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,
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<p>今天是农历初八了，年前一个月的时候就准备做下今年的年终总结，可是写了一点觉得太情绪化了，希望后面写个平淡点的，正好最近技术方面还没有看到一个完整成文的内容，就来写一下这一年的总结，尽量少写一点太情绪化的东西。</p>
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<h3 id="跳槽"><a href="#跳槽" class="headerlink" title="跳槽"></a>跳槽</h3><p>年初换了个公司，也算换了个环境，跟前公司不太一样，做的事情方向也不同，可能是侧重点不同，一开始有些不适应，主要是压力上，会觉得压力比较大，但是总体来说与人相处的部分还是不错的，做的技术方向还是Java，这里也感谢前东家让我有机会转了Java，个人感觉杭州整个市场还是Java比较有优势，不过在开始的时候总觉得对Java有点不适应，应该值得深究的东西还是很多的，而且对于面试来说，也是有很多可以问的，后面慢慢发现除开某里等一线超一线互联网公司之外，大部分的面试还是有大概的套路跟大纲的，不过更细致的则因人而异了，面试有时候也还看缘分，面试官关注的点跟应试者比较契合的话就很容易通过面试，不然的话总会有能刁难或者理性化地说比较难回答的问题。这个后面可以单独说一下，先按下不表。<br>刚进公司没多久就负责比较重要的项目，工期也比较紧张，整体来说那段时间的压力的确是比较大的，不过总算最后结果不坏，这里应该说对一些原来在前东家都是掌握的不太好的部分，比如maven，其实maven对于java程序员来说还是很重要的，但是我碰到过的面试基本没问过这个，我自己也在后面的面试中没问过相关的，不知道咋问，比如dependence分析、冲突解决，比如对bean的理解，这个算是我一直以来的疑问点，因为以前刚开始学Java学spring，上来就是bean，但是bean到底是啥，IOC是啥，可能网上的文章跟大多数书籍跟我的理解思路不太match，导致一直不能很好的理解这玩意，到后面才理解，要理解这个bean，需要有两个基本概念，一个是面向对象，一个是对象容器跟依赖反转，还是只说到这，后面可以有专题说一下，总之自认为技术上有了不小的长进了，方向上应该是偏实用的。这个重要的项目完成后慢慢能喘口气了，后面也有一些比较紧急且工作量大的，不过在我TL的帮助下还是能尽量协调好资源。</p>
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<h3 id="面试"><a href="#面试" class="headerlink" title="面试"></a>面试</h3><p>后面因为项目比较多，缺少开发，所以也参与帮忙做一些面试，这里总体感觉是面的候选人还是比较多样的，有些工作了蛮多年但是一些基础问题回答的不好，有些还是在校学生，但是面试技巧不错，针对常见的面试题都有不错的准备，不过还是觉得光靠这些面试题不能完全说明问题，真正工作了需要的是解决问题的人，而不是会背题的，退一步来说能好好准备面试还是比较重要的，也是双向选择中的基本尊重，印象比较深刻的是参加了去杭州某高校的校招面试，感觉参加校招的同学还是很多的，大部分是20年将毕业的研究生，挺多都是基础很扎实，对比起我刚要毕业时还是很汗颜，挺多来面试的同学都非常不错，那天强度也很大，从下午到那开始一直面到六七点，在这祝福那些来面试的同学，也都不容易的，能找到心仪的工作。</p>
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<h3 id="技术方向"><a href="#技术方向" class="headerlink" title="技术方向"></a>技术方向</h3><p>这一年前大半部分还是比较焦虑不能恢复那种主动找时间学习的状态，可能换了公司是主要的原因，初期有个适应的过程也比较正常，总体来说可能是到九十月份开始慢慢有所改善，对这些方面有学习了下，</p>
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<ul>
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<li>spring方向，spring真的是个庞然大物，但是还是要先抓住根本，慢慢发散去了解其他的细节，抓住bean的生命周期，当然也不是死记硬背，让我一个个背下来我也不行，但是知道它究竟是干嘛的，有啥用，并且在工作中能用起来是最重要的</li>
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<li>mysql数据库，这部分主要是关注了mvcc，知道了个大概，源码实现细节还没具体研究，有时间可以来个专题（一大堆待写的内容）</li>
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<li>java的一些源码，比如aqs这种，结合文章看了下源码，一开始总感觉静不下心来看，然后有一次被LD刺激了下就看完了，包括conditionObject等</li>
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<li>redis的源码，这里包括了Redis分布式锁和redis的数据结构源码，已经写成文章，不过比较着急成文，所以质量不是特别好，希望后面再来补补</li>
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<li>jvm源码，这部分正好是想了解下g1收集器，大概把周志明的书看完了，但是还没完整的理解掌握，还有就是g1收集器的部分，一是概念部分大概理解了，后面是就是想从源码层面去学习理解，这也是新一年的主要计划</li>
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<li>mq的部分是了解了zero copy，sendfile等，跟消息队列主题关系不大🤦♂️<br>这么看还是学了点东西的，希望新一年再接再厉。</li>
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</ul>
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<h3 id="生活"><a href="#生活" class="headerlink" title="生活"></a>生活</h3><p>住的地方没变化，主要是周边设施比较方便，暂时没找到更好的就没打算换，主要的问题是没电梯，一开始没觉得有啥，真正住起来还是觉得比较累的，希望后面租的可以有电梯，或者楼层低一点，还有就是要通下水道，第一次让师傅上门，花了两百大洋，后来自学成才了，让师傅通了一次才撑了一个月就不行了，后面自己通的差不多可以撑半年，还是比较有成就感的😀，然后就是跑步了，年初的时候去了紫金港跑步，后面因为工作的原因没去了，但是公司的跑步机倒是让我重拾起这个唯一的运动健身项目，后面因为肠胃问题，体重也需要控制，所以就周末回来也在家这边坚持跑步，下半年的话基本保持每周一次以上，比较那些跑马拉松的大牛还是差距很大，不过也是突破自我了，有一次跑了12公里，最远的距离，而且后面感觉跑十公里也不是特别吃不消了，这一年达成了300公里的目标，体重也稍有下降，比较满意的结果。</p>
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<h3 id="期待"><a href="#期待" class="headerlink" title="期待"></a>期待</h3><p>希望工作方面技术方面能有所长进，生活上能多点时间陪家人，继续跑步减肥，家人健健康康的，嗯</p>
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<p>这应该是 redis 系列的最后一篇了，讲下快表，其实最前面讲的链表在早先的 redis 版本中也作为 list 的数据结构使用过，但是单纯的链表的缺陷之前也说了，插入便利，但是空间利用率低，并且不能进行二分查找等，检索效率低，ziplist 压缩表的产生也是同理，希望获得更好的性能，包括存储空间和访问性能等，原来我也不懂这个快表要怎么快，然后明白了一个道理，其实并没有什么银弹，只是大牛们会在适合的时候使用最适合的数据结构来实现性能的最大化，这里面有一招就是不同数据结构的组合调整，比如 Java 中的 HashMap，在链表节点数大于 8 时会转变成红黑树，以此提高访问效率，不费话了，回到快表，quicklist，这个数据结构主要使用在 list 类型中，如果我说其实这个 quicklist 就是个链表，可能大家不太会相信，但是事实上的确可以认为 quicklist 是个双向链表，看下代码</p>
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<figure class="highlight c"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br><span class="line">39</span><br><span class="line">40</span><br><span class="line">41</span><br><span class="line">42</span><br><span class="line">43</span><br><span class="line">44</span><br><span class="line">45</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment">/* quicklistNode is a 32 byte struct describing a ziplist for a quicklist.</span></span><br><span class="line"><span class="comment"> * We use bit fields keep the quicklistNode at 32 bytes.</span></span><br><span class="line"><span class="comment"> * count: 16 bits, max 65536 (max zl bytes is 65k, so max count actually < 32k).</span></span><br><span class="line"><span class="comment"> * encoding: 2 bits, RAW=1, LZF=2.</span></span><br><span class="line"><span class="comment"> * container: 2 bits, NONE=1, ZIPLIST=2.</span></span><br><span class="line"><span class="comment"> * recompress: 1 bit, bool, true if node is temporarry decompressed for usage.</span></span><br><span class="line"><span class="comment"> * attempted_compress: 1 bit, boolean, used for verifying during testing.</span></span><br><span class="line"><span class="comment"> * extra: 10 bits, free for future use; pads out the remainder of 32 bits */</span></span><br><span class="line"><span class="keyword">typedef</span> <span class="class"><span class="keyword">struct</span> <span class="title">quicklistNode</span> {</span></span><br><span class="line"> <span class="class"><span class="keyword">struct</span> <span class="title">quicklistNode</span> *<span class="title">prev</span>;</span></span><br><span class="line"> <span class="class"><span class="keyword">struct</span> <span class="title">quicklistNode</span> *<span class="title">next</span>;</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">char</span> *zl;</span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">int</span> sz; <span class="comment">/* ziplist size in bytes */</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">int</span> count : <span class="number">16</span>; <span class="comment">/* count of items in ziplist */</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">int</span> encoding : <span class="number">2</span>; <span class="comment">/* RAW==1 or LZF==2 */</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">int</span> container : <span class="number">2</span>; <span class="comment">/* NONE==1 or ZIPLIST==2 */</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">int</span> recompress : <span class="number">1</span>; <span class="comment">/* was this node previous compressed? */</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">int</span> attempted_compress : <span class="number">1</span>; <span class="comment">/* node can't compress; too small */</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">int</span> extra : <span class="number">10</span>; <span class="comment">/* more bits to steal for future usage */</span></span><br><span class="line">} quicklistNode;</span><br><span class="line"></span><br><span class="line"><span class="comment">/* quicklistLZF is a 4+N byte struct holding 'sz' followed by 'compressed'.</span></span><br><span class="line"><span class="comment"> * 'sz' is byte length of 'compressed' field.</span></span><br><span class="line"><span class="comment"> * 'compressed' is LZF data with total (compressed) length 'sz'</span></span><br><span class="line"><span class="comment"> * <span class="doctag">NOTE:</span> uncompressed length is stored in quicklistNode->sz.</span></span><br><span class="line"><span class="comment"> * When quicklistNode->zl is compressed, node->zl points to a quicklistLZF */</span></span><br><span class="line"><span class="keyword">typedef</span> <span class="class"><span class="keyword">struct</span> <span class="title">quicklistLZF</span> {</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">int</span> sz; <span class="comment">/* LZF size in bytes*/</span></span><br><span class="line"> <span class="keyword">char</span> compressed[];</span><br><span class="line">} quicklistLZF;</span><br><span class="line"></span><br><span class="line"><span class="comment">/* quicklist is a 40 byte struct (on 64-bit systems) describing a quicklist.</span></span><br><span class="line"><span class="comment"> * 'count' is the number of total entries.</span></span><br><span class="line"><span class="comment"> * 'len' is the number of quicklist nodes.</span></span><br><span class="line"><span class="comment"> * 'compress' is: -1 if compression disabled, otherwise it's the number</span></span><br><span class="line"><span class="comment"> * of quicklistNodes to leave uncompressed at ends of quicklist.</span></span><br><span class="line"><span class="comment"> * 'fill' is the user-requested (or default) fill factor. */</span></span><br><span class="line"><span class="keyword">typedef</span> <span class="class"><span class="keyword">struct</span> <span class="title">quicklist</span> {</span></span><br><span class="line"> quicklistNode *head;</span><br><span class="line"> quicklistNode *tail;</span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> count; <span class="comment">/* total count of all entries in all ziplists */</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> len; <span class="comment">/* number of quicklistNodes */</span></span><br><span class="line"> <span class="keyword">int</span> <span class="built_in">fill</span> : <span class="number">16</span>; <span class="comment">/* fill factor for individual nodes */</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">int</span> compress : <span class="number">16</span>; <span class="comment">/* depth of end nodes not to compress;0=off */</span></span><br><span class="line">} quicklist;</span><br></pre></td></tr></table></figure>
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<p>粗略看下，quicklist 里有 head，tail, quicklistNode里有 prev，next 指针，是不是有链表的基本轮廓了，那么为啥这玩意要称为快表呢，快在哪，关键就在这个<code>unsigned char *zl;</code>zl 是不是前面又看到过，就是 ziplist ，这是什么鬼，链表里用压缩表，这不套娃么，先别急，回顾下前面说的 ziplist，ziplist 有哪些特点，内存利用率高，可以从表头快速定位到尾节点，节点可以从后往前找，但是有个缺点，就是从中间插入的效率比较低，需要整体往后移，这个其实是普通数组的优化版，但还是有数组的一些劣势，所以要真的快，是不是可以将链表跟数组真的结合起来。</p>
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<h2 id="ziplist"><a href="#ziplist" class="headerlink" title="ziplist"></a>ziplist</h2><p>这里有两个 redis 的配置参数，<code>list-max-ziplist-size</code> 和 <code>list-compress-depth</code>，先来说第一个，既然快表是将链表跟压缩表数组结合起来使用，那么具体怎么用呢，比如我有一个 10 个元素的 list，那具体怎么放，每个 quicklistNode 里放多大的 ziplist，假如每个快表节点的 ziplist 只放一个元素，那么其实这就退化成了一个链表，如果 10 个元素放在一个 quicklistNode 的 ziplist 里，那就退化成了一个 ziplist，所以有了这个 <code>list-max-ziplist-size</code>,而且它还比较牛，能取正负值，当是正值时，对应的就是每个 quicklistNode 的 ziplist 中的元素个数，比如配置了 <code>list-max-ziplist-size = 5</code>，那么我刚才的 10 个元素的 list 就是一个两个 quicklistNode 组成的快表，每个 quicklistNode 中的 ziplist 包含了五个元素，当 <code>list-max-ziplist-size</code>取负值的时候，它限制了 ziplist 的字节数</p>
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<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br></pre></td><td class="code"><pre><span class="line">size_t offset = (-fill) - 1;</span><br><span class="line">if (offset < (sizeof(optimization_level) / sizeof(*optimization_level))) {</span><br><span class="line"> if (sz <= optimization_level[offset]) {</span><br><span class="line"> return 1;</span><br><span class="line"> } else {</span><br><span class="line"> return 0;</span><br><span class="line"> }</span><br><span class="line">} else {</span><br><span class="line"> return 0;</span><br><span class="line">}</span><br><span class="line"></span><br><span class="line">/* Optimization levels for size-based filling */</span><br><span class="line">static const size_t optimization_level[] = {4096, 8192, 16384, 32768, 65536};</span><br><span class="line"></span><br><span class="line">/* Create a new quicklist.</span><br><span class="line"> * Free with quicklistRelease(). */</span><br><span class="line">quicklist *quicklistCreate(void) {</span><br><span class="line"> struct quicklist *quicklist;</span><br><span class="line"></span><br><span class="line"> quicklist = zmalloc(sizeof(*quicklist));</span><br><span class="line"> quicklist->head = quicklist->tail = NULL;</span><br><span class="line"> quicklist->len = 0;</span><br><span class="line"> quicklist->count = 0;</span><br><span class="line"> quicklist->compress = 0;</span><br><span class="line"> quicklist->fill = -2;</span><br><span class="line"> return quicklist;</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>这个 fill 就是传进来的 <code>list-max-ziplist-size</code>, 具体对应的就是</p>
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<ul>
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<li>-5: 每个quicklist节点上的ziplist大小不能超过64 Kb。（注：1kb => 1024 bytes）</li>
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<li>-4: 每个quicklist节点上的ziplist大小不能超过32 Kb。</li>
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<li>-3: 每个quicklist节点上的ziplist大小不能超过16 Kb。</li>
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<li>-2: 每个quicklist节点上的ziplist大小不能超过8 Kb。（-2是Redis给出的默认值）也就是上面的 <code>quicklist->fill = -2;</code></li>
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<li>-1: 每个quicklist节点上的ziplist大小不能超过4 Kb。</li>
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<h2 id="压缩"><a href="#压缩" class="headerlink" title="压缩"></a>压缩</h2><p><code>list-compress-depth</code>这个参数呢是用来配置压缩的，等等压缩是为啥，不是里面已经是压缩表了么，大牛们就是为了性能殚精竭虑，这里考虑到的是一个场景，一般状况下，list 都是两端的访问频率比较高，那么是不是可以对中间的数据进行压缩，那么这个参数就是用来表示</p>
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<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">/* depth of end nodes not to compress;0=off */</span><br></pre></td></tr></table></figure>
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<ul>
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<li>0，代表不压缩，默认值</li>
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<li>1，两端各一个节点不压缩</li>
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<li>2，两端各两个节点不压缩</li>
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<li>… 依次类推<br>压缩后的 ziplist 就会变成 quicklistLZF，然后替换 zl 指针，这里使用的是 <a href="http://oldhome.schmorp.de/marc/liblzf.html" target="_blank" rel="noopener">LZF</a> 压缩算法，压缩后的 quicklistLZF 中的 compressed 也是个柔性数组，压缩后的 ziplist 整个就放进这个柔性数组</li>
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</ul>
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<h2 id="插入过程"><a href="#插入过程" class="headerlink" title="插入过程"></a>插入过程</h2><p>简单说下插入元素的过程</p>
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<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br><span class="line">38</span><br><span class="line">39</span><br><span class="line">40</span><br><span class="line">41</span><br><span class="line">42</span><br><span class="line">43</span><br><span class="line">44</span><br><span class="line">45</span><br><span class="line">46</span><br><span class="line">47</span><br><span class="line">48</span><br><span class="line">49</span><br><span class="line">50</span><br><span class="line">51</span><br><span class="line">52</span><br><span class="line">53</span><br><span class="line">54</span><br><span class="line">55</span><br><span class="line">56</span><br><span class="line">57</span><br><span class="line">58</span><br><span class="line">59</span><br><span class="line">60</span><br><span class="line">61</span><br><span class="line">62</span><br><span class="line">63</span><br><span class="line">64</span><br><span class="line">65</span><br><span class="line">66</span><br><span class="line">67</span><br><span class="line">68</span><br><span class="line">69</span><br><span class="line">70</span><br><span class="line">71</span><br><span class="line">72</span><br><span class="line">73</span><br><span class="line">74</span><br><span class="line">75</span><br><span class="line">76</span><br><span class="line">77</span><br><span class="line">78</span><br><span class="line">79</span><br><span class="line">80</span><br><span class="line">81</span><br><span class="line">82</span><br><span class="line">83</span><br><span class="line">84</span><br><span class="line">85</span><br><span class="line">86</span><br><span class="line">87</span><br><span class="line">88</span><br><span class="line">89</span><br><span class="line">90</span><br><span class="line">91</span><br><span class="line">92</span><br><span class="line">93</span><br><span class="line">94</span><br><span class="line">95</span><br><span class="line">96</span><br><span class="line">97</span><br><span class="line">98</span><br><span class="line">99</span><br><span class="line">100</span><br><span class="line">101</span><br><span class="line">102</span><br><span class="line">103</span><br><span class="line">104</span><br><span class="line">105</span><br><span class="line">106</span><br><span class="line">107</span><br></pre></td><td class="code"><pre><span class="line">/* Wrapper to allow argument-based switching between HEAD/TAIL pop */</span><br><span class="line">void quicklistPush(quicklist *quicklist, void *value, const size_t sz,</span><br><span class="line"> int where) {</span><br><span class="line"> if (where == QUICKLIST_HEAD) {</span><br><span class="line"> quicklistPushHead(quicklist, value, sz);</span><br><span class="line"> } else if (where == QUICKLIST_TAIL) {</span><br><span class="line"> quicklistPushTail(quicklist, value, sz);</span><br><span class="line"> }</span><br><span class="line">}</span><br><span class="line"></span><br><span class="line">/* Add new entry to head node of quicklist.</span><br><span class="line"> *</span><br><span class="line"> * Returns 0 if used existing head.</span><br><span class="line"> * Returns 1 if new head created. */</span><br><span class="line">int quicklistPushHead(quicklist *quicklist, void *value, size_t sz) {</span><br><span class="line"> quicklistNode *orig_head = quicklist->head;</span><br><span class="line"> if (likely(</span><br><span class="line"> _quicklistNodeAllowInsert(quicklist->head, quicklist->fill, sz))) {</span><br><span class="line"> quicklist->head->zl =</span><br><span class="line"> ziplistPush(quicklist->head->zl, value, sz, ZIPLIST_HEAD);</span><br><span class="line"> quicklistNodeUpdateSz(quicklist->head);</span><br><span class="line"> } else {</span><br><span class="line"> quicklistNode *node = quicklistCreateNode();</span><br><span class="line"> node->zl = ziplistPush(ziplistNew(), value, sz, ZIPLIST_HEAD);</span><br><span class="line"></span><br><span class="line"> quicklistNodeUpdateSz(node);</span><br><span class="line"> _quicklistInsertNodeBefore(quicklist, quicklist->head, node);</span><br><span class="line"> }</span><br><span class="line"> quicklist->count++;</span><br><span class="line"> quicklist->head->count++;</span><br><span class="line"> return (orig_head != quicklist->head);</span><br><span class="line">}</span><br><span class="line"></span><br><span class="line">/* Add new entry to tail node of quicklist.</span><br><span class="line"> *</span><br><span class="line"> * Returns 0 if used existing tail.</span><br><span class="line"> * Returns 1 if new tail created. */</span><br><span class="line">int quicklistPushTail(quicklist *quicklist, void *value, size_t sz) {</span><br><span class="line"> quicklistNode *orig_tail = quicklist->tail;</span><br><span class="line"> if (likely(</span><br><span class="line"> _quicklistNodeAllowInsert(quicklist->tail, quicklist->fill, sz))) {</span><br><span class="line"> quicklist->tail->zl =</span><br><span class="line"> ziplistPush(quicklist->tail->zl, value, sz, ZIPLIST_TAIL);</span><br><span class="line"> quicklistNodeUpdateSz(quicklist->tail);</span><br><span class="line"> } else {</span><br><span class="line"> quicklistNode *node = quicklistCreateNode();</span><br><span class="line"> node->zl = ziplistPush(ziplistNew(), value, sz, ZIPLIST_TAIL);</span><br><span class="line"></span><br><span class="line"> quicklistNodeUpdateSz(node);</span><br><span class="line"> _quicklistInsertNodeAfter(quicklist, quicklist->tail, node);</span><br><span class="line"> }</span><br><span class="line"> quicklist->count++;</span><br><span class="line"> quicklist->tail->count++;</span><br><span class="line"> return (orig_tail != quicklist->tail);</span><br><span class="line">}</span><br><span class="line"></span><br><span class="line">/* Wrappers for node inserting around existing node. */</span><br><span class="line">REDIS_STATIC void _quicklistInsertNodeBefore(quicklist *quicklist,</span><br><span class="line"> quicklistNode *old_node,</span><br><span class="line"> quicklistNode *new_node) {</span><br><span class="line"> __quicklistInsertNode(quicklist, old_node, new_node, 0);</span><br><span class="line">}</span><br><span class="line"></span><br><span class="line">REDIS_STATIC void _quicklistInsertNodeAfter(quicklist *quicklist,</span><br><span class="line"> quicklistNode *old_node,</span><br><span class="line"> quicklistNode *new_node) {</span><br><span class="line"> __quicklistInsertNode(quicklist, old_node, new_node, 1);</span><br><span class="line">}</span><br><span class="line"></span><br><span class="line">/* Insert 'new_node' after 'old_node' if 'after' is 1.</span><br><span class="line"> * Insert 'new_node' before 'old_node' if 'after' is 0.</span><br><span class="line"> * Note: 'new_node' is *always* uncompressed, so if we assign it to</span><br><span class="line"> * head or tail, we do not need to uncompress it. */</span><br><span class="line">REDIS_STATIC void __quicklistInsertNode(quicklist *quicklist,</span><br><span class="line"> quicklistNode *old_node,</span><br><span class="line"> quicklistNode *new_node, int after) {</span><br><span class="line"> if (after) {</span><br><span class="line"> new_node->prev = old_node;</span><br><span class="line"> if (old_node) {</span><br><span class="line"> new_node->next = old_node->next;</span><br><span class="line"> if (old_node->next)</span><br><span class="line"> old_node->next->prev = new_node;</span><br><span class="line"> old_node->next = new_node;</span><br><span class="line"> }</span><br><span class="line"> if (quicklist->tail == old_node)</span><br><span class="line"> quicklist->tail = new_node;</span><br><span class="line"> } else {</span><br><span class="line"> new_node->next = old_node;</span><br><span class="line"> if (old_node) {</span><br><span class="line"> new_node->prev = old_node->prev;</span><br><span class="line"> if (old_node->prev)</span><br><span class="line"> old_node->prev->next = new_node;</span><br><span class="line"> old_node->prev = new_node;</span><br><span class="line"> }</span><br><span class="line"> if (quicklist->head == old_node)</span><br><span class="line"> quicklist->head = new_node;</span><br><span class="line"> }</span><br><span class="line"> /* If this insert creates the only element so far, initialize head/tail. */</span><br><span class="line"> if (quicklist->len == 0) {</span><br><span class="line"> quicklist->head = quicklist->tail = new_node;</span><br><span class="line"> }</span><br><span class="line"></span><br><span class="line"> if (old_node)</span><br><span class="line"> quicklistCompress(quicklist, old_node);</span><br><span class="line"></span><br><span class="line"> quicklist->len++;</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>前面第一步先根据插入的是头还是尾选择不同的 push 函数，quicklistPushHead 或者 quicklistPushTail，举例分析下从头插入的 quicklistPushHead，先判断当前的 quicklistNode 节点还能不能允许再往 ziplist 里添加元素，如果可以就添加，如果不允许就新建一个 quicklistNode，然后调用 _quicklistInsertNodeBefore 将节点插进去，具体插入quicklist节点的操作类似链表的插入。</p>
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<a href="/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/" class="post-title-link" itemprop="url">redis数据结构介绍五-第五部分 对象</a>
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<p>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</p>
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<figure class="highlight c"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment">/* The actual Redis Object */</span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_STRING 0 <span class="comment">/* String object. */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_LIST 1 <span class="comment">/* List object. */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_SET 2 <span class="comment">/* Set object. */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_ZSET 3 <span class="comment">/* Sorted set object. */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_HASH 4 <span class="comment">/* Hash object. */</span></span></span><br><span class="line"><span class="comment">/*</span></span><br><span class="line"><span class="comment"> * Objects encoding. Some kind of objects like Strings and Hashes can be</span></span><br><span class="line"><span class="comment"> * internally represented in multiple ways. The 'encoding' field of the object</span></span><br><span class="line"><span class="comment"> * is set to one of this fields for this object. */</span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_ENCODING_RAW 0 <span class="comment">/* Raw representation */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_ENCODING_INT 1 <span class="comment">/* Encoded as integer */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_ENCODING_HT 2 <span class="comment">/* Encoded as hash table */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_ENCODING_ZIPMAP 3 <span class="comment">/* Encoded as zipmap */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_ENCODING_LINKEDLIST 4 <span class="comment">/* No longer used: old list encoding. */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_ENCODING_ZIPLIST 5 <span class="comment">/* Encoded as ziplist */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_ENCODING_INTSET 6 <span class="comment">/* Encoded as intset */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_ENCODING_SKIPLIST 7 <span class="comment">/* Encoded as skiplist */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_ENCODING_EMBSTR 8 <span class="comment">/* Embedded sds string encoding */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_ENCODING_QUICKLIST 9 <span class="comment">/* Encoded as linked list of ziplists */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_ENCODING_STREAM 10 <span class="comment">/* Encoded as a radix tree of listpacks */</span></span></span><br><span class="line"></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> LRU_BITS 24</span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> LRU_CLOCK_MAX ((1<span class="meta-string"><<LRU_BITS)-1) /* Max value of obj->lru */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> LRU_CLOCK_RESOLUTION 1000 <span class="comment">/* LRU clock resolution in ms */</span></span></span><br><span class="line"></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> OBJ_SHARED_REFCOUNT INT_MAX</span></span><br><span class="line"><span class="keyword">typedef</span> <span class="class"><span class="keyword">struct</span> <span class="title">redisObject</span> {</span></span><br><span class="line"> <span class="keyword">unsigned</span> type:<span class="number">4</span>;</span><br><span class="line"> <span class="keyword">unsigned</span> encoding:<span class="number">4</span>;</span><br><span class="line"> <span class="keyword">unsigned</span> lru:LRU_BITS; <span class="comment">/* LRU time (relative to global lru_clock) or</span></span><br><span class="line"><span class="comment"> * LFU data (least significant 8 bits frequency</span></span><br><span class="line"><span class="comment"> * and most significant 16 bits access time). */</span></span><br><span class="line"> <span class="keyword">int</span> refcount;</span><br><span class="line"> <span class="keyword">void</span> *ptr;</span><br><span class="line">} robj;</span><br></pre></td></tr></table></figure>
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<p>主体结构就是这个 redisObject，</p>
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<ul>
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<li>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</li>
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<li>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</li>
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<li>lru: 做LRU替换算法用，占24个bit</li>
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<li>refcount: 引用计数。它允许robj对象在某些情况下被共享。</li>
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<li>ptr: 指向底层实现数据结构的指针<br>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<br>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<br>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<br>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<br>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</li>
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<p>在 redis 中还有一类表型数据结构叫压缩表，ziplist，它的目的是替代链表，链表是个很容易理解的数据结构，双向链表有前后指针，有带头结点的有的不带，但是链表有个比较大的问题是相对于普通的数组，它的内存不连续，碎片化的存储，内存利用效率不高，而且指针寻址相对于直接使用偏移量的话，也有一定的效率劣势，当然这不是主要的原因，ziplist 设计的主要目的是让链表的内存使用更高效</p>
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<blockquote>
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<p>The ziplist is a specially encoded dually linked list that is designed to be very memory efficient.<br>这是摘自 redis 源码中ziplist.c 文件的注释，也说明了原因，它的大概结构是这样子</p>
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</blockquote>
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<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><zlbytes> <zltail> <zllen> <entry> <entry> ... <entry> <zlend></span><br></pre></td></tr></table></figure>
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<p>其中<br><code><zlbytes></code>表示 ziplist 占用的字节总数，类型是uint32_t，32 位的无符号整型，当然表示的字节数也包含自己本身占用的 4 个<br><code><zltail></code> 类型也是是uint32_t，表示ziplist表中最后一项（entry）在ziplist中的偏移字节数。<code><zltail></code>的存在，使得我们可以很方便地找到最后一项（不用遍历整个ziplist），从而可以在ziplist尾端快速地执行push或pop操作。<br><code><uint16_t zllen></code> 表示ziplist 中的数据项个数，因为是 16 位，所以当数量超过所能表示的最大的数量，它的 16 位全会置为 1，但是真实的数量需要遍历整个 ziplist 才能知道<br><code><entry></code>是具体的数据项，后面解释<br><code><zlend></code> ziplist 的最后一个字节，固定是255。<br>再看一下<code><entry></code>中的具体结构，</p>
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<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><prevlen> <encoding> <entry-data></span><br></pre></td></tr></table></figure>
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<p>首先这个<code><prevlen></code>有两种情况，一种是前面的元素的长度，如果是小于等于 253的时候就用一个uint8_t 来表示前一元素的长度，如果大于的话他将占用五个字节，第一个字节是 254，即表示这个字节已经表示不下了，需要后面的四个字节帮忙表示<br><code><encoding></code>这个就比较复杂，把源码的注释放下面先看下</p>
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<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br></pre></td><td class="code"><pre><span class="line">* |00pppppp| - 1 byte</span><br><span class="line">* String value with length less than or equal to 63 bytes (6 bits).</span><br><span class="line">* "pppppp" represents the unsigned 6 bit length.</span><br><span class="line">* |01pppppp|qqqqqqqq| - 2 bytes</span><br><span class="line">* String value with length less than or equal to 16383 bytes (14 bits).</span><br><span class="line">* IMPORTANT: The 14 bit number is stored in big endian.</span><br><span class="line">* |10000000|qqqqqqqq|rrrrrrrr|ssssssss|tttttttt| - 5 bytes</span><br><span class="line">* String value with length greater than or equal to 16384 bytes.</span><br><span class="line">* Only the 4 bytes following the first byte represents the length</span><br><span class="line">* up to 32^2-1. The 6 lower bits of the first byte are not used and</span><br><span class="line">* are set to zero.</span><br><span class="line">* IMPORTANT: The 32 bit number is stored in big endian.</span><br><span class="line">* |11000000| - 3 bytes</span><br><span class="line">* Integer encoded as int16_t (2 bytes).</span><br><span class="line">* |11010000| - 5 bytes</span><br><span class="line">* Integer encoded as int32_t (4 bytes).</span><br><span class="line">* |11100000| - 9 bytes</span><br><span class="line">* Integer encoded as int64_t (8 bytes).</span><br><span class="line">* |11110000| - 4 bytes</span><br><span class="line">* Integer encoded as 24 bit signed (3 bytes).</span><br><span class="line">* |11111110| - 2 bytes</span><br><span class="line">* Integer encoded as 8 bit signed (1 byte).</span><br><span class="line">* |1111xxxx| - (with xxxx between 0000 and 1101) immediate 4 bit integer.</span><br><span class="line">* Unsigned integer from 0 to 12. The encoded value is actually from</span><br><span class="line">* 1 to 13 because 0000 and 1111 can not be used, so 1 should be</span><br><span class="line">* subtracted from the encoded 4 bit value to obtain the right value.</span><br><span class="line">* |11111111| - End of ziplist special entry.</span><br></pre></td></tr></table></figure>
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<p>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<code><entry-data></code>，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。<br>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<br>剩下当是<code>11111110</code>时，则表示是一个1 字节的有符号数，如果是 <code>1111xxxx</code>，其中<code>xxxx</code>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。<br>看个具体的例子(上下有点对不齐，将就看)</p>
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<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line">[0f 00 00 00] [0c 00 00 00] [02 00] [00 f3] [02 f6] [ff]</span><br><span class="line">|**zlbytes***| |***zltail***| |*zllen*| |entry1 entry2| |zlend|</span><br></pre></td></tr></table></figure>
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<p>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<code>00f3</code>,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</p>
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<p>redis中对于 set 其实有两种处理，对于元素均为整型，并且元素数目较少时，使用 intset 作为底层数据结构，否则使用 dict 作为底层数据结构，先看一下代码先</p>
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<figure class="highlight c"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">typedef</span> <span class="class"><span class="keyword">struct</span> <span class="title">intset</span> {</span></span><br><span class="line"> <span class="comment">// 编码方式</span></span><br><span class="line"> <span class="keyword">uint32_t</span> encoding;</span><br><span class="line"> <span class="comment">// 集合包含的元素数量</span></span><br><span class="line"> <span class="keyword">uint32_t</span> length;</span><br><span class="line"> <span class="comment">// 保存元素的数组</span></span><br><span class="line"> <span class="keyword">int8_t</span> contents[];</span><br><span class="line">} intset;</span><br><span class="line"></span><br><span class="line"><span class="comment">/* Note that these encodings are ordered, so:</span></span><br><span class="line"><span class="comment"> * INTSET_ENC_INT16 < INTSET_ENC_INT32 < INTSET_ENC_INT64. */</span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> INTSET_ENC_INT16 (sizeof(int16_t))</span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> INTSET_ENC_INT32 (sizeof(int32_t))</span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> INTSET_ENC_INT64 (sizeof(int64_t))</span></span><br></pre></td></tr></table></figure>
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<p>一眼看，为啥整型还需要编码，然后 int8_t 怎么能存下大整形呢，带着这些疑问，我们一步步分析下去，这里的编码其实指的是这个整型集合里存的究竟是多大的整型，16 位，还是 32 位，还是 64 位，结构体下面的宏定义就是表示了 encoding 的可能取值，INTSET_ENC_INT16 表示每个元素用2个字节存储，INTSET_ENC_INT32 表示每个元素用4个字节存储，INTSET_ENC_INT64 表示每个元素用8个字节存储。因此，intset中存储的整数最多只能占用64bit。length 就是正常的表示集合中元素的数量。最奇怪的应该就是这个 contents 了，是个 int8_t 的数组，那放毛线数据啊，最小的都有 16 位，这里我在看代码和《redis 设计与实现》的时候也有点懵逼，后来查了下发现这是个比较取巧的用法，这里我用自己的理解表述一下，先看看 8，16，32，64 的关系，一眼看就知道都是 2 的 N 次，并且呈两倍关系，而且 8 位刚好一个字节，所以呢其实这里的contents 不是个常规意义上的 int8_t 类型的数组，而是个柔性数组。看下 wiki 的定义</p>
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<blockquote>
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<p>Flexible array members<a href="https://en.wikipedia.org/wiki/Flexible_array_member#cite_note-1" target="_blank" rel="noopener">1</a> were introduced in the <a href="https://en.wikipedia.org/wiki/C99" target="_blank" rel="noopener">C99</a> standard of the <a href="https://en.wikipedia.org/wiki/C_(programming_language)" target="_blank" rel="noopener">C programming language</a> (in particular, in section §6.7.2.1, item 16, page 103).<a href="https://en.wikipedia.org/wiki/Flexible_array_member#cite_note-2" target="_blank" rel="noopener">2</a> It is a member of a struct, which is an array without a given dimension. It must be the last member of such a struct and it must be accompanied by at least one other member, as in the following example:</p>
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<figure class="highlight c"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br></pre></td><td class="code"><pre><span class="line"><span class="class"><span class="keyword">struct</span> <span class="title">vectord</span> {</span></span><br><span class="line"> <span class="keyword">size_t</span> len;</span><br><span class="line"> <span class="keyword">double</span> arr[]; <span class="comment">// the flexible array member must be last</span></span><br><span class="line">};</span><br></pre></td></tr></table></figure>
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<p>在初始化这个 intset 的时候，这个contents数组是不占用空间的，后面的反正用到了申请，那么这里就有一个问题，给出了三种可能的 encoding 值，他们能随便换吗，显然不行，首先在 intset 中数据的存放是有序的，这个有部分原因是方便二分查找，然后存放数据其实随着数据的大小不同会有一个升级的过程，看下图<br><img data-src="https://i.loli.net/2020/01/10/qIc6HgP7wfCLipN.png" alt=""><br>新创建的intset只有一个header，总共8个字节。其中encoding = 2, length = 0, 类型都是uint32_t，各占 4 字节，添加15, 5两个元素之后，因为它们是比较小的整数，都能使用2个字节表示，所以encoding不变，值还是2，也就是默认的 <code>INTSET_ENC_INT16</code>，当添加32768的时候，它不再能用2个字节来表示了（2个字节能表达的数据范围是-215~215-1，而32768等于215，超出范围了），因此encoding必须升级到INTSET_ENC_INT32（值为4），即用4个字节表示一个元素。在添加每个元素的过程中，intset始终保持从小到大有序。与ziplist类似，intset也是按小端（little endian）模式存储的（参见维基百科词条<a href="https://en.wikipedia.org/wiki/Endianness" target="_blank" rel="noopener">Endianness</a>）。比如，在上图中intset添加完所有数据之后，表示encoding字段的4个字节应该解释成0x00000004，而第4个数据应该解释成0x00008000 = 32768</p>
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<h2 id="跳表-skiplist"><a href="#跳表-skiplist" class="headerlink" title="跳表 skiplist"></a>跳表 skiplist</h2><p>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<br><img data-src="https://i.loli.net/2020/01/03/Og9i3pCIfxrMhja.png" alt=""><br>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<br><img data-src="https://i.loli.net/2020/01/03/81P2baupiedOmNf.png" alt=""><br>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，<br><img data-src="https://i.loli.net/2020/01/03/NBguAphilKjs2MO.png" alt=""><br>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。<br>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</p>
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<figure class="highlight c"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment">/* ZSETs use a specialized version of Skiplists */</span></span><br><span class="line"><span class="keyword">typedef</span> <span class="class"><span class="keyword">struct</span> <span class="title">zskiplistNode</span> {</span></span><br><span class="line"> sds ele;</span><br><span class="line"> <span class="keyword">double</span> score;</span><br><span class="line"> <span class="class"><span class="keyword">struct</span> <span class="title">zskiplistNode</span> *<span class="title">backward</span>;</span></span><br><span class="line"> <span class="class"><span class="keyword">struct</span> <span class="title">zskiplistLevel</span> {</span></span><br><span class="line"> <span class="class"><span class="keyword">struct</span> <span class="title">zskiplistNode</span> *<span class="title">forward</span>;</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> span;</span><br><span class="line"> } level[];</span><br><span class="line">} zskiplistNode;</span><br><span class="line"></span><br><span class="line"><span class="keyword">typedef</span> <span class="class"><span class="keyword">struct</span> <span class="title">zskiplist</span> {</span></span><br><span class="line"> <span class="class"><span class="keyword">struct</span> <span class="title">zskiplistNode</span> *<span class="title">header</span>, *<span class="title">tail</span>;</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> length;</span><br><span class="line"> <span class="keyword">int</span> level;</span><br><span class="line">} zskiplist;</span><br><span class="line"></span><br><span class="line"><span class="keyword">typedef</span> <span class="class"><span class="keyword">struct</span> <span class="title">zset</span> {</span></span><br><span class="line"> dict *dict;</span><br><span class="line"> zskiplist *zsl;</span><br><span class="line">} zset;</span><br></pre></td></tr></table></figure>
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<p>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</p>
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<figure class="highlight c"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br></pre></td><td class="code"><pre><span class="line"><span class="meta">#<span class="meta-keyword">define</span> ZSKIPLIST_P 0.25 <span class="comment">/* Skiplist P = 1/4 */</span></span></span><br><span class="line"><span class="function"><span class="keyword">int</span> <span class="title">zslRandomLevel</span><span class="params">(<span class="keyword">void</span>)</span> </span>{</span><br><span class="line"> <span class="keyword">int</span> level = <span class="number">1</span>;</span><br><span class="line"> <span class="keyword">while</span> ((<span class="built_in">random</span>()&<span class="number">0xFFFF</span>) < (ZSKIPLIST_P * <span class="number">0xFFFF</span>))</span><br><span class="line"> level += <span class="number">1</span>;</span><br><span class="line"> <span class="keyword">return</span> (level<ZSKIPLIST_MAXLEVEL) ? level : ZSKIPLIST_MAXLEVEL;</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>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<br>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。</p>
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<p>redis是现在服务端很常用的缓存中间件，其实原来还有<code>memcache</code>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。<br>redis 主要有五种数据结构，<code>Strings</code>，<code>Lists</code>，<code>Sets</code>，<code>Hashes</code>，<code>Sorted Sets</code>，这五种数据结构先简单介绍下，<code>Strings</code>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；<code>Lists</code>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<code>Sets</code>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；<code>Hashes</code>是叫散列，类似于 Python 中的字典结构；还有就是<code>Sorted Sets</code>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。</p>
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<h2 id="SDS-简单动态字符串"><a href="#SDS-简单动态字符串" class="headerlink" title="SDS 简单动态字符串"></a>SDS 简单动态字符串</h2><p>先从<code>Strings</code>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 <code>char[]</code> 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</p>
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<figure class="highlight c"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br></pre></td><td class="code"><pre><span class="line"><span class="class"><span class="keyword">struct</span> <span class="title">sdshdr</span> {</span></span><br><span class="line"> <span class="comment">// 字符串长度</span></span><br><span class="line"> <span class="keyword">int</span> len;</span><br><span class="line"> <span class="comment">// 字符串空余字符数</span></span><br><span class="line"> <span class="keyword">int</span> <span class="built_in">free</span>;</span><br><span class="line"> <span class="comment">// 字符串内容</span></span><br><span class="line"> <span class="keyword">char</span> buf[];</span><br><span class="line">};</span><br></pre></td></tr></table></figure>
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<p>这里引用了 redis 在 github 上最早的 2.2 版本的代码，代码路径是<code>https://github.com/antirez/redis/blob/2.2/src/sds.h</code>,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<code>\0</code>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 <code>O(N)</code>简化到了<code>O(1)</code>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</p>
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<h2 id="链表"><a href="#链表" class="headerlink" title="链表"></a>链表</h2><p>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</p>
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<figure class="highlight c"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">typedef</span> <span class="class"><span class="keyword">struct</span> <span class="title">listNode</span> {</span></span><br><span class="line"> <span class="comment">// 前置节点</span></span><br><span class="line"> <span class="class"><span class="keyword">struct</span> <span class="title">listNode</span> *<span class="title">prev</span>;</span></span><br><span class="line"> <span class="comment">// 后置节点</span></span><br><span class="line"> <span class="class"><span class="keyword">struct</span> <span class="title">listNode</span> *<span class="title">next</span>;</span></span><br><span class="line"> <span class="comment">// 值</span></span><br><span class="line"> <span class="keyword">void</span> *value;</span><br><span class="line">} listNode;</span><br><span class="line"></span><br><span class="line"><span class="keyword">typedef</span> <span class="class"><span class="keyword">struct</span> <span class="title">list</span> {</span></span><br><span class="line"> <span class="comment">// 链表表头</span></span><br><span class="line"> listNode *head;</span><br><span class="line"> <span class="comment">// 当前节点，也可以说是最后节点</span></span><br><span class="line"> listNode *tail;</span><br><span class="line"> <span class="comment">// 节点复制函数</span></span><br><span class="line"> <span class="keyword">void</span> *(*dup)(<span class="keyword">void</span> *ptr);</span><br><span class="line"> <span class="comment">// 节点值释放函数</span></span><br><span class="line"> <span class="keyword">void</span> (*<span class="built_in">free</span>)(<span class="keyword">void</span> *ptr);</span><br><span class="line"> <span class="comment">// 节点值比较函数</span></span><br><span class="line"> <span class="keyword">int</span> (*match)(<span class="keyword">void</span> *ptr, <span class="keyword">void</span> *key);</span><br><span class="line"> <span class="comment">// 链表包含的节点数量</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">int</span> len;</span><br><span class="line">} <span class="built_in">list</span>;</span><br></pre></td></tr></table></figure>
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<p>代码地址是这个<code>https://github.com/antirez/redis/blob/2.2/src/adlist.h</code><br>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<br>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 <code>O(1)</code>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。</p>
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<h2 id="字典"><a href="#字典" class="headerlink" title="字典"></a>字典</h2><p>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<br>下面来看看代码</p>
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<figure class="highlight c"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">typedef</span> <span class="class"><span class="keyword">struct</span> <span class="title">dictEntry</span> {</span></span><br><span class="line"> <span class="keyword">void</span> *key;</span><br><span class="line"> <span class="keyword">void</span> *val;</span><br><span class="line"> <span class="class"><span class="keyword">struct</span> <span class="title">dictEntry</span> *<span class="title">next</span>;</span></span><br><span class="line">} dictEntry;</span><br><span class="line"></span><br><span class="line"><span class="keyword">typedef</span> <span class="class"><span class="keyword">struct</span> <span class="title">dictType</span> {</span></span><br><span class="line"> <span class="function"><span class="keyword">unsigned</span> <span class="title">int</span> <span class="params">(*hashFunction)</span><span class="params">(<span class="keyword">const</span> <span class="keyword">void</span> *key)</span></span>;</span><br><span class="line"> <span class="keyword">void</span> *(*keyDup)(<span class="keyword">void</span> *privdata, <span class="keyword">const</span> <span class="keyword">void</span> *key);</span><br><span class="line"> <span class="keyword">void</span> *(*valDup)(<span class="keyword">void</span> *privdata, <span class="keyword">const</span> <span class="keyword">void</span> *obj);</span><br><span class="line"> <span class="keyword">int</span> (*keyCompare)(<span class="keyword">void</span> *privdata, <span class="keyword">const</span> <span class="keyword">void</span> *key1, <span class="keyword">const</span> <span class="keyword">void</span> *key2);</span><br><span class="line"> <span class="keyword">void</span> (*keyDestructor)(<span class="keyword">void</span> *privdata, <span class="keyword">void</span> *key);</span><br><span class="line"> <span class="keyword">void</span> (*valDestructor)(<span class="keyword">void</span> *privdata, <span class="keyword">void</span> *obj);</span><br><span class="line">} dictType;</span><br><span class="line"></span><br><span class="line"><span class="comment">/* This is our hash table structure. Every dictionary has two of this as we</span></span><br><span class="line"><span class="comment"> * implement incremental rehashing, for the old to the new table. */</span></span><br><span class="line"><span class="keyword">typedef</span> <span class="class"><span class="keyword">struct</span> <span class="title">dictht</span> {</span></span><br><span class="line"> dictEntry **table;</span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> <span class="built_in">size</span>;</span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> sizemask;</span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> used;</span><br><span class="line">} dictht;</span><br><span class="line"></span><br><span class="line"><span class="keyword">typedef</span> <span class="class"><span class="keyword">struct</span> <span class="title">dict</span> {</span></span><br><span class="line"> dictType *type;</span><br><span class="line"> <span class="keyword">void</span> *privdata;</span><br><span class="line"> dictht ht[<span class="number">2</span>];</span><br><span class="line"> <span class="keyword">int</span> rehashidx; <span class="comment">/* rehashing not in progress if rehashidx == -1 */</span></span><br><span class="line"> <span class="keyword">int</span> iterators; <span class="comment">/* number of iterators currently running */</span></span><br><span class="line">} dict;</span><br></pre></td></tr></table></figure>
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<p>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~<br><img data-src="https://i.loli.net/2019/12/29/UL4AR1HSEKOh9Qm.png" alt=""><br>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。<br>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。<br>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。<br>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。</p>
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<p>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<code>Spring Boot</code>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</p>
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<h2 id="饿汉模式"><a href="#饿汉模式" class="headerlink" title="饿汉模式"></a>饿汉模式</h2><figure class="highlight java"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">public</span> <span class="class"><span class="keyword">class</span> <span class="title">Singleton1</span> </span>{</span><br><span class="line"> <span class="comment">// 首先，将构造方法变成私有的</span></span><br><span class="line"> <span class="function"><span class="keyword">private</span> <span class="title">Singleton1</span><span class="params">()</span> </span>{};</span><br><span class="line"> <span class="comment">// 创建私有静态实例，这样第一次使用的时候就会进行创建</span></span><br><span class="line"> <span class="keyword">private</span> <span class="keyword">static</span> Singleton instance = <span class="keyword">new</span> Singleton1();</span><br><span class="line"></span><br><span class="line"> <span class="comment">// 使用这个对象都是通过这个 getInstance 来获取</span></span><br><span class="line"> <span class="function"><span class="keyword">public</span> <span class="keyword">static</span> Singleton1 <span class="title">getInstance</span><span class="params">()</span> </span>{</span><br><span class="line"> <span class="keyword">return</span> instance;</span><br><span class="line"> }</span><br><span class="line"> <span class="comment">// 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(...)，</span></span><br><span class="line"> <span class="comment">// 本来是不想要生成 Singleton 实例的，不过没办法，已经生成了</span></span><br><span class="line"> <span class="function"><span class="keyword">public</span> <span class="keyword">static</span> Date <span class="title">getDate</span><span class="params">(String mode)</span> </span>{<span class="keyword">return</span> <span class="keyword">new</span> Date();}</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>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<code>getDate</code>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</p>
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<h2 id="饱汉模式"><a href="#饱汉模式" class="headerlink" title="饱汉模式"></a>饱汉模式</h2><figure class="highlight java"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">public</span> <span class="class"><span class="keyword">class</span> <span class="title">Singleton2</span> </span>{</span><br><span class="line"> <span class="comment">// 首先，也是先堵死 new Singleton() 这条路,将构造方法变成私有</span></span><br><span class="line"> <span class="function"><span class="keyword">private</span> <span class="title">Singleton2</span><span class="params">()</span> </span>{}</span><br><span class="line"> <span class="comment">// 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</span></span><br><span class="line"> <span class="keyword">private</span> <span class="keyword">static</span> <span class="keyword">volatile</span> Singleton2 instance = <span class="keyword">null</span>;</span><br><span class="line"></span><br><span class="line"> <span class="keyword">private</span> <span class="keyword">int</span> m = <span class="number">9</span>;</span><br><span class="line"></span><br><span class="line"> <span class="function"><span class="keyword">public</span> <span class="keyword">static</span> Singleton <span class="title">getInstance</span><span class="params">()</span> </span>{</span><br><span class="line"> <span class="keyword">if</span> (instance == <span class="keyword">null</span>) {</span><br><span class="line"> <span class="comment">// 加锁</span></span><br><span class="line"> <span class="keyword">synchronized</span> (Singleton2<span class="class">.<span class="keyword">class</span>) </span>{</span><br><span class="line"> <span class="comment">// 这一次判断也是必须的，不然会有并发问题</span></span><br><span class="line"> <span class="keyword">if</span> (instance == <span class="keyword">null</span>) {</span><br><span class="line"> instance = <span class="keyword">new</span> Singleton2();</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"> <span class="keyword">return</span> instance;</span><br><span class="line"> }</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>这里容易错的有三点，理解了其实就比较好记了</p>
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<p>第一点，为啥不在 getInstance 上整个代码块加 <code>synchronized</code>，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。<br>第二点，为啥<code>synchronized</code>之已经检查了 <code>instance == null</code>,还要在里面再检查一次，这个有个术语，叫 <code>double check lock</code>,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。<br>第三点，为啥要<code>volatile</code>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，<code>instance = new Singleton();</code>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<code>volatile</code>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<code>volatile</code>也是不可缺少的</p>
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<h2 id="嵌套类"><a href="#嵌套类" class="headerlink" title="嵌套类"></a>嵌套类</h2><figure class="highlight java"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">public</span> <span class="class"><span class="keyword">class</span> <span class="title">Singleton3</span> </span>{</span><br><span class="line"></span><br><span class="line"> <span class="function"><span class="keyword">private</span> <span class="title">Singleton3</span><span class="params">()</span> </span>{}</span><br><span class="line"> <span class="comment">// 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</span></span><br><span class="line"> <span class="keyword">private</span> <span class="keyword">static</span> <span class="class"><span class="keyword">class</span> <span class="title">Holder</span> </span>{</span><br><span class="line"> <span class="keyword">private</span> <span class="keyword">static</span> Singleton3 instance = <span class="keyword">new</span> Singleton3();</span><br><span class="line"> }</span><br><span class="line"> <span class="function"><span class="keyword">public</span> <span class="keyword">static</span> Singleton3 <span class="title">getInstance</span><span class="params">()</span> </span>{</span><br><span class="line"> <span class="keyword">return</span> Holder.instance;</span><br><span class="line"> }</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>这个我个人感觉是饿汉模式的升级版，可以在调用<code>getInstance</code>的时候去实例化对象，也是比较推荐的</p>
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<h2 id="枚举单例"><a href="#枚举单例" class="headerlink" title="枚举单例"></a>枚举单例</h2><figure class="highlight java"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">public</span> <span class="keyword">enum</span> Singleton {</span><br><span class="line"> INSTANCE;</span><br><span class="line"> </span><br><span class="line"> <span class="function"><span class="keyword">public</span> <span class="keyword">void</span> <span class="title">doSomething</span><span class="params">()</span></span>{</span><br><span class="line"> <span class="comment">//todo doSomething</span></span><br><span class="line"> }</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>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。</p>
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<a href="/2019/12/18/1Q84%E8%AF%BB%E5%90%8E%E6%84%9F/" class="post-title-link" itemprop="url">村上春树《1Q84》读后感</a>
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<p>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）。</p>
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<p>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。</p>
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<p>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。</p>
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<p>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；</p>
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<p>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。</p>
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<p>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。</p>
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<p>2019年12月18日23:37:19 更新<br>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<br>暂时先写到这，未完待续~</p>
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<a href="/2019/12/10/Redis-Part-1/" class="post-title-link" itemprop="url">Redis_分布式锁</a>
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<p>今天看了一下 <code>redis</code> 分布式锁 <code>redlock</code> 的实现，简单记录下，</p>
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<h2 id="加锁"><a href="#加锁" class="headerlink" title="加锁"></a>加锁</h2><p>原先我对 <code>redis</code> 锁的概念就是加锁使用 <code>setnx</code>，解锁使用 <code>lua</code> 脚本，但是 <code>setnx</code> 具体是啥，<code>lua</code> 脚本是啥不是很清楚<br>首先简单思考下这个问题，首先为啥不是先 <code>get</code> 一下 <code>key</code> 存不存在，然后再 <code>set</code> 一个 <code>key value</code>，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 <code>get</code> 一下 <code>key</code>，如果不存在再 <code>set</code> 值的话，那就不是原子操作了；第二个是可不可以直接 <code>set</code> 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 <code>setnx</code> 给了我们这种原子命令</p>
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<p>然后是 <code>setnx</code> 的键和值分别是啥，键比较容易想到是要锁住的资源，比如 <code>user_id</code>, 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<br>面再说，这里其实是把<code>user_id</code> 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 <code>gc</code> 停顿等原因卡死了，这个时候<code>redis</code> 的锁或者说就是 <code>redis</code> 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。</p>
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<p>上面其实还有两个问题，一个是当 <code>gc</code> 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 <code>redis</code> 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 <code>redis</code> 提供了这种支持</p>
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<figure class="highlight plain"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">SET resource_name my_random_value NX PX 30000</span><br></pre></td></tr></table></figure>
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<p>这里借鉴一下解释下，<code>resource_name</code>就是 key，代表要锁住的东西，<code>my_random_value</code>就是识别我这个线程的，<code>NX</code>代表只有在不存在的时候才设置，然后<code>PX 30000</code>表示超时时间是 30秒自动过期</p>
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<p>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。</p>
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<h2 id="解锁"><a href="#解锁" class="headerlink" title="解锁"></a>解锁</h2><p>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<code>del key</code>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 <code>get</code> 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<code>lua</code> 脚本来操作这种</p>
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<figure class="highlight lua"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">if</span> redis.call(<span class="string">"get"</span>,KEYS[<span class="number">1</span>]) == ARGV[<span class="number">1</span>] <span class="keyword">then</span></span><br><span class="line"> <span class="keyword">return</span> redis.call(<span class="string">"del"</span>,KEYS[<span class="number">1</span>])</span><br><span class="line"><span class="keyword">else</span></span><br><span class="line"> <span class="keyword">return</span> <span class="number">0</span></span><br><span class="line"><span class="keyword">end</span></span><br></pre></td></tr></table></figure>
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<p>这里的<code>KEYS[1]</code>就是前面加锁的<code>resource_name</code>,<code>ARGV[1]</code>就是线程的随机值<code>my_random_value</code></p>
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<h2 id="多节点"><a href="#多节点" class="headerlink" title="多节点"></a>多节点</h2><p>前面说的其实是单节点 <code>redis</code> 作为分布式锁的情况，那么当我们的 <code>redis</code> 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<br><code>redis</code> 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 <code>redis</code>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<br>这里就引出了开头说到的<code>redlock</code>，这个可是 <code>redis</code>的作者写的, 他的加锁过程是分以下几步去做这个事情</p>
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<ul>
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<li>获取当前时间（毫秒数）。</li>
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<li>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）。</li>
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<li>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。</li>
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<li>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。</li>
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<li>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）。<br>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。<br>初步记录就先到这。</li>
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<span itemprop="copyrightYear">2020</span>
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<span class="with-love">
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<i class="fa fa-user"></i>
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</span>
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<span class="author" itemprop="copyrightHolder">Nicksxs</span>
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</div>
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<script>
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function leancloudSelector(url) {
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url = encodeURI(url);
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return document.getElementById(url).querySelector('.leancloud-visitors-count');
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}
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if (CONFIG.page.isPost) {
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function addCount(Counter) {
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var visitors = document.querySelector('.leancloud_visitors');
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var url = decodeURI(visitors.getAttribute('id'));
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var title = visitors.getAttribute('data-flag-title');
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Counter('get', `/classes/Counter?where=${JSON.stringify({ url })}`)
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.then(response => response.json())
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.then(({ results }) => {
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if (results.length > 0) {
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var counter = results[0];
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Counter('put', '/classes/Counter/' + counter.objectId, { time: { '__op': 'Increment', 'amount': 1 } })
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.then(response => response.json())
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.then(() => {
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leancloudSelector(url).innerText = counter.time + 1;
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})
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.catch(error => {
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console.error('Failed to save visitor count', error);
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})
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} else {
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leancloudSelector(url).innerText = 'Counter not initialized! More info at console err msg.';
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|
console.error('ATTENTION! LeanCloud counter has security bug, see how to solve it here: https://github.com/theme-next/hexo-leancloud-counter-security. \n However, you can still use LeanCloud without security, by setting `security` option to `false`.');
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}
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})
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.catch(error => {
|
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console.error('LeanCloud Counter Error', error);
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});
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}
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} else {
|
|
function showTime(Counter) {
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var visitors = document.querySelectorAll('.leancloud_visitors');
|
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var entries = [...visitors].map(element => {
|
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return decodeURI(element.getAttribute('id'));
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});
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Counter('get', `/classes/Counter?where=${JSON.stringify({ url: { '$in': entries } })}`)
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.then(response => response.json())
|
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.then(({ results }) => {
|
|
if (results.length === 0) {
|
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document.querySelectorAll('.leancloud_visitors .leancloud-visitors-count').forEach(element => {
|
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element.innerText = 0;
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});
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return;
|
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}
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for (let item of results) {
|
|
let { url, time } = item;
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|
leancloudSelector(url).innerText = time;
|
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}
|
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for (let url of entries) {
|
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var element = leancloudSelector(url);
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|
if (element.innerText == '') {
|
|
element.innerText = 0;
|
|
}
|
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}
|
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})
|
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.catch(error => {
|
|
console.error('LeanCloud Counter Error', error);
|
|
});
|
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}
|
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}
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|
|
fetch('https://app-router.leancloud.cn/2/route?appId=ysza182Vghlqjdt7QiwGLLJy-gzGzoHsz')
|
|
.then(response => response.json())
|
|
.then(({ api_server }) => {
|
|
var Counter = (method, url, data) => {
|
|
return fetch(`https://${api_server}/1.1${url}`, {
|
|
method: method,
|
|
headers: {
|
|
'X-LC-Id': 'ysza182Vghlqjdt7QiwGLLJy-gzGzoHsz',
|
|
'X-LC-Key': 's9GDqbn7gnGGkusf66YRVccw',
|
|
'Content-Type': 'application/json',
|
|
},
|
|
body: JSON.stringify(data)
|
|
});
|
|
};
|
|
if (CONFIG.page.isPost) {
|
|
if (CONFIG.hostname !== location.hostname) return;
|
|
addCount(Counter);
|
|
} else if (document.querySelectorAll('.post-title-link').length >= 1) {
|
|
showTime(Counter);
|
|
}
|
|
});
|
|
</script>
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|
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</div>
|
|
</footer>
|
|
</div>
|
|
|
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|
|
<script src="/lib/anime.min.js"></script>
|
|
<script src="//cdn.jsdelivr.net/npm/jquery@3/dist/jquery.min.js"></script>
|
|
<script src="//cdn.jsdelivr.net/gh/fancyapps/fancybox@3/dist/jquery.fancybox.min.js"></script>
|
|
<script src="//cdn.jsdelivr.net/npm/lozad@1/dist/lozad.min.js"></script>
|
|
<script src="/lib/velocity/velocity.min.js"></script>
|
|
<script src="/lib/velocity/velocity.ui.min.js"></script>
|
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|
|
<script src="/js/utils.js"></script>
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|
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<script src="/js/motion.js"></script>
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<script src="/js/schemes/pisces.js"></script>
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<script src="/js/next-boot.js"></script>
|
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<script>
|
|
(function(){
|
|
var bp = document.createElement('script');
|
|
var curProtocol = window.location.protocol.split(':')[0];
|
|
bp.src = (curProtocol === 'https') ? 'https://zz.bdstatic.com/linksubmit/push.js' : 'http://push.zhanzhang.baidu.com/push.js';
|
|
var s = document.getElementsByTagName("script")[0];
|
|
s.parentNode.insertBefore(bp, s);
|
|
})();
|
|
</script>
|
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|
|
<script>
|
|
function loadCount() {
|
|
var d = document, s = d.createElement('script');
|
|
s.src = 'https://nicksxs.disqus.com/count.js';
|
|
s.id = 'dsq-count-scr';
|
|
(d.head || d.body).appendChild(s);
|
|
}
|
|
// defer loading until the whole page loading is completed
|
|
window.addEventListener('load', loadCount, false);
|
|
</script>
|
|
|
|
</body>
|
|
</html>
|