数据，即使我的数据不平衡到最极端的情况，前 1005 条数据都出在某个分表中，也可以正确获得最后的结果，但是明显的问题就是大分页，数据较多，就会导致非常大的问题，即使如 sharding-jdbc 对于合并排序的优化做得比较好，也还是需要传输那么大量的数据，并且查询也耗时，那么有没有解决方案呢，应该说有两个，或者说主要是想讲后者
第一个办法是像这种查询，如果业务上不需要进行跳页，而是只给下一页，那么我们就能把前一次的最大偏移量的 create_time 记录下来，下一页就可以拿着这个偏移量进行查询，这个比较简单易懂，就不多说了
第二个办法是看的58 沈剑的一篇文章，尝试理解讲述一下，
这个办法的第一步跟前面那个错误的方法或者说不准确的方法一样，先是将分页偏移量平均后在三个表里进行查询

-
t0
334 10158 nick95  18  1641548941767
335 10098 nick11  18  1641548941879
336 10167 nick51  18  1641548942089
337 10167 nick3 18  1641548942119
338 10170 nick57  18  1641548942169


t1
334 10105 nick98  18  1641548939071   最小
335 10174 nick94  18  1641548939377
336 10129 nick85  18  1641548939442
337 10141 nick84  18  1641548939480
338 10096 nick74  18  1641548939668

t2
334 10184 nick11  18  1641548945075
335 10109 nick93  18  1641548945382
336 10181 nick41  18  1641548945583
337 10130 nick80  18  1641548945993
338 10184 nick19  18  1641548946294  最大
-

然后要做什么呢，其实目标比较明白，因为前面那种方法其实就是我知道了前一页的偏移量，所以可以直接当做条件来进行查询，那这里我也想着拿到这个条件，所以我将第一遍查出来的最小的 create_time 和最大的 create_time 找出来，然后再去三个表里查询，其实主要是最小值，因为我拿着最小值去查以后我就能知道这个最小值在每个表里处在什么位置，

-
t0
322 10161 nick81  18  1641548939284
323 10113 nick16  18  1641548939393
324 10110 nick56  18  1641548939577
325 10116 nick69  18  1641548939588
326 10173 nick51  18  1641548939646

t1
334 10105 nick98  18  1641548939071
335 10174 nick94  18  1641548939377
336 10129 nick85  18  1641548939442
337 10141 nick84  18  1641548939480
338 10096 nick74  18  1641548939668

t2
297 10136 nick28  18  1641548939161
298 10142 nick68  18  1641548939177
299 10124 nick41  18  1641548939237
300 10148 nick87  18  1641548939510
301 10169 nick23  18  1641548939715
-

我只贴了前五条数据，为了方便知道偏移量，每个分表都使用了自增主键，我们可以看到前一次查询的最小值分别在其他两个表里的位置分别是 322-1 和 297-1，那么对于总体来说这个时间应该是在 322 - 1 + 333 + 297 - 1 = 951，那这样子我只要对后面的数据最多每个表查 1000 - 951 + 5 = 54 条数据再进行合并排序就可以获得最终正确的结果。
这个就是传说中的二次查询法。

-]]> - - Java - - - Java - Sharding-Jdbc - - - - 聊一下 Java 的日志系列二 - /2024/01/14/%E8%81%8A%E4%B8%80%E4%B8%8B-Java-%E7%9A%84%E6%97%A5%E5%BF%97%E7%B3%BB%E5%88%97%E4%BA%8C/ - log 初始化过程，首先是在启动类里会获取 logger

-
private static final Log logger = LogFactory.getLog(SpringApplication.class);
-

然后是

-
public static Log getLog(Class clazz) throws LogConfigurationException {
        return getFactory().getInstance(clazz);
    }
-

继续下去是
org.apache.commons.logging.impl.SLF4JLogFactory#getInstance(java.lang.Class)

-
public Log getInstance(Class clazz) throws LogConfigurationException {
    return this.getInstance(clazz.getName());
}
public Log getInstance(String name) throws LogConfigurationException {
    Log instance = (Log)this.loggerMap.get(name);
    if (instance != null) {
        return instance;
    } else {
        Logger slf4jLogger = LoggerFactory.getLogger(name);
        Object newInstance;
        if (slf4jLogger instanceof LocationAwareLogger) {
            newInstance = new SLF4JLocationAwareLog((LocationAwareLogger)slf4jLogger);
        } else {
            newInstance = new SLF4JLog(slf4jLogger);
        }

        Log oldInstance = (Log)this.loggerMap.putIfAbsent(name, newInstance);
        return (Log)(oldInstance == null ? newInstance : oldInstance);
    }
}
-

然后再往下处理就是 LoggerFactory.getLogger(name); 了，跟普通的获取 logger 一样

-
public static Logger getLogger(String name) {
    ILoggerFactory iLoggerFactory = getILoggerFactory();
    return iLoggerFactory.getLogger(name);
}
-

继续下去会先判断是否已初始化

-
public static ILoggerFactory getILoggerFactory() {
        if (INITIALIZATION_STATE == UNINITIALIZED) {
            synchronized (LoggerFactory.class) {
                if (INITIALIZATION_STATE == UNINITIALIZED) {
                    INITIALIZATION_STATE = ONGOING_INITIALIZATION;
                    performInitialization();
                }
            }
        }
        switch (INITIALIZATION_STATE) {
        case SUCCESSFUL_INITIALIZATION:
            return StaticLoggerBinder.getSingleton().getLoggerFactory();
        case NOP_FALLBACK_INITIALIZATION:
            return NOP_FALLBACK_FACTORY;
        case FAILED_INITIALIZATION:
            throw new IllegalStateException(UNSUCCESSFUL_INIT_MSG);
        case ONGOING_INITIALIZATION:
            // support re-entrant behavior.
            // See also http://jira.qos.ch/browse/SLF4J-97
            return SUBST_FACTORY;
        }
        throw new IllegalStateException("Unreachable code");
    }
-

第一次调用的话就会走到 org.slf4j.LoggerFactory#performInitialization 里面是先调用绑定，这也是 slf4j 门面模式的特点

-
private final static void performInitialization() {
    bind();
    if (INITIALIZATION_STATE == SUCCESSFUL_INITIALIZATION) {
        versionSanityCheck();
    }
}
- - -
private final static void bind() {
        try {
            Set<URL> staticLoggerBinderPathSet = null;
            // skip check under android, see also
            // http://jira.qos.ch/browse/SLF4J-328
            if (!isAndroid()) {
                staticLoggerBinderPathSet = findPossibleStaticLoggerBinderPathSet();
                reportMultipleBindingAmbiguity(staticLoggerBinderPathSet);
            }
            // the next line does the binding
            StaticLoggerBinder.getSingleton();
            INITIALIZATION_STATE = SUCCESSFUL_INITIALIZATION;
            reportActualBinding(staticLoggerBinderPathSet);
            fixSubstituteLoggers();
            replayEvents();
            // release all resources in SUBST_FACTORY
            SUBST_FACTORY.clear();
        } catch (NoClassDefFoundError ncde) {
            String msg = ncde.getMessage();
            if (messageContainsOrgSlf4jImplStaticLoggerBinder(msg)) {
                INITIALIZATION_STATE = NOP_FALLBACK_INITIALIZATION;
                Util.report("Failed to load class \"org.slf4j.impl.StaticLoggerBinder\".");
                Util.report("Defaulting to no-operation (NOP) logger implementation");
                Util.report("See " + NO_STATICLOGGERBINDER_URL + " for further details.");
            } else {
                failedBinding(ncde);
                throw ncde;
            }
        } catch (java.lang.NoSuchMethodError nsme) {
            String msg = nsme.getMessage();
            if (msg != null && msg.contains("org.slf4j.impl.StaticLoggerBinder.getSingleton()")) {
                INITIALIZATION_STATE = FAILED_INITIALIZATION;
                Util.report("slf4j-api 1.6.x (or later) is incompatible with this binding.");
                Util.report("Your binding is version 1.5.5 or earlier.");
                Util.report("Upgrade your binding to version 1.6.x.");
            }
            throw nsme;
        } catch (Exception e) {
            failedBinding(e);
            throw new IllegalStateException("Unexpected initialization failure", e);
        }
    }
-

非安卓环境会进入第一个 if 逻辑，先要去找static_logger_binder

-
static Set<URL> findPossibleStaticLoggerBinderPathSet() {
        // use Set instead of list in order to deal with bug #138
        // LinkedHashSet appropriate here because it preserves insertion order
        // during iteration
        Set<URL> staticLoggerBinderPathSet = new LinkedHashSet<URL>();
        try {
            ClassLoader loggerFactoryClassLoader = LoggerFactory.class.getClassLoader();
            Enumeration<URL> paths;
            if (loggerFactoryClassLoader == null) {
                paths = ClassLoader.getSystemResources(STATIC_LOGGER_BINDER_PATH);
            } else {
                paths = loggerFactoryClassLoader.getResources(STATIC_LOGGER_BINDER_PATH);
            }
            while (paths.hasMoreElements()) {
                URL path = paths.nextElement();
                staticLoggerBinderPathSet.add(path);
            }
        } catch (IOException ioe) {
            Util.report("Error getting resources from path", ioe);
        }
        return staticLoggerBinderPathSet;
    }
-

上面的 STATIC_LOGGER_BINDER_PATH
就是 org/slf4j/impl/StaticLoggerBinder.class 如果找不到在外层方法就会抛出 NoSuchMethodError 错误，然后就是通过 StaticLoggerBinder.getSingleton(); 获取 StaticLoggerBinder 实例了

-
public static StaticLoggerBinder getSingleton() {
    return SINGLETON;
}
private static StaticLoggerBinder SINGLETON = new StaticLoggerBinder();
-

比较重要的是这里的 static 代码块还有一个逻辑，就是下面这个初始化逻辑

-
static {
    SINGLETON.init();
}
void init() {
    try {
        try {
            new ContextInitializer(defaultLoggerContext).autoConfig();
        } catch (JoranException je) {
            Util.report("Failed to auto configure default logger context", je);
        }
        // logback-292
        if (!StatusUtil.contextHasStatusListener(defaultLoggerContext)) {
            StatusPrinter.printInCaseOfErrorsOrWarnings(defaultLoggerContext);
        }
        contextSelectorBinder.init(defaultLoggerContext, KEY);
        initialized = true;
    } catch (Exception t) { // see LOGBACK-1159
        Util.report("Failed to instantiate [" + LoggerContext.class.getName() + "]", t);
    }
}
-

上面的 defaultLoggerContext 也是通过静态代码块处理的

-
private LoggerContext defaultLoggerContext = new LoggerContext();
-

然后是调用 ch.qos.logback.classic.util.ContextInitializer#autoConfig 方法

-
public void autoConfig() throws JoranException {
        StatusListenerConfigHelper.installIfAsked(loggerContext);
        URL url = findURLOfDefaultConfigurationFile(true);
        if (url != null) {
            configureByResource(url);
        } else {
            Configurator c = EnvUtil.loadFromServiceLoader(Configurator.class);
            if (c != null) {
                try {
                    c.setContext(loggerContext);
                    c.configure(loggerContext);
                } catch (Exception e) {
                    throw new LogbackException(String.format("Failed to initialize Configurator: %s using ServiceLoader", c != null ? c.getClass()
                                    .getCanonicalName() : "null"), e);
                }
            } else {
                BasicConfigurator basicConfigurator = new BasicConfigurator();
                basicConfigurator.setContext(loggerContext);
                basicConfigurator.configure(loggerContext);
            }
        }
    }
-

前面会先查找配置文件路径
URL url = findURLOfDefaultConfigurationFile(true); 还是调用这个类内的 ch.qos.logback.classic.util.ContextInitializer#findURLOfDefaultConfigurationFile 方法

-
public URL findURLOfDefaultConfigurationFile(boolean updateStatus) {
    ClassLoader myClassLoader = Loader.getClassLoaderOfObject(this);
    URL url = findConfigFileURLFromSystemProperties(myClassLoader, updateStatus);
    if (url != null) {
        return url;
    }

    url = getResource(TEST_AUTOCONFIG_FILE, myClassLoader, updateStatus);
    if (url != null) {
        return url;
    }

    url = getResource(GROOVY_AUTOCONFIG_FILE, myClassLoader, updateStatus);
    if (url != null) {
        return url;
    }

    return getResource(AUTOCONFIG_FILE, myClassLoader, updateStatus);
}
-

才发现原来这里也是硬编码了文件名

-
public class ContextInitializer {

    final public static String GROOVY_AUTOCONFIG_FILE = "logback.groovy";
    final public static String AUTOCONFIG_FILE = "logback.xml";
    final public static String TEST_AUTOCONFIG_FILE = "logback-test.xml";
    final public static String CONFIG_FILE_PROPERTY = "logback.configurationFile";

-

如果不为空就调用了
ch.qos.logback.classic.util.ContextInitializer#configureByResource 这边是根据后缀判断处理方法

-
public void configureByResource(URL url) throws JoranException {
        if (url == null) {
            throw new IllegalArgumentException("URL argument cannot be null");
        }
        final String urlString = url.toString();
        if (urlString.endsWith("groovy")) {
            if (EnvUtil.isGroovyAvailable()) {
                // avoid directly referring to GafferConfigurator so as to avoid
                // loading groovy.lang.GroovyObject . See also http://jira.qos.ch/browse/LBCLASSIC-214
                GafferUtil.runGafferConfiguratorOn(loggerContext, this, url);
            } else {
                StatusManager sm = loggerContext.getStatusManager();
                sm.add(new ErrorStatus("Groovy classes are not available on the class path. ABORTING INITIALIZATION.", loggerContext));
            }
        } else if (urlString.endsWith("xml")) {
            JoranConfigurator configurator = new JoranConfigurator();
            configurator.setContext(loggerContext);
            configurator.doConfigure(url);
        } else {
            throw new LogbackException("Unexpected filename extension of file [" + url.toString() + "]. Should be either .groovy or .xml");
        }
    }
-

因为我们找到的是 logback.xml，所以走的是
ch.qos.logback.classic.joran.JoranConfigurator ，
然后调用了
ch.qos.logback.core.joran.GenericConfigurator#doConfigure(java.net.URL)
这个 GenericConfigurator 是 JoranConfigurator 的父类

-
public final void doConfigure(URL url) throws JoranException {
        InputStream in = null;
        try {
            informContextOfURLUsedForConfiguration(getContext(), url);
            URLConnection urlConnection = url.openConnection();
            // per http://jira.qos.ch/browse/LBCORE-105
            // per http://jira.qos.ch/browse/LBCORE-127
            urlConnection.setUseCaches(false);

            in = urlConnection.getInputStream();
            doConfigure(in, url.toExternalForm());
        } catch (IOException ioe) {
            String errMsg = "Could not open URL [" + url + "].";
            addError(errMsg, ioe);
            throw new JoranException(errMsg, ioe);
        } finally {
            if (in != null) {
                try {
                    in.close();
                } catch (IOException ioe) {
                    String errMsg = "Could not close input stream";
                    addError(errMsg, ioe);
                    throw new JoranException(errMsg, ioe);
                }
            }
        }
    }
-

然后继续调用
ch.qos.logback.core.joran.GenericConfigurator#doConfigure(java.io.InputStream, java.lang.String) 处理具体的内容，前面处理了内容获取，因为如果是走的 url 文件就需要从网络获取文件流，

-
public final void doConfigure(InputStream inputStream, String systemId) throws JoranException {
    InputSource inputSource = new InputSource(inputStream);
    inputSource.setSystemId(systemId);
    doConfigure(inputSource);
}
-

而实际的处理 xml 内容则是在
ch.qos.logback.core.joran.GenericConfigurator#doConfigure(org.xml.sax.InputSource)

-
public final void doConfigure(final InputSource inputSource) throws JoranException {

    long threshold = System.currentTimeMillis();
    // if (!ConfigurationWatchListUtil.wasConfigurationWatchListReset(context)) {
    // informContextOfURLUsedForConfiguration(getContext(), null);
    // }
    SaxEventRecorder recorder = new SaxEventRecorder(context);
    recorder.recordEvents(inputSource);
    doConfigure(recorder.saxEventList);
    // no exceptions a this level
    StatusUtil statusUtil = new StatusUtil(context);
    if (statusUtil.noXMLParsingErrorsOccurred(threshold)) {
        addInfo("Registering current configuration as safe fallback point");
        registerSafeConfiguration(recorder.saxEventList);
    }
}
-

需要解析 xml 了，先是调用 buildInterpreter 构建了 Interpreter

-
public void doConfigure(final List<SaxEvent> eventList) throws JoranException {
    buildInterpreter();
    // disallow simultaneous configurations of the same context
    synchronized (context.getConfigurationLock()) {
        interpreter.getEventPlayer().play(eventList);
    }
}
-

build 里还有一些逻辑，就是匹配后面要处理的规则集，就是要确认那些标签要处理

-
protected void buildInterpreter() {
        RuleStore rs = new SimpleRuleStore(context);
        addInstanceRules(rs);
        this.interpreter = new Interpreter(context, rs, initialElementPath());
        InterpretationContext interpretationContext = interpreter.getInterpretationContext();
        interpretationContext.setContext(context);
        addImplicitRules(interpreter);
        addDefaultNestedComponentRegistryRules(interpretationContext.getDefaultNestedComponentRegistry());
    }
-

第一步就是先 new 一个 ch.qos.logback.core.joran.spi.SimpleRuleStore 然后调用了 ch.qos.logback.classic.joran.JoranConfigurator#addInstanceRules 来添加规则，就是下面的，可以看到对于 logger,appender 这些的配置，其中前面点的父类也又一些规则 ,ch.qos.logback.core.joran.JoranConfiguratorBase 逻辑类似就不展开了，这里的规则就对应了后面的各种 Action，就是对应的处理逻辑

-
public void addInstanceRules(RuleStore rs) {
    // parent rules already added
    super.addInstanceRules(rs);

    rs.addRule(new ElementSelector("configuration"), new ConfigurationAction());

    rs.addRule(new ElementSelector("configuration/contextName"), new ContextNameAction());
    rs.addRule(new ElementSelector("configuration/contextListener"), new LoggerContextListenerAction());
    rs.addRule(new ElementSelector("configuration/insertFromJNDI"), new InsertFromJNDIAction());
    rs.addRule(new ElementSelector("configuration/evaluator"), new EvaluatorAction());

    rs.addRule(new ElementSelector("configuration/appender/sift"), new SiftAction());
    rs.addRule(new ElementSelector("configuration/appender/sift/*"), new NOPAction());

    rs.addRule(new ElementSelector("configuration/logger"), new LoggerAction());
    rs.addRule(new ElementSelector("configuration/logger/level"), new LevelAction());

    rs.addRule(new ElementSelector("configuration/root"), new RootLoggerAction());
    rs.addRule(new ElementSelector("configuration/root/level"), new LevelAction());
    rs.addRule(new ElementSelector("configuration/logger/appender-ref"), new AppenderRefAction<ILoggingEvent>());
    rs.addRule(new ElementSelector("configuration/root/appender-ref"), new AppenderRefAction<ILoggingEvent>());

    // add if-then-else support
    rs.addRule(new ElementSelector("*/if"), new IfAction());
    rs.addRule(new ElementSelector("*/if/then"), new ThenAction());
    rs.addRule(new ElementSelector("*/if/then/*"), new NOPAction());
    rs.addRule(new ElementSelector("*/if/else"), new ElseAction());
    rs.addRule(new ElementSelector("*/if/else/*"), new NOPAction());

    // add jmxConfigurator only if we have JMX available.
    // If running under JDK 1.4 (retrotranslateed logback) then we
    // might not have JMX.
    if (PlatformInfo.hasJMXObjectName()) {
        rs.addRule(new ElementSelector("configuration/jmxConfigurator"), new JMXConfiguratorAction());
    }
    rs.addRule(new ElementSelector("configuration/include"), new IncludeAction());

    rs.addRule(new ElementSelector("configuration/consolePlugin"), new ConsolePluginAction());

    rs.addRule(new ElementSelector("configuration/receiver"), new ReceiverAction());

}
-

然后调用了 interpreter 的 eventPlayer 处理 xml 的各个标签

-
public void play(List<SaxEvent> aSaxEventList) {
        eventList = aSaxEventList;
        SaxEvent se;
        for (currentIndex = 0; currentIndex < eventList.size(); currentIndex++) {
            se = eventList.get(currentIndex);

            if (se instanceof StartEvent) {
                interpreter.startElement((StartEvent) se);
                // invoke fireInPlay after startElement processing
                interpreter.getInterpretationContext().fireInPlay(se);
            }
            if (se instanceof BodyEvent) {
                // invoke fireInPlay before characters processing
                interpreter.getInterpretationContext().fireInPlay(se);
                interpreter.characters((BodyEvent) se);
            }
            if (se instanceof EndEvent) {
                // invoke fireInPlay before endElement processing
                interpreter.getInterpretationContext().fireInPlay(se);
                interpreter.endElement((EndEvent) se);
            }

        }
    }
-

接下去就在 startElement 中调用会先获取 getApplicableActionList 适配的 Action， callBeginAction

-
private void startElement(String namespaceURI, String localName, String qName, Attributes atts) {

        String tagName = getTagName(localName, qName);
        elementPath.push(tagName);

        if (skip != null) {
            // every startElement pushes an action list
            pushEmptyActionList();
            return;
        }

        List<Action> applicableActionList = getApplicableActionList(elementPath, atts);
        if (applicableActionList != null) {
            actionListStack.add(applicableActionList);
            callBeginAction(applicableActionList, tagName, atts);
        } else {
            // every startElement pushes an action list
            pushEmptyActionList();
            String errMsg = "no applicable action for [" + tagName + "], current ElementPath  is [" + elementPath + "]";
            cai.addError(errMsg);
        }
    }
-

里面就是用了 ruleStore 来判断是否适配，并且取出对应的 Action

-
List<Action> getApplicableActionList(ElementPath elementPath, Attributes attributes) {
    List<Action> applicableActionList = ruleStore.matchActions(elementPath);

    // logger.debug("set of applicable patterns: " + applicableActionList);
    if (applicableActionList == null) {
        applicableActionList = lookupImplicitAction(elementPath, attributes, interpretationContext);
    }

    return applicableActionList;
}
-

比如我这边往下处理，通过规则匹配拿到了 LoggerAction, 然后调用 Action.begin 方法

-
void callBeginAction(List<Action> applicableActionList, String tagName, Attributes atts) {
        if (applicableActionList == null) {
            return;
        }

        Iterator<Action> i = applicableActionList.iterator();
        while (i.hasNext()) {
            Action action = (Action) i.next();
            // now let us invoke the action. We catch and report any eventual
            // exceptions
            try {
                action.begin(interpretationContext, tagName, atts);
            } catch (ActionException e) {
                skip = elementPath.duplicate();
                cai.addError("ActionException in Action for tag [" + tagName + "]", e);
            } catch (RuntimeException e) {
                skip = elementPath.duplicate();
                cai.addError("RuntimeException in Action for tag [" + tagName + "]", e);
            }
        }
    }
-

就是下面这个

-
public void begin(InterpretationContext ec, String name, Attributes attributes) {
        // Let us forget about previous errors (in this object)
        inError = false;
        logger = null;

        LoggerContext loggerContext = (LoggerContext) this.context;

        String loggerName = ec.subst(attributes.getValue(NAME_ATTRIBUTE));

        if (OptionHelper.isEmpty(loggerName)) {
            inError = true;
            String aroundLine = getLineColStr(ec);
            String errorMsg = "No 'name' attribute in element " + name + ", around " + aroundLine;
            addError(errorMsg);
            return;
        }

        logger = loggerContext.getLogger(loggerName);

        String levelStr = ec.subst(attributes.getValue(LEVEL_ATTRIBUTE));

        if (!OptionHelper.isEmpty(levelStr)) {
            if (ActionConst.INHERITED.equalsIgnoreCase(levelStr) || ActionConst.NULL.equalsIgnoreCase(levelStr)) {
                addInfo("Setting level of logger [" + loggerName + "] to null, i.e. INHERITED");
                logger.setLevel(null);
            } else {
                Level level = Level.toLevel(levelStr);
                addInfo("Setting level of logger [" + loggerName + "] to " + level);
                logger.setLevel(level);
            }
        }

        String additivityStr = ec.subst(attributes.getValue(ActionConst.ADDITIVITY_ATTRIBUTE));
        if (!OptionHelper.isEmpty(additivityStr)) {
            boolean additive = OptionHelper.toBoolean(additivityStr, true);
            addInfo("Setting additivity of logger [" + loggerName + "] to " + additive);
            logger.setAdditive(additive);
        }
        ec.pushObject(logger);
    }
-

这里就会处理 logger 获取逻辑

-
public final Logger getLogger(final String name) {

        if (name == null) {
            throw new IllegalArgumentException("name argument cannot be null");
        }

        // if we are asking for the root logger, then let us return it without
        // wasting time
        if (Logger.ROOT_LOGGER_NAME.equalsIgnoreCase(name)) {
            return root;
        }

        int i = 0;
        Logger logger = root;

        // check if the desired logger exists, if it does, return it
        // without further ado.
        Logger childLogger = (Logger) loggerCache.get(name);
        // if we have the child, then let us return it without wasting time
        if (childLogger != null) {
            return childLogger;
        }

        // if the desired logger does not exist, them create all the loggers
        // in between as well (if they don't already exist)
        String childName;
        while (true) {
            int h = LoggerNameUtil.getSeparatorIndexOf(name, i);
            if (h == -1) {
                childName = name;
            } else {
                childName = name.substring(0, h);
            }
            // move i left of the last point
            i = h + 1;
            synchronized (logger) {
                childLogger = logger.getChildByName(childName);
                if (childLogger == null) {
                    childLogger = logger.createChildByName(childName);
                    loggerCache.put(childName, childLogger);
                    incSize();
                }
            }
            logger = childLogger;
            if (h == -1) {
                return childLogger;
            }
        }
    }
-

如果从 loggerCache 中能取到就直接获取，如果不能就会去创建

-]]> - - Java - - - Java - - - - 聊一下 Java 的日志系列三 - /2024/01/21/%E8%81%8A%E4%B8%80%E4%B8%8B-Java-%E7%9A%84%E6%97%A5%E5%BF%97%E7%B3%BB%E5%88%97%E4%B8%89/ - 上周因为一些事情没有更新在这里，是因为新电脑还没到，手头没有把移动硬盘里的 time machine 恢复出来的机器，所以单独更了一篇在新建的一个 cloudflare page 服务上，总体体验还可以，就是有个小点后面可以讲一下，继续完善下 Java 的这个日志，或者说主要讲的是 logback
前面讲了logback 的初始化逻辑，后面就是我最开始来看这个的逻辑，日志的滚动策略的触发逻辑
我们常规的记录日志的方式比如

-
logger.info("log some thing and biz info: {}",biz);
-

这里就调用了
ch.qos.logback.classic.Logger#info(java.lang.String, java.lang.Object)

-
public void info(String format, Object arg) {
    filterAndLog_1(FQCN, null, Level.INFO, format, arg, null);
}
-

这里的 FQCN 就是这个类的全限定名

-
public static final String FQCN = ch.qos.logback.classic.Logger.class.getName();
-

这个具体的 filterAndLog_1 方法还是在同一个 Logger 类里的
ch.qos.logback.classic.Logger#filterAndLog_1

-
private void filterAndLog_1(final String localFQCN, final Marker marker, final Level level, final String msg, final Object param, final Throwable t) {

    final FilterReply decision = loggerContext.getTurboFilterChainDecision_1(marker, this, level, msg, param, t);

    if (decision == FilterReply.NEUTRAL) {
        if (effectiveLevelInt > level.levelInt) {
            return;
        }
    } else if (decision == FilterReply.DENY) {
        return;
    }

    buildLoggingEventAndAppend(localFQCN, marker, level, msg, new Object[] { param }, t);
}
-

这里面先是走过滤器逻辑，如果是拒绝的，那就不往下执行，也就不执行下面的写日志逻辑了，如果是中性的，那就判断日志级别是否符合，如果直接是拒绝就 return 了，如果是 ACCEPT 就往下执行了

-
public enum FilterReply {
    DENY, NEUTRAL, ACCEPT;
}
-

然后继续调用同样的类的方法
ch.qos.logback.classic.Logger#buildLoggingEventAndAppend

-
private void buildLoggingEventAndAppend(final String localFQCN, final Marker marker, final Level level, final String msg, final Object[] params,
                final Throwable t) {
    LoggingEvent le = new LoggingEvent(localFQCN, this, level, msg, t, params);
    le.setMarker(marker);
    callAppenders(le);
}
-

先把日志包装成 LoggingEvent ，然后调用
ch.qos.logback.classic.Logger#callAppenders

-
public void callAppenders(ILoggingEvent event) {
    int writes = 0;
    for (Logger l = this; l != null; l = l.parent) {
        writes += l.appendLoopOnAppenders(event);
        if (!l.additive) {
            break;
        }
    }
    // No appenders in hierarchy
    if (writes == 0) {
        loggerContext.noAppenderDefinedWarning(this);
    }
}
-

这里会按 Logger 调用 appendLoopOnAppenders

-
private int appendLoopOnAppenders(ILoggingEvent event) {
    if (aai != null) {
        return aai.appendLoopOnAppenders(event);
    } else {
        return 0;
    }
-

继续调用事件的
ch.qos.logback.core.spi.AppenderAttachableImpl#appendLoopOnAppenders

-
public int appendLoopOnAppenders(E e) {
    int size = 0;
    final Appender<E>[] appenderArray = appenderList.asTypedArray();
    final int len = appenderArray.length;
    for (int i = 0; i < len; i++) {
        appenderArray[i].doAppend(e);
        size++;
    }
    return size;
}
-

因为 Logger 里有关联 appender，就具体调用关联的 appender 来添加日志
然后就接着调用
ch.qos.logback.core.UnsynchronizedAppenderBase#doAppend 方法

-
public void doAppend(E eventObject) {
        // WARNING: The guard check MUST be the first statement in the
        // doAppend() method.

        // prevent re-entry.
        if (Boolean.TRUE.equals(guard.get())) {
            return;
        }

        try {
            guard.set(Boolean.TRUE);

            if (!this.started) {
                if (statusRepeatCount++ < ALLOWED_REPEATS) {
                    addStatus(new WarnStatus("Attempted to append to non started appender [" + name + "].", this));
                }
                return;
            }

            if (getFilterChainDecision(eventObject) == FilterReply.DENY) {
                return;
            }

            // ok, we now invoke derived class' implementation of append
            this.append(eventObject);

        } catch (Exception e) {
            if (exceptionCount++ < ALLOWED_REPEATS) {
                addError("Appender [" + name + "] failed to append.", e);
            }
        } finally {
            guard.set(Boolean.FALSE);
        }
    }
-

这里先判断了 guard 的状态，guard 是个 ThreadLocal，是为了拦截异常的无限循环调用，这里有些疑惑的，看了一圈可能相关的是前面的 Logger 会往父级查找，然后如果不同层级的 Logger 关联了相同的 appender 的话，或者这个 doAppend 又被其他 appender 调用了，就可能会出现循环调用，然后会在开始实际的 append的之前先设置 guard 状态，
然后再执行 append，这里会走到
ch.qos.logback.core.OutputStreamAppender#append

-
@Override
protected void append(E eventObject) {
    if (!isStarted()) {
        return;
    }

    subAppend(eventObject);
}
-

忘了补充下，我们这里使用的是
ch.qos.logback.core.rolling.RollingFileAppender
接下去就是调用的 RollingFileAppender 的 subAppend 方法

-
@Override
protected void subAppend(E event) {
    // The roll-over check must precede actual writing. This is the
    // only correct behavior for time driven triggers.

    // We need to synchronize on triggeringPolicy so that only one rollover
    // occurs at a time
    synchronized (triggeringPolicy) {
        if (triggeringPolicy.isTriggeringEvent(currentlyActiveFile, event)) {
            rollover();
        }
    }

    super.subAppend(event);
}
-

这里就会先判断是否触发事件，
而这里就是主要的逻辑，看是否需要走 rollover，也就是具体的滚动逻辑

-
@Override
    public boolean isTriggeringEvent(File activeFile, final E event) {

        long time = getCurrentTime();

        // first check for roll-over based on time
        if (time >= nextCheck) {
            Date dateInElapsedPeriod = dateInCurrentPeriod;
            elapsedPeriodsFileName = tbrp.fileNamePatternWithoutCompSuffix.convertMultipleArguments(dateInElapsedPeriod, currentPeriodsCounter);
            currentPeriodsCounter = 0;
            setDateInCurrentPeriod(time);
            computeNextCheck();
            return true;
        }

        // next check for roll-over based on size
        if (invocationGate.isTooSoon(time)) {
            return false;
        }

        if (activeFile == null) {
            addWarn("activeFile == null");
            return false;
        }
        if (maxFileSize == null) {
            addWarn("maxFileSize = null");
            return false;
        }
        if (activeFile.length() >= maxFileSize.getSize()) {

            elapsedPeriodsFileName = tbrp.fileNamePatternWithoutCompSuffix.convertMultipleArguments(dateInCurrentPeriod, currentPeriodsCounter);
            currentPeriodsCounter++;
            return true;
        }

        return false;
    }
-

这里主要就用到了 nextCheck 判断，如果通过判断就可以执行滚动了，然后就是后面的判断，是否太快了，也就是 isTooSoon 然后再看当前的活跃日志以及最大文件大小是否设置，然后如果当前的活跃日志的大小超过了配置也会触发滚动

-]]> - - Java - - - Java - - 聊聊 RocketMQ 的 Broker 源码 /2020/07/19/%E8%81%8A%E8%81%8A-RocketMQ-%E7%9A%84-Broker-%E6%BA%90%E7%A0%81/ @@ -6070,28 +6170,56 @@ user3: - 聊聊 Java 自带的那些*逆天*工具 - /2020/08/02/%E8%81%8A%E8%81%8A-Java-%E8%87%AA%E5%B8%A6%E7%9A%84%E9%82%A3%E4%BA%9B%E9%80%86%E5%A4%A9%E5%B7%A5%E5%85%B7/ - 原谅我的标题党，其实这些工具的确很厉害，之前其实介绍过一点相关的，是从我一次问题排查的过程中用到的，但是最近又有碰到一次排查问题，发现其实用 idea 直接 dump thread 是不现实的，毕竟服务器环境的没法这么操作，那就得用 Java 的那些工具了

-

jstack & jps

譬如 jstack，这个命令其实不能更简单了
看看 help 信息

用-l参数可以打出锁的额外信息，然后后面的 pid 就是进程 id 咯，机智的小伙伴会问了（就你这个小白才问这么蠢的问题🤦‍♂️），怎么看 Java 应用的进程呢
那就是 jps 了，命令也很简单，一般直接用 jps命令就好了，不过也可以 help 看一下

稍微解释下，-q是只显示进程 id，-m是输出给main 方法的参数，比如我在配置中加给参数

然后用 jps -m查看

-v加上小 v 的话就是打印 jvm 参数

还是有点东西，然后就继续介绍 jstack 了，然后我们看看 jstack 出来是啥，为了加点内容我加了个死锁

-
public static void main(String[] args) throws InterruptedException {
        SpringApplication.run(ThreadDumpDemoApplication.class, args);
        ReentrantLock lock1 = new ReentrantLock();
        ReentrantLock lock2 = new ReentrantLock();
        Thread t1 = new Thread() {
            @Override
            public void run() {
                try {
                    lock1.lock();
                    TimeUnit.SECONDS.sleep(1);
                    lock2.lock();
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            }
        };
        Thread t2 = new Thread() {
            @Override
            public void run() {
                try {
                    lock2.lock();
                    TimeUnit.SECONDS.sleep(1);
                    lock1.lock();
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            }
        };
        t1.setName("mythread1");
        t2.setName("mythread2");
        t1.start();
        t2.start();
        Thread.sleep(10000);
    }
-

然后看看出来时怎么样的

-
2020-08-02 21:50:32
Full thread dump Java HotSpot(TM) 64-Bit Server VM (25.201-b09 mixed mode):

"DestroyJavaVM" #147 prio=5 os_prio=31 tid=0x00007fc9dd807000 nid=0x2603 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"mythread2" #140 prio=5 os_prio=31 tid=0x00007fc9dd877000 nid=0x9903 waiting on condition [0x0000700006fb9000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$2.run(ThreadDumpDemoApplication.java:34)

   Locked ownable synchronizers:
        - <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)

"mythread1" #139 prio=5 os_prio=31 tid=0x00007fc9de873800 nid=0x9a03 waiting on condition [0x0000700006eb6000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$1.run(ThreadDumpDemoApplication.java:22)

   Locked ownable synchronizers:
        - <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)

"http-nio-8080-Acceptor" #137 daemon prio=5 os_prio=31 tid=0x00007fc9de1ac000 nid=0x9b03 runnable [0x0000700006db3000]
   java.lang.Thread.State: RUNNABLE
        at sun.nio.ch.ServerSocketChannelImpl.accept0(Native Method)
        at sun.nio.ch.ServerSocketChannelImpl.accept(ServerSocketChannelImpl.java:422)
        at sun.nio.ch.ServerSocketChannelImpl.accept(ServerSocketChannelImpl.java:250)
        - locked <0x000000076f1e4820> (a java.lang.Object)
        at org.apache.tomcat.util.net.NioEndpoint.serverSocketAccept(NioEndpoint.java:469)
        at org.apache.tomcat.util.net.NioEndpoint.serverSocketAccept(NioEndpoint.java:71)
        at org.apache.tomcat.util.net.Acceptor.run(Acceptor.java:95)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-ClientPoller" #136 daemon prio=5 os_prio=31 tid=0x00007fc9dd876800 nid=0x6503 runnable [0x0000700006cb0000]
   java.lang.Thread.State: RUNNABLE
        at sun.nio.ch.KQueueArrayWrapper.kevent0(Native Method)
        at sun.nio.ch.KQueueArrayWrapper.poll(KQueueArrayWrapper.java:198)
        at sun.nio.ch.KQueueSelectorImpl.doSelect(KQueueSelectorImpl.java:117)
        at sun.nio.ch.SelectorImpl.lockAndDoSelect(SelectorImpl.java:86)
        - locked <0x000000076f2978c8> (a sun.nio.ch.Util$3)
        - locked <0x000000076f2978b8> (a java.util.Collections$UnmodifiableSet)
        - locked <0x000000076f297798> (a sun.nio.ch.KQueueSelectorImpl)
        at sun.nio.ch.SelectorImpl.select(SelectorImpl.java:97)
        at org.apache.tomcat.util.net.NioEndpoint$Poller.run(NioEndpoint.java:709)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-10" #135 daemon prio=5 os_prio=31 tid=0x00007fc9de1af000 nid=0x9d03 waiting on condition [0x0000700006bad000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-9" #134 daemon prio=5 os_prio=31 tid=0x00007fc9de1ab800 nid=0x6403 waiting on condition [0x0000700006aaa000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-8" #133 daemon prio=5 os_prio=31 tid=0x00007fc9de873000 nid=0x9f03 waiting on condition [0x00007000069a7000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-7" #132 daemon prio=5 os_prio=31 tid=0x00007fc9df0a1800 nid=0xa103 waiting on condition [0x00007000068a4000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-6" #131 daemon prio=5 os_prio=31 tid=0x00007fc9df242800 nid=0x6103 waiting on condition [0x00007000067a1000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-5" #130 daemon prio=5 os_prio=31 tid=0x00007fc9de872000 nid=0x5f03 waiting on condition [0x000070000669e000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-4" #129 daemon prio=5 os_prio=31 tid=0x00007fc9de1a6000 nid=0x5e03 waiting on condition [0x000070000659b000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-3" #128 daemon prio=5 os_prio=31 tid=0x00007fc9de871800 nid=0x5c03 waiting on condition [0x0000700006498000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-2" #127 daemon prio=5 os_prio=31 tid=0x00007fc9dead9000 nid=0x5b03 waiting on condition [0x0000700006395000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-exec-1" #126 daemon prio=5 os_prio=31 tid=0x00007fc9ddb00000 nid=0x5a03 waiting on condition [0x0000700006292000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f26aa00> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.LinkedBlockingQueue.take(LinkedBlockingQueue.java:442)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:107)
        at org.apache.tomcat.util.threads.TaskQueue.take(TaskQueue.java:33)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"http-nio-8080-BlockPoller" #125 daemon prio=5 os_prio=31 tid=0x00007fc9df242000 nid=0xa503 runnable [0x000070000618f000]
   java.lang.Thread.State: RUNNABLE
        at sun.nio.ch.KQueueArrayWrapper.kevent0(Native Method)
        at sun.nio.ch.KQueueArrayWrapper.poll(KQueueArrayWrapper.java:198)
        at sun.nio.ch.KQueueSelectorImpl.doSelect(KQueueSelectorImpl.java:117)
        at sun.nio.ch.SelectorImpl.lockAndDoSelect(SelectorImpl.java:86)
        - locked <0x000000076f1eea30> (a sun.nio.ch.Util$3)
        - locked <0x000000076f1ee198> (a java.util.Collections$UnmodifiableSet)
        - locked <0x000000076f1ee010> (a sun.nio.ch.KQueueSelectorImpl)
        at sun.nio.ch.SelectorImpl.select(SelectorImpl.java:97)
        at org.apache.tomcat.util.net.NioBlockingSelector$BlockPoller.run(NioBlockingSelector.java:313)

   Locked ownable synchronizers:
        - None

"container-0" #124 prio=5 os_prio=31 tid=0x00007fc9df06a000 nid=0x5803 waiting on condition [0x000070000608c000]
   java.lang.Thread.State: TIMED_WAITING (sleeping)
        at java.lang.Thread.sleep(Native Method)
        at org.apache.catalina.core.StandardServer.await(StandardServer.java:570)
        at org.springframework.boot.web.embedded.tomcat.TomcatWebServer$1.run(TomcatWebServer.java:197)

   Locked ownable synchronizers:
        - None

"Catalina-utility-2" #123 prio=1 os_prio=31 tid=0x00007fc9de886000 nid=0xa80f waiting on condition [0x0000700005f89000]
   java.lang.Thread.State: WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076c88ab58> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2039)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1088)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"Catalina-utility-1" #122 prio=1 os_prio=31 tid=0x00007fc9de884000 nid=0x5667 waiting on condition [0x0000700005e86000]
   java.lang.Thread.State: TIMED_WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076c88ab58> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:215)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:2078)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1093)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at org.apache.tomcat.util.threads.TaskThread$WrappingRunnable.run(TaskThread.java:61)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"RMI Scheduler(0)" #15 daemon prio=5 os_prio=31 tid=0x00007fc9de9ee000 nid=0x5503 waiting on condition [0x0000700005d83000]
   java.lang.Thread.State: TIMED_WAITING (parking)
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x00000006c0015410> (a java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject)
        at java.util.concurrent.locks.LockSupport.parkNanos(LockSupport.java:215)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.awaitNanos(AbstractQueuedSynchronizer.java:2078)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:1093)
        at java.util.concurrent.ScheduledThreadPoolExecutor$DelayedWorkQueue.take(ScheduledThreadPoolExecutor.java:809)
        at java.util.concurrent.ThreadPoolExecutor.getTask(ThreadPoolExecutor.java:1074)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1134)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"Attach Listener" #13 daemon prio=9 os_prio=31 tid=0x00007fc9df149800 nid=0x3c07 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"RMI TCP Accept-0" #11 daemon prio=5 os_prio=31 tid=0x00007fc9df100000 nid=0x4003 runnable [0x0000700005977000]
   java.lang.Thread.State: RUNNABLE
        at java.net.PlainSocketImpl.socketAccept(Native Method)
        at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:409)
        at java.net.ServerSocket.implAccept(ServerSocket.java:545)
        at java.net.ServerSocket.accept(ServerSocket.java:513)
        at sun.management.jmxremote.LocalRMIServerSocketFactory$1.accept(LocalRMIServerSocketFactory.java:52)
        at sun.rmi.transport.tcp.TCPTransport$AcceptLoop.executeAcceptLoop(TCPTransport.java:405)
        at sun.rmi.transport.tcp.TCPTransport$AcceptLoop.run(TCPTransport.java:377)
        at java.lang.Thread.run(Thread.java:748)

   Locked ownable synchronizers:
        - None

"Service Thread" #9 daemon prio=9 os_prio=31 tid=0x00007fc9df0ce800 nid=0x4103 runnable [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"C1 CompilerThread2" #8 daemon prio=9 os_prio=31 tid=0x00007fc9df0ce000 nid=0x4203 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"C2 CompilerThread1" #7 daemon prio=9 os_prio=31 tid=0x00007fc9de0a3800 nid=0x3503 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"C2 CompilerThread0" #6 daemon prio=9 os_prio=31 tid=0x00007fc9de89b000 nid=0x3403 waiting on condition [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"Monitor Ctrl-Break" #5 daemon prio=5 os_prio=31 tid=0x00007fc9df0ca000 nid=0x3303 runnable [0x0000700005468000]
   java.lang.Thread.State: RUNNABLE
        at java.net.SocketInputStream.socketRead0(Native Method)
        at java.net.SocketInputStream.socketRead(SocketInputStream.java:116)
        at java.net.SocketInputStream.read(SocketInputStream.java:171)
        at java.net.SocketInputStream.read(SocketInputStream.java:141)
        at sun.nio.cs.StreamDecoder.readBytes(StreamDecoder.java:284)
        at sun.nio.cs.StreamDecoder.implRead(StreamDecoder.java:326)
        at sun.nio.cs.StreamDecoder.read(StreamDecoder.java:178)
        - locked <0x00000006c001b760> (a java.io.InputStreamReader)
        at java.io.InputStreamReader.read(InputStreamReader.java:184)
        at java.io.BufferedReader.fill(BufferedReader.java:161)
        at java.io.BufferedReader.readLine(BufferedReader.java:324)
        - locked <0x00000006c001b760> (a java.io.InputStreamReader)
        at java.io.BufferedReader.readLine(BufferedReader.java:389)
        at com.intellij.rt.execution.application.AppMainV2$1.run(AppMainV2.java:64)

   Locked ownable synchronizers:
        - None

"Signal Dispatcher" #4 daemon prio=9 os_prio=31 tid=0x00007fc9de824000 nid=0x4503 runnable [0x0000000000000000]
   java.lang.Thread.State: RUNNABLE

   Locked ownable synchronizers:
        - None

"Finalizer" #3 daemon prio=8 os_prio=31 tid=0x00007fc9dd811800 nid=0x4f03 in Object.wait() [0x0000700005262000]
   java.lang.Thread.State: WAITING (on object monitor)
        at java.lang.Object.wait(Native Method)
        - waiting on <0x00000006c0008348> (a java.lang.ref.ReferenceQueue$Lock)
        at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:144)
        - locked <0x00000006c0008348> (a java.lang.ref.ReferenceQueue$Lock)
        at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:165)
        at java.lang.ref.Finalizer$FinalizerThread.run(Finalizer.java:216)

   Locked ownable synchronizers:
        - None

"Reference Handler" #2 daemon prio=10 os_prio=31 tid=0x00007fc9de02a000 nid=0x5003 in Object.wait() [0x000070000515f000]
   java.lang.Thread.State: WAITING (on object monitor)
        at java.lang.Object.wait(Native Method)
        - waiting on <0x00000006c001b940> (a java.lang.ref.Reference$Lock)
        at java.lang.Object.wait(Object.java:502)
        at java.lang.ref.Reference.tryHandlePending(Reference.java:191)
        - locked <0x00000006c001b940> (a java.lang.ref.Reference$Lock)
        at java.lang.ref.Reference$ReferenceHandler.run(Reference.java:153)

   Locked ownable synchronizers:
        - None

"VM Thread" os_prio=31 tid=0x00007fc9df00b800 nid=0x2c03 runnable 

"GC task thread#0 (ParallelGC)" os_prio=31 tid=0x00007fc9de805000 nid=0x1e07 runnable 

"GC task thread#1 (ParallelGC)" os_prio=31 tid=0x00007fc9de003800 nid=0x2a03 runnable 

"GC task thread#2 (ParallelGC)" os_prio=31 tid=0x00007fc9df002000 nid=0x5403 runnable 

"GC task thread#3 (ParallelGC)" os_prio=31 tid=0x00007fc9df002800 nid=0x5203 runnable 

"VM Periodic Task Thread" os_prio=31 tid=0x00007fc9df11a800 nid=0x3a03 waiting on condition 

JNI global references: 1087


Found one Java-level deadlock:
=============================
"mythread2":
  waiting for ownable synchronizer 0x000000076f5d4330, (a java.util.concurrent.locks.ReentrantLock$NonfairSync),
  which is held by "mythread1"
"mythread1":
  waiting for ownable synchronizer 0x000000076f5d4360, (a java.util.concurrent.locks.ReentrantLock$NonfairSync),
  which is held by "mythread2"

Java stack information for the threads listed above:
===================================================
"mythread2":
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4330> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$2.run(ThreadDumpDemoApplication.java:34)
"mythread1":
        at sun.misc.Unsafe.park(Native Method)
        - parking to wait for  <0x000000076f5d4360> (a java.util.concurrent.locks.ReentrantLock$NonfairSync)
        at java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireQueued(AbstractQueuedSynchronizer.java:870)
        at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquire(AbstractQueuedSynchronizer.java:1199)
        at java.util.concurrent.locks.ReentrantLock$NonfairSync.lock(ReentrantLock.java:209)
        at java.util.concurrent.locks.ReentrantLock.lock(ReentrantLock.java:285)
        at com.nicksxs.thread_dump_demo.ThreadDumpDemoApplication$1.run(ThreadDumpDemoApplication.java:22)

Found 1 deadlock.
-

前面的信息其实上次就看过了，后面就可以发现有个死锁了，

上面比较长，把主要的截出来，就是这边的，这点就很强大了。

-

jmap

惯例还是看一下帮助信息

这个相对命令比较多，不过因为现在 dump 下来我们可能会用文件模式，然后将文件下载下来使用 mat 进行分析，所以可以使用
jmap -dump:live,format=b,file=heap.bin <pid>
命令照着上面看的就是打印活着的对象，然后以二进制格式，文件名叫 heap.bin 然后最后就是进程 id，打印出来以后可以用 mat 打开

这样就可以很清晰的看到应用里的各种信息，jmap 直接在命令中还可以看很多信息，比如使用jmap -histo <pid>打印对象的实例数和对象占用的内存

jmap -finalizerinfo <pid> 打印正在等候回收的对象

-

小tips

对于一些应用内存已经占满了，jstack 和 jmap 可能会连不上的情况，可以使用-F参数强制打印线程或者 dump 文件，但是要注意这两者使用的用户必须与 java 进程启动用户一致，并且使用的 jdk 也要一致

+ 聊聊 Sharding-Jdbc 分库分表下的分页方案 + /2022/01/09/%E8%81%8A%E8%81%8A-Sharding-Jdbc-%E5%88%86%E5%BA%93%E5%88%86%E8%A1%A8%E4%B8%8B%E7%9A%84%E5%88%86%E9%A1%B5%E6%96%B9%E6%A1%88/ + 前面在聊 Sharding-Jdbc 的时候看到了一篇文章，关于一个分页的查询，一直比较直接的想法就是分库分表下的分页是非常不合理的，一般我们的实操方案都是分表加上 ES 搜索做分页，或者通过合表读写分离的方案，因为对于 sharding-jdbc 如果没有带分表键，查询基本都是只能在所有分表都执行一遍，然后再加上分页，基本上是分页越大后续的查询越耗资源，但是仔细的去想这个细节还是这次，就简单说说
首先就是我的分表结构

+
CREATE TABLE `student_time_0` (
  `id` int(11) unsigned NOT NULL AUTO_INCREMENT,
  `user_id` int(11) NOT NULL,
  `name` varchar(200) COLLATE utf8_bin DEFAULT NULL,
  `age` tinyint(3) unsigned DEFAULT NULL,
  `create_time` bigint(20) DEFAULT NULL,
  PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=674 DEFAULT CHARSET=utf8 COLLATE=utf8_bin;
+

有这样的三个表，student_time_0, student_time_1, student_time_2, 以 user_id 作为分表键，根据表数量取模作为分表依据
这里先构造点数据，

+
insert into student_time (`name`, `user_id`, `age`, `create_time`) values (?, ?, ?, ?)
+

主要是为了保证 create_time 唯一比较好说明问题，

+
int i = 0;
try (
        Connection conn = dataSource.getConnection();
        PreparedStatement ps = conn.prepareStatement(insertSql)) {
    do {
        ps.setString(1, localName + new Random().nextInt(100));
        ps.setLong(2, 10086L + (new Random().nextInt(100)));
        ps.setInt(3, 18);
        ps.setLong(4, new Date().getTime());


        int result = ps.executeUpdate();
        LOGGER.info("current execute result: {}", result);
        Thread.sleep(new Random().nextInt(100));
        i++;
    } while (i <= 2000);
+

三个表的数据分别是 673，678，650，说明符合预期了，各个表数据不一样，接下来比如我们想要做一个这样的分页查询

+
select * from student_time ORDER BY create_time ASC limit 1000, 5;
+

student_time 对于我们使用的 sharding-jdbc 来说当然是逻辑表，首先从一无所知去想这个查询如果我们自己来处理应该是怎么做，
首先是不是可以每个表都从 333 开始取 5 条数据，类似于下面的查询，然后进行 15 条的合并重排序获取前面的 5 条

+
select * from student_time_0 ORDER BY create_time ASC limit 333, 5;
select * from student_time_1 ORDER BY create_time ASC limit 333, 5;
select * from student_time_2 ORDER BY create_time ASC limit 333, 5;
+

忽略前面 limit 差的 1，这个结果除非三个表的分布是绝对的均匀，否则结果肯定会出现一定的偏差，以为每个表的 333 这个位置对于其他表来说都不一定是一样的，这样对于最后整体的结果，就会出现偏差
因为一直在纠结怎么让这个更直观的表现出来，所以尝试画了个图

黑色的框代表我从每个表里按排序从 334 到 338 的 5 条数据， 他们在每个表里都是代表了各自正确的排序值，但是对于我们想要的其实是合表后的 1001，1005 这五条，然后我们假设总的排序值位于前 1000 的分布是第 0 个表是 320 条，第 1 个表是 340 条，第 2 个表是 340 条，那么可以明显地看出来我这么查的结果简单合并肯定是不对的。
那么 sharding-jdbc 是如何保证这个结果的呢，其实就是我在每个表里都查分页偏移量和分页大小那么多的数据，在我这个例子里就是对于 0，1，2 三个分表每个都查 1005 条数据，即使我的数据不平衡到最极端的情况，前 1005 条数据都出在某个分表中，也可以正确获得最后的结果，但是明显的问题就是大分页，数据较多，就会导致非常大的问题，即使如 sharding-jdbc 对于合并排序的优化做得比较好，也还是需要传输那么大量的数据，并且查询也耗时，那么有没有解决方案呢，应该说有两个，或者说主要是想讲后者
第一个办法是像这种查询，如果业务上不需要进行跳页，而是只给下一页，那么我们就能把前一次的最大偏移量的 create_time 记录下来，下一页就可以拿着这个偏移量进行查询，这个比较简单易懂，就不多说了
第二个办法是看的58 沈剑的一篇文章，尝试理解讲述一下，
这个办法的第一步跟前面那个错误的方法或者说不准确的方法一样，先是将分页偏移量平均后在三个表里进行查询

+
t0
334 10158 nick95  18  1641548941767
335 10098 nick11  18  1641548941879
336 10167 nick51  18  1641548942089
337 10167 nick3 18  1641548942119
338 10170 nick57  18  1641548942169


t1
334 10105 nick98  18  1641548939071   最小
335 10174 nick94  18  1641548939377
336 10129 nick85  18  1641548939442
337 10141 nick84  18  1641548939480
338 10096 nick74  18  1641548939668

t2
334 10184 nick11  18  1641548945075
335 10109 nick93  18  1641548945382
336 10181 nick41  18  1641548945583
337 10130 nick80  18  1641548945993
338 10184 nick19  18  1641548946294  最大
+

然后要做什么呢，其实目标比较明白，因为前面那种方法其实就是我知道了前一页的偏移量，所以可以直接当做条件来进行查询，那这里我也想着拿到这个条件，所以我将第一遍查出来的最小的 create_time 和最大的 create_time 找出来，然后再去三个表里查询，其实主要是最小值，因为我拿着最小值去查以后我就能知道这个最小值在每个表里处在什么位置，

+
t0
322 10161 nick81  18  1641548939284
323 10113 nick16  18  1641548939393
324 10110 nick56  18  1641548939577
325 10116 nick69  18  1641548939588
326 10173 nick51  18  1641548939646

t1
334 10105 nick98  18  1641548939071
335 10174 nick94  18  1641548939377
336 10129 nick85  18  1641548939442
337 10141 nick84  18  1641548939480
338 10096 nick74  18  1641548939668

t2
297 10136 nick28  18  1641548939161
298 10142 nick68  18  1641548939177
299 10124 nick41  18  1641548939237
300 10148 nick87  18  1641548939510
301 10169 nick23  18  1641548939715
+

我只贴了前五条数据，为了方便知道偏移量，每个分表都使用了自增主键，我们可以看到前一次查询的最小值分别在其他两个表里的位置分别是 322-1 和 297-1，那么对于总体来说这个时间应该是在 322 - 1 + 333 + 297 - 1 = 951，那这样子我只要对后面的数据最多每个表查 1000 - 951 + 5 = 54 条数据再进行合并排序就可以获得最终正确的结果。
这个就是传说中的二次查询法。

]]> Java - Thread dump - 问题排查 - 工具 Java - JPS - JStack - JMap + Sharding-Jdbc + + + + 聊聊 Sharding-Jdbc 的简单原理初篇 + /2021/12/26/%E8%81%8A%E8%81%8A-Sharding-Jdbc-%E7%9A%84%E7%AE%80%E5%8D%95%E5%8E%9F%E7%90%86%E5%88%9D%E7%AF%87/ + 在上一篇 sharding-jdbc 的介绍中其实碰到过一个问题，这里也引出了一个比较有意思的话题
就是我在执行 query 的时候犯过一个比较难发现的错误，

+
ResultSet resultSet = ps.executeQuery(sql);
+

实际上应该是

+
ResultSet resultSet = ps.executeQuery();
+

而这里的差别就是，是否传 sql 这个参数，首先我们要知道这个 ps 是什么，它也是个接口java.sql.PreparedStatement,而真正的实现类是org.apache.shardingsphere.driver.jdbc.core.statement.ShardingSpherePreparedStatement,我们来看下继承关系

这里可以看到继承关系里有org.apache.shardingsphere.driver.jdbc.unsupported.AbstractUnsupportedOperationPreparedStatement
那么在我上面的写错的代码里

+
@Override
public final ResultSet executeQuery(final String sql) throws SQLException {
    throw new SQLFeatureNotSupportedException("executeQuery with SQL for PreparedStatement");
}
+

这个报错一开始让我有点懵，后来点进去了发现是这么个异常，但是我其实一开始是用的更新语句，以为更新不支持，因为平时使用没有深究过，以为是不是需要使用 Mybatis 才可以执行更新，但是理论上也不应该，再往上看原来这些异常是由 sharding-jdbc 包装的，也就是在上面说的AbstractUnsupportedOperationPreparedStatement，这其实也是一种设计思想，本身 jdbc 提供了一系列接口，由各家去支持，包括 mysql，sql server，oracle 等，而正因为这个设计，所以 sharding-jdbc 也可以在此基础上进行设计，我们可以总体地看下 sharding-jdbc 的实现基础

看了前面ShardingSpherePreparedStatement的继承关系，应该也能猜到这里的几个类都是实现了 jdbc 的基础接口，

在前一篇的 demo 中的

+
Connection conn = dataSource.getConnection();
+

其实就获得了org.apache.shardingsphere.driver.jdbc.core.connection.ShardingSphereConnection#ShardingSphereConnection
然后获得java.sql.PreparedStatement

+
PreparedStatement ps = conn.prepareStatement(sql)
+

就是获取了org.apache.shardingsphere.driver.jdbc.core.statement.ShardingSpherePreparedStatement
然后就是执行

+
ResultSet resultSet = ps.executeQuery();
+

然后获得结果
org.apache.shardingsphere.driver.jdbc.core.resultset.ShardingSphereResultSet

+

其实像 mybatis 也是基于这样去实现的

+]]> + + Java + + + Java + Sharding-Jdbc @@ -6149,47 +6277,16 @@ user3: - 聊聊 Sharding-Jdbc 的简单原理初篇 - /2021/12/26/%E8%81%8A%E8%81%8A-Sharding-Jdbc-%E7%9A%84%E7%AE%80%E5%8D%95%E5%8E%9F%E7%90%86%E5%88%9D%E7%AF%87/ - 在上一篇 sharding-jdbc 的介绍中其实碰到过一个问题，这里也引出了一个比较有意思的话题
就是我在执行 query 的时候犯过一个比较难发现的错误，

-
ResultSet resultSet = ps.executeQuery(sql);
-

实际上应该是

-
ResultSet resultSet = ps.executeQuery();
-

而这里的差别就是，是否传 sql 这个参数，首先我们要知道这个 ps 是什么，它也是个接口java.sql.PreparedStatement,而真正的实现类是org.apache.shardingsphere.driver.jdbc.core.statement.ShardingSpherePreparedStatement,我们来看下继承关系

这里可以看到继承关系里有org.apache.shardingsphere.driver.jdbc.unsupported.AbstractUnsupportedOperationPreparedStatement
那么在我上面的写错的代码里

-
@Override
public final ResultSet executeQuery(final String sql) throws SQLException {
    throw new SQLFeatureNotSupportedException("executeQuery with SQL for PreparedStatement");
}
-

这个报错一开始让我有点懵，后来点进去了发现是这么个异常，但是我其实一开始是用的更新语句，以为更新不支持，因为平时使用没有深究过，以为是不是需要使用 Mybatis 才可以执行更新，但是理论上也不应该，再往上看原来这些异常是由 sharding-jdbc 包装的，也就是在上面说的AbstractUnsupportedOperationPreparedStatement，这其实也是一种设计思想，本身 jdbc 提供了一系列接口，由各家去支持，包括 mysql，sql server，oracle 等，而正因为这个设计，所以 sharding-jdbc 也可以在此基础上进行设计，我们可以总体地看下 sharding-jdbc 的实现基础

看了前面ShardingSpherePreparedStatement的继承关系，应该也能猜到这里的几个类都是实现了 jdbc 的基础接口，

在前一篇的 demo 中的

-
Connection conn = dataSource.getConnection();
-

其实就获得了org.apache.shardingsphere.driver.jdbc.core.connection.ShardingSphereConnection#ShardingSphereConnection
然后获得java.sql.PreparedStatement

-
PreparedStatement ps = conn.prepareStatement(sql)
-

就是获取了org.apache.shardingsphere.driver.jdbc.core.statement.ShardingSpherePreparedStatement
然后就是执行

-
ResultSet resultSet = ps.executeQuery();
-

然后获得结果
org.apache.shardingsphere.driver.jdbc.core.resultset.ShardingSphereResultSet

-

其实像 mybatis 也是基于这样去实现的

-]]> - - Java - - - Java - Sharding-Jdbc - - - - 聊聊 mysql 的 MVCC 续续篇之锁分析 - /2020/05/10/%E8%81%8A%E8%81%8A-mysql-%E7%9A%84-MVCC-%E7%BB%AD%E7%BB%AD%E7%AF%87%E4%B9%8B%E5%8A%A0%E9%94%81%E5%88%86%E6%9E%90/ - 看完前面两篇水文之后，感觉不得不来分析下 mysql 的锁了，其实前面说到幻读的时候是有个前提没提到的，比如一个select * from table1 where id = 1这种查询语句其实是不会加传说中的锁的，当然这里是指在 RR 或者 RC 隔离级别下，
看一段 mysql官方文档

+ 聊聊 mysql 的 MVCC 续篇 + /2020/05/02/%E8%81%8A%E8%81%8A-mysql-%E7%9A%84-MVCC-%E7%BB%AD%E7%AF%87/ + 上一篇聊了mysql 的 innodb 引擎基于 read view 实现的 mvcc 和事务隔离级别，可能有些细心的小伙伴会发现一些问题，第一个是在 RC 级别下的事务提交后的可见性，这里涉及到了三个参数，m_low_limit_id，m_up_limit_id，m_ids，之前看到知乎的一篇写的非常不错的文章，但是就在这一点上似乎有点疑惑，这里基于源码和注释来解释下这个问题

+
/**
Opens a read view where exactly the transactions serialized before this
point in time are seen in the view.
@param id		Creator transaction id */

void ReadView::prepare(trx_id_t id) {
  ut_ad(mutex_own(&trx_sys->mutex));

  m_creator_trx_id = id;

  m_low_limit_no = m_low_limit_id = m_up_limit_id = trx_sys->max_trx_id;
+

m_low_limit_id赋的值是trx_sys->max_trx_id，代表的是当前系统最小的未分配的事务 id，所以呢，举个例子，当前有三个活跃事务，事务 id 分别是 100，200，300，而 m_up_limit_id = 100, m_low_limit_id = 301，当事务 id 是 200 的提交之后，它的更新就是可以被 100 和 300 看到，而不是说 m_ids 里没了 200，并且 200 比 100 大就应该不可见了

+

幻读

还有一个问题是幻读的问题，这貌似也是个高频面试题，啥意思呢，或者说跟它最常拿来比较的脏读，脏读是指读到了别的事务未提交的数据，因为未提交，严格意义上来讲，不一定是会被最后落到库里，可能会回滚，也就是在 read uncommitted 级别下会出现的问题，但是幻读不太一样，幻读是指两次查询的结果数量不一样，比如我查了第一次是 select * from table1 where id < 10 for update,查出来了一条结果 id 是 5，然后再查一下发现出来了一条 id 是 5，一条 id 是 7，那是不是有点尴尬了，其实呢这个点我觉得脏读跟幻读也比较是从原理层面来命名，如果第一次接触的同学发觉有点不理解也比较正常，因为从逻辑上讲总之都是数据不符合预期，但是基于源码层面其实是不同的情况，幻读是在原先的 read view 无法完全解决的，怎么解决呢，简单的来说就是锁咯，我们知道innodb 是基于 record lock 行锁的，但是貌似没有办法解决这种问题，那么 innodb 就引入了 gap lock 间隙锁，比如上面说的情况下，id 小于 10 的情况下，是都应该锁住的，gap lock 其实是基于索引结构来锁的，因为索引树除了树形结构之外，还有一个next record 的指针，gap lock 也是基于这个来锁的
看一下 mysql 的文档

-

SELECT ... FROM is a consistent read, reading a snapshot of the database and setting no locks unless the transaction isolation level is set to SERIALIZABLE. For SERIALIZABLE level, the search sets shared next-key locks on the index records it encounters. However, only an index record lock is required for statements that lock rows using a unique index to search for a unique row.

+

SELECT … FOR UPDATE sets an exclusive next-key lock on every record the search encounters. However, only an index record lock is required for statements that lock rows using a unique index to search for a unique row.

-

纯粹的这种一致性读，实际读取的是快照，也就是基于 read view 的读取方式，除非当前隔离级别是SERIALIZABLE
但是对于以下几类

-
    -
  • select * from table where ? lock in share mode;
    • -
  • select * from table where ? for update;
    • -
  • insert into table values (...);
    • -
  • update table set ? where ?;
    • -
  • delete from table where ?;
    • -
-

除了第一条是 S 锁之外，其他都是 X 排他锁，这边在顺带下，S 锁表示共享锁， X 表示独占锁，同为 S 锁之间不冲突，S 与 X，X 与 S，X 与 X 之间都冲突，也就是加了前者，后者就加不上了
我们知道对于 RC 级别会出现幻读现象，对于 RR 级别不会出现，主要的区别是 RR 级别下对于以上的加锁读取都根据情况加上了 gap 锁，那么是不是 RR 级别下以上所有的都是要加 gap 锁呢，当然不是
举个例子，RR 事务隔离级别下，table1 有个主键id 字段
select * from table1 where id = 10 for update
这条语句要加 gap 锁吗？
答案是不需要，这里其实算是我看了这么久的一点自己的理解，啥时候要加 gap 锁，判断的条件是根据我查询的数据是否会因为不加 gap 锁而出现数量的不一致，我上面这条查询语句，在什么情况下会出现查询结果数量不一致呢，只要在这条记录被更新或者删除的时候，有没有可能我第一次查出来一条，第二次变成两条了呢，不可能，因为是主键索引。
再变更下这个题的条件，当 id 不是主键，但是是唯一索引，这样需要怎么加锁，注意问题是怎么加锁，不是需不需要加 gap 锁，这里呢就是稍微延伸一下，把聚簇索引（主键索引）和二级索引带一下，当 id 不是主键，说明是个二级索引，但是它是唯一索引，体会下，首先对于 id = 10这个二级索引肯定要加锁，要不要锁 gap 呢，不用，因为是唯一索引，id = 10 只可能有这一条记录，然后呢，这样是不是就好了，还不行，因为啥，因为它是二级索引，对应的主键索引的记录才是真正的数据，万一被更新掉了咋办，所以在 id = 10 对应的主键索引上也需要加上锁（默认都是 record lock行锁），那主键索引上要不要加 gap 呢，也不用，也是精确定位到这一条记录
最后呢，当 id 不是主键，也不是唯一索引，只是个普通的索引，这里就需要大名鼎鼎的 gap 锁了，
是时候画个图了

其实核心的目的还是不让这个 id=10 的记录不会出现幻读，那么就需要在 id 这个索引上加上三个 gap 锁，主键索引上就不用了，在 id 索引上已经控制住了id = 10 不会出现幻读，主键索引上这两条对应的记录已经锁了，所以就这样 OK 了

+

对于一个 for update 查询，在 RR 级别下，会设置一个 next-key lock在每一条被查询到的记录上，next-lock 又是啥呢，其实就是 gap 锁和 record 锁的结合体，比如我在数据库里有 id 是 1，3，5，7，10，对于上面那条查询，查出来的结果就是 1，3，5，7，那么按照文档里描述的，对于这几条记录都会加上next-key lock，也就是(-∞, 1], (1, 3], (3, 5], (5, 7], (7, 10) 这些区间和记录会被锁起来，不让插入，再唠叨一下呢，就是其实如果是只读的事务，光 read view 一致性读就够了，如果是有写操作的呢，就需要锁了。

]]> Mysql @@ -6210,16 +6307,21 @@ user3: - 聊聊 mysql 的 MVCC 续篇 - /2020/05/02/%E8%81%8A%E8%81%8A-mysql-%E7%9A%84-MVCC-%E7%BB%AD%E7%AF%87/ - 上一篇聊了mysql 的 innodb 引擎基于 read view 实现的 mvcc 和事务隔离级别，可能有些细心的小伙伴会发现一些问题，第一个是在 RC 级别下的事务提交后的可见性，这里涉及到了三个参数，m_low_limit_id，m_up_limit_id，m_ids，之前看到知乎的一篇写的非常不错的文章，但是就在这一点上似乎有点疑惑，这里基于源码和注释来解释下这个问题

-
/**
Opens a read view where exactly the transactions serialized before this
point in time are seen in the view.
@param id		Creator transaction id */

void ReadView::prepare(trx_id_t id) {
  ut_ad(mutex_own(&trx_sys->mutex));

  m_creator_trx_id = id;

  m_low_limit_no = m_low_limit_id = m_up_limit_id = trx_sys->max_trx_id;
-

m_low_limit_id赋的值是trx_sys->max_trx_id，代表的是当前系统最小的未分配的事务 id，所以呢，举个例子，当前有三个活跃事务，事务 id 分别是 100，200，300，而 m_up_limit_id = 100, m_low_limit_id = 301，当事务 id 是 200 的提交之后，它的更新就是可以被 100 和 300 看到，而不是说 m_ids 里没了 200，并且 200 比 100 大就应该不可见了

-

幻读

还有一个问题是幻读的问题，这貌似也是个高频面试题，啥意思呢，或者说跟它最常拿来比较的脏读，脏读是指读到了别的事务未提交的数据，因为未提交，严格意义上来讲，不一定是会被最后落到库里，可能会回滚，也就是在 read uncommitted 级别下会出现的问题，但是幻读不太一样，幻读是指两次查询的结果数量不一样，比如我查了第一次是 select * from table1 where id < 10 for update,查出来了一条结果 id 是 5，然后再查一下发现出来了一条 id 是 5，一条 id 是 7，那是不是有点尴尬了，其实呢这个点我觉得脏读跟幻读也比较是从原理层面来命名，如果第一次接触的同学发觉有点不理解也比较正常，因为从逻辑上讲总之都是数据不符合预期，但是基于源码层面其实是不同的情况，幻读是在原先的 read view 无法完全解决的，怎么解决呢，简单的来说就是锁咯，我们知道innodb 是基于 record lock 行锁的，但是貌似没有办法解决这种问题，那么 innodb 就引入了 gap lock 间隙锁，比如上面说的情况下，id 小于 10 的情况下，是都应该锁住的，gap lock 其实是基于索引结构来锁的，因为索引树除了树形结构之外，还有一个next record 的指针，gap lock 也是基于这个来锁的
看一下 mysql 的文档

+ 聊聊 mysql 的 MVCC 续续篇之锁分析 + /2020/05/10/%E8%81%8A%E8%81%8A-mysql-%E7%9A%84-MVCC-%E7%BB%AD%E7%BB%AD%E7%AF%87%E4%B9%8B%E5%8A%A0%E9%94%81%E5%88%86%E6%9E%90/ + 看完前面两篇水文之后，感觉不得不来分析下 mysql 的锁了，其实前面说到幻读的时候是有个前提没提到的，比如一个select * from table1 where id = 1这种查询语句其实是不会加传说中的锁的，当然这里是指在 RR 或者 RC 隔离级别下，
看一段 mysql官方文档

-

SELECT … FOR UPDATE sets an exclusive next-key lock on every record the search encounters. However, only an index record lock is required for statements that lock rows using a unique index to search for a unique row.

+

SELECT ... FROM is a consistent read, reading a snapshot of the database and setting no locks unless the transaction isolation level is set to SERIALIZABLE. For SERIALIZABLE level, the search sets shared next-key locks on the index records it encounters. However, only an index record lock is required for statements that lock rows using a unique index to search for a unique row.

-

对于一个 for update 查询，在 RR 级别下，会设置一个 next-key lock在每一条被查询到的记录上，next-lock 又是啥呢，其实就是 gap 锁和 record 锁的结合体，比如我在数据库里有 id 是 1，3，5，7，10，对于上面那条查询，查出来的结果就是 1，3，5，7，那么按照文档里描述的，对于这几条记录都会加上next-key lock，也就是(-∞, 1], (1, 3], (3, 5], (5, 7], (7, 10) 这些区间和记录会被锁起来，不让插入，再唠叨一下呢，就是其实如果是只读的事务，光 read view 一致性读就够了，如果是有写操作的呢，就需要锁了。

+

纯粹的这种一致性读，实际读取的是快照，也就是基于 read view 的读取方式，除非当前隔离级别是SERIALIZABLE
但是对于以下几类

+
    +
  • select * from table where ? lock in share mode;
    • +
  • select * from table where ? for update;
    • +
  • insert into table values (...);
    • +
  • update table set ? where ?;
    • +
  • delete from table where ?;
    • +
+

除了第一条是 S 锁之外，其他都是 X 排他锁，这边在顺带下，S 锁表示共享锁， X 表示独占锁，同为 S 锁之间不冲突，S 与 X，X 与 S，X 与 X 之间都冲突，也就是加了前者，后者就加不上了
我们知道对于 RC 级别会出现幻读现象，对于 RR 级别不会出现，主要的区别是 RR 级别下对于以上的加锁读取都根据情况加上了 gap 锁，那么是不是 RR 级别下以上所有的都是要加 gap 锁呢，当然不是
举个例子，RR 事务隔离级别下，table1 有个主键id 字段
select * from table1 where id = 10 for update
这条语句要加 gap 锁吗？
答案是不需要，这里其实算是我看了这么久的一点自己的理解，啥时候要加 gap 锁，判断的条件是根据我查询的数据是否会因为不加 gap 锁而出现数量的不一致，我上面这条查询语句，在什么情况下会出现查询结果数量不一致呢，只要在这条记录被更新或者删除的时候，有没有可能我第一次查出来一条，第二次变成两条了呢，不可能，因为是主键索引。
再变更下这个题的条件，当 id 不是主键，但是是唯一索引，这样需要怎么加锁，注意问题是怎么加锁，不是需不需要加 gap 锁，这里呢就是稍微延伸一下，把聚簇索引（主键索引）和二级索引带一下，当 id 不是主键，说明是个二级索引，但是它是唯一索引，体会下，首先对于 id = 10这个二级索引肯定要加锁，要不要锁 gap 呢，不用，因为是唯一索引，id = 10 只可能有这一条记录，然后呢，这样是不是就好了，还不行，因为啥，因为它是二级索引，对应的主键索引的记录才是真正的数据，万一被更新掉了咋办，所以在 id = 10 对应的主键索引上也需要加上锁（默认都是 record lock行锁），那主键索引上要不要加 gap 呢，也不用，也是精确定位到这一条记录
最后呢，当 id 不是主键，也不是唯一索引，只是个普通的索引，这里就需要大名鼎鼎的 gap 锁了，
是时候画个图了

其实核心的目的还是不让这个 id=10 的记录不会出现幻读，那么就需要在 id 这个索引上加上三个 gap 锁，主键索引上就不用了，在 id 索引上已经控制住了id = 10 不会出现幻读，主键索引上这两条对应的记录已经锁了，所以就这样 OK 了

]]> Mysql @@ -6279,37 +6381,6 @@ user3: read view - - 聊聊 redis 缓存的应用问题 - /2021/01/31/%E8%81%8A%E8%81%8A-redis-%E7%BC%93%E5%AD%98%E7%9A%84%E5%BA%94%E7%94%A8%E9%97%AE%E9%A2%98/ - 前面写过一系列的 redis 源码分析的，但是实际上很多的问题还是需要结合实际的使用，然后其实就避不开缓存使用的三个著名问题，穿透，击穿和雪崩，这三个概念也是有着千丝万缕的关系，

-

缓存穿透

缓存穿透是指当数据库中本身就不存在这个数据的时候，使用一般的缓存策略时访问不到缓存后就访问数据库，但是因为数据库也没数据，所以如果不做任何策略优化的话，这类数据就每次都会访问一次数据库，对数据库压力也会比较大。

-

缓存击穿

缓存击穿跟穿透比较类似的，都是访问缓存不在，然后去访问数据库，与穿透不一样的是击穿是在数据库中存在数据，但是可能由于第一次访问，或者缓存过期了，需要访问到数据库，这对于访问量小的情况其实算是个正常情况，但是随着请求量变高就会引发一些性能隐患。

-

缓存雪崩

缓存雪崩就是击穿的大规模集群效应，当大量的缓存过期失效的时候，这些请求都是直接访问到数据库了，会对数据库造成很大的压力。

-

对于以上三种场景也有一些比较常见的解决方案，但也不能说是万无一失的，需要随着业务去寻找合适的方案

-

解决缓存穿透

对于数据库中就没这个数据的时候，一种是可以对这个 key 设置下空值，即以一个特定的表示是数据库不存在的，这种情况需要合理地调整过期时间，当这个 key 在数据库中有数据了的话，也需要有策略去更新这个值，并且如果这类 key 非常多，这个方法就会不太合适，就可以使用第二种方法，就是布隆过滤器，bloom filter，前置一个布隆过滤器，当这个 key 在数据库不存在的话，先用布隆过滤器挡一道，如果不在的话就直接返回了，当然布隆过滤器不是绝对的准确的

-

解决缓存击穿

当一个 key 的缓存过期了，如果大量请求过来访问这个 key，请求都会落在数据库里，这个时候就可以使用一些类似于互斥锁的方式去让一个线程去访问数据库，更新缓存，但是这里其实也有个问题，就是如果是热点 key 其实这种方式也比较危险，万一更新失败，或者更新操作的时候耗时比较久，就会有一大堆请求卡在那，这种情况可能需要有一些异步提前刷新缓存，可以结合具体场景选择方式

-

解决缓存雪崩

雪崩的情况是指大批量的 key 都一起过期了，击穿的放大版，大批量的请求都打到数据库上了，一方面有可能直接缓存不可用了，就需要用集群化高可用的缓存服务，然后对于实际使用中也可以使用本地缓存结合 redis 缓存，去提高可用性，再配合一些限流措施，然后就是缓存使用过程总的过期时间最好能加一些随机值，防止在同一时间过期而导致雪崩，结合互斥锁防止大量请求打到数据库。

-]]> - - Redis - 应用 - 缓存 - 缓存 - 穿透 - 击穿 - 雪崩 - - - Redis - 缓存穿透 - 缓存击穿 - 缓存雪崩 - 布隆过滤器 - bloom filter - 互斥锁 - - 聊聊 mysql 索引的一些细节 /2020/12/27/%E8%81%8A%E8%81%8A-mysql-%E7%B4%A2%E5%BC%95%E7%9A%84%E4%B8%80%E4%BA%9B%E7%BB%86%E8%8A%82/ @@ -6343,45 +6414,60 @@ user3: - 聊聊一次 brew update 引发的血案 - /2020/06/13/%E8%81%8A%E8%81%8A%E4%B8%80%E6%AC%A1-brew-update-%E5%BC%95%E5%8F%91%E7%9A%84%E8%A1%80%E6%A1%88/ - 熟悉我的人（谁熟悉你啊🙄）知道我以前写过 PHP，虽然现在在工作中没用到了，但是自己的一些小工具还是会用 PHP 来写，但是在 Mac 碰到了一个环境相关的问题，因为我也是个更新狂魔，用了 brew 之后因为 gfw 的原因，如果长时间不更新，有时候要装一个用它装一个软件的话，前置的更新耗时就会让人非常头大，所以我基本会隔天 update 一下，但是这样会带来一个很心烦的问题，就是像这样，因为我是要用一个固定版本的 PHP，如果一直升需要一直配扩展啥的也很麻烦，如果一直升级 PHP 到最新版可能会比较少碰到这个问题

-
dyld: Library not loaded: /usr/local/opt/icu4c/lib/libicui18n.64.dylib
-

这是什么鬼啊，然后我去这个目录下看了下，已经都是libicui18n.67.dylib了，而且它没有把原来的版本保留下来，首先这个是个叫 icu4c是啥玩意，谷歌了一下

-
-

ICU4C是ICU在C/C++平台下的版本, ICU(International Component for Unicode)是基于”IBM公共许可证”的，与开源组织合作研究的, 用于支持软件国际化的开源项目。ICU4C提供了C/C++平台强大的国际化开发能力，软件开发者几乎可以使用ICU4C解决任何国际化的问题，根据各地的风俗和语言习惯，实现对数字、货币、时间、日期、和消息的格式化、解析，对字符串进行大小写转换、整理、搜索和排序等功能，必须一提的是，ICU4C提供了强大的BIDI算法，对阿拉伯语等BIDI语言提供了完善的支持。

-
-

然后首先想到的解决方案就是能不能我使用brew install icu4c@64来重装下原来的版本，发现不行，并木有，之前的做法就只能是去网上把 64 的下载下来，然后放到这个目录，比较麻烦不智能，虽然没抱着希望在谷歌着，不过这次竟然给我找到了一个我认为非常 nice 的解决方案，因为是在 Stack Overflow 找到的，本着写给像我这样的小小白看的，那就稍微翻译一下
第一步，我们到 brew的目录下

-
cd $(brew --prefix)/Homebrew/Library/Taps/homebrew/homebrew-core/Formula
-

这个可以理解为是 maven 的 pom 文件，不过有很多不同之处，使用ruby 写的，然后一个文件对应一个组件或者软件，那我们看下有个叫icu4c.rb的文件，
第二步看看它的提交历史

-
git log --follow icu4c.rb
-

在 git log 的海洋中寻找，寻找它的(64版本)的身影

第三步注意这三个红框，Stack Overflow 给出来的答案这一步是找到这个 commit id 直接切出一个新分支

-
git checkout -b icu4c-63 e7f0f10dc63b1dc1061d475f1a61d01b70ef2cb7
-

其实注意 commit id 旁边的红框，这个是有tag 的，可以直接

-
git checkout icu4c-64
-

PS: 因为我的问题是出在 64 的问题，Stack Overflow 回答的是 63 的，反正是一样的解决方法
第四部，切回去之后我们就可以用 brew 提供的基于文件的安装命令来重新装上 64 版本

-
brew reinstall ./icu4c.rb
-

然后就是第五步，切换版本

-
brew switch icu4c 64.2
-

最后把分支切回来

-
git checkout master
-

是不是感觉很厉害的解决方法，大佬还提供了一个更牛的，直接写个 zsh 方法

-
# zsh
function hiicu64() {
  local last_dir=$(pwd)

  cd $(brew --prefix)/Homebrew/Library/Taps/homebrew/homebrew-core/Formula
  git checkout icu4c-4
  brew reinstall ./icu4c.rb
  brew switch icu4c 64.2
  git checkout master

  cd $last_dir
}
-

对应自己的版本改改版本号就可以了，非常好用。

+ 聊聊 redis 缓存的应用问题 + /2021/01/31/%E8%81%8A%E8%81%8A-redis-%E7%BC%93%E5%AD%98%E7%9A%84%E5%BA%94%E7%94%A8%E9%97%AE%E9%A2%98/ + 前面写过一系列的 redis 源码分析的，但是实际上很多的问题还是需要结合实际的使用，然后其实就避不开缓存使用的三个著名问题，穿透，击穿和雪崩，这三个概念也是有着千丝万缕的关系，

+

缓存穿透

缓存穿透是指当数据库中本身就不存在这个数据的时候，使用一般的缓存策略时访问不到缓存后就访问数据库，但是因为数据库也没数据，所以如果不做任何策略优化的话，这类数据就每次都会访问一次数据库，对数据库压力也会比较大。

+

缓存击穿

缓存击穿跟穿透比较类似的，都是访问缓存不在，然后去访问数据库，与穿透不一样的是击穿是在数据库中存在数据，但是可能由于第一次访问，或者缓存过期了，需要访问到数据库，这对于访问量小的情况其实算是个正常情况，但是随着请求量变高就会引发一些性能隐患。

+

缓存雪崩

缓存雪崩就是击穿的大规模集群效应，当大量的缓存过期失效的时候，这些请求都是直接访问到数据库了，会对数据库造成很大的压力。

+

对于以上三种场景也有一些比较常见的解决方案，但也不能说是万无一失的，需要随着业务去寻找合适的方案

+

解决缓存穿透

对于数据库中就没这个数据的时候，一种是可以对这个 key 设置下空值，即以一个特定的表示是数据库不存在的，这种情况需要合理地调整过期时间，当这个 key 在数据库中有数据了的话，也需要有策略去更新这个值，并且如果这类 key 非常多，这个方法就会不太合适，就可以使用第二种方法，就是布隆过滤器，bloom filter，前置一个布隆过滤器，当这个 key 在数据库不存在的话，先用布隆过滤器挡一道，如果不在的话就直接返回了，当然布隆过滤器不是绝对的准确的

+

解决缓存击穿

当一个 key 的缓存过期了，如果大量请求过来访问这个 key，请求都会落在数据库里，这个时候就可以使用一些类似于互斥锁的方式去让一个线程去访问数据库，更新缓存，但是这里其实也有个问题，就是如果是热点 key 其实这种方式也比较危险，万一更新失败，或者更新操作的时候耗时比较久，就会有一大堆请求卡在那，这种情况可能需要有一些异步提前刷新缓存，可以结合具体场景选择方式

+

解决缓存雪崩

雪崩的情况是指大批量的 key 都一起过期了，击穿的放大版，大批量的请求都打到数据库上了，一方面有可能直接缓存不可用了，就需要用集群化高可用的缓存服务，然后对于实际使用中也可以使用本地缓存结合 redis 缓存，去提高可用性，再配合一些限流措施，然后就是缓存使用过程总的过期时间最好能加一些随机值，防止在同一时间过期而导致雪崩，结合互斥锁防止大量请求打到数据库。

]]> - Mac - PHP - Homebrew - PHP - icu4c + Redis + 应用 + 缓存 + 缓存 + 穿透 + 击穿 + 雪崩 - Mac - PHP - Homebrew - icu4c - zsh + Redis + 缓存穿透 + 缓存击穿 + 缓存雪崩 + 布隆过滤器 + bloom filter + 互斥锁 + + + + 聊聊Java中的单例模式 + /2019/12/21/%E8%81%8A%E8%81%8AJava%E4%B8%AD%E7%9A%84%E5%8D%95%E4%BE%8B%E6%A8%A1%E5%BC%8F/ + 这是个 Java 面试的高频问题，我也遇到过，以往都是觉得这类题没意思，网上一搜一大堆，也不愿意记，其实说回来，主要还是没静下心来好好去理解，今天无意中看到一个课程，基本帮我把一些疑惑的点讲清楚了，首先单例是啥意思，这个其实是有范围一说，比如我起了个Spring Boot应用，在这个应用范围内，我的常规 bean 是单例的，意味着 getBean 的时候其实永远只会拿到那一个对象，那要怎么来写一个单例呢，首先就是传说中的饿汉模式，也是最简单的

+

饿汉模式

public class Singleton1 {
    // 首先，将构造方法变成私有的
    private Singleton1() {};
    // 创建私有静态实例，这样第一次使用的时候就会进行创建
    private static Singleton instance = new Singleton1();

    // 使用这个对象都是通过这个 getInstance 来获取
    public static Singleton1 getInstance() {
        return instance;
    }
    // 瞎写一个静态方法。这里想说的是，如果我们只是要调用 Singleton.getDate(...)，
    // 本来是不想要生成 Singleton 实例的，不过没办法，已经生成了
    public static Date getDate(String mode) {return new Date();}
}
+

上面借鉴了一些代码，其实这是最基本，也不会错的方法，但是正如其中getDate方法里说的问题，有时候并没有想那这个对象，但是因为我调用了这个类的静态方法，导致对象已经生成了，可能这也是饿汉模式名字的来由，不管三七二十一给你生成个单例就完事了，不管有没有用，但是这种个人觉得也没啥大问题，如果是面试的话最好说出来它的缺点

+

饱汉模式

public class Singleton2 {
    // 首先，也是先堵死 new Singleton() 这条路,将构造方法变成私有
    private Singleton2() {}
    // 和饿汉模式相比，这边不需要先实例化出来，注意这里的 volatile，它是必须的
    private static volatile Singleton2 instance = null;

    private int m = 9;

    public static Singleton getInstance() {
        if (instance == null) {
            // 加锁
            synchronized (Singleton2.class) {
                // 这一次判断也是必须的，不然会有并发问题
                if (instance == null) {
                    instance = new Singleton2();
                }
            }
        }
        return instance;
    }
}
+

这里容易错的有三点，理解了其实就比较好记了

+

第一点，为啥不在 getInstance 上整个代码块加 synchronized，这个其实比较容易理解，就是锁的力度太大，性能太差了，这点其实也要去理解，可以举个夸张的例子，比如我一个电商的服务，如果为了避免一个人的订单出现问题，是不是可以从请求入口就把他锁住，到请求结束释放，那么里面做的事情都有保障，然而这显然不可能，因为我们想要这种竞态条件抢占资源的时间尽量减少，防止其他线程等待。
第二点，为啥synchronized之已经检查了 instance == null,还要在里面再检查一次，这个有个术语，叫 double check lock,但是为啥要这么做呢，其实很简单，想象当有两个线程，都过了第一步为空判断，这个时候只有一个线程能拿到这个锁，另一个线程就等待了，如果不再判断一次，那么第一个线程新建完对象释放锁之后，第二个线程又能拿到锁，再去创建一个对象。
第三点，为啥要volatile关键字，原先对它的理解是它修饰的变量在 JMM 中能及时将变量值写到主存中，但是它还有个很重要的作用，就是防止指令重排序，instance = new Singleton();这行代码其实在底层是分成三条指令执行的，第一条是在堆上申请了一块内存放这个对象，但是对象的字段啥的都还是默认值，第二条是设置对象的值，比如上面的 m 是 9，然后第三条是将这个对象和虚拟机栈上的指针建立引用关联，那么如果我不用volatile关键字，这三条指令就有可能出现重排，比如变成了 1-3-2 这种顺序，当执行完第二步时，有个线程来访问这个对象了，先判断是不是空，发现不是空的，就拿去直接用了，是不是就出现问题了，所以这个volatile也是不可缺少的

+

嵌套类

public class Singleton3 {

    private Singleton3() {}
    // 主要是使用了 嵌套类可以访问外部类的静态属性和静态方法 的特性
    private static class Holder {
        private static Singleton3 instance = new Singleton3();
    }
    public static Singleton3 getInstance() {
        return Holder.instance;
    }
}
+

这个我个人感觉是饿汉模式的升级版，可以在调用getInstance的时候去实例化对象，也是比较推荐的

+

枚举单例

public enum Singleton {
    INSTANCE;
    
    public void doSomething(){
        //todo doSomething
    }
}
+

枚举很特殊，它在类加载的时候会初始化里面的所有的实例，而且 JVM 保证了它们不会再被实例化，所以它天生就是单例的。

+]]> + + Java + Design Patterns + Singleton + + + 设计模式 + Design Patterns + 单例 + Singleton @@ -6420,29 +6506,45 @@ user3: - 聊聊Java中的单例模式 - /2019/12/21/%E8%81%8A%E8%81%8AJava%E4%B8%AD%E7%9A%84%E5%8D%95%E4%BE%8B%E6%A8%A1%E5%BC%8F/ - 这是个 Java 面试的高频问题，我也遇到过，以往都是觉得这类题没意思，网上一搜一大堆，也不愿意记，其实说回来，主要还是没静下心来好好去理解，今天无意中看到一个课程，基本帮我把一些疑惑的点讲清楚了，首先单例是啥意思，这个其实是有范围一说，比如我起了个Spring Boot应用，在这个应用范围内，我的常规 bean 是单例的，意味着 getBean 的时候其实永远只会拿到那一个对象，那要怎么来写一个单例呢，首先就是传说中的饿汉模式，也是最简单的

-

饿汉模式

public class Singleton1 {
    // 首先，将构造方法变成私有的
    private Singleton1() {};
    // 创建私有静态实例，这样第一次使用的时候就会进行创建
    private static Singleton instance = new Singleton1();

    // 使用这个对象都是通过这个 getInstance 来获取
    public static Singleton1 getInstance() {
        return instance;
    }
    // 瞎写一个静态方法。这里想说的是，如果我们只是要调用 Singleton.getDate(...)，
    // 本来是不想要生成 Singleton 实例的，不过没办法，已经生成了
    public static Date getDate(String mode) {return new Date();}
}
-

上面借鉴了一些代码，其实这是最基本，也不会错的方法，但是正如其中getDate方法里说的问题，有时候并没有想那这个对象，但是因为我调用了这个类的静态方法，导致对象已经生成了，可能这也是饿汉模式名字的来由，不管三七二十一给你生成个单例就完事了，不管有没有用，但是这种个人觉得也没啥大问题，如果是面试的话最好说出来它的缺点

-

饱汉模式

public class Singleton2 {
    // 首先，也是先堵死 new Singleton() 这条路,将构造方法变成私有
    private Singleton2() {}
    // 和饿汉模式相比，这边不需要先实例化出来，注意这里的 volatile，它是必须的
    private static volatile Singleton2 instance = null;

    private int m = 9;

    public static Singleton getInstance() {
        if (instance == null) {
            // 加锁
            synchronized (Singleton2.class) {
                // 这一次判断也是必须的，不然会有并发问题
                if (instance == null) {
                    instance = new Singleton2();
                }
            }
        }
        return instance;
    }
}
-

这里容易错的有三点，理解了其实就比较好记了

-

第一点，为啥不在 getInstance 上整个代码块加 synchronized，这个其实比较容易理解，就是锁的力度太大，性能太差了，这点其实也要去理解，可以举个夸张的例子，比如我一个电商的服务，如果为了避免一个人的订单出现问题，是不是可以从请求入口就把他锁住，到请求结束释放，那么里面做的事情都有保障，然而这显然不可能，因为我们想要这种竞态条件抢占资源的时间尽量减少，防止其他线程等待。
第二点，为啥synchronized之已经检查了 instance == null,还要在里面再检查一次，这个有个术语，叫 double check lock,但是为啥要这么做呢，其实很简单，想象当有两个线程，都过了第一步为空判断，这个时候只有一个线程能拿到这个锁，另一个线程就等待了，如果不再判断一次，那么第一个线程新建完对象释放锁之后，第二个线程又能拿到锁，再去创建一个对象。
第三点，为啥要volatile关键字，原先对它的理解是它修饰的变量在 JMM 中能及时将变量值写到主存中，但是它还有个很重要的作用，就是防止指令重排序，instance = new Singleton();这行代码其实在底层是分成三条指令执行的，第一条是在堆上申请了一块内存放这个对象，但是对象的字段啥的都还是默认值，第二条是设置对象的值，比如上面的 m 是 9，然后第三条是将这个对象和虚拟机栈上的指针建立引用关联，那么如果我不用volatile关键字，这三条指令就有可能出现重排，比如变成了 1-3-2 这种顺序，当执行完第二步时，有个线程来访问这个对象了，先判断是不是空，发现不是空的，就拿去直接用了，是不是就出现问题了，所以这个volatile也是不可缺少的

-

嵌套类

public class Singleton3 {

    private Singleton3() {}
    // 主要是使用了 嵌套类可以访问外部类的静态属性和静态方法 的特性
    private static class Holder {
        private static Singleton3 instance = new Singleton3();
    }
    public static Singleton3 getInstance() {
        return Holder.instance;
    }
}
-

这个我个人感觉是饿汉模式的升级版，可以在调用getInstance的时候去实例化对象，也是比较推荐的

-

枚举单例

public enum Singleton {
    INSTANCE;
    
    public void doSomething(){
        //todo doSomething
    }
}
-

枚举很特殊，它在类加载的时候会初始化里面的所有的实例，而且 JVM 保证了它们不会再被实例化，所以它天生就是单例的。

+ 聊聊一次 brew update 引发的血案 + /2020/06/13/%E8%81%8A%E8%81%8A%E4%B8%80%E6%AC%A1-brew-update-%E5%BC%95%E5%8F%91%E7%9A%84%E8%A1%80%E6%A1%88/ + 熟悉我的人（谁熟悉你啊🙄）知道我以前写过 PHP，虽然现在在工作中没用到了，但是自己的一些小工具还是会用 PHP 来写，但是在 Mac 碰到了一个环境相关的问题，因为我也是个更新狂魔，用了 brew 之后因为 gfw 的原因，如果长时间不更新，有时候要装一个用它装一个软件的话，前置的更新耗时就会让人非常头大，所以我基本会隔天 update 一下，但是这样会带来一个很心烦的问题，就是像这样，因为我是要用一个固定版本的 PHP，如果一直升需要一直配扩展啥的也很麻烦，如果一直升级 PHP 到最新版可能会比较少碰到这个问题

+
dyld: Library not loaded: /usr/local/opt/icu4c/lib/libicui18n.64.dylib
+

这是什么鬼啊，然后我去这个目录下看了下，已经都是libicui18n.67.dylib了，而且它没有把原来的版本保留下来，首先这个是个叫 icu4c是啥玩意，谷歌了一下

+
+

ICU4C是ICU在C/C++平台下的版本, ICU(International Component for Unicode)是基于”IBM公共许可证”的，与开源组织合作研究的, 用于支持软件国际化的开源项目。ICU4C提供了C/C++平台强大的国际化开发能力，软件开发者几乎可以使用ICU4C解决任何国际化的问题，根据各地的风俗和语言习惯，实现对数字、货币、时间、日期、和消息的格式化、解析，对字符串进行大小写转换、整理、搜索和排序等功能，必须一提的是，ICU4C提供了强大的BIDI算法，对阿拉伯语等BIDI语言提供了完善的支持。

+
+

然后首先想到的解决方案就是能不能我使用brew install icu4c@64来重装下原来的版本，发现不行，并木有，之前的做法就只能是去网上把 64 的下载下来，然后放到这个目录，比较麻烦不智能，虽然没抱着希望在谷歌着，不过这次竟然给我找到了一个我认为非常 nice 的解决方案，因为是在 Stack Overflow 找到的，本着写给像我这样的小小白看的，那就稍微翻译一下
第一步，我们到 brew的目录下

+
cd $(brew --prefix)/Homebrew/Library/Taps/homebrew/homebrew-core/Formula
+

这个可以理解为是 maven 的 pom 文件，不过有很多不同之处，使用ruby 写的，然后一个文件对应一个组件或者软件，那我们看下有个叫icu4c.rb的文件，
第二步看看它的提交历史

+
git log --follow icu4c.rb
+

在 git log 的海洋中寻找，寻找它的(64版本)的身影

第三步注意这三个红框，Stack Overflow 给出来的答案这一步是找到这个 commit id 直接切出一个新分支

+
git checkout -b icu4c-63 e7f0f10dc63b1dc1061d475f1a61d01b70ef2cb7
+

其实注意 commit id 旁边的红框，这个是有tag 的，可以直接

+
git checkout icu4c-64
+

PS: 因为我的问题是出在 64 的问题，Stack Overflow 回答的是 63 的，反正是一样的解决方法
第四部，切回去之后我们就可以用 brew 提供的基于文件的安装命令来重新装上 64 版本

+
brew reinstall ./icu4c.rb
+

然后就是第五步，切换版本

+
brew switch icu4c 64.2
+

最后把分支切回来

+
git checkout master
+

是不是感觉很厉害的解决方法，大佬还提供了一个更牛的，直接写个 zsh 方法

+
# zsh
function hiicu64() {
  local last_dir=$(pwd)

  cd $(brew --prefix)/Homebrew/Library/Taps/homebrew/homebrew-core/Formula
  git checkout icu4c-4
  brew reinstall ./icu4c.rb
  brew switch icu4c 64.2
  git checkout master

  cd $last_dir
}
+

对应自己的版本改改版本号就可以了，非常好用。

]]> - Java - Design Patterns - Singleton + Mac + PHP + Homebrew + PHP + icu4c - 设计模式 - Design Patterns - 单例 - Singleton + Mac + PHP + Homebrew + icu4c + zsh @@ -6505,6 +6607,23 @@ user3: 海蛎煎 + + 聊聊如何识别和意识到日常生活中的各类危险 + /2021/06/06/%E8%81%8A%E8%81%8A%E5%A6%82%E4%BD%95%E8%AF%86%E5%88%AB%E5%92%8C%E6%84%8F%E8%AF%86%E5%88%B0%E6%97%A5%E5%B8%B8%E7%94%9F%E6%B4%BB%E4%B8%AD%E7%9A%84%E5%90%84%E7%B1%BB%E5%8D%B1%E9%99%A9/ + 这篇博客的灵感又是来自于我从绍兴来杭州的路上，在我们进站以后上电梯快到的时候，突然前面不动了，右边我能看到的是有个人的行李箱一时拎不起来，另一边后面看到其实是个小孩子在那哭闹，一位妈妈就在那停着安抚或者可能有点手足无措，其实这一点应该是在几年前慢慢意识到是个非常危险的场景，特别是像绍兴北站这样上去站台是非常长的电梯，因为最近扩建改造，车次减少了很多，所以每一班都有很多人，检票上站台的电梯都是满员运转，试想这种情况，如果刚才那位妈妈再多停留一点时间，很可能就会出现后面的人上不来被挤下去，再严重点就是踩踏事件，但是这类情况很少人真的意识到，非常明显的例子就是很多人拿着比较大比较重的行李箱，不走垂梯，并且在快到的时候没有提前准备好，有可能在玩手机啥的，如果提不动，后面又是挤满人了，就很可能出现前面说的这种情况，并且其实这种是非紧急情况，大多数人都没有心理准备，一旦发生后果可能就会很严重，例如火灾地震疏散大部分人或者说负责引导的都是指示要有序撤离，防止踩踏，但是普通坐个扶梯，一般都不会有这个意识，但是如果这个时间比较长，出现了人员站不住往后倒了，真的会很严重。所以如果自己是带娃的或者带了很重的行李箱的，请提前做好准备，看到前面有人带的，最好也保持一定距离。
还有比如日常走路，旁边有车子停着的情况，比较基本的看车灯有没有亮着，亮着的是否是倒车灯，这种应该特别注意远离，至少保持距离，不能挨着走，很多人特别是一些老年人，在一些人比较多的路上，往往完全无视旁边这些车的状态，我走我的路，谁敢阻拦我，管他车在那动不动，其实真的非常危险，车子本身有视线死角，再加上司机的驾驶习惯和状态，想去送死跟碰瓷的除外，还有就是有一些车会比较特殊，车子发动着，但是没灯，可能是车子灯坏了或者司机通过什么方式关了灯，这种比较难避开，不过如果车子打着了，一般会有比较大的热量散发，车子刚灭了也会有，反正能远离点尽量远离，从轿车的车前面走过挨着走要比从屁股后面挨着走稍微安全一些，但也最好不要挨着车走。
最后一点其实是我觉得是我自己比较怕死，一般对来向的车或者从侧面出来的车会做更长的预判距离，特别是电瓶车，一般是不让人的，像送外卖的小哥，的确他们不太容易，但是真的很危险啊，基本就生死看刹车，能刹住就赚了，刹不住就看身子骨扛不扛撞了，只是这里要多说点又要谈到资本的趋利性了，总是想法设法的压榨以获取更多的利益，也不扯远了，能远离就远离吧。

+]]> + + 生活 + + + 生活 + 糟心事 + 扶梯 + 踩踏 + 安全 + 电瓶车 + + 聊聊对 FunctionalInterface 注解的一些理解 /2023/10/15/%E8%81%8A%E8%81%8A%E5%AF%B9-FunctionalInterface-%E6%B3%A8%E8%A7%A3%E7%9A%84%E4%B8%80%E4%BA%9B%E7%90%86%E8%A7%A3/ @@ -6531,53 +6650,17 @@ user3: /2020/05/22/%E8%81%8A%E8%81%8A%E6%88%91%E5%88%9A%E5%AD%A6%E4%BC%9A%E7%9A%84%E5%BA%94%E7%94%A8%E8%AF%8A%E6%96%AD%E6%96%B9%E6%B3%95/ 因为传说中的出身问题，我以前写的是PHP，在使用 swoole 之前，基本的应用调试手段就是简单粗暴的 var_dump，exit，对于单进程模型的 PHP 也是简单有效，技术栈换成 Java 之后，就变得没那么容易，一方面是需要编译，另一方面是一般都是基于 spring 的项目，如果问题定位比较模糊，那框架层的是很难靠简单的 System.out.println 或者打 log 解决，(PS：我觉得可能我写的东西比较适合从 PHP 这种弱类型语言转到 Java 的小白同学)这个时候一方面因为是 Java，有了非常好用的 idea IDE 的支持，可以各种花式调试，条件断点尤其牛叉，但是又因为有 Spring+Java 的双重原因，有些情况下单步调试可以把手按废掉，这也是我之前一直比较困惑苦逼的点，后来随着慢慢精（jiang）进（you）之后，比如对于一个 oom 的情况，我们可以通过启动参数加上-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=xx/xx 来配置溢出时的堆dump 日志，获取到这个文件后，我们可以通过像 Memory Analyzer (MAT)[https://www.eclipse.org/mat/] (The Eclipse Memory Analyzer is a fast and feature-rich Java heap analyzer that helps you find memory leaks and reduce memory consumption.)来查看诊断问题所在，之前用到的时候是因为有个死循环一直往链表里塞数据，属于比较简单的，后来一次是由于运维进行应用迁移时按默认的统一配置了堆内存大小，导致内存的确不够用，所以溢出了，
今天想说的其实主要是我们的 thread dump，这也是我最近才真正用的一个方法，可能真的很小白了，用过 ide 的单步调试其实都知道会有一个一层层的玩意，比如函数从 A，调用了 B，再从 B 调用了 C，一直往下(因为是 Java，所以还有很多🤦‍♂️)，这个其实也是大部分语言的调用模型，利用了栈这个数据结构，通过这个结构我们可以知道代码的调用链路，由于对于一个 spring 应用，在本身框架代码量非常庞大的情况下，外加如果应用代码也是非常多的时候，有时候通过单步调试真的很难短时间定位到问题，需要非常大的耐心和仔细观察，当然不是说完全不行，举个例子当我的应用经常启动需要非常长的时间，因为本身应用有非常多个 bean，比较难说究竟是 bean 的加载的确很慢还是有什么异常原因，这种时候就可以使用 thread dump 了，具体怎么操作呢

如果在idea 中运行或者调试时，可以直接点击这个照相机一样的按钮，右边就会出现了左边会显示所有的线程，右边会显示线程栈，

"main@1" prio=5 tid=0x1 nid=NA runnable
  java.lang.Thread.State: RUNNABLE
	  at TreeDistance.treeDist(TreeDistance.java:64)
	  at TreeDistance.treeDist(TreeDistance.java:65)
	  at TreeDistance.treeDist(TreeDistance.java:65)
	  at TreeDistance.treeDist(TreeDistance.java:65)
	  at TreeDistance.main(TreeDistance.java:45)
-

这就是我们主线程的堆栈信息了，main 表示这个线程名，prio表示优先级，默认是 5，tid 表示线程 id，nid 表示对应的系统线程，后面的runnable 表示目前线程状态，因为是被我打了断点，所以是就许状态，然后下面就是对应的线程栈内容了，在TreeDistance类的 treeDist方法中，对应的文件行数是 64 行。
这里使用 thread dump一般也不会是上面我截图代码里的这种代码量很少的，一般是大型项目，有时候跑着跑着没反应，又不知道跑到哪了，特别是一些刚接触的大项目或者需要定位一个大项目的一个疑难问题，一时没思路时，可以使用这个方法，个人觉得非常有帮助。

-]]> - - Java - Thread dump - 问题排查 - 工具 - - - Java - Thread dump - - - - 聊聊如何识别和意识到日常生活中的各类危险 - /2021/06/06/%E8%81%8A%E8%81%8A%E5%A6%82%E4%BD%95%E8%AF%86%E5%88%AB%E5%92%8C%E6%84%8F%E8%AF%86%E5%88%B0%E6%97%A5%E5%B8%B8%E7%94%9F%E6%B4%BB%E4%B8%AD%E7%9A%84%E5%90%84%E7%B1%BB%E5%8D%B1%E9%99%A9/ - 这篇博客的灵感又是来自于我从绍兴来杭州的路上，在我们进站以后上电梯快到的时候，突然前面不动了，右边我能看到的是有个人的行李箱一时拎不起来，另一边后面看到其实是个小孩子在那哭闹，一位妈妈就在那停着安抚或者可能有点手足无措，其实这一点应该是在几年前慢慢意识到是个非常危险的场景，特别是像绍兴北站这样上去站台是非常长的电梯，因为最近扩建改造，车次减少了很多，所以每一班都有很多人，检票上站台的电梯都是满员运转，试想这种情况，如果刚才那位妈妈再多停留一点时间，很可能就会出现后面的人上不来被挤下去，再严重点就是踩踏事件，但是这类情况很少人真的意识到，非常明显的例子就是很多人拿着比较大比较重的行李箱，不走垂梯，并且在快到的时候没有提前准备好，有可能在玩手机啥的，如果提不动，后面又是挤满人了，就很可能出现前面说的这种情况，并且其实这种是非紧急情况，大多数人都没有心理准备，一旦发生后果可能就会很严重，例如火灾地震疏散大部分人或者说负责引导的都是指示要有序撤离，防止踩踏，但是普通坐个扶梯，一般都不会有这个意识，但是如果这个时间比较长，出现了人员站不住往后倒了，真的会很严重。所以如果自己是带娃的或者带了很重的行李箱的，请提前做好准备，看到前面有人带的，最好也保持一定距离。
还有比如日常走路，旁边有车子停着的情况，比较基本的看车灯有没有亮着，亮着的是否是倒车灯，这种应该特别注意远离，至少保持距离，不能挨着走，很多人特别是一些老年人，在一些人比较多的路上，往往完全无视旁边这些车的状态，我走我的路，谁敢阻拦我，管他车在那动不动，其实真的非常危险，车子本身有视线死角，再加上司机的驾驶习惯和状态，想去送死跟碰瓷的除外，还有就是有一些车会比较特殊，车子发动着，但是没灯，可能是车子灯坏了或者司机通过什么方式关了灯，这种比较难避开，不过如果车子打着了，一般会有比较大的热量散发，车子刚灭了也会有，反正能远离点尽量远离，从轿车的车前面走过挨着走要比从屁股后面挨着走稍微安全一些，但也最好不要挨着车走。
最后一点其实是我觉得是我自己比较怕死，一般对来向的车或者从侧面出来的车会做更长的预判距离，特别是电瓶车，一般是不让人的，像送外卖的小哥，的确他们不太容易，但是真的很危险啊，基本就生死看刹车，能刹住就赚了，刹不住就看身子骨扛不扛撞了，只是这里要多说点又要谈到资本的趋利性了，总是想法设法的压榨以获取更多的利益，也不扯远了，能远离就远离吧。

-]]> - - 生活 - - - 生活 - 糟心事 - 扶梯 - 踩踏 - 安全 - 电瓶车 - - - - 聊聊最近平淡的生活之又聊通勤 - /2021/11/07/%E8%81%8A%E8%81%8A%E6%9C%80%E8%BF%91%E5%B9%B3%E6%B7%A1%E7%9A%84%E7%94%9F%E6%B4%BB/ - 一直以来过着特别平淡普通的生活，不过大多数人应该都这样吧，也许有些人可以把平凡的生活过得精彩，最简单的说明就是朋友圈吧，看我一年的盆友圈虽然在发，不过大概 90%的都是发发跑步的打卡，偶尔会有稀稀拉拉的点赞，天天上班，也不喜欢发什么状态，觉得没什么人关注，索性不发。

-

只是这么平淡的生活就有一些自己比较心烦纠结的，之前有提到过的交通，最近似乎又发现了一点，就真相总是让人跌破眼镜，以前觉得我可能是胆子比较小，所以会觉得怎么路上这些电瓶都是这么肆无忌惮的往我冲过来，后面慢慢有一种借用电视剧读心神探的概念，安全距离，觉得大部分人跟我一样，骑电瓶车什么的总还是有个安全距离，只是可能这个安全距离对于不同的人不一样，那些骑电瓶车的潜意识里的安全距离是非常短，所以经常会骑车离着你非常近才会刹车，但是这个安全距离理论最近又被推翻了，因为经历过几次电瓶车就是已经跟你有身体接触了，但是没到把人撞倒的程度，似乎这些骑电瓶车的觉得步行的行人在人行道上是空气，蹭一下也无所谓，反正不能挡我的路，总感觉要不是我在前面骑自行车太慢挡着电瓶车，不然他们都能起飞去干掉 F35 解放湾湾了；

-

另一个问题应该是说我们交通规则普及的太少，虽然我们没有路权这个名词概念，但是其实是有这个优先级的，包括像杭州是以公交车在人行道礼让行人闻名的，其实这个文明的行为只限于人行道在直行路中间的，大部分在十字路口，右转的公交车很少会让直行人行道的，前提是直行的绿灯的时候，特别是像公交车这样，车身特别长，右转的时候会有比较大的死角，如果是公交车先转，行人或者自行车很容易被卷进去，非常危险的，私家车就更不用说了，反正右转即使人行道上人非常多要转的也是一秒都不等，所以我自己在开车的时候是尽量在右转的时候等人行道上的行人或者骑车的走完，因为总会觉得我是不是有点双标，骑车走路的时候希望开车的能按规则让我，自己开车的时候又想赶紧开走，所以在开车的时候尽量做到让行车和骑车的。

-

还有个其实是写着写着想起来的，比如我骑车左转的时候，因为我是左转到对角那就到了，跟那些左转后要再直行的不一样，我们应该在学车的时候也学过，超车要从左边超，但是往往那些骑电瓶车的在左转的时候会从我右边超过来再往左边撇过去，如果留的空间大还好，有些电瓶车就是如果车头超过了就不管他的车屁股，如果我不减速，自行车就被刮倒了，可能的确是别人就不是人，只要不把你撞倒就无所谓，反正为了你自己不被撞倒你肯定会让的。

+

这就是我们主线程的堆栈信息了，main 表示这个线程名，prio表示优先级，默认是 5，tid 表示线程 id，nid 表示对应的系统线程，后面的runnable 表示目前线程状态，因为是被我打了断点，所以是就许状态，然后下面就是对应的线程栈内容了，在TreeDistance类的 treeDist方法中，对应的文件行数是 64 行。
这里使用 thread dump一般也不会是上面我截图代码里的这种代码量很少的，一般是大型项目，有时候跑着跑着没反应，又不知道跑到哪了，特别是一些刚接触的大项目或者需要定位一个大项目的一个疑难问题，一时没思路时，可以使用这个方法，个人觉得非常有帮助。

]]> - 生活 + Java + Thread dump + 问题排查 + 工具 - 生活 - 糟心事 - 规则 - 电瓶车 - 骑车 + Java + Thread dump @@ -6638,23 +6721,29 @@ user3: - 聊聊最近平淡的生活之《花束般的恋爱》观后感 - /2021/12/31/%E8%81%8A%E8%81%8A%E6%9C%80%E8%BF%91%E5%B9%B3%E6%B7%A1%E7%9A%84%E7%94%9F%E6%B4%BB%E4%B9%8B%E3%80%8A%E8%8A%B1%E6%9D%9F%E8%88%AC%E7%9A%84%E6%81%8B%E7%88%B1%E3%80%8B%E8%A7%82%E5%90%8E%E6%84%9F/ - 周末在领导的提议下看了豆瓣的年度榜单，本来感觉没啥心情看的，看到主演有有村架纯就觉得可以看一下，颜值即正义嘛，男主小麦跟女主小娟（后面简称小麦跟小娟）是两个在一次非常偶然的没赶上地铁末班车事件中相识，这里得说下日本这种通宵营业的店好像挺不错的，看着也挺正常，国内估计只有酒吧之类的可以。晚上去的地方是有点暗暗的，好像也有点类似酒吧，旁边有类似于 dj 那种，然后同桌的还有除了男女主的另外一对男女，也是因为没赶上地铁末班车的，但也是陌生人，然后小麦突然看到了有个非常有名的电影人，小娟竟然也认识，然后旁边那对完全不认识，还在那吹自己看过很多电影，比如《肖申克的救赎》，于是男女主都特别鄙夷地看着他们，然后他们又去了另一个有点像泡澡的地方席地而坐，他们发现了自己的鞋子都是一样的，然后在女的去上厕所的时候，小麦暗恋的学姐也来了，然后小麦就去跟学姐他们一起坐了，小娟回来后有点不开心就说去朋友家睡，幸好小麦看出来了（他竟然看出来了，本来以为应该是没填过恋爱很木讷的），就追出去，然后就去了小麦家，到了家小娟发现小麦家的书柜上的书简直就跟她自己家的一模一样，小麦还给小娟吹了头发，一起吃烤饭团，看电影，第二天送小娟上了公交，还约好了一起看木乃伊展，然而并没有交换联系方式，但是他们还是约上了一起看了木乃伊展，在餐馆就出现了片头那一幕的来源，因为餐馆他们想一起听歌，就用有线耳机一人一个耳朵听，但是旁边就有个大叔说“你们是不是不爱音乐，左右耳朵是不一样的，只有一起听才是真正的音乐”这样的话，然后的剧情有点跳，因为是指他们一直在这家餐馆吃饭，中间有他们一起出去玩情节穿插着，也是在这他们确立了关系，可以说主体就是体现了他们非常的合拍和默契，就像一些影评说的，这部电影是说如何跟百分百合拍的人分手，然后就是正常的恋爱开始啪啪啪，一直腻在床上，也没去就业说明会，后面也有讲了一点小麦带着小娟去认识他的朋友，也把小娟介绍给了他们认识，这里算是个小伏笔，后面他们分手也有这里的人的一些关系，接下去的剧情说实话我是不太喜欢的，如果一部八分的电影只是说恋爱被现实打败的话，我觉得在我这是不合格的，但是事实也是这样，小麦其实是有家里的资助，所以后面还是按自己的喜好给一些机构画点插画，小娟则要出去工作，因为小娟家庭观念也是要让她出去有正经工作，用脚指头想也能知道肯定不顺利，然后就是暂时在一家蛋糕店工作，小麦就每天去接小娟，日子过得甜甜蜜蜜，后面小娟在自己的努力下考了个什么资格证，去了一家医院还是什么做前台行政，这中间当然就有父母来见面吃饭了，他们在开始恋爱不久就同居合租了，然后小娟父母就是来说要让她有个正经工作，对男的说的话就是人生就是责任这类的话，而小麦爸爸算是个导火索，因为小麦家里是做烟花生意的，他爸让他就做烟花生意，因为要回老家，并且小麦也不想做，所以就拒绝了，然后他爸就说不给他每个月五万的资助，这也导致了小麦需要去找工作，这个过程也是很辛苦，本来想要年前找好工作，然后事与愿违，后面有一次小娟被同事吐槽怎么从来不去团建，于是她就去了（我以为会拒绝），正在团建的时候小麦给她电话，说找到工作了，是一个创业物流公司这种，这里剧情就是我觉得比较俗套的，小麦各种被虐，累成狗，但是就像小娟爸爸说的话，人生就是责任，所以一直在坚持，但是这样也导致了跟小娟的交流也越来越少，他们原来最爱的漫画，爱玩的游戏，也只剩小娟一个人看，一个人玩，而正是这个时候，小娟说她辞掉了工作，去做一个不是太靠谱的漫画改造的密室逃脱，然后这里其实有一点后面争议很大的，就是这个工作其实是前面小麦介绍给小娟的那些朋友中一个的女朋友介绍的，而在有个剧情就是小娟有一次在这个密室逃脱的老板怀里醒过来，是在 KTV 那样的场景里，这就有很多人觉得小娟是不是出轨了，我觉得其实不那么重要，因为这个离职的事情已经让一切矛盾都摆在眼前，小麦其实是接受这种需要承担责任的生活，也想着要跟小娟结婚，但是小娟似乎还是想要过着那样理想的生活，做自己想做的事情，看自己爱看的漫画，也要小麦能像以前那样一直那么默契的有着相同的爱好，这里的触发点其实还有个是那个小麦的朋友（也就是他女朋友介绍小娟那个不靠谱工作的）的葬礼上，小麦在参加完葬礼后有挺多想倾诉的，而小娟只是想睡了，这个让小麦第二天起来都不想理小娟，只是这里我不太理解，难道这点闹情绪都不能接受吗，所谓的合拍也只是毫无限制的情况下的合拍吧，真正的生活怎么可能如此理想呢，即使没有物质生活的压力，也会有其他的各种压力和限制，在这之后其实小麦想说的是小娟是不是没有想跟自己继续在一起的想法了，而小娟觉得都不说话了，还怎么结婚呢，后面其实导演搞了个小 trick，突然放了异常婚礼，但是不是男女主的，我并不觉得这个桥段很好，在婚礼里男女主都觉得自己想要跟对方说分手了，但是当他们去了最开始一直去的餐馆的时候，一个算是一个现实映照的就是他们一直坐的位子被占了，可能也是导演想通过这个来说明他们已经回不去了，在餐馆交谈的时候，小麦其实是说他们结婚吧，并没有想前面婚礼上预设地要分手，但是小娟放弃了，不想结婚，因为不想过那样的生活了，而小麦觉得可能生活就是那样，不可能一直保持刚恋爱时候的那种感觉，生活就是责任，人生就意味着责任。

-

我的一些观点也在前面说了，恋爱到婚姻，即使物质没问题，经济没问题，也会有各种各样的问题，需要一起去解决，因为结婚就意味着需要相互扶持，而不是各取所需，可能我的要求比较高，后面男女主在分手后还一起住了一段时间，我原来还在想会不会通过这个方式让他们继续去磨合同步，只是我失望了，最后给个打分可能是 5 到 6 分吧，勉强及格，好的影视剧应该源于生活高于生活，这一部可能还比不上生活。

+ 聊聊最近平淡的生活之又聊通勤 + /2021/11/07/%E8%81%8A%E8%81%8A%E6%9C%80%E8%BF%91%E5%B9%B3%E6%B7%A1%E7%9A%84%E7%94%9F%E6%B4%BB/ + 一直以来过着特别平淡普通的生活，不过大多数人应该都这样吧，也许有些人可以把平凡的生活过得精彩，最简单的说明就是朋友圈吧，看我一年的盆友圈虽然在发，不过大概 90%的都是发发跑步的打卡，偶尔会有稀稀拉拉的点赞，天天上班，也不喜欢发什么状态，觉得没什么人关注，索性不发。

+

只是这么平淡的生活就有一些自己比较心烦纠结的，之前有提到过的交通，最近似乎又发现了一点，就真相总是让人跌破眼镜，以前觉得我可能是胆子比较小，所以会觉得怎么路上这些电瓶都是这么肆无忌惮的往我冲过来，后面慢慢有一种借用电视剧读心神探的概念，安全距离，觉得大部分人跟我一样，骑电瓶车什么的总还是有个安全距离，只是可能这个安全距离对于不同的人不一样，那些骑电瓶车的潜意识里的安全距离是非常短，所以经常会骑车离着你非常近才会刹车，但是这个安全距离理论最近又被推翻了，因为经历过几次电瓶车就是已经跟你有身体接触了，但是没到把人撞倒的程度，似乎这些骑电瓶车的觉得步行的行人在人行道上是空气，蹭一下也无所谓，反正不能挡我的路，总感觉要不是我在前面骑自行车太慢挡着电瓶车，不然他们都能起飞去干掉 F35 解放湾湾了；

+

另一个问题应该是说我们交通规则普及的太少，虽然我们没有路权这个名词概念，但是其实是有这个优先级的，包括像杭州是以公交车在人行道礼让行人闻名的，其实这个文明的行为只限于人行道在直行路中间的，大部分在十字路口，右转的公交车很少会让直行人行道的，前提是直行的绿灯的时候，特别是像公交车这样，车身特别长，右转的时候会有比较大的死角，如果是公交车先转，行人或者自行车很容易被卷进去，非常危险的，私家车就更不用说了，反正右转即使人行道上人非常多要转的也是一秒都不等，所以我自己在开车的时候是尽量在右转的时候等人行道上的行人或者骑车的走完，因为总会觉得我是不是有点双标，骑车走路的时候希望开车的能按规则让我，自己开车的时候又想赶紧开走，所以在开车的时候尽量做到让行车和骑车的。

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还有个其实是写着写着想起来的，比如我骑车左转的时候，因为我是左转到对角那就到了，跟那些左转后要再直行的不一样，我们应该在学车的时候也学过，超车要从左边超，但是往往那些骑电瓶车的在左转的时候会从我右边超过来再往左边撇过去，如果留的空间大还好，有些电瓶车就是如果车头超过了就不管他的车屁股，如果我不减速，自行车就被刮倒了，可能的确是别人就不是人，只要不把你撞倒就无所谓，反正为了你自己不被撞倒你肯定会让的。

]]> 生活 生活 - 看剧 + 糟心事 + 规则 + 电瓶车 + 骑车 - 聊聊最近平淡的生活之看《神探狄仁杰》 - /2021/12/19/%E8%81%8A%E8%81%8A%E6%9C%80%E8%BF%91%E5%B9%B3%E6%B7%A1%E7%9A%84%E7%94%9F%E6%B4%BB%E4%B9%8B%E7%9C%8B%E3%80%8A%E7%A5%9E%E6%8E%A2%E7%8B%84%E4%BB%81%E6%9D%B0%E3%80%8B/ - 其实最近看的不止这一部，前面看了《继承者们》，《少年包青天》这些，就一起聊下，其中看《继承者们》算是个人比较喜欢，以前就有这种看剧的习惯，这个跟《一生一世》里任嘉伦说自己看《寻秦记》看了几十遍一样，我看喜欢的剧也基本上会看不止五遍，继承者们是有帅哥美女看，而且印象中剧情也挺甜的，一般情况下最好是已经有点遗忘剧情了，因为我个人觉得看剧分两种，无聊了又心情不太好，可以看些这类轻松又看过的剧，可以不完全专心地看剧，另外有心情专心看的时候，可以看一些需要思考，一些探案类的或者烧脑类。
最近看了《神探狄仁杰》，因为跟前面看的《少年包青天》都是这类古装探案剧，正好有些感想，《少年包青天》算是儿时阴影，本来是不太会去看的，正好有一次有机会跟 LD 一起看了会就也觉得比较有意思就看了下去，不得不说，以前的这些剧还是很不错的，包括剧情和演员，第一部一共是 40 集，看的过程中也发现了大概是五个案子，平均八集一个案子，整体节奏还是比较慢的，但是基本每个案子其实都是构思得很巧妙，很久以前看过但是现在基本不太记得剧情了，每个案子在前面几集的时候基本都猜不到犯案逻辑，但是在看了狄仁杰之后，发现两部剧也有比较大的差别，少年包青天相对来说逻辑性会更强一些，个人主观觉得推理的严谨性更高，可能剧本打磨上更将就一下，而狄仁杰因为要提现他的个人强项，不比少年包青天中有公孙策一时瑜亮的情节，狄仁杰中分工明确，李元芳是个武力担当，曾泰是捧哏的，相对来说是狄仁杰在案子里从始至终地推进案情，有些甚至有些玄乎，会有一些跳脱跟不合理，有些像是狄仁杰的奇遇，不过这些想法是私人的观点，并不是想要评孰优孰劣；第二个感受是不知道是不是年代关系，特别是少年包青天，每个案件的大 boss 基本都不是个完全的坏人，甚至都是比较情有可原的可怜人，因为一些特殊原因，而好几个都是包拯身边的人，这一点其实跟狄仁杰里第一个使团惊魂案件比较类似，虎敬晖也是个人物形象比较丰满的角色，不是个标签化的淡薄形象，跟金木兰的感情和反叛行动在最后都说明的缘由，而且也有随着跟狄仁杰一起办案被其影响感化，最终为了救狄仁杰而被金木兰所杀，只是这样金木兰这个角色就会有些偏执和符号化，当然剧本肯定不是能面面俱到，这样的剧本已经比现在很多流量剧的好很多了。还想到了前阵子看的《指环王》中的白袍萨鲁曼在剧中也是个比较单薄的角色，这样的电影彪炳影史也没办法把个个人物都设计得完整有血有肉，或者说这本来也是应该有侧重点，当然其实我也不觉得指环王就是绝对的最好的，因为相对来说故事情节的复杂性等真的不如西游记，只是在 86 版之后的各种乱七八糟的翻牌和乱拍已经让这个真正的王者神话故事有点力不从心，这里边有部西游记后传是个人还比较喜欢的，虽然武打动作比较鬼畜，但是剧情基本是无敌的，在西游的架构上衍生出来这么完整丰富的故事，人物角色也都有各自的出彩点。
说回狄仁杰，在这之前也看过徐克拍的几部狄仁杰的电影版，第一部刘德华拍得相对完成度更高，故事性也可圈可点，后面几部就是剧情拉胯，靠特效拉回来一点分，虽说这个也是所谓的狄仁杰宇宙的构思在里面但是现在来看基本是跟西游那些差不多，完全没有整体性可言，打一枪换一个地方，演员也没有延续性，剧情也是前后跳脱，没什么关联跟承上启下，导致质量层次不一，更不用谈什么狄仁杰宇宙了，不过这个事情也是难说，原因很多，现在资本都是更加趋利的，一些需要更长久时间才能有回报的投资是很难获得资本青睐，所以只能将重心投给选择一些流量明星，而本来应该将资源投给剧本打磨的基本就没了，再深入说也没意义了，社会现状就是这样。
还有一点感想是，以前的剧里的拍摄环境还是比较惨的，看着一些房子，甚至皇宫都是比较破旧的，地面还是石板这种，想想以前的演员的环境再想想现在的，比如成龙说的，以前他拍剧就是啪摔了，问这条有没有过，过了就直接送医院，而不是现在可能手蹭破点皮就大叫，甚至还有饭圈这些破事。

+ 聊聊最近平淡的生活之《花束般的恋爱》观后感 + /2021/12/31/%E8%81%8A%E8%81%8A%E6%9C%80%E8%BF%91%E5%B9%B3%E6%B7%A1%E7%9A%84%E7%94%9F%E6%B4%BB%E4%B9%8B%E3%80%8A%E8%8A%B1%E6%9D%9F%E8%88%AC%E7%9A%84%E6%81%8B%E7%88%B1%E3%80%8B%E8%A7%82%E5%90%8E%E6%84%9F/ + 周末在领导的提议下看了豆瓣的年度榜单，本来感觉没啥心情看的，看到主演有有村架纯就觉得可以看一下，颜值即正义嘛，男主小麦跟女主小娟（后面简称小麦跟小娟）是两个在一次非常偶然的没赶上地铁末班车事件中相识，这里得说下日本这种通宵营业的店好像挺不错的，看着也挺正常，国内估计只有酒吧之类的可以。晚上去的地方是有点暗暗的，好像也有点类似酒吧，旁边有类似于 dj 那种，然后同桌的还有除了男女主的另外一对男女，也是因为没赶上地铁末班车的，但也是陌生人，然后小麦突然看到了有个非常有名的电影人，小娟竟然也认识，然后旁边那对完全不认识，还在那吹自己看过很多电影，比如《肖申克的救赎》，于是男女主都特别鄙夷地看着他们，然后他们又去了另一个有点像泡澡的地方席地而坐，他们发现了自己的鞋子都是一样的，然后在女的去上厕所的时候，小麦暗恋的学姐也来了，然后小麦就去跟学姐他们一起坐了，小娟回来后有点不开心就说去朋友家睡，幸好小麦看出来了（他竟然看出来了，本来以为应该是没填过恋爱很木讷的），就追出去，然后就去了小麦家，到了家小娟发现小麦家的书柜上的书简直就跟她自己家的一模一样，小麦还给小娟吹了头发，一起吃烤饭团，看电影，第二天送小娟上了公交，还约好了一起看木乃伊展，然而并没有交换联系方式，但是他们还是约上了一起看了木乃伊展，在餐馆就出现了片头那一幕的来源，因为餐馆他们想一起听歌，就用有线耳机一人一个耳朵听，但是旁边就有个大叔说“你们是不是不爱音乐，左右耳朵是不一样的，只有一起听才是真正的音乐”这样的话，然后的剧情有点跳，因为是指他们一直在这家餐馆吃饭，中间有他们一起出去玩情节穿插着，也是在这他们确立了关系，可以说主体就是体现了他们非常的合拍和默契，就像一些影评说的，这部电影是说如何跟百分百合拍的人分手，然后就是正常的恋爱开始啪啪啪，一直腻在床上，也没去就业说明会，后面也有讲了一点小麦带着小娟去认识他的朋友，也把小娟介绍给了他们认识，这里算是个小伏笔，后面他们分手也有这里的人的一些关系，接下去的剧情说实话我是不太喜欢的，如果一部八分的电影只是说恋爱被现实打败的话，我觉得在我这是不合格的，但是事实也是这样，小麦其实是有家里的资助，所以后面还是按自己的喜好给一些机构画点插画，小娟则要出去工作，因为小娟家庭观念也是要让她出去有正经工作，用脚指头想也能知道肯定不顺利，然后就是暂时在一家蛋糕店工作，小麦就每天去接小娟，日子过得甜甜蜜蜜，后面小娟在自己的努力下考了个什么资格证，去了一家医院还是什么做前台行政，这中间当然就有父母来见面吃饭了，他们在开始恋爱不久就同居合租了，然后小娟父母就是来说要让她有个正经工作，对男的说的话就是人生就是责任这类的话，而小麦爸爸算是个导火索，因为小麦家里是做烟花生意的，他爸让他就做烟花生意，因为要回老家，并且小麦也不想做，所以就拒绝了，然后他爸就说不给他每个月五万的资助，这也导致了小麦需要去找工作，这个过程也是很辛苦，本来想要年前找好工作，然后事与愿违，后面有一次小娟被同事吐槽怎么从来不去团建，于是她就去了（我以为会拒绝），正在团建的时候小麦给她电话，说找到工作了，是一个创业物流公司这种，这里剧情就是我觉得比较俗套的，小麦各种被虐，累成狗，但是就像小娟爸爸说的话，人生就是责任，所以一直在坚持，但是这样也导致了跟小娟的交流也越来越少，他们原来最爱的漫画，爱玩的游戏，也只剩小娟一个人看，一个人玩，而正是这个时候，小娟说她辞掉了工作，去做一个不是太靠谱的漫画改造的密室逃脱，然后这里其实有一点后面争议很大的，就是这个工作其实是前面小麦介绍给小娟的那些朋友中一个的女朋友介绍的，而在有个剧情就是小娟有一次在这个密室逃脱的老板怀里醒过来，是在 KTV 那样的场景里，这就有很多人觉得小娟是不是出轨了，我觉得其实不那么重要，因为这个离职的事情已经让一切矛盾都摆在眼前，小麦其实是接受这种需要承担责任的生活，也想着要跟小娟结婚，但是小娟似乎还是想要过着那样理想的生活，做自己想做的事情，看自己爱看的漫画，也要小麦能像以前那样一直那么默契的有着相同的爱好，这里的触发点其实还有个是那个小麦的朋友（也就是他女朋友介绍小娟那个不靠谱工作的）的葬礼上，小麦在参加完葬礼后有挺多想倾诉的，而小娟只是想睡了，这个让小麦第二天起来都不想理小娟，只是这里我不太理解，难道这点闹情绪都不能接受吗，所谓的合拍也只是毫无限制的情况下的合拍吧，真正的生活怎么可能如此理想呢，即使没有物质生活的压力，也会有其他的各种压力和限制，在这之后其实小麦想说的是小娟是不是没有想跟自己继续在一起的想法了，而小娟觉得都不说话了，还怎么结婚呢，后面其实导演搞了个小 trick，突然放了异常婚礼，但是不是男女主的，我并不觉得这个桥段很好，在婚礼里男女主都觉得自己想要跟对方说分手了，但是当他们去了最开始一直去的餐馆的时候，一个算是一个现实映照的就是他们一直坐的位子被占了，可能也是导演想通过这个来说明他们已经回不去了，在餐馆交谈的时候，小麦其实是说他们结婚吧，并没有想前面婚礼上预设地要分手，但是小娟放弃了，不想结婚，因为不想过那样的生活了，而小麦觉得可能生活就是那样，不可能一直保持刚恋爱时候的那种感觉，生活就是责任，人生就意味着责任。

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我的一些观点也在前面说了，恋爱到婚姻，即使物质没问题，经济没问题，也会有各种各样的问题，需要一起去解决，因为结婚就意味着需要相互扶持，而不是各取所需，可能我的要求比较高，后面男女主在分手后还一起住了一段时间，我原来还在想会不会通过这个方式让他们继续去磨合同步，只是我失望了，最后给个打分可能是 5 到 6 分吧，勉强及格，好的影视剧应该源于生活高于生活，这一部可能还比不上生活。

]]> 生活 @@ -6665,29 +6754,26 @@ user3: - 聊聊这次换车牌及其他 - /2022/02/20/%E8%81%8A%E8%81%8A%E8%BF%99%E6%AC%A1%E6%8D%A2%E8%BD%A6%E7%89%8C%E5%8F%8A%E5%85%B6%E4%BB%96/ - 去年 8 月份运气比较好，摇到了车牌，本来其实应该很早就开始摇的，前面第一次换工作没注意社保断缴了一个月，也是大意失荆州，后面到了 17 年社保满两年了，好像只摇了一次，还是就没摇过，有点忘了，好像是什么原因导致那次也没摇成功，但是后面暂住证就取消了，需要居住证，居住证又要一年及以上的租房合同，并且那会买车以后也不怎么开，住的地方车位还好，但是公司车位一个月要两三千，甚至还是打车上下班比较实惠，所以也没放在心上，后面摇到房以后，也觉得应该准备起来车子，就开始办了居住证，居住证其实还可以用劳动合同，而且办起来也挺快，大概是三四月份开始摇，到 8 月份的某一天收到短信说摇到了，一开始还挺开心，不过心里抱着也不怎么开，也没怎么大放在心上，不过这里有一点就是我把那个照片直接发出去，上面有着我的身份证号，被 LD 说了一顿，以后也应该小心点，但是后面不知道是哪里看了下，说杭州上牌已经需要国六标准的车了，瞬间感觉是空欢喜了，可是有同事说是可以的，我就又打了官方的电话，结果说可以的，要先转籍，然后再做上牌。

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转籍其实是很方便的，在交警 12123 App 上申请就行了，在转籍以后，需要去实地验车，验车的话，在支付宝-杭州交警生活号里进行预约，找就近的车管所就好，需要准备一些东西，首先是行驶证，机动车登记证书，身份证，居住证，还有车上需要准备的东西是要有三脚架和反光背心，反光背心是最近几个月开始要的，问过之前去验车的只需要三脚架就好了，预约好了的话建议是赶上班时间越早越好，不然过去排队时间要很久，而且人多了以后会很乱，各种插队，而且有很多都是汽车销售，一个销售带着一堆车，我们附近那个进去的小路没一会就堵满车，进去需要先排队，然后扫码，接着交资料，这两个都排着队，如果去晚了就要排很久的队，交完资料才是排队等验车，验车就是打开引擎盖，有人会帮忙拓印发动机车架号，然后验车的会各种检查一下，车里面，还有后备箱，建议车内整理干净点，后备箱不要放杂物，检验完了之后，需要把三脚架跟反光背心放在后备箱盖子上，人在旁边拍个照，然后需要把车牌遮住后再拍个车子的照片，再之后就是去把车牌卸了，这个多吐槽下，那边应该是本来那边师傅帮忙卸车牌，结果他就说是教我们拆，虽然也不算难，但是不排除师傅有在偷懒，完了之后就是把旧车牌交回去，然后需要在手机上（警察叔叔 App）提交各种资料，包括身份证，行驶证，机动车登记证书，提交了之后就等寄车牌过来了。

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这里面缺失的一个环节就是选号了，选号杭州有两个方式，一种就是根据交管局定期发布的选号号段，可以自定义拼 20 个号，在手机上的交警 12123 App 上可以三个一组的形式提交，如果有没被选走的，就可以预选到这个了，但是这种就是也需要有一定策略，最新出的号段能选中的概率大一点，然后数字全是 8，6 这种的肯定会一早就被选走，然后如果跟我一样可以提前选下尾号，因为尾号数字影响限号，我比较有可能周五回家，所以得避开 5，0 的，第二种就是 50 选一跟以前新车选号一样，就不介绍了。第一种选中了以后可以在前面交还旧车牌的时候填上等着寄过来了，因为我是第一种选中的，第二种也可以在手机上选，也在可以在交还车牌的时候现场选。

-

总体过程其实是 LD 在各种查资料跟帮我跑来跑去，要不是 LD，估计在交管局那边我就懵逼了，各种插队，而且车子开着车子，也不能随便跑，所以建议办这个的时候有个人一起比较好。

+ 聊聊最近平淡的生活之看看老剧 + /2021/11/21/%E8%81%8A%E8%81%8A%E6%9C%80%E8%BF%91%E5%B9%B3%E6%B7%A1%E7%9A%84%E7%94%9F%E6%B4%BB%E4%B9%8B%E7%9C%8B%E7%9C%8B%E8%80%81%E5%89%A7/ + 最近因为也没什么好看的新剧和综艺所以就看看一些以前看过的老剧，我是个非常念旧的人吧，很多剧都会反反复复地看，一方面之前看过觉得好看的的确是一直记着，还有就是平时工作完了回来就想能放松下，剧情太纠结的，太烧脑的都不喜欢，也就是我常挂在口头的不喜欢看费脑子的剧，跟我不喜欢狼人杀的原因也类似。

+

前面其实是看的太阳的后裔，跟 LD 一起看的，之前其实算是看过一点，但是没有看的很完整，并且很多剧情也忘了，只是这个我我可能看得更少一点，因为最开始的时候觉得男主应该是男二，可能对长得这样的男主并且是这样的人设有点失望，感觉不是特别像个特种兵，但是由于本来也比较火，而且 LD 比较喜欢就从这个开始看了，有两个点是比较想说的

+

韩剧虽然被吐槽的很多，但是很多剧的质量，情节把控还是优于目前非常多国内剧的，相对来说剧情发展的前后承接不是那么硬凹出来的，而且人设都立得住，这个是非常重要的，很多国内剧怎么说呢，就是当爹的看起来就比儿子没大几岁，三四十岁的人去演一个十岁出头的小姑娘，除非容貌异常，比如刘晓庆这种，不然就会觉得导演在把我们观众当傻子。瞬间就没有想看下去的欲望了。

+

再一点就是情节是大众都能接受度比较高的，现在有很多普遍会找一些新奇的视角，比如卖腐，想某某令，两部都叫某某令，这其实是一个点，延伸出去就是跟前面说的一点有点类似，xx 老祖，人看着就二三十，叫 xx 老祖，（喜欢的人轻喷哈）然后名字有一堆，同一个人物一会叫这个名字，一会又叫另一个名字，然后一堆死表情。

+

因为今天有个特殊的事情发生，所以简短的写（shui）一篇了

]]> 生活 生活 - 换车牌 + 看剧 - 聊聊最近平淡的生活之看看老剧 - /2021/11/21/%E8%81%8A%E8%81%8A%E6%9C%80%E8%BF%91%E5%B9%B3%E6%B7%A1%E7%9A%84%E7%94%9F%E6%B4%BB%E4%B9%8B%E7%9C%8B%E7%9C%8B%E8%80%81%E5%89%A7/ - 最近因为也没什么好看的新剧和综艺所以就看看一些以前看过的老剧，我是个非常念旧的人吧，很多剧都会反反复复地看，一方面之前看过觉得好看的的确是一直记着，还有就是平时工作完了回来就想能放松下，剧情太纠结的，太烧脑的都不喜欢，也就是我常挂在口头的不喜欢看费脑子的剧，跟我不喜欢狼人杀的原因也类似。

-

前面其实是看的太阳的后裔，跟 LD 一起看的，之前其实算是看过一点，但是没有看的很完整，并且很多剧情也忘了，只是这个我我可能看得更少一点，因为最开始的时候觉得男主应该是男二，可能对长得这样的男主并且是这样的人设有点失望，感觉不是特别像个特种兵，但是由于本来也比较火，而且 LD 比较喜欢就从这个开始看了，有两个点是比较想说的

-

韩剧虽然被吐槽的很多，但是很多剧的质量，情节把控还是优于目前非常多国内剧的，相对来说剧情发展的前后承接不是那么硬凹出来的，而且人设都立得住，这个是非常重要的，很多国内剧怎么说呢，就是当爹的看起来就比儿子没大几岁，三四十岁的人去演一个十岁出头的小姑娘，除非容貌异常，比如刘晓庆这种，不然就会觉得导演在把我们观众当傻子。瞬间就没有想看下去的欲望了。

-

再一点就是情节是大众都能接受度比较高的，现在有很多普遍会找一些新奇的视角，比如卖腐，想某某令，两部都叫某某令，这其实是一个点，延伸出去就是跟前面说的一点有点类似，xx 老祖，人看着就二三十，叫 xx 老祖，（喜欢的人轻喷哈）然后名字有一堆，同一个人物一会叫这个名字，一会又叫另一个名字，然后一堆死表情。

-

因为今天有个特殊的事情发生，所以简短的写（shui）一篇了

+ 聊聊最近平淡的生活之看《神探狄仁杰》 + /2021/12/19/%E8%81%8A%E8%81%8A%E6%9C%80%E8%BF%91%E5%B9%B3%E6%B7%A1%E7%9A%84%E7%94%9F%E6%B4%BB%E4%B9%8B%E7%9C%8B%E3%80%8A%E7%A5%9E%E6%8E%A2%E7%8B%84%E4%BB%81%E6%9D%B0%E3%80%8B/ + 其实最近看的不止这一部，前面看了《继承者们》，《少年包青天》这些，就一起聊下，其中看《继承者们》算是个人比较喜欢，以前就有这种看剧的习惯，这个跟《一生一世》里任嘉伦说自己看《寻秦记》看了几十遍一样，我看喜欢的剧也基本上会看不止五遍，继承者们是有帅哥美女看，而且印象中剧情也挺甜的，一般情况下最好是已经有点遗忘剧情了，因为我个人觉得看剧分两种，无聊了又心情不太好，可以看些这类轻松又看过的剧，可以不完全专心地看剧，另外有心情专心看的时候，可以看一些需要思考，一些探案类的或者烧脑类。
最近看了《神探狄仁杰》，因为跟前面看的《少年包青天》都是这类古装探案剧，正好有些感想，《少年包青天》算是儿时阴影，本来是不太会去看的，正好有一次有机会跟 LD 一起看了会就也觉得比较有意思就看了下去，不得不说，以前的这些剧还是很不错的，包括剧情和演员，第一部一共是 40 集，看的过程中也发现了大概是五个案子，平均八集一个案子，整体节奏还是比较慢的，但是基本每个案子其实都是构思得很巧妙，很久以前看过但是现在基本不太记得剧情了，每个案子在前面几集的时候基本都猜不到犯案逻辑，但是在看了狄仁杰之后，发现两部剧也有比较大的差别，少年包青天相对来说逻辑性会更强一些，个人主观觉得推理的严谨性更高，可能剧本打磨上更将就一下，而狄仁杰因为要提现他的个人强项，不比少年包青天中有公孙策一时瑜亮的情节，狄仁杰中分工明确，李元芳是个武力担当，曾泰是捧哏的，相对来说是狄仁杰在案子里从始至终地推进案情，有些甚至有些玄乎，会有一些跳脱跟不合理，有些像是狄仁杰的奇遇，不过这些想法是私人的观点，并不是想要评孰优孰劣；第二个感受是不知道是不是年代关系，特别是少年包青天，每个案件的大 boss 基本都不是个完全的坏人，甚至都是比较情有可原的可怜人，因为一些特殊原因，而好几个都是包拯身边的人，这一点其实跟狄仁杰里第一个使团惊魂案件比较类似，虎敬晖也是个人物形象比较丰满的角色，不是个标签化的淡薄形象，跟金木兰的感情和反叛行动在最后都说明的缘由，而且也有随着跟狄仁杰一起办案被其影响感化，最终为了救狄仁杰而被金木兰所杀，只是这样金木兰这个角色就会有些偏执和符号化，当然剧本肯定不是能面面俱到，这样的剧本已经比现在很多流量剧的好很多了。还想到了前阵子看的《指环王》中的白袍萨鲁曼在剧中也是个比较单薄的角色，这样的电影彪炳影史也没办法把个个人物都设计得完整有血有肉，或者说这本来也是应该有侧重点，当然其实我也不觉得指环王就是绝对的最好的，因为相对来说故事情节的复杂性等真的不如西游记，只是在 86 版之后的各种乱七八糟的翻牌和乱拍已经让这个真正的王者神话故事有点力不从心，这里边有部西游记后传是个人还比较喜欢的，虽然武打动作比较鬼畜，但是剧情基本是无敌的，在西游的架构上衍生出来这么完整丰富的故事，人物角色也都有各自的出彩点。
说回狄仁杰，在这之前也看过徐克拍的几部狄仁杰的电影版，第一部刘德华拍得相对完成度更高，故事性也可圈可点，后面几部就是剧情拉胯，靠特效拉回来一点分，虽说这个也是所谓的狄仁杰宇宙的构思在里面但是现在来看基本是跟西游那些差不多，完全没有整体性可言，打一枪换一个地方，演员也没有延续性，剧情也是前后跳脱，没什么关联跟承上启下，导致质量层次不一，更不用谈什么狄仁杰宇宙了，不过这个事情也是难说，原因很多，现在资本都是更加趋利的，一些需要更长久时间才能有回报的投资是很难获得资本青睐，所以只能将重心投给选择一些流量明星，而本来应该将资源投给剧本打磨的基本就没了，再深入说也没意义了，社会现状就是这样。
还有一点感想是，以前的剧里的拍摄环境还是比较惨的，看着一些房子，甚至皇宫都是比较破旧的，地面还是石板这种，想想以前的演员的环境再想想现在的，比如成龙说的，以前他拍剧就是啪摔了，问这条有没有过，过了就直接送医院，而不是现在可能手蹭破点皮就大叫，甚至还有饭圈这些破事。

]]> 生活 @@ -6716,6 +6802,22 @@ user3: 修电脑的 + + 聊聊这次换车牌及其他 + /2022/02/20/%E8%81%8A%E8%81%8A%E8%BF%99%E6%AC%A1%E6%8D%A2%E8%BD%A6%E7%89%8C%E5%8F%8A%E5%85%B6%E4%BB%96/ + 去年 8 月份运气比较好，摇到了车牌，本来其实应该很早就开始摇的，前面第一次换工作没注意社保断缴了一个月，也是大意失荆州，后面到了 17 年社保满两年了，好像只摇了一次，还是就没摇过，有点忘了，好像是什么原因导致那次也没摇成功，但是后面暂住证就取消了，需要居住证，居住证又要一年及以上的租房合同，并且那会买车以后也不怎么开，住的地方车位还好，但是公司车位一个月要两三千，甚至还是打车上下班比较实惠，所以也没放在心上，后面摇到房以后，也觉得应该准备起来车子，就开始办了居住证，居住证其实还可以用劳动合同，而且办起来也挺快，大概是三四月份开始摇，到 8 月份的某一天收到短信说摇到了，一开始还挺开心，不过心里抱着也不怎么开，也没怎么大放在心上，不过这里有一点就是我把那个照片直接发出去，上面有着我的身份证号，被 LD 说了一顿，以后也应该小心点，但是后面不知道是哪里看了下，说杭州上牌已经需要国六标准的车了，瞬间感觉是空欢喜了，可是有同事说是可以的，我就又打了官方的电话，结果说可以的，要先转籍，然后再做上牌。

+

转籍其实是很方便的，在交警 12123 App 上申请就行了，在转籍以后，需要去实地验车，验车的话，在支付宝-杭州交警生活号里进行预约，找就近的车管所就好，需要准备一些东西，首先是行驶证，机动车登记证书，身份证，居住证，还有车上需要准备的东西是要有三脚架和反光背心，反光背心是最近几个月开始要的，问过之前去验车的只需要三脚架就好了，预约好了的话建议是赶上班时间越早越好，不然过去排队时间要很久，而且人多了以后会很乱，各种插队，而且有很多都是汽车销售，一个销售带着一堆车，我们附近那个进去的小路没一会就堵满车，进去需要先排队，然后扫码，接着交资料，这两个都排着队，如果去晚了就要排很久的队，交完资料才是排队等验车，验车就是打开引擎盖，有人会帮忙拓印发动机车架号，然后验车的会各种检查一下，车里面，还有后备箱，建议车内整理干净点，后备箱不要放杂物，检验完了之后，需要把三脚架跟反光背心放在后备箱盖子上，人在旁边拍个照，然后需要把车牌遮住后再拍个车子的照片，再之后就是去把车牌卸了，这个多吐槽下，那边应该是本来那边师傅帮忙卸车牌，结果他就说是教我们拆，虽然也不算难，但是不排除师傅有在偷懒，完了之后就是把旧车牌交回去，然后需要在手机上（警察叔叔 App）提交各种资料，包括身份证，行驶证，机动车登记证书，提交了之后就等寄车牌过来了。

+

这里面缺失的一个环节就是选号了，选号杭州有两个方式，一种就是根据交管局定期发布的选号号段，可以自定义拼 20 个号，在手机上的交警 12123 App 上可以三个一组的形式提交，如果有没被选走的，就可以预选到这个了，但是这种就是也需要有一定策略，最新出的号段能选中的概率大一点，然后数字全是 8，6 这种的肯定会一早就被选走，然后如果跟我一样可以提前选下尾号，因为尾号数字影响限号，我比较有可能周五回家，所以得避开 5，0 的，第二种就是 50 选一跟以前新车选号一样，就不介绍了。第一种选中了以后可以在前面交还旧车牌的时候填上等着寄过来了，因为我是第一种选中的，第二种也可以在手机上选，也在可以在交还车牌的时候现场选。

+

总体过程其实是 LD 在各种查资料跟帮我跑来跑去，要不是 LD，估计在交管局那边我就懵逼了，各种插队，而且车子开着车子，也不能随便跑，所以建议办这个的时候有个人一起比较好。

+]]> + + 生活 + + + 生活 + 换车牌 + + 聊聊那些加塞狗 /2021/01/17/%E8%81%8A%E8%81%8A%E9%82%A3%E4%BA%9B%E5%8A%A0%E5%A1%9E%E7%8B%97/ @@ -6762,21 +6864,15 @@ user3: - 记一个容器中 dubbo 注册的小知识点 - /2022/10/09/%E8%AE%B0%E4%B8%80%E4%B8%AA%E5%AE%B9%E5%99%A8%E4%B8%AD-dubbo-%E6%B3%A8%E5%86%8C%E7%9A%84%E5%B0%8F%E7%9F%A5%E8%AF%86%E7%82%B9/ - 在目前环境下使用容器部署Java应用还是挺普遍的，但是有一些问题也是随之而来需要解决的，比如容器中应用的dubbo注册，在比较早的版本的dubbo中，就是简单地获取网卡的ip地址。
具体代码在这个方法里 com.alibaba.dubbo.config.ServiceConfig#doExportUrlsFor1Protocol

-
private void doExportUrlsFor1Protocol(ProtocolConfig protocolConfig, List<URL> registryURLs) {
        String name = protocolConfig.getName();
        if (name == null || name.length() == 0) {
            name = "dubbo";
        }

        String host = protocolConfig.getHost();
        if (provider != null && (host == null || host.length() == 0)) {
            host = provider.getHost();
        }
        boolean anyhost = false;
        if (NetUtils.isInvalidLocalHost(host)) {
            anyhost = true;
            try {
                host = InetAddress.getLocalHost().getHostAddress();
            } catch (UnknownHostException e) {
                logger.warn(e.getMessage(), e);
            }
            if (NetUtils.isInvalidLocalHost(host)) {
                if (registryURLs != null && registryURLs.size() > 0) {
                    for (URL registryURL : registryURLs) {
                        try {
                            Socket socket = new Socket();
                            try {
                                SocketAddress addr = new InetSocketAddress(registryURL.getHost(), registryURL.getPort());
                                socket.connect(addr, 1000);
                                host = socket.getLocalAddress().getHostAddress();
                                break;
                            } finally {
                                try {
                                    socket.close();
                                } catch (Throwable e) {}
                            }
                        } catch (Exception e) {
                            logger.warn(e.getMessage(), e);
                        }
                    }
                }
                if (NetUtils.isInvalidLocalHost(host)) {
                    host = NetUtils.getLocalHost();
                }
            }
        }
-

通过jdk自带的方法 java.net.InetAddress#getLocalHost来获取本机地址，这样子对于容器来讲，获取到容器内部ip注册上去其实是没办法被调用到的，
而在之后的版本中例如dubbo 2.6.5，则可以通过在docker中设置环境变量的形式来注入docker所在的宿主机地址，
代码同样在com.alibaba.dubbo.config.ServiceConfig#doExportUrlsFor1Protocol这个方法中，但是获取host的方法变成了 com.alibaba.dubbo.config.ServiceConfig#findConfigedHosts

-
private String findConfigedHosts(ProtocolConfig protocolConfig, List<URL> registryURLs, Map<String, String> map) {
        boolean anyhost = false;

        String hostToBind = getValueFromConfig(protocolConfig, Constants.DUBBO_IP_TO_BIND);
        if (hostToBind != null && hostToBind.length() > 0 && isInvalidLocalHost(hostToBind)) {
            throw new IllegalArgumentException("Specified invalid bind ip from property:" + Constants.DUBBO_IP_TO_BIND + ", value:" + hostToBind);
        }

        // if bind ip is not found in environment, keep looking up
        if (hostToBind == null || hostToBind.length() == 0) {
            hostToBind = protocolConfig.getHost();
            if (provider != null && (hostToBind == null || hostToBind.length() == 0)) {
                hostToBind = provider.getHost();
            }
            if (isInvalidLocalHost(hostToBind)) {
                anyhost = true;
                try {
                    hostToBind = InetAddress.getLocalHost().getHostAddress();
                } catch (UnknownHostException e) {
                    logger.warn(e.getMessage(), e);
                }
                if (isInvalidLocalHost(hostToBind)) {
                    if (registryURLs != null && !registryURLs.isEmpty()) {
                        for (URL registryURL : registryURLs) {
                            if (Constants.MULTICAST.equalsIgnoreCase(registryURL.getParameter("registry"))) {
                                // skip multicast registry since we cannot connect to it via Socket
                                continue;
                            }
                            try {
                                Socket socket = new Socket();
                                try {
                                    SocketAddress addr = new InetSocketAddress(registryURL.getHost(), registryURL.getPort());
                                    socket.connect(addr, 1000);
                                    hostToBind = socket.getLocalAddress().getHostAddress();
                                    break;
                                } finally {
                                    try {
                                        socket.close();
                                    } catch (Throwable e) {
                                    }
                                }
                            } catch (Exception e) {
                                logger.warn(e.getMessage(), e);
                            }
                        }
                    }
                    if (isInvalidLocalHost(hostToBind)) {
                        hostToBind = getLocalHost();
                    }
                }
            }
        }

        map.put(Constants.BIND_IP_KEY, hostToBind);

        // registry ip is not used for bind ip by default
        String hostToRegistry = getValueFromConfig(protocolConfig, Constants.DUBBO_IP_TO_REGISTRY);
        if (hostToRegistry != null && hostToRegistry.length() > 0 && isInvalidLocalHost(hostToRegistry)) {
            throw new IllegalArgumentException("Specified invalid registry ip from property:" + Constants.DUBBO_IP_TO_REGISTRY + ", value:" + hostToRegistry);
        } else if (hostToRegistry == null || hostToRegistry.length() == 0) {
            // bind ip is used as registry ip by default
            hostToRegistry = hostToBind;
        }

        map.put(Constants.ANYHOST_KEY, String.valueOf(anyhost));

        return hostToRegistry;
    }
-

String hostToRegistry = getValueFromConfig(protocolConfig, Constants.DUBBO_IP_TO_REGISTRY);
就是这一行，

-
private String getValueFromConfig(ProtocolConfig protocolConfig, String key) {
    String protocolPrefix = protocolConfig.getName().toUpperCase() + "_";
    String port = ConfigUtils.getSystemProperty(protocolPrefix + key);
    if (port == null || port.length() == 0) {
        port = ConfigUtils.getSystemProperty(key);
    }
    return port;
}
-

也就是配置了DUBBO_IP_TO_REGISTRY这个环境变量

+ 记录一次折腾自组 nas 的失败经历-续篇 + /2023/05/14/%E8%AE%B0%E5%BD%95%E4%B8%80%E6%AC%A1%E6%8A%98%E8%85%BE%E8%87%AA%E7%BB%84-nas-%E7%9A%84%E5%A4%B1%E8%B4%A5%E7%BB%8F%E5%8E%86-%E7%BB%AD%E7%AF%87/ + 上次记录了前面的一些失败经验，最重要的点还没提到，先发一下配置单
cpu i7-8700k
主板 技嘉 z370m-ds3h
内存 光威 ddr4-3200Mhz
硬盘 京东京造 512g
散热 利民 PA120
电源 先马平头哥额定 550w
机箱 爱国者半岛铁盒 F10
cpu 跟主板是板 U 套装某鱼买的二手的，说实话如果不是后面的网卡问题，这个板 U 套装还是比较良心的，一次点亮（以前没组装过，还不知道有点不亮的情况，后面就体验到了），但是这里就出现了一个很大的坑，因为我这次是想要在裸机上装 exsi，然后看到了群里苏大的一篇 exsi 最新版本 8 的镜像构建文章，硬件也不是很旧，就想着用最新的系统，镜像写进 ventoy 后启动发现报错找不到网卡，这会我还没发现问题的严重性，想着按一些教程打个驱动进去就好了，而且我还以为驱动只要跟镜像 iso 放一块就行了，后面随着深入了解就知道要把驱动打进 iso 镜像里，但是找了一通发现我的网卡是瑞昱的 RTL8168，这个型号的板载网卡，走的是 PCIE 通道，有驱动的最后支持的系统是 exsi6.7，再往后就没有完整打包好的社区版驱动可以使用了，所以这是踩的第一个大坑，照理这个事情也没这么大问题，退回来 6.7 不就行了，问题恰恰是我那时候还不懂，又想用更新的系统，所以就在网上搜了半天，发现华硕的 z370 tuf gaming 系列是用的 intel 的网卡，社区的网卡驱动对 intel 的网卡支持比较好，所以想着还是换个主板算了，其实还有不少选择，买个 pcie 的 intel 网卡或者 usb 的其他千兆网卡，有个说出来可能比较难理解的，usb 的社区版驱动反而比 pcie 的支持得广，pcie 的还是只支持 intel 的。
在某多多上买了个二手的 z370 tuf gaming 主板，结果踩到了第二个坑，可能比较小白的经验是，前面因为买的板 U 套装，他 cpu 是直接装在主板上邮给我的，所以我没装过 cpu，这回买来这块二手的华硕主板对我来说是第一次装 cpu，不过好像难度不大，一下就装好了，但结果就很惨，就是点不亮，散热器风扇会转，但是键盘灯不亮，而且散热风扇还转得很快，我还试着把内存换个槽，结果四个槽都不行，这个时候就很害怕了，看上去这家店也不像是太坑的，毕竟大量地在卖，所以我就很担心是不是前面 cpu 装的不对，把针脚什么的搞坏了，这个时候已经搞到晚上很迟了，但还是忍不住又装回原来的技嘉主板试了下，幸好能正常点亮，算了，还是就用技嘉这块主板吧，接口配置稍微差了点，网卡也不支持最新版的 exsi，所以我就用 vmware workstation 了，在 win10 的 lstc 上装一个，有点性能损耗就损耗吧，反正我也不暴力使用，能跑跑其他 Ubuntu 虚拟机啥的就可以了，或者回到前面的结果，可以装 6.7 的，网上带了瑞昱网卡驱动的 exsi6.7 的镜像挺多的，可以自己打一个或者用别人打包好的。折腾不止踩坑不止呐。

]]> - java + nas - dubbo + nas @@ -6792,15 +6888,21 @@ user3: - 记录一次折腾自组 nas 的失败经历-续篇 - /2023/05/14/%E8%AE%B0%E5%BD%95%E4%B8%80%E6%AC%A1%E6%8A%98%E8%85%BE%E8%87%AA%E7%BB%84-nas-%E7%9A%84%E5%A4%B1%E8%B4%A5%E7%BB%8F%E5%8E%86-%E7%BB%AD%E7%AF%87/ - 上次记录了前面的一些失败经验，最重要的点还没提到，先发一下配置单
cpu i7-8700k
主板 技嘉 z370m-ds3h
内存 光威 ddr4-3200Mhz
硬盘 京东京造 512g
散热 利民 PA120
电源 先马平头哥额定 550w
机箱 爱国者半岛铁盒 F10
cpu 跟主板是板 U 套装某鱼买的二手的，说实话如果不是后面的网卡问题，这个板 U 套装还是比较良心的，一次点亮（以前没组装过，还不知道有点不亮的情况，后面就体验到了），但是这里就出现了一个很大的坑，因为我这次是想要在裸机上装 exsi，然后看到了群里苏大的一篇 exsi 最新版本 8 的镜像构建文章，硬件也不是很旧，就想着用最新的系统，镜像写进 ventoy 后启动发现报错找不到网卡，这会我还没发现问题的严重性，想着按一些教程打个驱动进去就好了，而且我还以为驱动只要跟镜像 iso 放一块就行了，后面随着深入了解就知道要把驱动打进 iso 镜像里，但是找了一通发现我的网卡是瑞昱的 RTL8168，这个型号的板载网卡，走的是 PCIE 通道，有驱动的最后支持的系统是 exsi6.7，再往后就没有完整打包好的社区版驱动可以使用了，所以这是踩的第一个大坑，照理这个事情也没这么大问题，退回来 6.7 不就行了，问题恰恰是我那时候还不懂，又想用更新的系统，所以就在网上搜了半天，发现华硕的 z370 tuf gaming 系列是用的 intel 的网卡，社区的网卡驱动对 intel 的网卡支持比较好，所以想着还是换个主板算了，其实还有不少选择，买个 pcie 的 intel 网卡或者 usb 的其他千兆网卡，有个说出来可能比较难理解的，usb 的社区版驱动反而比 pcie 的支持得广，pcie 的还是只支持 intel 的。
在某多多上买了个二手的 z370 tuf gaming 主板，结果踩到了第二个坑，可能比较小白的经验是，前面因为买的板 U 套装，他 cpu 是直接装在主板上邮给我的，所以我没装过 cpu，这回买来这块二手的华硕主板对我来说是第一次装 cpu，不过好像难度不大，一下就装好了，但结果就很惨，就是点不亮，散热器风扇会转，但是键盘灯不亮，而且散热风扇还转得很快，我还试着把内存换个槽，结果四个槽都不行，这个时候就很害怕了，看上去这家店也不像是太坑的，毕竟大量地在卖，所以我就很担心是不是前面 cpu 装的不对，把针脚什么的搞坏了，这个时候已经搞到晚上很迟了，但还是忍不住又装回原来的技嘉主板试了下，幸好能正常点亮，算了，还是就用技嘉这块主板吧，接口配置稍微差了点，网卡也不支持最新版的 exsi，所以我就用 vmware workstation 了，在 win10 的 lstc 上装一个，有点性能损耗就损耗吧，反正我也不暴力使用，能跑跑其他 Ubuntu 虚拟机啥的就可以了，或者回到前面的结果，可以装 6.7 的，网上带了瑞昱网卡驱动的 exsi6.7 的镜像挺多的，可以自己打一个或者用别人打包好的。折腾不止踩坑不止呐。

+ 记一个容器中 dubbo 注册的小知识点 + /2022/10/09/%E8%AE%B0%E4%B8%80%E4%B8%AA%E5%AE%B9%E5%99%A8%E4%B8%AD-dubbo-%E6%B3%A8%E5%86%8C%E7%9A%84%E5%B0%8F%E7%9F%A5%E8%AF%86%E7%82%B9/ + 在目前环境下使用容器部署Java应用还是挺普遍的，但是有一些问题也是随之而来需要解决的，比如容器中应用的dubbo注册，在比较早的版本的dubbo中，就是简单地获取网卡的ip地址。
具体代码在这个方法里 com.alibaba.dubbo.config.ServiceConfig#doExportUrlsFor1Protocol

+
private void doExportUrlsFor1Protocol(ProtocolConfig protocolConfig, List<URL> registryURLs) {
        String name = protocolConfig.getName();
        if (name == null || name.length() == 0) {
            name = "dubbo";
        }

        String host = protocolConfig.getHost();
        if (provider != null && (host == null || host.length() == 0)) {
            host = provider.getHost();
        }
        boolean anyhost = false;
        if (NetUtils.isInvalidLocalHost(host)) {
            anyhost = true;
            try {
                host = InetAddress.getLocalHost().getHostAddress();
            } catch (UnknownHostException e) {
                logger.warn(e.getMessage(), e);
            }
            if (NetUtils.isInvalidLocalHost(host)) {
                if (registryURLs != null && registryURLs.size() > 0) {
                    for (URL registryURL : registryURLs) {
                        try {
                            Socket socket = new Socket();
                            try {
                                SocketAddress addr = new InetSocketAddress(registryURL.getHost(), registryURL.getPort());
                                socket.connect(addr, 1000);
                                host = socket.getLocalAddress().getHostAddress();
                                break;
                            } finally {
                                try {
                                    socket.close();
                                } catch (Throwable e) {}
                            }
                        } catch (Exception e) {
                            logger.warn(e.getMessage(), e);
                        }
                    }
                }
                if (NetUtils.isInvalidLocalHost(host)) {
                    host = NetUtils.getLocalHost();
                }
            }
        }
+

通过jdk自带的方法 java.net.InetAddress#getLocalHost来获取本机地址，这样子对于容器来讲，获取到容器内部ip注册上去其实是没办法被调用到的，
而在之后的版本中例如dubbo 2.6.5，则可以通过在docker中设置环境变量的形式来注入docker所在的宿主机地址，
代码同样在com.alibaba.dubbo.config.ServiceConfig#doExportUrlsFor1Protocol这个方法中，但是获取host的方法变成了 com.alibaba.dubbo.config.ServiceConfig#findConfigedHosts

+
private String findConfigedHosts(ProtocolConfig protocolConfig, List<URL> registryURLs, Map<String, String> map) {
        boolean anyhost = false;

        String hostToBind = getValueFromConfig(protocolConfig, Constants.DUBBO_IP_TO_BIND);
        if (hostToBind != null && hostToBind.length() > 0 && isInvalidLocalHost(hostToBind)) {
            throw new IllegalArgumentException("Specified invalid bind ip from property:" + Constants.DUBBO_IP_TO_BIND + ", value:" + hostToBind);
        }

        // if bind ip is not found in environment, keep looking up
        if (hostToBind == null || hostToBind.length() == 0) {
            hostToBind = protocolConfig.getHost();
            if (provider != null && (hostToBind == null || hostToBind.length() == 0)) {
                hostToBind = provider.getHost();
            }
            if (isInvalidLocalHost(hostToBind)) {
                anyhost = true;
                try {
                    hostToBind = InetAddress.getLocalHost().getHostAddress();
                } catch (UnknownHostException e) {
                    logger.warn(e.getMessage(), e);
                }
                if (isInvalidLocalHost(hostToBind)) {
                    if (registryURLs != null && !registryURLs.isEmpty()) {
                        for (URL registryURL : registryURLs) {
                            if (Constants.MULTICAST.equalsIgnoreCase(registryURL.getParameter("registry"))) {
                                // skip multicast registry since we cannot connect to it via Socket
                                continue;
                            }
                            try {
                                Socket socket = new Socket();
                                try {
                                    SocketAddress addr = new InetSocketAddress(registryURL.getHost(), registryURL.getPort());
                                    socket.connect(addr, 1000);
                                    hostToBind = socket.getLocalAddress().getHostAddress();
                                    break;
                                } finally {
                                    try {
                                        socket.close();
                                    } catch (Throwable e) {
                                    }
                                }
                            } catch (Exception e) {
                                logger.warn(e.getMessage(), e);
                            }
                        }
                    }
                    if (isInvalidLocalHost(hostToBind)) {
                        hostToBind = getLocalHost();
                    }
                }
            }
        }

        map.put(Constants.BIND_IP_KEY, hostToBind);

        // registry ip is not used for bind ip by default
        String hostToRegistry = getValueFromConfig(protocolConfig, Constants.DUBBO_IP_TO_REGISTRY);
        if (hostToRegistry != null && hostToRegistry.length() > 0 && isInvalidLocalHost(hostToRegistry)) {
            throw new IllegalArgumentException("Specified invalid registry ip from property:" + Constants.DUBBO_IP_TO_REGISTRY + ", value:" + hostToRegistry);
        } else if (hostToRegistry == null || hostToRegistry.length() == 0) {
            // bind ip is used as registry ip by default
            hostToRegistry = hostToBind;
        }

        map.put(Constants.ANYHOST_KEY, String.valueOf(anyhost));

        return hostToRegistry;
    }
+

String hostToRegistry = getValueFromConfig(protocolConfig, Constants.DUBBO_IP_TO_REGISTRY);
就是这一行，

+
private String getValueFromConfig(ProtocolConfig protocolConfig, String key) {
    String protocolPrefix = protocolConfig.getName().toUpperCase() + "_";
    String port = ConfigUtils.getSystemProperty(protocolPrefix + key);
    if (port == null || port.length() == 0) {
        port = ConfigUtils.getSystemProperty(key);
    }
    return port;
}
+

也就是配置了DUBBO_IP_TO_REGISTRY这个环境变量

]]> - nas + java - nas + dubbo @@ -6859,22 +6961,6 @@ user3: stream - - 记录下 phpunit 的入门使用方法之setUp和tearDown - /2022/10/23/%E8%AE%B0%E5%BD%95%E4%B8%8B-phpunit-%E7%9A%84%E5%85%A5%E9%97%A8%E4%BD%BF%E7%94%A8%E6%96%B9%E6%B3%95%E4%B9%8BsetUp%E5%92%8CtearDown/ - 可能是太久没写单测了，写个单测发现不符合预期，后来验证下才反应过来
我们来看下demo

-
class RenameTest extends TestCase
{
    public function setUp(): void
    {
        var_dump("setUp");
    }

    public function test1()
    {
        var_dump("test1");
        assertEquals(1, 1);
    }

    public function test2()
    {
        var_dump("test2");
        assertEquals(1, 1);
    }

    protected function tearDown(): void
    {
        var_dump("tearDown");
    }
}
-

因为我是想写个重命名的小工具，希望通过setUp和tearDown做一些文件初始化和清理工作，但是我把两个case的初始化跟清理工作写到了单个setUp和tearDown中，这样就出现了异常的错误
通过上面的示例代码，可以看到执行结果

-
❯ vendor/bin/phpunit
PHPUnit 9.5.25 by Sebastian Bergmann and contributors.

.string(5) "setUp"
string(5) "test1"
string(8) "tearDown"
.                                                                  2 / 2 (100%)string(5) "setUp"
string(5) "test2"
string(8) "tearDown"


Time: 00:00.005, Memory: 6.00 MB

OK (2 tests, 2 assertions)
-

其实就是很简单的会在每个test方法前后都执行setUp和tearDown

-]]> - - php - - - php - - 记录下 phpunit 的入门使用方法 /2022/10/16/%E8%AE%B0%E5%BD%95%E4%B8%8B-phpunit-%E7%9A%84%E5%85%A5%E9%97%A8%E4%BD%BF%E7%94%A8%E6%96%B9%E6%B3%95/ @@ -6888,6 +6974,22 @@ user3: 
<?php

// require_once 'vendor/autoload.php';

use PHPUnit\Framework\TestCase;
use Nicksxs\PhpRename\Rename;
use function PHPUnit\Framework\assertEquals;

class RenameTest extends TestCase 
{
    public function setUp() :void
    {
        $myfile = fopen(__DIR__ . DIRECTORY_SEPARATOR . "oldfile.txt", "w") or die("Unable to open file!");
        $txt = "file test1\n";
        fwrite($myfile, $txt);
        fclose($myfile);
    }
    public function testRename()
    {
        Rename::renameSingleFile(__DIR__ . DIRECTORY_SEPARATOR . "oldfile.txt", "newfile");
        assertEquals(is_file(__DIR__ . DIRECTORY_SEPARATOR . "newfile.txt"), true);
    }

    protected function tearDown(): void
    {
        unlink(__DIR__ . DIRECTORY_SEPARATOR . "newfile.txt");
    }
}

setUp 跟 tearDown 就是初始化跟结束清理的，但是注意如果不指明 __DIR__ ,待会的目录就会在执行 vendor/bin/phpunit 下面，
或者也可以指定在一个 tmp/ 目录下
最后就可以通过vendor/bin/phpunit 来执行测试
执行结果

❯ vendor/bin/phpunit
PHPUnit 9.5.25 by Sebastian Bergmann and contributors.

.                                                                   1 / 1 (100%)

Time: 00:00.005, Memory: 6.00 MB

OK (1 test, 1 assertion)
+]]> + + php + + + php + + + + 记录下 phpunit 的入门使用方法之setUp和tearDown + /2022/10/23/%E8%AE%B0%E5%BD%95%E4%B8%8B-phpunit-%E7%9A%84%E5%85%A5%E9%97%A8%E4%BD%BF%E7%94%A8%E6%96%B9%E6%B3%95%E4%B9%8BsetUp%E5%92%8CtearDown/ + 可能是太久没写单测了，写个单测发现不符合预期，后来验证下才反应过来
我们来看下demo

+
class RenameTest extends TestCase
{
    public function setUp(): void
    {
        var_dump("setUp");
    }

    public function test1()
    {
        var_dump("test1");
        assertEquals(1, 1);
    }

    public function test2()
    {
        var_dump("test2");
        assertEquals(1, 1);
    }

    protected function tearDown(): void
    {
        var_dump("tearDown");
    }
}
+

因为我是想写个重命名的小工具，希望通过setUp和tearDown做一些文件初始化和清理工作，但是我把两个case的初始化跟清理工作写到了单个setUp和tearDown中，这样就出现了异常的错误
通过上面的示例代码，可以看到执行结果

+
❯ vendor/bin/phpunit
PHPUnit 9.5.25 by Sebastian Bergmann and contributors.

.string(5) "setUp"
string(5) "test1"
string(8) "tearDown"
.                                                                  2 / 2 (100%)string(5) "setUp"
string(5) "test2"
string(8) "tearDown"


Time: 00:00.005, Memory: 6.00 MB

OK (2 tests, 2 assertions)
+

其实就是很简单的会在每个test方法前后都执行setUp和tearDown

]]> php @@ -7050,21 +7152,6 @@ user3: 生活 - - 阿里云 rds 主从延迟排查 - /2023/12/24/%E9%98%BF%E9%87%8C%E4%BA%91-rds-%E4%B8%BB%E4%BB%8E%E5%BB%B6%E8%BF%9F%E6%8E%92%E6%9F%A5/ - 昨天同学问我是不是数据库主从延迟有点高，可能有一分多钟，然后我就去看了rds 的监控，发现主实例上的监控显示的延迟才 1.2 秒，而且是最高 1.2 秒，感觉这样的话应该就没啥问题，然后同学跟我说他加了日志，大致的逻辑是主库数据落库以后就会发一条 mq 消息出来，然后消费者接收到以后回去从库查一下这个数据，结果发现延迟了 90 多秒才查到数据，这种情况比较可能的猜测是阿里云这个监控的逻辑可能是从库在获得第一条同步数据的时候，而不是最终同步完成，但是跟阿里云咨询了并不是，使用的就是 show slave status 结果里的 Seconds_Behind_Master 指标，那这第一种情况就否定掉了，这里其实是犯了个错误，应该去从库看这个延迟的，不过对于阿里云来说在 rds 监控是看不到从库的监控的，只能到 das，也就是阿里云的数据库自治服务可以看到，这里能看到从库的延迟监控，发现的确有这么高，这样就要考虑为啥会出现这种情况，阿里云同学反馈的是这段时间的 iops 很高，并且 cpu 也比较高，让我排查下 binlog，这里就碰到一个小问题，阿里云 rds 的线上实例我们没法在本地连接，并且密码也是在代码里加密过的，去服务器上连接一方面需要装 mysql 客户端，另一方面是怕拉取日志会有性能影响，幸好阿里云这点做的比较好，在 rds 的”备份恢复”–> “日志备份”菜单里可以找到binlog 文件， 在这里其实大致就发现了问题，因为出问题的时间段内升成 binlog 的量大大超过其他时间段，然后通过内网下载后就可以对 binlog 进行分析了，这里我们用到了 mysqlbinlog 工具，主要就是找具体是哪些写入导致这个问题，mysqlbinlog 可以在 mysql 官网下载 mysql 的压缩包，注意是压缩包，这样解压了直接用就好了，不用完整安装 mysql，一般我们需要对 binlog 进行 base64 的反编码，

-
./mysqlbinlog -vv --base64-output=decode-rows mysql-bin.xxxx | less
- -

这样查看里面的具体信息，发现是大量的 insert 数据，再经过排查发现同一个 binlog 文件近 500M 全是同一个表的数据插入，再根据表对应的业务查找发现是有个业务逻辑会在这个时间点全量删除后在生成插入数据，后续需要进行优化

-]]> - - Mysql - - - mysql - - 难得的大扫除 /2022/04/10/%E9%9A%BE%E5%BE%97%E7%9A%84%E5%A4%A7%E6%89%AB%E9%99%A4/ @@ -7079,103 +7166,18 @@ user3: - 聊一聊 https 的逻辑 - /2024/03/10/%E8%81%8A%E4%B8%80%E8%81%8A-https-%E7%9A%84%E9%80%BB%E8%BE%91/ - https 和 tls

https 我原本的理解来自于几个概念

-

第一个是非对称加密

-

也就是公钥可以公开在网上，然后用公钥加密，由私有的私钥进行解密，然后就对 https 有了初步的偏颇的概念，就是浏览器用公钥进行加密，服务器端用私钥进行解密，这里再仔细想想会延伸出来几个问题，也是逐步完善我的后续理解

-

第二个就是非对称加密以后的对称加密

-

因为对加密的理解是超大的质数（这个还来源于大学的数据结构老师）相乘后会很难做质因数分解，比如最大的质数2^82,589,933 − 1，用十进制表示有24,862,048位，用现在计算机来算也是非常难的，那如果一直采用非对称加密，这个效率也会比较低，所以在网上查了一番之后知道了是先采用非对称加密，然后再用对称加密，因为非对称加密先有了安全保证，后续的消息就可以用对称加密的方式来进行传输安全了

-

第三个是最近一次看到的

-

也是一直缺乏思考的问题，因为 https 我们在使用的时候都会购买证书或者使用免费的证书，那这个证书和前面说的公私钥是什么关系，好像一直是悬空的，没想过这中间的相关性，证书究竟是怎么起作用的

-

下面是摘自 cloudflare 的 tls 握手流程，把证书的使用方式说的比较明白了

-

TLS 握手是由客户端和服务器交换的一系列数据报或消息。TLS 握手涉及多个步骤，因为客户端和服务器要交换完成握手和进行进一步对话所需的信息。

-

TLS 握手中的确切步骤将根据所使用的密钥交换算法的种类和双方支持的密码套件而有所不同。RSA 密钥交换算法虽然现在被认为不安全，但曾在 1.3 之前的 TLS 版本中使用。大致如下：

-
    -
  1. “客户端问候（client hello）” 消息： 客户端通过向服务器发送“问候”消息来开始握手。该消息将包含客户端支持的 TLS 版本，支持的密码套件，以及称为一串称为“客户端随机数（client random）”的随机字节。
    2. -
  2. “服务器问候（server hello）”消息： 作为对 client hello 消息的回复，服务器发送一条消息，内含服务器的 SSL 证书、服务器选择的密码套件，以及“服务器随机数（server random）”，即由服务器生成的另一串随机字节。
    3. -
  3. 身份验证： 客户端使用颁发该证书的证书颁发机构验证服务器的 SSL 证书。此举确认服务器是其声称的身份，且客户端正在与该域的实际所有者进行交互。
    4. -
  4. 预主密钥： 客户端再发送一串随机字节，即“预主密钥（premaster secret）”。预主密钥是使用公钥加密的，只能使用服务器的私钥解密。（客户端从服务器的 SSL 证书中获得公钥。）
    5. -
  5. 私钥被使用：服务器对预主密钥进行解密。
    6. -
  6. 生成会话密钥：客户端和服务器均使用客户端随机数、服务器随机数和预主密钥生成会话密钥。双方应得到相同的结果。
    7. -
  7. 客户端就绪：客户端发送一条“已完成”消息，该消息用会话密钥加密。
    8. -
  8. 服务器就绪：服务器发送一条“已完成”消息，该消息用会话密钥加密。
    9. -
  9. 实现安全对称加密：已完成握手，并使用会话密钥继续进行通信。
    10. -
-

为了学习这个过程，我们尝试用 Chrome 的自带抓包工具，以往这是可以通过在 Chrome 地址栏中输入 chrome://net-internals/#events 来打开，现在变成了两部分，chrome://net-export/ 这里可以开始抓包，然后会记录下一个抓包日志文件里，

-

-

然后再打开

-

https://netlog-viewer.appspot.com/#events 来查看具体的日志

-

这里我们以打开百度为例，即在打开 chrome://net-export/ 并启动抓包后，再在一个新 tab 打开 baidu.com，然后关闭

-

将日志文件在 https://netlog-viewer.appspot.com/#events 打开

-

-

这里可以看到

-

-

--> type 1 表示现在 tls 握手进行到哪一步了, 对应的值表示不同的阶段

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
代码(type)释义
0HelloRequest
1ClientHello
2ServerHello
11Certificate
12ServerKeyExchange
13CertificateRequest
14ServerHelloDone
15CertificateVerify
16ClientKeyExchange
20Finished
-

具体的对应关系是在这边

-

比如 11 之后表示我们从服务端收到了证书

-

-

然后就要去验证证书的可靠性

-

-

后面是验证后的结果

-

-

-

最后就是交换对称会话秘钥然后完成握手

-

+ 阿里云 rds 主从延迟排查 + /2023/12/24/%E9%98%BF%E9%87%8C%E4%BA%91-rds-%E4%B8%BB%E4%BB%8E%E5%BB%B6%E8%BF%9F%E6%8E%92%E6%9F%A5/ + 昨天同学问我是不是数据库主从延迟有点高，可能有一分多钟，然后我就去看了rds 的监控，发现主实例上的监控显示的延迟才 1.2 秒，而且是最高 1.2 秒，感觉这样的话应该就没啥问题，然后同学跟我说他加了日志，大致的逻辑是主库数据落库以后就会发一条 mq 消息出来，然后消费者接收到以后回去从库查一下这个数据，结果发现延迟了 90 多秒才查到数据，这种情况比较可能的猜测是阿里云这个监控的逻辑可能是从库在获得第一条同步数据的时候，而不是最终同步完成，但是跟阿里云咨询了并不是，使用的就是 show slave status 结果里的 Seconds_Behind_Master 指标，那这第一种情况就否定掉了，这里其实是犯了个错误，应该去从库看这个延迟的，不过对于阿里云来说在 rds 监控是看不到从库的监控的，只能到 das，也就是阿里云的数据库自治服务可以看到，这里能看到从库的延迟监控，发现的确有这么高，这样就要考虑为啥会出现这种情况，阿里云同学反馈的是这段时间的 iops 很高，并且 cpu 也比较高，让我排查下 binlog，这里就碰到一个小问题，阿里云 rds 的线上实例我们没法在本地连接，并且密码也是在代码里加密过的，去服务器上连接一方面需要装 mysql 客户端，另一方面是怕拉取日志会有性能影响，幸好阿里云这点做的比较好，在 rds 的”备份恢复”–> “日志备份”菜单里可以找到binlog 文件， 在这里其实大致就发现了问题，因为出问题的时间段内升成 binlog 的量大大超过其他时间段，然后通过内网下载后就可以对 binlog 进行分析了，这里我们用到了 mysqlbinlog 工具，主要就是找具体是哪些写入导致这个问题，mysqlbinlog 可以在 mysql 官网下载 mysql 的压缩包，注意是压缩包，这样解压了直接用就好了，不用完整安装 mysql，一般我们需要对 binlog 进行 base64 的反编码，

+
./mysqlbinlog -vv --base64-output=decode-rows mysql-bin.xxxx | less
+ +

这样查看里面的具体信息，发现是大量的 insert 数据，再经过排查发现同一个 binlog 文件近 500M 全是同一个表的数据插入，再根据表对应的业务查找发现是有个业务逻辑会在这个时间点全量删除后在生成插入数据，后续需要进行优化

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}标签: dubbo | Nicksxs's Blog

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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}标签: dubbo | Nicksxs's Blog

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2022
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a:hover{background:var(--body-bg-color)}.main-inner{background:var(--content-bg-color);box-shadow:initial;padding:40px}@media (max-width:991px){.main-inner{padding:20px}}.sub-menu{border-bottom:1px solid #ddd}.post-block:first-of-type{padding-top:40px}@media (max-width:767px){.pagination{margin-bottom:10px}}标签: windows | Nicksxs's Blog

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