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<p>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<code>select * from table1 where id = 1</code>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，<br>看一段 mysql官方文档</p>
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<blockquote>
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<p><code>SELECT ... FROM</code> 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. </p>
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<p>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<br>但是对于以下几类</p>
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<ul>
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<li><code>select * from table where ? lock in share mode;</code></li>
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<li><code>select * from table where ? for update;</code></li>
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<li><code>insert into table values (...);</code></li>
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<li><code>update table set ? where ?;</code></li>
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<li><code>delete from table where ?;</code> </li>
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</ul>
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<p>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<br>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<br>举个例子，RR 事务隔离级别下，table1 有个主键id 字段<br><code>select * from table1 where id = 10 for update</code><br>这条语句要加 gap 锁吗？<br>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。<br>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<br>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，<br>是时候画个图了<br><img data-src="https://mystore-1255223546.cos.ap-chengdu.myqcloud.com/uPic/WX20200510-1126082x.png" alt=""><br>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</p>
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<p>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</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></pre></td><td class="code"><pre><span class="line"><span class="comment">/**</span></span><br><span class="line"><span class="comment">Opens a read view where exactly the transactions serialized before this</span></span><br><span class="line"><span class="comment">point in time are seen in the view.</span></span><br><span class="line"><span class="comment">@param id Creator transaction id */</span></span><br><span class="line"></span><br><span class="line"><span class="function"><span class="keyword">void</span> <span class="title">ReadView::prepare</span><span class="params">(<span class="keyword">trx_id_t</span> id)</span> </span>{</span><br><span class="line"> ut_ad(mutex_own(&trx_sys->mutex));</span><br><span class="line"></span><br><span class="line"> m_creator_trx_id = id;</span><br><span class="line"></span><br><span class="line"> m_low_limit_no = m_low_limit_id = m_up_limit_id = trx_sys->max_trx_id;</span><br></pre></td></tr></table></figure>
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<p>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</p>
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<h2 id="幻读"><a href="#幻读" class="headerlink" title="幻读"></a>幻读</h2><p>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 <code>select * from table1 where id < 10 for update</code>,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<br>看一下 mysql 的文档</p>
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<blockquote>
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<p>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. </p>
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<p>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。</p>
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<p>很久以前，有位面试官问到，你知道 mysql 的事务隔离级别吗，“额 O__O …，不太清楚”，完了之后我就去网上找相关的文章，找到了这篇<a href="https://www.cnblogs.com/zhoujinyi/p/3437475.html" target="_blank" rel="noopener">MySQL 四种事务隔离级的说明</a>, 文章写得特别好，看了这个就懂了各个事务隔离级别都是啥，不过看了这个之后多思考一下的话还是会发现问题，这么神奇的事务隔离级别是怎么实现的呢</p>
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<p>其中 innodb 的事务隔离用到了标题里说到的 mvcc，<a href="https://en.wikipedia.org/wiki/Multiversion_concurrency_control" target="_blank" rel="noopener"><strong>Multiversion concurrency control</strong></a>, 直译过来就是多版本并发控制，先不讲这个究竟是个啥，考虑下如果纯猜测，这个事务隔离级别应该会是怎么样实现呢，愚钝的我想了下，可以在事务开始的时候拷贝一个表，这个可以支持 RR 级别，RC 级别就不支持了，而且要是个非常大的表，想想就不可行</p>
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<p>腆着脸说虽然这个不可行，但是思路是对的，具体实行起来需要做一系列（肥肠多）的改动，首先根据我的理解，其实这个拷贝一个表是变成拷贝一条记录，但是如果有多个事务，那就得拷贝多次，这个问题其实可以借助版本管理系统来解释，在用版本管理系统，git 之类的之前，很原始的可能是开发完一个功能后，就打个压缩包用时间等信息命名，然后如果后面要找回这个就直接用这个压缩包的就行了，后来有了 svn，git 中心式和分布式的版本管理系统，它的一个特点是粒度可以控制到文件和代码行级别，对应的我们的 mysql 事务是不是也可以从一开始预想的表级别细化到行的级别，可能之前很多人都了解过，数据库的一行记录除了我们用户自定义的字段，还有一些额外的字段，去源码<a href="https://github.com/mysql/mysql-server/blob/8.0/storage/innobase/include/data0type.h#L170" target="_blank" rel="noopener">data0type.h</a>里捞一下</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></pre></td><td class="code"><pre><span class="line"><span class="comment">/* Precise data types for system columns and the length of those columns;</span></span><br><span class="line"><span class="comment"><span class="doctag">NOTE:</span> the values must run from 0 up in the order given! All codes must</span></span><br><span class="line"><span class="comment">be less than 256 */</span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> DATA_ROW_ID 0 <span class="comment">/* row id: a 48-bit integer */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> DATA_ROW_ID_LEN 6 <span class="comment">/* stored length for row id */</span></span></span><br><span class="line"></span><br><span class="line"><span class="comment">/** Transaction id: 6 bytes */</span></span><br><span class="line"><span class="keyword">constexpr</span> <span class="keyword">size_t</span> DATA_TRX_ID = <span class="number">1</span>;</span><br><span class="line"></span><br><span class="line"><span class="comment">/** Transaction ID type size in bytes. */</span></span><br><span class="line"><span class="keyword">constexpr</span> <span class="keyword">size_t</span> DATA_TRX_ID_LEN = <span class="number">6</span>;</span><br><span class="line"></span><br><span class="line"><span class="comment">/** Rollback data pointer: 7 bytes */</span></span><br><span class="line"><span class="keyword">constexpr</span> <span class="keyword">size_t</span> DATA_ROLL_PTR = <span class="number">2</span>;</span><br><span class="line"></span><br><span class="line"><span class="comment">/** Rollback data pointer type size in bytes. */</span></span><br><span class="line"><span class="keyword">constexpr</span> <span class="keyword">size_t</span> DATA_ROLL_PTR_LEN = <span class="number">7</span>;</span><br></pre></td></tr></table></figure>
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<p>一个是 <code>DATA_ROW_ID</code>，这个是在数据没指定主键的时候会生成一个隐藏的，如果用户有指定主键就是主键了</p>
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<p>一个是 <code>DATA_TRX_ID</code>，这个表示这条记录的事务 ID</p>
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<p>还有一个是 <code>DATA_ROLL_PTR</code> 指向回滚段的指针</p>
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<p>指向的回滚段其实就是我们常说的 undo log，这里面的具体结构就是个链表，在 mvcc 里会使用到这个，还有就是这个 <code>DATA_TRX_ID</code>，每条记录都记录了这个事务 ID，表示的是这条记录的当前值是被哪个事务修改的，下面就扯回事务了，我们知道 <code>Read Uncommitted</code>， 其实用不到隔离，直接读取当前值就好了，到了 <code>Read Committed</code> 级别，我们要让事务读取到提交过的值，mysql 使用了一个叫 <code>read view</code> 的玩意，它里面有这些值是我们需要注意的，</p>
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<p><code>m_low_limit_id</code>, 这个是 read view 创建时最大的活跃事务 id</p>
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<p><code>m_up_limit_id</code>, 这个是 read view 创建时最小的活跃事务 id</p>
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<p><code>m_ids</code>, 这个是 read view 创建时所有的活跃事务 id 数组</p>
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<p><code>m_creator_trx_id 这个是当前记录的创建事务 id</code></p>
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<p>判断事务的可见性主要的逻辑是这样，</p>
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<ol>
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<li>当记录的事务 <code>id</code> 小于最小活跃事务 id，说明是可见的，</li>
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<li>如果记录的事务 <code>id</code> 等于当前事务 id，说明是自己的更改，可见</li>
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<li>如果记录的事务 <code>id</code> 大于最大的活跃事务 <code>id</code>, 不可见</li>
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<li>如果记录的事务 <code>id</code> 介于 <code>m_low_limit_id</code> 和 <code>m_up_limit_id</code> 之间，则要判断它是否在 <code>m_ids</code> 中，如果在，不可见，如果不在，表示已提交，可见<br>具体的<a href="https://github.com/mysql/mysql-server/blob/8.0/storage/innobase/include/read0types.h#L160" target="_blank" rel="noopener">代码</a>捞一下看看<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></pre></td><td class="code"><pre><span class="line"><span class="comment">/** Check whether the changes by id are visible.</span></span><br><span class="line"><span class="comment"> @param[in] id transaction id to check against the view</span></span><br><span class="line"><span class="comment"> @param[in] name table name</span></span><br><span class="line"><span class="comment"> @return whether the view sees the modifications of id. */</span></span><br><span class="line"> <span class="function"><span class="keyword">bool</span> <span class="title">changes_visible</span><span class="params">(<span class="keyword">trx_id_t</span> id, <span class="keyword">const</span> <span class="keyword">table_name_t</span> &name)</span> <span class="keyword">const</span></span></span><br><span class="line"><span class="function"> <span class="title">MY_ATTRIBUTE</span><span class="params">((warn_unused_result))</span> </span>{</span><br><span class="line"> ut_ad(id > <span class="number">0</span>);</span><br><span class="line"></span><br><span class="line"> <span class="keyword">if</span> (id < m_up_limit_id || id == m_creator_trx_id) {</span><br><span class="line"> <span class="keyword">return</span> (<span class="literal">true</span>);</span><br><span class="line"> }</span><br><span class="line"></span><br><span class="line"> check_trx_id_sanity(id, name);</span><br><span class="line"></span><br><span class="line"> <span class="keyword">if</span> (id >= m_low_limit_id) {</span><br><span class="line"> <span class="keyword">return</span> (<span class="literal">false</span>);</span><br><span class="line"></span><br><span class="line"> } <span class="keyword">else</span> <span class="keyword">if</span> (m_ids.empty()) {</span><br><span class="line"> <span class="keyword">return</span> (<span class="literal">true</span>);</span><br><span class="line"> }</span><br><span class="line"></span><br><span class="line"> <span class="keyword">const</span> <span class="keyword">ids_t</span>::value_type *p = m_ids.data();</span><br><span class="line"></span><br><span class="line"> <span class="keyword">return</span> (!<span class="built_in">std</span>::binary_search(p, p + m_ids.<span class="built_in">size</span>(), id));</span><br><span class="line"> }</span><br></pre></td></tr></table></figure>
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剩下来一点是啥呢，就是 <code>Read Committed</code> 和 <code>Repeated Read</code> 也不一样，那前面说的 <code>read view</code> 都能支持吗，又是怎么支持呢，假如这个 <code>read view</code> 是在事务一开始就创建，那好像能支持的只是 RR 事务隔离级别，其实呢，这是通过创建 <code>read view</code>的时机，对于 RR 级别，就是在事务的第一个 <code>select</code> 语句是创建，对于 RC 级别，是在每个 <code>select</code> 语句执行前都是创建一次，那样就可以保证能读到所有已提交的数据</li>
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<h3 id="LRU"><a href="#LRU" class="headerlink" title="LRU"></a>LRU</h3><p>说完了过期策略再说下淘汰策略，redis 使用的策略是近似的 lru 策略，为什么是近似的呢，先来看下什么是 lru，看下 wiki 的介绍<br><img data-src="https://i.loli.net/2020/04/14/wWyhc2dQfb4BYsK.png" alt="">，图中一共有四个槽的存储空间，依次访问顺序是 A B C D E D F，<br>当第一次访问 D 时刚好占满了坑，并且值是 4，这个值越小代表越先被淘汰，当 E 进来时，看了下已经存在的四个里 A 是最小的，代表是最早存在并且最早被访问的，那就先淘汰它了，E 占领了 A 的位置，并设置值为 4，然后又访问 D 了，D 已经存在了，不过又被访问到了，得更新值为 5，然后是 F 进来了，这时 B 是最老的且最近未被访问，所以就淘汰它了。以上是一个 lru 的简要说明，但是 redis 没有严格按照这个去执行，理由跟前面过期策略一致，最严格的过期策略应该是每个 key 都有对应的定时器，当超时时马上就能清除，但是问题是这样的cpu 消耗太大，所换来的内存效率不太值得，淘汰策略也是这样，类似于上图，要维护所有 key 的一个有序 lru 值，并且遍历将最小的淘汰，redis 采用的是抽样的形式，最初的实现方式是随机从 dict 抽取 5 个 key，淘汰一个 lru 最小的，这样子勉强能达到淘汰的目的，但是效果不是特别好，后面在 redis 3.0开始，将随机抽取改成了维护一个 pool，pool 的大小默认是 16，每次放入的都是按lru 值有序排列好，每一次放入的必须是 lru小于 pool 中最小的 lru 才允许放入，直到放满，后面再有新的就会将大的踢出。<br>redis 针对这个策略的改进做了一个实验，这里借用下图<br><img data-src="https://i.loli.net/2020/04/18/QwcROpB345ezEkX.png" alt=""><br>首先背景是这图中的所有点都对应一个 redis 的 key，灰色部分加入后被顺序访问过一遍，然后又加入了绿色部分，那么按照理论的 lru 算法，应该是图左上中，浅灰色部分全都被淘汰，那么对比来看看图右上，左下和右下，左下表示 2.8 版本就是随机抽样 5 个 key，淘汰其中 lru 最小的一个，发现是灰色和浅灰色的都有被淘汰的，右下的 3.0 版本抽样数量不变的情况下，稍好一些，当 3.0 版本的抽样数量调整成 10 后，已经较为接近理论上的 lru 策略了，通过代码来简要分析下</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></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">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>对于 lru 策略来说，lru 字段记录的就是<a href="https://github.com/antirez/redis/blob/unstable/src/server.h#L603" target="_blank" rel="noopener"><code>redisObj</code></a> 的LRU time，<br>redis 在访问数据时，都会调用<a href="https://github.com/antirez/redis/blob/unstable/src/db.c#L55" target="_blank" rel="noopener"><code>lookupKey</code></a>方法</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">/* Low level key lookup API, not actually called directly from commands</span></span><br><span class="line"><span class="comment"> * implementations that should instead rely on lookupKeyRead(),</span></span><br><span class="line"><span class="comment"> * lookupKeyWrite() and lookupKeyReadWithFlags(). */</span></span><br><span class="line"><span class="function">robj *<span class="title">lookupKey</span><span class="params">(redisDb *db, robj *key, <span class="keyword">int</span> flags)</span> </span>{</span><br><span class="line"> dictEntry *de = dictFind(db->dict,key->ptr);</span><br><span class="line"> <span class="keyword">if</span> (de) {</span><br><span class="line"> robj *val = dictGetVal(de);</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Update the access time for the ageing algorithm.</span></span><br><span class="line"><span class="comment"> * Don't do it if we have a saving child, as this will trigger</span></span><br><span class="line"><span class="comment"> * a copy on write madness. */</span></span><br><span class="line"> <span class="keyword">if</span> (!hasActiveChildProcess() && !(flags & LOOKUP_NOTOUCH)){</span><br><span class="line"> <span class="keyword">if</span> (server.maxmemory_policy & MAXMEMORY_FLAG_LFU) {</span><br><span class="line"> <span class="comment">// 这个是后面一节的内容</span></span><br><span class="line"> updateLFU(val);</span><br><span class="line"> } <span class="keyword">else</span> {</span><br><span class="line"> <span class="comment">// 对于这个分支，访问时就会去更新 lru 值</span></span><br><span class="line"> val->lru = LRU_CLOCK();</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"> <span class="keyword">return</span> val;</span><br><span class="line"> } <span class="keyword">else</span> {</span><br><span class="line"> <span class="keyword">return</span> <span class="literal">NULL</span>;</span><br><span class="line"> }</span><br><span class="line">}</span><br><span class="line"><span class="comment">/* This function is used to obtain the current LRU clock.</span></span><br><span class="line"><span class="comment"> * If the current resolution is lower than the frequency we refresh the</span></span><br><span class="line"><span class="comment"> * LRU clock (as it should be in production servers) we return the</span></span><br><span class="line"><span class="comment"> * precomputed value, otherwise we need to resort to a system call. */</span></span><br><span class="line"><span class="function"><span class="keyword">unsigned</span> <span class="keyword">int</span> <span class="title">LRU_CLOCK</span><span class="params">(<span class="keyword">void</span>)</span> </span>{</span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">int</span> lruclock;</span><br><span class="line"> <span class="keyword">if</span> (<span class="number">1000</span>/server.hz <= LRU_CLOCK_RESOLUTION) {</span><br><span class="line"> <span class="comment">// 如果服务器的频率server.hz大于 1 时就是用系统预设的 lruclock</span></span><br><span class="line"> lruclock = server.lruclock;</span><br><span class="line"> } <span class="keyword">else</span> {</span><br><span class="line"> lruclock = getLRUClock();</span><br><span class="line"> }</span><br><span class="line"> <span class="keyword">return</span> lruclock;</span><br><span class="line">}</span><br><span class="line"><span class="comment">/* Return the LRU clock, based on the clock resolution. This is a time</span></span><br><span class="line"><span class="comment"> * in a reduced-bits format that can be used to set and check the</span></span><br><span class="line"><span class="comment"> * object->lru field of redisObject structures. */</span></span><br><span class="line"><span class="function"><span class="keyword">unsigned</span> <span class="keyword">int</span> <span class="title">getLRUClock</span><span class="params">(<span class="keyword">void</span>)</span> </span>{</span><br><span class="line"> <span class="keyword">return</span> (mstime()/LRU_CLOCK_RESOLUTION) & LRU_CLOCK_MAX;</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>redis 处理命令是在这里<a href="https://github.com/antirez/redis/blob/unstable/src/server.c#L3355" target="_blank" rel="noopener"><code>processCommand</code></a></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></pre></td><td class="code"><pre><span class="line"><span class="comment">/* If this function gets called we already read a whole</span></span><br><span class="line"><span class="comment"> * command, arguments are in the client argv/argc fields.</span></span><br><span class="line"><span class="comment"> * processCommand() execute the command or prepare the</span></span><br><span class="line"><span class="comment"> * server for a bulk read from the client.</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * If C_OK is returned the client is still alive and valid and</span></span><br><span class="line"><span class="comment"> * other operations can be performed by the caller. Otherwise</span></span><br><span class="line"><span class="comment"> * if C_ERR is returned the client was destroyed (i.e. after QUIT). */</span></span><br><span class="line"><span class="function"><span class="keyword">int</span> <span class="title">processCommand</span><span class="params">(client *c)</span> </span>{</span><br><span class="line"> moduleCallCommandFilters(c);</span><br><span class="line"></span><br><span class="line"> </span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Handle the maxmemory directive.</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * Note that we do not want to reclaim memory if we are here re-entering</span></span><br><span class="line"><span class="comment"> * the event loop since there is a busy Lua script running in timeout</span></span><br><span class="line"><span class="comment"> * condition, to avoid mixing the propagation of scripts with the</span></span><br><span class="line"><span class="comment"> * propagation of DELs due to eviction. */</span></span><br><span class="line"> <span class="keyword">if</span> (server.maxmemory && !server.lua_timedout) {</span><br><span class="line"> <span class="keyword">int</span> out_of_memory = freeMemoryIfNeededAndSafe() == C_ERR;</span><br><span class="line"> <span class="comment">/* freeMemoryIfNeeded may flush slave output buffers. This may result</span></span><br><span class="line"><span class="comment"> * into a slave, that may be the active client, to be freed. */</span></span><br><span class="line"> <span class="keyword">if</span> (server.current_client == <span class="literal">NULL</span>) <span class="keyword">return</span> C_ERR;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* It was impossible to free enough memory, and the command the client</span></span><br><span class="line"><span class="comment"> * is trying to execute is denied during OOM conditions or the client</span></span><br><span class="line"><span class="comment"> * is in MULTI/EXEC context? Error. */</span></span><br><span class="line"> <span class="keyword">if</span> (out_of_memory &&</span><br><span class="line"> (c->cmd->flags & CMD_DENYOOM ||</span><br><span class="line"> (c->flags & CLIENT_MULTI &&</span><br><span class="line"> c->cmd->proc != execCommand &&</span><br><span class="line"> c->cmd->proc != discardCommand)))</span><br><span class="line"> {</span><br><span class="line"> flagTransaction(c);</span><br><span class="line"> addReply(c, shared.oomerr);</span><br><span class="line"> <span class="keyword">return</span> C_OK;</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>这里只摘了部分，当需要清理内存时就会调用, 然后调用了<a href="https://github.com/antirez/redis/blob/unstable/src/evict.c#L631" target="_blank" rel="noopener"><code>freeMemoryIfNeededAndSafe</code></a></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><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 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class="line">122</span><br><span class="line">123</span><br><span class="line">124</span><br><span class="line">125</span><br><span class="line">126</span><br><span class="line">127</span><br><span class="line">128</span><br><span class="line">129</span><br><span class="line">130</span><br><span class="line">131</span><br><span class="line">132</span><br><span class="line">133</span><br><span class="line">134</span><br><span class="line">135</span><br><span class="line">136</span><br><span class="line">137</span><br><span class="line">138</span><br><span class="line">139</span><br><span class="line">140</span><br><span class="line">141</span><br><span class="line">142</span><br><span class="line">143</span><br><span class="line">144</span><br><span class="line">145</span><br><span class="line">146</span><br><span class="line">147</span><br><span class="line">148</span><br><span class="line">149</span><br><span class="line">150</span><br><span class="line">151</span><br><span class="line">152</span><br><span class="line">153</span><br><span class="line">154</span><br><span class="line">155</span><br><span class="line">156</span><br><span class="line">157</span><br><span class="line">158</span><br><span class="line">159</span><br><span class="line">160</span><br><span class="line">161</span><br><span class="line">162</span><br><span class="line">163</span><br><span class="line">164</span><br><span class="line">165</span><br><span class="line">166</span><br><span class="line">167</span><br><span class="line">168</span><br><span class="line">169</span><br><span class="line">170</span><br><span class="line">171</span><br><span class="line">172</span><br><span class="line">173</span><br><span class="line">174</span><br><span class="line">175</span><br><span class="line">176</span><br><span class="line">177</span><br><span class="line">178</span><br><span class="line">179</span><br><span class="line">180</span><br><span class="line">181</span><br><span class="line">182</span><br><span class="line">183</span><br><span class="line">184</span><br><span class="line">185</span><br><span class="line">186</span><br><span class="line">187</span><br><span class="line">188</span><br><span class="line">189</span><br><span class="line">190</span><br><span class="line">191</span><br><span class="line">192</span><br><span class="line">193</span><br><span class="line">194</span><br><span class="line">195</span><br><span class="line">196</span><br><span class="line">197</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment">/* This is a wrapper for freeMemoryIfNeeded() that only really calls the</span></span><br><span class="line"><span class="comment"> * function if right now there are the conditions to do so safely:</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * - There must be no script in timeout condition.</span></span><br><span class="line"><span class="comment"> * - Nor we are loading data right now.</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> */</span></span><br><span class="line"><span class="function"><span class="keyword">int</span> <span class="title">freeMemoryIfNeededAndSafe</span><span class="params">(<span class="keyword">void</span>)</span> </span>{</span><br><span class="line"> <span class="keyword">if</span> (server.lua_timedout || server.loading) <span class="keyword">return</span> C_OK;</span><br><span class="line"> <span class="keyword">return</span> freeMemoryIfNeeded();</span><br><span class="line">}</span><br><span class="line"><span class="comment">/* This function is periodically called to see if there is memory to free</span></span><br><span class="line"><span class="comment"> * according to the current "maxmemory" settings. In case we are over the</span></span><br><span class="line"><span class="comment"> * memory limit, the function will try to free some memory to return back</span></span><br><span class="line"><span class="comment"> * under the limit.</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * The function returns C_OK if we are under the memory limit or if we</span></span><br><span class="line"><span class="comment"> * were over the limit, but the attempt to free memory was successful.</span></span><br><span class="line"><span class="comment"> * Otehrwise if we are over the memory limit, but not enough memory</span></span><br><span class="line"><span class="comment"> * was freed to return back under the limit, the function returns C_ERR. */</span></span><br><span class="line"><span class="function"><span class="keyword">int</span> <span class="title">freeMemoryIfNeeded</span><span class="params">(<span class="keyword">void</span>)</span> </span>{</span><br><span class="line"> <span class="keyword">int</span> keys_freed = <span class="number">0</span>;</span><br><span class="line"> <span class="comment">/* By default replicas should ignore maxmemory</span></span><br><span class="line"><span class="comment"> * and just be masters exact copies. */</span></span><br><span class="line"> <span class="keyword">if</span> (server.masterhost && server.repl_slave_ignore_maxmemory) <span class="keyword">return</span> C_OK;</span><br><span class="line"></span><br><span class="line"> <span class="keyword">size_t</span> mem_reported, mem_tofree, mem_freed;</span><br><span class="line"> <span class="keyword">mstime_t</span> latency, eviction_latency;</span><br><span class="line"> <span class="keyword">long</span> <span class="keyword">long</span> delta;</span><br><span class="line"> <span class="keyword">int</span> slaves = listLength(server.slaves);</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* When clients are paused the dataset should be static not just from the</span></span><br><span class="line"><span class="comment"> * POV of clients not being able to write, but also from the POV of</span></span><br><span class="line"><span class="comment"> * expires and evictions of keys not being performed. */</span></span><br><span class="line"> <span class="keyword">if</span> (clientsArePaused()) <span class="keyword">return</span> C_OK;</span><br><span class="line"> <span class="keyword">if</span> (getMaxmemoryState(&mem_reported,<span class="literal">NULL</span>,&mem_tofree,<span class="literal">NULL</span>) == C_OK)</span><br><span class="line"> <span class="keyword">return</span> C_OK;</span><br><span class="line"></span><br><span class="line"> mem_freed = <span class="number">0</span>;</span><br><span class="line"></span><br><span class="line"> <span class="keyword">if</span> (server.maxmemory_policy == MAXMEMORY_NO_EVICTION)</span><br><span class="line"> <span class="keyword">goto</span> cant_free; <span class="comment">/* We need to free memory, but policy forbids. */</span></span><br><span class="line"></span><br><span class="line"> latencyStartMonitor(latency);</span><br><span class="line"> <span class="keyword">while</span> (mem_freed < mem_tofree) {</span><br><span class="line"> <span class="keyword">int</span> j, k, i;</span><br><span class="line"> <span class="keyword">static</span> <span class="keyword">unsigned</span> <span class="keyword">int</span> next_db = <span class="number">0</span>;</span><br><span class="line"> sds bestkey = <span class="literal">NULL</span>;</span><br><span class="line"> <span class="keyword">int</span> bestdbid;</span><br><span class="line"> redisDb *db;</span><br><span class="line"> dict *dict;</span><br><span class="line"> dictEntry *de;</span><br><span class="line"></span><br><span class="line"> <span class="keyword">if</span> (server.maxmemory_policy & (MAXMEMORY_FLAG_LRU|MAXMEMORY_FLAG_LFU) ||</span><br><span class="line"> server.maxmemory_policy == MAXMEMORY_VOLATILE_TTL)</span><br><span class="line"> {</span><br><span class="line"> <span class="class"><span class="keyword">struct</span> <span class="title">evictionPoolEntry</span> *<span class="title">pool</span> = <span class="title">EvictionPoolLRU</span>;</span></span><br><span class="line"></span><br><span class="line"> <span class="keyword">while</span>(bestkey == <span class="literal">NULL</span>) {</span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> total_keys = <span class="number">0</span>, keys;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* We don't want to make local-db choices when expiring keys,</span></span><br><span class="line"><span class="comment"> * so to start populate the eviction pool sampling keys from</span></span><br><span class="line"><span class="comment"> * every DB. */</span></span><br><span class="line"> <span class="keyword">for</span> (i = <span class="number">0</span>; i < server.dbnum; i++) {</span><br><span class="line"> db = server.db+i;</span><br><span class="line"> dict = (server.maxmemory_policy & MAXMEMORY_FLAG_ALLKEYS) ?</span><br><span class="line"> db->dict : db->expires;</span><br><span class="line"> <span class="keyword">if</span> ((keys = dictSize(dict)) != <span class="number">0</span>) {</span><br><span class="line"> evictionPoolPopulate(i, dict, db->dict, pool);</span><br><span class="line"> total_keys += keys;</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"> <span class="keyword">if</span> (!total_keys) <span class="keyword">break</span>; <span class="comment">/* No keys to evict. */</span></span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Go backward from best to worst element to evict. */</span></span><br><span class="line"> <span class="keyword">for</span> (k = EVPOOL_SIZE<span class="number">-1</span>; k >= <span class="number">0</span>; k--) {</span><br><span class="line"> <span class="keyword">if</span> (pool[k].key == <span class="literal">NULL</span>) <span class="keyword">continue</span>;</span><br><span class="line"> bestdbid = pool[k].dbid;</span><br><span class="line"></span><br><span class="line"> <span class="keyword">if</span> (server.maxmemory_policy & MAXMEMORY_FLAG_ALLKEYS) {</span><br><span class="line"> de = dictFind(server.db[pool[k].dbid].dict,</span><br><span class="line"> pool[k].key);</span><br><span class="line"> } <span class="keyword">else</span> {</span><br><span class="line"> de = dictFind(server.db[pool[k].dbid].expires,</span><br><span class="line"> pool[k].key);</span><br><span class="line"> }</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Remove the entry from the pool. */</span></span><br><span class="line"> <span class="keyword">if</span> (pool[k].key != pool[k].cached)</span><br><span class="line"> sdsfree(pool[k].key);</span><br><span class="line"> pool[k].key = <span class="literal">NULL</span>;</span><br><span class="line"> pool[k].idle = <span class="number">0</span>;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* If the key exists, is our pick. Otherwise it is</span></span><br><span class="line"><span class="comment"> * a ghost and we need to try the next element. */</span></span><br><span class="line"> <span class="keyword">if</span> (de) {</span><br><span class="line"> bestkey = dictGetKey(de);</span><br><span class="line"> <span class="keyword">break</span>;</span><br><span class="line"> } <span class="keyword">else</span> {</span><br><span class="line"> <span class="comment">/* Ghost... Iterate again. */</span></span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* volatile-random and allkeys-random policy */</span></span><br><span class="line"> <span class="keyword">else</span> <span class="keyword">if</span> (server.maxmemory_policy == MAXMEMORY_ALLKEYS_RANDOM ||</span><br><span class="line"> server.maxmemory_policy == MAXMEMORY_VOLATILE_RANDOM)</span><br><span class="line"> {</span><br><span class="line"> <span class="comment">/* When evicting a random key, we try to evict a key for</span></span><br><span class="line"><span class="comment"> * each DB, so we use the static 'next_db' variable to</span></span><br><span class="line"><span class="comment"> * incrementally visit all DBs. */</span></span><br><span class="line"> <span class="keyword">for</span> (i = <span class="number">0</span>; i < server.dbnum; i++) {</span><br><span class="line"> j = (++next_db) % server.dbnum;</span><br><span class="line"> db = server.db+j;</span><br><span class="line"> dict = (server.maxmemory_policy == MAXMEMORY_ALLKEYS_RANDOM) ?</span><br><span class="line"> db->dict : db->expires;</span><br><span class="line"> <span class="keyword">if</span> (dictSize(dict) != <span class="number">0</span>) {</span><br><span class="line"> de = dictGetRandomKey(dict);</span><br><span class="line"> bestkey = dictGetKey(de);</span><br><span class="line"> bestdbid = j;</span><br><span class="line"> <span class="keyword">break</span>;</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Finally remove the selected key. */</span></span><br><span class="line"> <span class="keyword">if</span> (bestkey) {</span><br><span class="line"> db = server.db+bestdbid;</span><br><span class="line"> robj *keyobj = createStringObject(bestkey,sdslen(bestkey));</span><br><span class="line"> propagateExpire(db,keyobj,server.lazyfree_lazy_eviction);</span><br><span class="line"> <span class="comment">/* We compute the amount of memory freed by db*Delete() alone.</span></span><br><span class="line"><span class="comment"> * It is possible that actually the memory needed to propagate</span></span><br><span class="line"><span class="comment"> * the DEL in AOF and replication link is greater than the one</span></span><br><span class="line"><span class="comment"> * we are freeing removing the key, but we can't account for</span></span><br><span class="line"><span class="comment"> * that otherwise we would never exit the loop.</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * AOF and Output buffer memory will be freed eventually so</span></span><br><span class="line"><span class="comment"> * we only care about memory used by the key space. */</span></span><br><span class="line"> delta = (<span class="keyword">long</span> <span class="keyword">long</span>) zmalloc_used_memory();</span><br><span class="line"> latencyStartMonitor(eviction_latency);</span><br><span class="line"> <span class="keyword">if</span> (server.lazyfree_lazy_eviction)</span><br><span class="line"> dbAsyncDelete(db,keyobj);</span><br><span class="line"> <span class="keyword">else</span></span><br><span class="line"> dbSyncDelete(db,keyobj);</span><br><span class="line"> latencyEndMonitor(eviction_latency);</span><br><span class="line"> latencyAddSampleIfNeeded(<span class="string">"eviction-del"</span>,eviction_latency);</span><br><span class="line"> latencyRemoveNestedEvent(latency,eviction_latency);</span><br><span class="line"> delta -= (<span class="keyword">long</span> <span class="keyword">long</span>) zmalloc_used_memory();</span><br><span class="line"> mem_freed += delta;</span><br><span class="line"> server.stat_evictedkeys++;</span><br><span class="line"> notifyKeyspaceEvent(NOTIFY_EVICTED, <span class="string">"evicted"</span>,</span><br><span class="line"> keyobj, db->id);</span><br><span class="line"> decrRefCount(keyobj);</span><br><span class="line"> keys_freed++;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* When the memory to free starts to be big enough, we may</span></span><br><span class="line"><span class="comment"> * start spending so much time here that is impossible to</span></span><br><span class="line"><span class="comment"> * deliver data to the slaves fast enough, so we force the</span></span><br><span class="line"><span class="comment"> * transmission here inside the loop. */</span></span><br><span class="line"> <span class="keyword">if</span> (slaves) flushSlavesOutputBuffers();</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Normally our stop condition is the ability to release</span></span><br><span class="line"><span class="comment"> * a fixed, pre-computed amount of memory. However when we</span></span><br><span class="line"><span class="comment"> * are deleting objects in another thread, it's better to</span></span><br><span class="line"><span class="comment"> * check, from time to time, if we already reached our target</span></span><br><span class="line"><span class="comment"> * memory, since the "mem_freed" amount is computed only</span></span><br><span class="line"><span class="comment"> * across the dbAsyncDelete() call, while the thread can</span></span><br><span class="line"><span class="comment"> * release the memory all the time. */</span></span><br><span class="line"> <span class="keyword">if</span> (server.lazyfree_lazy_eviction && !(keys_freed % <span class="number">16</span>)) {</span><br><span class="line"> <span class="keyword">if</span> (getMaxmemoryState(<span class="literal">NULL</span>,<span class="literal">NULL</span>,<span class="literal">NULL</span>,<span class="literal">NULL</span>) == C_OK) {</span><br><span class="line"> <span class="comment">/* Let's satisfy our stop condition. */</span></span><br><span class="line"> mem_freed = mem_tofree;</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"> } <span class="keyword">else</span> {</span><br><span class="line"> latencyEndMonitor(latency);</span><br><span class="line"> latencyAddSampleIfNeeded(<span class="string">"eviction-cycle"</span>,latency);</span><br><span class="line"> <span class="keyword">goto</span> cant_free; <span class="comment">/* nothing to free... */</span></span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"> latencyEndMonitor(latency);</span><br><span class="line"> latencyAddSampleIfNeeded(<span class="string">"eviction-cycle"</span>,latency);</span><br><span class="line"> <span class="keyword">return</span> C_OK;</span><br><span class="line"></span><br><span class="line">cant_free:</span><br><span class="line"> <span class="comment">/* We are here if we are not able to reclaim memory. There is only one</span></span><br><span class="line"><span class="comment"> * last thing we can try: check if the lazyfree thread has jobs in queue</span></span><br><span class="line"><span class="comment"> * and wait... */</span></span><br><span class="line"> <span class="keyword">while</span>(bioPendingJobsOfType(BIO_LAZY_FREE)) {</span><br><span class="line"> <span class="keyword">if</span> (((mem_reported - zmalloc_used_memory()) + mem_freed) >= mem_tofree)</span><br><span class="line"> <span class="keyword">break</span>;</span><br><span class="line"> usleep(<span class="number">1000</span>);</span><br><span class="line"> }</span><br><span class="line"> <span class="keyword">return</span> C_ERR;</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>这里就是根据具体策略去淘汰 key，首先是要往 pool 更新 key，更新key 的方法是<a href="https://github.com/antirez/redis/blob/unstable/src/evict.c#L162" target="_blank" rel="noopener"><code>evictionPoolPopulate</code></a></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><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></pre></td><td class="code"><pre><span class="line"><span class="function"><span class="keyword">void</span> <span class="title">evictionPoolPopulate</span><span class="params">(<span class="keyword">int</span> dbid, dict *sampledict, dict *keydict, struct evictionPoolEntry *pool)</span> </span>{</span><br><span class="line"> <span class="keyword">int</span> j, k, count;</span><br><span class="line"> dictEntry *samples[server.maxmemory_samples];</span><br><span class="line"></span><br><span class="line"> count = dictGetSomeKeys(sampledict,samples,server.maxmemory_samples);</span><br><span class="line"> <span class="keyword">for</span> (j = <span class="number">0</span>; j < count; j++) {</span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> <span class="keyword">long</span> idle;</span><br><span class="line"> sds key;</span><br><span class="line"> robj *o;</span><br><span class="line"> dictEntry *de;</span><br><span class="line"></span><br><span class="line"> de = samples[j];</span><br><span class="line"> key = dictGetKey(de);</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* If the dictionary we are sampling from is not the main</span></span><br><span class="line"><span class="comment"> * dictionary (but the expires one) we need to lookup the key</span></span><br><span class="line"><span class="comment"> * again in the key dictionary to obtain the value object. */</span></span><br><span class="line"> <span class="keyword">if</span> (server.maxmemory_policy != MAXMEMORY_VOLATILE_TTL) {</span><br><span class="line"> <span class="keyword">if</span> (sampledict != keydict) de = dictFind(keydict, key);</span><br><span class="line"> o = dictGetVal(de);</span><br><span class="line"> }</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Calculate the idle time according to the policy. This is called</span></span><br><span class="line"><span class="comment"> * idle just because the code initially handled LRU, but is in fact</span></span><br><span class="line"><span class="comment"> * just a score where an higher score means better candidate. */</span></span><br><span class="line"> <span class="keyword">if</span> (server.maxmemory_policy & MAXMEMORY_FLAG_LRU) {</span><br><span class="line"> idle = estimateObjectIdleTime(o);</span><br><span class="line"> } <span class="keyword">else</span> <span class="keyword">if</span> (server.maxmemory_policy & MAXMEMORY_FLAG_LFU) {</span><br><span class="line"> <span class="comment">/* When we use an LRU policy, we sort the keys by idle time</span></span><br><span class="line"><span class="comment"> * so that we expire keys starting from greater idle time.</span></span><br><span class="line"><span class="comment"> * However when the policy is an LFU one, we have a frequency</span></span><br><span class="line"><span class="comment"> * estimation, and we want to evict keys with lower frequency</span></span><br><span class="line"><span class="comment"> * first. So inside the pool we put objects using the inverted</span></span><br><span class="line"><span class="comment"> * frequency subtracting the actual frequency to the maximum</span></span><br><span class="line"><span class="comment"> * frequency of 255. */</span></span><br><span class="line"> idle = <span class="number">255</span>-LFUDecrAndReturn(o);</span><br><span class="line"> } <span class="keyword">else</span> <span class="keyword">if</span> (server.maxmemory_policy == MAXMEMORY_VOLATILE_TTL) {</span><br><span class="line"> <span class="comment">/* In this case the sooner the expire the better. */</span></span><br><span class="line"> idle = ULLONG_MAX - (<span class="keyword">long</span>)dictGetVal(de);</span><br><span class="line"> } <span class="keyword">else</span> {</span><br><span class="line"> serverPanic(<span class="string">"Unknown eviction policy in evictionPoolPopulate()"</span>);</span><br><span class="line"> }</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Insert the element inside the pool.</span></span><br><span class="line"><span class="comment"> * First, find the first empty bucket or the first populated</span></span><br><span class="line"><span class="comment"> * bucket that has an idle time smaller than our idle time. */</span></span><br><span class="line"> k = <span class="number">0</span>;</span><br><span class="line"> <span class="keyword">while</span> (k < EVPOOL_SIZE &&</span><br><span class="line"> pool[k].key &&</span><br><span class="line"> pool[k].idle < idle) k++;</span><br><span class="line"> <span class="keyword">if</span> (k == <span class="number">0</span> && pool[EVPOOL_SIZE<span class="number">-1</span>].key != <span class="literal">NULL</span>) {</span><br><span class="line"> <span class="comment">/* Can't insert if the element is < the worst element we have</span></span><br><span class="line"><span class="comment"> * and there are no empty buckets. */</span></span><br><span class="line"> <span class="keyword">continue</span>;</span><br><span class="line"> } <span class="keyword">else</span> <span class="keyword">if</span> (k < EVPOOL_SIZE && pool[k].key == <span class="literal">NULL</span>) {</span><br><span class="line"> <span class="comment">/* Inserting into empty position. No setup needed before insert. */</span></span><br><span class="line"> } <span class="keyword">else</span> {</span><br><span class="line"> <span class="comment">/* Inserting in the middle. Now k points to the first element</span></span><br><span class="line"><span class="comment"> * greater than the element to insert. */</span></span><br><span class="line"> <span class="keyword">if</span> (pool[EVPOOL_SIZE<span class="number">-1</span>].key == <span class="literal">NULL</span>) {</span><br><span class="line"> <span class="comment">/* Free space on the right? Insert at k shifting</span></span><br><span class="line"><span class="comment"> * all the elements from k to end to the right. */</span></span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Save SDS before overwriting. */</span></span><br><span class="line"> sds cached = pool[EVPOOL_SIZE<span class="number">-1</span>].cached;</span><br><span class="line"> memmove(pool+k+<span class="number">1</span>,pool+k,</span><br><span class="line"> <span class="keyword">sizeof</span>(pool[<span class="number">0</span>])*(EVPOOL_SIZE-k<span class="number">-1</span>));</span><br><span class="line"> pool[k].cached = cached;</span><br><span class="line"> } <span class="keyword">else</span> {</span><br><span class="line"> <span class="comment">/* No free space on right? Insert at k-1 */</span></span><br><span class="line"> k--;</span><br><span class="line"> <span class="comment">/* Shift all elements on the left of k (included) to the</span></span><br><span class="line"><span class="comment"> * left, so we discard the element with smaller idle time. */</span></span><br><span class="line"> sds cached = pool[<span class="number">0</span>].cached; <span class="comment">/* Save SDS before overwriting. */</span></span><br><span class="line"> <span class="keyword">if</span> (pool[<span class="number">0</span>].key != pool[<span class="number">0</span>].cached) sdsfree(pool[<span class="number">0</span>].key);</span><br><span class="line"> memmove(pool,pool+<span class="number">1</span>,<span class="keyword">sizeof</span>(pool[<span class="number">0</span>])*k);</span><br><span class="line"> pool[k].cached = cached;</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Try to reuse the cached SDS string allocated in the pool entry,</span></span><br><span class="line"><span class="comment"> * because allocating and deallocating this object is costly</span></span><br><span class="line"><span class="comment"> * (according to the profiler, not my fantasy. Remember:</span></span><br><span class="line"><span class="comment"> * premature optimizbla bla bla bla. */</span></span><br><span class="line"> <span class="keyword">int</span> klen = sdslen(key);</span><br><span class="line"> <span class="keyword">if</span> (klen > EVPOOL_CACHED_SDS_SIZE) {</span><br><span class="line"> pool[k].key = sdsdup(key);</span><br><span class="line"> } <span class="keyword">else</span> {</span><br><span class="line"> <span class="built_in">memcpy</span>(pool[k].cached,key,klen+<span class="number">1</span>);</span><br><span class="line"> sdssetlen(pool[k].cached,klen);</span><br><span class="line"> pool[k].key = pool[k].cached;</span><br><span class="line"> }</span><br><span class="line"> pool[k].idle = idle;</span><br><span class="line"> pool[k].dbid = dbid;</span><br><span class="line"> }</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p><code>Redis</code>随机选择<code>maxmemory_samples</code>数量的key，然后计算这些<code>key</code>的空闲时间<code>idle time</code>，当满足条件时(比pool中的某些键的空闲时间还大)就可以进<code>pool</code>。<code>pool</code>更新之后，就淘汰<code>pool</code>中空闲时间最大的键。</p>
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<p><a href="https://github.com/antirez/redis/blob/unstable/src/evict.c#L90" target="_blank" rel="noopener"><code>estimateObjectIdleTime</code></a>用来计算Redis对象的空闲时间：</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></pre></td><td class="code"><pre><span class="line"><span class="comment">/* Given an object returns the min number of milliseconds the object was never</span></span><br><span class="line"><span class="comment"> * requested, using an approximated LRU algorithm. */</span></span><br><span class="line"><span class="function"><span class="keyword">unsigned</span> <span class="keyword">long</span> <span class="keyword">long</span> <span class="title">estimateObjectIdleTime</span><span class="params">(robj *o)</span> </span>{</span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> <span class="keyword">long</span> lruclock = LRU_CLOCK();</span><br><span class="line"> <span class="keyword">if</span> (lruclock >= o->lru) {</span><br><span class="line"> <span class="keyword">return</span> (lruclock - o->lru) * LRU_CLOCK_RESOLUTION;</span><br><span class="line"> } <span class="keyword">else</span> {</span><br><span class="line"> <span class="keyword">return</span> (lruclock + (LRU_CLOCK_MAX - o->lru)) *</span><br><span class="line"> LRU_CLOCK_RESOLUTION;</span><br><span class="line"> }</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>空闲时间第一种是 lurclock 大于对象的 lru，那么就是减一下乘以精度，因为 lruclock 有可能是已经预生成的，所以会可能走下面这个</p>
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<h3 id="LFU"><a href="#LFU" class="headerlink" title="LFU"></a>LFU</h3><p>上面介绍了LRU 的算法，但是考虑一种场景</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></pre></td><td class="code"><pre><span class="line">~~~~~A~~~~~A~~~~~A~~~~A~~~~~A~~~~~A~~|</span><br><span class="line">~~B~~B~~B~~B~~B~~B~~B~~B~~B~~B~~B~~B~|</span><br><span class="line">~~~~~~~~~~C~~~~~~~~~C~~~~~~~~~C~~~~~~|</span><br><span class="line">~~~~~D~~~~~~~~~~D~~~~~~~~~D~~~~~~~~~D|</span><br></pre></td></tr></table></figure>
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<p>可以发现，当采用 lru 的淘汰策略的时候，D 是最新的，会被认为是最值得保留的，但是事实上还不如 A 跟 B，然后 antirez 大神就想到了LFU (Least Frequently Used) 这个算法, 显然对于上面的四个 key 的访问频率，保留优先级应该是 B > A > C = D<br>那要怎么来实现这个 LFU 算法呢，其实像LRU，理想的情况就是维护个链表，把最新访问的放到头上去，但是这个会影响访问速度，注意到前面代码的应该可以看到，redisObject 的 lru 字段其实是两用的，当策略是 LFU 时，这个字段就另作他用了，它的 24 位长度被分成两部分</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></pre></td><td class="code"><pre><span class="line"> 16 bits 8 bits</span><br><span class="line">+----------------+--------+</span><br><span class="line">+ Last decr time | LOG_C |</span><br><span class="line">+----------------+--------+</span><br></pre></td></tr></table></figure>
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<p>前16位字段是最后一次递减时间，因此Redis知道 上一次计数器递减，后8位是 计数器 counter。<br>LFU 的主体策略就是当这个 key 被访问的次数越多频率越高他就越容易被保留下来，并且是最近被访问的频率越高。这其实有两个事情要做，一个是在访问的时候增加计数值，在一定长时间不访问时进行衰减，所以这里用了两个值，前 16 位记录上一次衰减的时间，后 8 位记录具体的计数值。<br>Redis4.0之后为maxmemory_policy淘汰策略添加了两个LFU模式：</p>
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<p><code>volatile-lfu</code>：对有过期时间的key采用LFU淘汰策略<br><code>allkeys-lfu</code>：对全部key采用LFU淘汰策略<br>还有2个配置可以调整LFU算法： </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></pre></td><td class="code"><pre><span class="line">lfu-log-factor 10</span><br><span class="line">lfu-decay-time 1</span><br><span class="line">``` </span><br><span class="line">`lfu-log-factor` 可以调整计数器counter的增长速度，lfu-log-factor越大，counter增长的越慢。</span><br><span class="line"></span><br><span class="line">`lfu-decay-time`是一个以分钟为单位的数值，可以调整counter的减少速度</span><br><span class="line">这里有个问题是 8 位大小够计么，访问一次加 1 的话的确不够，不过大神就是大神，才不会这么简单的加一。往下看代码</span><br><span class="line">```C</span><br><span class="line">/* Low level key lookup API, not actually called directly from commands</span><br><span class="line"> * implementations that should instead rely on lookupKeyRead(),</span><br><span class="line"> * lookupKeyWrite() and lookupKeyReadWithFlags(). */</span><br><span class="line">robj *lookupKey(redisDb *db, robj *key, int flags) {</span><br><span class="line"> dictEntry *de = dictFind(db->dict,key->ptr);</span><br><span class="line"> if (de) {</span><br><span class="line"> robj *val = dictGetVal(de);</span><br><span class="line"></span><br><span class="line"> /* Update the access time for the ageing algorithm.</span><br><span class="line"> * Don't do it if we have a saving child, as this will trigger</span><br><span class="line"> * a copy on write madness. */</span><br><span class="line"> if (!hasActiveChildProcess() && !(flags & LOOKUP_NOTOUCH)){</span><br><span class="line"> if (server.maxmemory_policy & MAXMEMORY_FLAG_LFU) {</span><br><span class="line"> // 当淘汰策略是 LFU 时，就会调用这个updateLFU</span><br><span class="line"> updateLFU(val);</span><br><span class="line"> } else {</span><br><span class="line"> val->lru = LRU_CLOCK();</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"> return val;</span><br><span class="line"> } else {</span><br><span class="line"> return NULL;</span><br><span class="line"> }</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p><a href="https://github.com/antirez/redis/blob/unstable/src/db.c#L46" target="_blank" rel="noopener"><code>updateLFU</code></a> 这个其实个入口，调用了两个重要的方法</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="comment">/* Update LFU when an object is accessed.</span></span><br><span class="line"><span class="comment"> * Firstly, decrement the counter if the decrement time is reached.</span></span><br><span class="line"><span class="comment"> * Then logarithmically increment the counter, and update the access time. */</span></span><br><span class="line"><span class="function"><span class="keyword">void</span> <span class="title">updateLFU</span><span class="params">(robj *val)</span> </span>{</span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> counter = LFUDecrAndReturn(val);</span><br><span class="line"> counter = LFULogIncr(counter);</span><br><span class="line"> val->lru = (LFUGetTimeInMinutes()<<<span class="number">8</span>) | counter;</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>首先来看看<a href="https://github.com/antirez/redis/blob/unstable/src/evict.c#L335" target="_blank" rel="noopener"><code>LFUDecrAndReturn</code></a>，这个方法的作用是根据上一次衰减时间和系统配置的 <code>lfu-decay-time</code> 参数来确定需要将 counter 减去多少</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">/* If the object decrement time is reached decrement the LFU counter but</span></span><br><span class="line"><span class="comment"> * do not update LFU fields of the object, we update the access time</span></span><br><span class="line"><span class="comment"> * and counter in an explicit way when the object is really accessed.</span></span><br><span class="line"><span class="comment"> * And we will times halve the counter according to the times of</span></span><br><span class="line"><span class="comment"> * elapsed time than server.lfu_decay_time.</span></span><br><span class="line"><span class="comment"> * Return the object frequency counter.</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * This function is used in order to scan the dataset for the best object</span></span><br><span class="line"><span class="comment"> * to fit: as we check for the candidate, we incrementally decrement the</span></span><br><span class="line"><span class="comment"> * counter of the scanned objects if needed. */</span></span><br><span class="line"><span class="function"><span class="keyword">unsigned</span> <span class="keyword">long</span> <span class="title">LFUDecrAndReturn</span><span class="params">(robj *o)</span> </span>{</span><br><span class="line"> <span class="comment">// 右移 8 位，拿到上次衰减时间</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> ldt = o->lru >> <span class="number">8</span>;</span><br><span class="line"> <span class="comment">// 对 255 做与操作，拿到 counter 值</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> counter = o->lru & <span class="number">255</span>;</span><br><span class="line"> <span class="comment">// 根据lfu_decay_time来算出过了多少个衰减周期</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> num_periods = server.lfu_decay_time ? LFUTimeElapsed(ldt) / server.lfu_decay_time : <span class="number">0</span>;</span><br><span class="line"> <span class="keyword">if</span> (num_periods)</span><br><span class="line"> counter = (num_periods > counter) ? <span class="number">0</span> : counter - num_periods;</span><br><span class="line"> <span class="keyword">return</span> counter;</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>然后是加，调用了<a href="https://github.com/antirez/redis/blob/unstable/src/evict.c#L315" target="_blank" rel="noopener"><code>LFULogIncr</code></a></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></pre></td><td class="code"><pre><span class="line"><span class="comment">/* Logarithmically increment a counter. The greater is the current counter value</span></span><br><span class="line"><span class="comment"> * the less likely is that it gets really implemented. Saturate it at 255. */</span></span><br><span class="line"><span class="function"><span class="keyword">uint8_t</span> <span class="title">LFULogIncr</span><span class="params">(<span class="keyword">uint8_t</span> counter)</span> </span>{</span><br><span class="line"> <span class="comment">// 最大值就是 255，到顶了就不加了</span></span><br><span class="line"> <span class="keyword">if</span> (counter == <span class="number">255</span>) <span class="keyword">return</span> <span class="number">255</span>;</span><br><span class="line"> <span class="comment">// 生成个随机小数</span></span><br><span class="line"> <span class="keyword">double</span> r = (<span class="keyword">double</span>)rand()/RAND_MAX;</span><br><span class="line"> <span class="comment">// 减去个基础值，LFU_INIT_VAL = 5，防止刚进来就被逐出</span></span><br><span class="line"> <span class="keyword">double</span> baseval = counter - LFU_INIT_VAL;</span><br><span class="line"> <span class="comment">// 如果是小于 0，</span></span><br><span class="line"> <span class="keyword">if</span> (baseval < <span class="number">0</span>) baseval = <span class="number">0</span>;</span><br><span class="line"> <span class="comment">// 如果 baseval 是 0，那么 p 就是 1了，后面 counter 直接加一，如果不是的话，得看系统参数lfu_log_factor，这个越大，除出来的 p 越小，那么 counter++的可能性也越小，这样子就把前面的疑问给解决了，不是直接+1 的</span></span><br><span class="line"> <span class="keyword">double</span> p = <span class="number">1.0</span>/(baseval*server.lfu_log_factor+<span class="number">1</span>);</span><br><span class="line"> <span class="keyword">if</span> (r < p) counter++;</span><br><span class="line"> <span class="keyword">return</span> counter;</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>大概的变化速度可以参考</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></pre></td><td class="code"><pre><span class="line">+--------+------------+------------+------------+------------+------------+</span><br><span class="line">| factor | 100 hits | 1000 hits | 100K hits | 1M hits | 10M hits |</span><br><span class="line">+--------+------------+------------+------------+------------+------------+</span><br><span class="line">| 0 | 104 | 255 | 255 | 255 | 255 |</span><br><span class="line">+--------+------------+------------+------------+------------+------------+</span><br><span class="line">| 1 | 18 | 49 | 255 | 255 | 255 |</span><br><span class="line">+--------+------------+------------+------------+------------+------------+</span><br><span class="line">| 10 | 10 | 18 | 142 | 255 | 255 |</span><br><span class="line">+--------+------------+------------+------------+------------+------------+</span><br><span class="line">| 100 | 8 | 11 | 49 | 143 | 255 |</span><br><span class="line">+--------+------------+------------+------------+------------+------------+</span><br></pre></td></tr></table></figure>
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<p>简而言之就是 lfu_log_factor 越大变化的越慢</p>
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<h3 id="总结"><a href="#总结" class="headerlink" title="总结"></a>总结</h3><p>总结一下，redis 实现了近似的 lru 淘汰策略，通过增加了淘汰 key 的池子(pool)，并且增大每次抽样的 key 的数量来将淘汰效果更进一步地接近于 lru，这是 lru 策略，但是对于前面举的一个例子，其实 lru 并不能保证 key 的淘汰就如我们预期，所以在后期又引入了 lfu 的策略，lfu的策略比较巧妙，复用了 redis 对象的 lru 字段，并且使用了factor 参数来控制计数器递增的速度，防止 8 位的计数器太早溢出。</p>
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<p>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。<br>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，</p>
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<h2 id="redis过期策略"><a href="#redis过期策略" class="headerlink" title="redis过期策略"></a>redis过期策略</h2><p>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<br>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<br>主要代码是</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><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></pre></td><td class="code"><pre><span class="line"><span class="comment">/* This function is called when we are going to perform some operation</span></span><br><span class="line"><span class="comment"> * in a given key, but such key may be already logically expired even if</span></span><br><span class="line"><span class="comment"> * it still exists in the database. The main way this function is called</span></span><br><span class="line"><span class="comment"> * is via lookupKey*() family of functions.</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * The behavior of the function depends on the replication role of the</span></span><br><span class="line"><span class="comment"> * instance, because slave instances do not expire keys, they wait</span></span><br><span class="line"><span class="comment"> * for DELs from the master for consistency matters. However even</span></span><br><span class="line"><span class="comment"> * slaves will try to have a coherent return value for the function,</span></span><br><span class="line"><span class="comment"> * so that read commands executed in the slave side will be able to</span></span><br><span class="line"><span class="comment"> * behave like if the key is expired even if still present (because the</span></span><br><span class="line"><span class="comment"> * master has yet to propagate the DEL).</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * In masters as a side effect of finding a key which is expired, such</span></span><br><span class="line"><span class="comment"> * key will be evicted from the database. Also this may trigger the</span></span><br><span class="line"><span class="comment"> * propagation of a DEL/UNLINK command in AOF / replication stream.</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * The return value of the function is 0 if the key is still valid,</span></span><br><span class="line"><span class="comment"> * otherwise the function returns 1 if the key is expired. */</span></span><br><span class="line"><span class="function"><span class="keyword">int</span> <span class="title">expireIfNeeded</span><span class="params">(redisDb *db, robj *key)</span> </span>{</span><br><span class="line"> <span class="keyword">if</span> (!keyIsExpired(db,key)) <span class="keyword">return</span> <span class="number">0</span>;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* If we are running in the context of a slave, instead of</span></span><br><span class="line"><span class="comment"> * evicting the expired key from the database, we return ASAP:</span></span><br><span class="line"><span class="comment"> * the slave key expiration is controlled by the master that will</span></span><br><span class="line"><span class="comment"> * send us synthesized DEL operations for expired keys.</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * Still we try to return the right information to the caller,</span></span><br><span class="line"><span class="comment"> * that is, 0 if we think the key should be still valid, 1 if</span></span><br><span class="line"><span class="comment"> * we think the key is expired at this time. */</span></span><br><span class="line"> <span class="keyword">if</span> (server.masterhost != <span class="literal">NULL</span>) <span class="keyword">return</span> <span class="number">1</span>;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Delete the key */</span></span><br><span class="line"> server.stat_expiredkeys++;</span><br><span class="line"> propagateExpire(db,key,server.lazyfree_lazy_expire);</span><br><span class="line"> notifyKeyspaceEvent(NOTIFY_EXPIRED,</span><br><span class="line"> <span class="string">"expired"</span>,key,db->id);</span><br><span class="line"> <span class="keyword">return</span> server.lazyfree_lazy_expire ? dbAsyncDelete(db,key) :</span><br><span class="line"> dbSyncDelete(db,key);</span><br><span class="line">}</span><br><span class="line"></span><br><span class="line"><span class="comment">/* Check if the key is expired. */</span></span><br><span class="line"><span class="function"><span class="keyword">int</span> <span class="title">keyIsExpired</span><span class="params">(redisDb *db, robj *key)</span> </span>{</span><br><span class="line"> <span class="keyword">mstime_t</span> when = getExpire(db,key);</span><br><span class="line"> <span class="keyword">mstime_t</span> now;</span><br><span class="line"></span><br><span class="line"> <span class="keyword">if</span> (when < <span class="number">0</span>) <span class="keyword">return</span> <span class="number">0</span>; <span class="comment">/* No expire for this key */</span></span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Don't expire anything while loading. It will be done later. */</span></span><br><span class="line"> <span class="keyword">if</span> (server.loading) <span class="keyword">return</span> <span class="number">0</span>;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* If we are in the context of a Lua script, we pretend that time is</span></span><br><span class="line"><span class="comment"> * blocked to when the Lua script started. This way a key can expire</span></span><br><span class="line"><span class="comment"> * only the first time it is accessed and not in the middle of the</span></span><br><span class="line"><span class="comment"> * script execution, making propagation to slaves / AOF consistent.</span></span><br><span class="line"><span class="comment"> * See issue #1525 on Github for more information. */</span></span><br><span class="line"> <span class="keyword">if</span> (server.lua_caller) {</span><br><span class="line"> now = server.lua_time_start;</span><br><span class="line"> }</span><br><span class="line"> <span class="comment">/* If we are in the middle of a command execution, we still want to use</span></span><br><span class="line"><span class="comment"> * a reference time that does not change: in that case we just use the</span></span><br><span class="line"><span class="comment"> * cached time, that we update before each call in the call() function.</span></span><br><span class="line"><span class="comment"> * This way we avoid that commands such as RPOPLPUSH or similar, that</span></span><br><span class="line"><span class="comment"> * may re-open the same key multiple times, can invalidate an already</span></span><br><span class="line"><span class="comment"> * open object in a next call, if the next call will see the key expired,</span></span><br><span class="line"><span class="comment"> * while the first did not. */</span></span><br><span class="line"> <span class="keyword">else</span> <span class="keyword">if</span> (server.fixed_time_expire > <span class="number">0</span>) {</span><br><span class="line"> now = server.mstime;</span><br><span class="line"> }</span><br><span class="line"> <span class="comment">/* For the other cases, we want to use the most fresh time we have. */</span></span><br><span class="line"> <span class="keyword">else</span> {</span><br><span class="line"> now = mstime();</span><br><span class="line"> }</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* The key expired if the current (virtual or real) time is greater</span></span><br><span class="line"><span class="comment"> * than the expire time of the key. */</span></span><br><span class="line"> <span class="keyword">return</span> now > when;</span><br><span class="line">}</span><br><span class="line"><span class="comment">/* Return the expire time of the specified key, or -1 if no expire</span></span><br><span class="line"><span class="comment"> * is associated with this key (i.e. the key is non volatile) */</span></span><br><span class="line"><span class="function"><span class="keyword">long</span> <span class="keyword">long</span> <span class="title">getExpire</span><span class="params">(redisDb *db, robj *key)</span> </span>{</span><br><span class="line"> dictEntry *de;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* No expire? return ASAP */</span></span><br><span class="line"> <span class="keyword">if</span> (dictSize(db->expires) == <span class="number">0</span> ||</span><br><span class="line"> (de = dictFind(db->expires,key->ptr)) == <span class="literal">NULL</span>) <span class="keyword">return</span> <span class="number">-1</span>;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* The entry was found in the expire dict, this means it should also</span></span><br><span class="line"><span class="comment"> * be present in the main dict (safety check). */</span></span><br><span class="line"> serverAssertWithInfo(<span class="literal">NULL</span>,key,dictFind(db->dict,key->ptr) != <span class="literal">NULL</span>);</span><br><span class="line"> <span class="keyword">return</span> dictGetSignedIntegerVal(de);</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>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。<br>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</p>
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class="line">302</span><br><span class="line">303</span><br><span class="line">304</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment">/* This function handles 'background' operations we are required to do</span></span><br><span class="line"><span class="comment"> * incrementally in Redis databases, such as active key expiring, resizing,</span></span><br><span class="line"><span class="comment"> * rehashing. */</span></span><br><span class="line"><span class="function"><span class="keyword">void</span> <span class="title">databasesCron</span><span class="params">(<span class="keyword">void</span>)</span> </span>{</span><br><span class="line"> <span class="comment">/* Expire keys by random sampling. Not required for slaves</span></span><br><span class="line"><span class="comment"> * as master will synthesize DELs for us. */</span></span><br><span class="line"> <span class="keyword">if</span> (server.active_expire_enabled) {</span><br><span class="line"> <span class="keyword">if</span> (server.masterhost == <span class="literal">NULL</span>) {</span><br><span class="line"> activeExpireCycle(ACTIVE_EXPIRE_CYCLE_SLOW);</span><br><span class="line"> } <span class="keyword">else</span> {</span><br><span class="line"> expireSlaveKeys();</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Defrag keys gradually. */</span></span><br><span class="line"> activeDefragCycle();</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Perform hash tables rehashing if needed, but only if there are no</span></span><br><span class="line"><span class="comment"> * other processes saving the DB on disk. Otherwise rehashing is bad</span></span><br><span class="line"><span class="comment"> * as will cause a lot of copy-on-write of memory pages. */</span></span><br><span class="line"> <span class="keyword">if</span> (!hasActiveChildProcess()) {</span><br><span class="line"> <span class="comment">/* We use global counters so if we stop the computation at a given</span></span><br><span class="line"><span class="comment"> * DB we'll be able to start from the successive in the next</span></span><br><span class="line"><span class="comment"> * cron loop iteration. */</span></span><br><span class="line"> <span class="keyword">static</span> <span class="keyword">unsigned</span> <span class="keyword">int</span> resize_db = <span class="number">0</span>;</span><br><span class="line"> <span class="keyword">static</span> <span class="keyword">unsigned</span> <span class="keyword">int</span> rehash_db = <span class="number">0</span>;</span><br><span class="line"> <span class="keyword">int</span> dbs_per_call = CRON_DBS_PER_CALL;</span><br><span class="line"> <span class="keyword">int</span> j;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Don't test more DBs than we have. */</span></span><br><span class="line"> <span class="keyword">if</span> (dbs_per_call > server.dbnum) dbs_per_call = server.dbnum;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Resize */</span></span><br><span class="line"> <span class="keyword">for</span> (j = <span class="number">0</span>; j < dbs_per_call; j++) {</span><br><span class="line"> tryResizeHashTables(resize_db % server.dbnum);</span><br><span class="line"> resize_db++;</span><br><span class="line"> }</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Rehash */</span></span><br><span class="line"> <span class="keyword">if</span> (server.activerehashing) {</span><br><span class="line"> <span class="keyword">for</span> (j = <span class="number">0</span>; j < dbs_per_call; j++) {</span><br><span class="line"> <span class="keyword">int</span> work_done = incrementallyRehash(rehash_db);</span><br><span class="line"> <span class="keyword">if</span> (work_done) {</span><br><span class="line"> <span class="comment">/* If the function did some work, stop here, we'll do</span></span><br><span class="line"><span class="comment"> * more at the next cron loop. */</span></span><br><span class="line"> <span class="keyword">break</span>;</span><br><span class="line"> } <span class="keyword">else</span> {</span><br><span class="line"> <span class="comment">/* If this db didn't need rehash, we'll try the next one. */</span></span><br><span class="line"> rehash_db++;</span><br><span class="line"> rehash_db %= server.dbnum;</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line">}</span><br><span class="line"><span class="comment">/* Try to expire a few timed out keys. The algorithm used is adaptive and</span></span><br><span class="line"><span class="comment"> * will use few CPU cycles if there are few expiring keys, otherwise</span></span><br><span class="line"><span class="comment"> * it will get more aggressive to avoid that too much memory is used by</span></span><br><span class="line"><span class="comment"> * keys that can be removed from the keyspace.</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * Every expire cycle tests multiple databases: the next call will start</span></span><br><span class="line"><span class="comment"> * again from the next db, with the exception of exists for time limit: in that</span></span><br><span class="line"><span class="comment"> * case we restart again from the last database we were processing. Anyway</span></span><br><span class="line"><span class="comment"> * no more than CRON_DBS_PER_CALL databases are tested at every iteration.</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * The function can perform more or less work, depending on the "type"</span></span><br><span class="line"><span class="comment"> * argument. It can execute a "fast cycle" or a "slow cycle". The slow</span></span><br><span class="line"><span class="comment"> * cycle is the main way we collect expired cycles: this happens with</span></span><br><span class="line"><span class="comment"> * the "server.hz" frequency (usually 10 hertz).</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * However the slow cycle can exit for timeout, since it used too much time.</span></span><br><span class="line"><span class="comment"> * For this reason the function is also invoked to perform a fast cycle</span></span><br><span class="line"><span class="comment"> * at every event loop cycle, in the beforeSleep() function. The fast cycle</span></span><br><span class="line"><span class="comment"> * will try to perform less work, but will do it much more often.</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * The following are the details of the two expire cycles and their stop</span></span><br><span class="line"><span class="comment"> * conditions:</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * If type is ACTIVE_EXPIRE_CYCLE_FAST the function will try to run a</span></span><br><span class="line"><span class="comment"> * "fast" expire cycle that takes no longer than EXPIRE_FAST_CYCLE_DURATION</span></span><br><span class="line"><span class="comment"> * microseconds, and is not repeated again before the same amount of time.</span></span><br><span class="line"><span class="comment"> * The cycle will also refuse to run at all if the latest slow cycle did not</span></span><br><span class="line"><span class="comment"> * terminate because of a time limit condition.</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * If type is ACTIVE_EXPIRE_CYCLE_SLOW, that normal expire cycle is</span></span><br><span class="line"><span class="comment"> * executed, where the time limit is a percentage of the REDIS_HZ period</span></span><br><span class="line"><span class="comment"> * as specified by the ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC define. In the</span></span><br><span class="line"><span class="comment"> * fast cycle, the check of every database is interrupted once the number</span></span><br><span class="line"><span class="comment"> * of already expired keys in the database is estimated to be lower than</span></span><br><span class="line"><span class="comment"> * a given percentage, in order to avoid doing too much work to gain too</span></span><br><span class="line"><span class="comment"> * little memory.</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * The configured expire "effort" will modify the baseline parameters in</span></span><br><span class="line"><span class="comment"> * order to do more work in both the fast and slow expire cycles.</span></span><br><span class="line"><span class="comment"> */</span></span><br><span class="line"></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP 20 <span class="comment">/* Keys for each DB loop. */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> ACTIVE_EXPIRE_CYCLE_FAST_DURATION 1000 <span class="comment">/* Microseconds. */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC 25 <span class="comment">/* Max % of CPU to use. */</span></span></span><br><span class="line"><span class="meta">#<span class="meta-keyword">define</span> ACTIVE_EXPIRE_CYCLE_ACCEPTABLE_STALE 10 <span class="comment">/* % of stale keys after which</span></span></span><br><span class="line"><span class="meta"><span class="comment"> we do extra efforts. */</span></span></span><br><span class="line"><span class="function"><span class="keyword">void</span> <span class="title">activeExpireCycle</span><span class="params">(<span class="keyword">int</span> type)</span> </span>{</span><br><span class="line"> <span class="comment">/* Adjust the running parameters according to the configured expire</span></span><br><span class="line"><span class="comment"> * effort. The default effort is 1, and the maximum configurable effort</span></span><br><span class="line"><span class="comment"> * is 10. */</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span></span><br><span class="line"> effort = server.active_expire_effort<span class="number">-1</span>, <span class="comment">/* Rescale from 0 to 9. */</span></span><br><span class="line"> config_keys_per_loop = ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP +</span><br><span class="line"> ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP/<span class="number">4</span>*effort,</span><br><span class="line"> config_cycle_fast_duration = ACTIVE_EXPIRE_CYCLE_FAST_DURATION +</span><br><span class="line"> ACTIVE_EXPIRE_CYCLE_FAST_DURATION/<span class="number">4</span>*effort,</span><br><span class="line"> config_cycle_slow_time_perc = ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC +</span><br><span class="line"> <span class="number">2</span>*effort,</span><br><span class="line"> config_cycle_acceptable_stale = ACTIVE_EXPIRE_CYCLE_ACCEPTABLE_STALE-</span><br><span class="line"> effort;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* This function has some global state in order to continue the work</span></span><br><span class="line"><span class="comment"> * incrementally across calls. */</span></span><br><span class="line"> <span class="keyword">static</span> <span class="keyword">unsigned</span> <span class="keyword">int</span> current_db = <span class="number">0</span>; <span class="comment">/* Last DB tested. */</span></span><br><span class="line"> <span class="keyword">static</span> <span class="keyword">int</span> timelimit_exit = <span class="number">0</span>; <span class="comment">/* Time limit hit in previous call? */</span></span><br><span class="line"> <span class="keyword">static</span> <span class="keyword">long</span> <span class="keyword">long</span> last_fast_cycle = <span class="number">0</span>; <span class="comment">/* When last fast cycle ran. */</span></span><br><span class="line"></span><br><span class="line"> <span class="keyword">int</span> j, iteration = <span class="number">0</span>;</span><br><span class="line"> <span class="keyword">int</span> dbs_per_call = CRON_DBS_PER_CALL;</span><br><span class="line"> <span class="keyword">long</span> <span class="keyword">long</span> start = ustime(), timelimit, elapsed;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* When clients are paused the dataset should be static not just from the</span></span><br><span class="line"><span class="comment"> * POV of clients not being able to write, but also from the POV of</span></span><br><span class="line"><span class="comment"> * expires and evictions of keys not being performed. */</span></span><br><span class="line"> <span class="keyword">if</span> (clientsArePaused()) <span class="keyword">return</span>;</span><br><span class="line"></span><br><span class="line"> <span class="keyword">if</span> (type == ACTIVE_EXPIRE_CYCLE_FAST) {</span><br><span class="line"> <span class="comment">/* Don't start a fast cycle if the previous cycle did not exit</span></span><br><span class="line"><span class="comment"> * for time limit, unless the percentage of estimated stale keys is</span></span><br><span class="line"><span class="comment"> * too high. Also never repeat a fast cycle for the same period</span></span><br><span class="line"><span class="comment"> * as the fast cycle total duration itself. */</span></span><br><span class="line"> <span class="keyword">if</span> (!timelimit_exit &&</span><br><span class="line"> server.stat_expired_stale_perc < config_cycle_acceptable_stale)</span><br><span class="line"> <span class="keyword">return</span>;</span><br><span class="line"></span><br><span class="line"> <span class="keyword">if</span> (start < last_fast_cycle + (<span class="keyword">long</span> <span class="keyword">long</span>)config_cycle_fast_duration*<span class="number">2</span>)</span><br><span class="line"> <span class="keyword">return</span>;</span><br><span class="line"></span><br><span class="line"> last_fast_cycle = start;</span><br><span class="line"> }</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* We usually should test CRON_DBS_PER_CALL per iteration, with</span></span><br><span class="line"><span class="comment"> * two exceptions:</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * 1) Don't test more DBs than we have.</span></span><br><span class="line"><span class="comment"> * 2) If last time we hit the time limit, we want to scan all DBs</span></span><br><span class="line"><span class="comment"> * in this iteration, as there is work to do in some DB and we don't want</span></span><br><span class="line"><span class="comment"> * expired keys to use memory for too much time. */</span></span><br><span class="line"> <span class="keyword">if</span> (dbs_per_call > server.dbnum || timelimit_exit)</span><br><span class="line"> dbs_per_call = server.dbnum;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* We can use at max 'config_cycle_slow_time_perc' percentage of CPU</span></span><br><span class="line"><span class="comment"> * time per iteration. Since this function gets called with a frequency of</span></span><br><span class="line"><span class="comment"> * server.hz times per second, the following is the max amount of</span></span><br><span class="line"><span class="comment"> * microseconds we can spend in this function. */</span></span><br><span class="line"> timelimit = config_cycle_slow_time_perc*<span class="number">1000000</span>/server.hz/<span class="number">100</span>;</span><br><span class="line"> timelimit_exit = <span class="number">0</span>;</span><br><span class="line"> <span class="keyword">if</span> (timelimit <= <span class="number">0</span>) timelimit = <span class="number">1</span>;</span><br><span class="line"></span><br><span class="line"> <span class="keyword">if</span> (type == ACTIVE_EXPIRE_CYCLE_FAST)</span><br><span class="line"> timelimit = config_cycle_fast_duration; <span class="comment">/* in microseconds. */</span></span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Accumulate some global stats as we expire keys, to have some idea</span></span><br><span class="line"><span class="comment"> * about the number of keys that are already logically expired, but still</span></span><br><span class="line"><span class="comment"> * existing inside the database. */</span></span><br><span class="line"> <span class="keyword">long</span> total_sampled = <span class="number">0</span>;</span><br><span class="line"> <span class="keyword">long</span> total_expired = <span class="number">0</span>;</span><br><span class="line"></span><br><span class="line"> <span class="keyword">for</span> (j = <span class="number">0</span>; j < dbs_per_call && timelimit_exit == <span class="number">0</span>; j++) {</span><br><span class="line"> <span class="comment">/* Expired and checked in a single loop. */</span></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> expired, sampled;</span><br><span class="line"></span><br><span class="line"> redisDb *db = server.db+(current_db % server.dbnum);</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Increment the DB now so we are sure if we run out of time</span></span><br><span class="line"><span class="comment"> * in the current DB we'll restart from the next. This allows to</span></span><br><span class="line"><span class="comment"> * distribute the time evenly across DBs. */</span></span><br><span class="line"> current_db++;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Continue to expire if at the end of the cycle more than 25%</span></span><br><span class="line"><span class="comment"> * of the keys were expired. */</span></span><br><span class="line"> <span class="keyword">do</span> {</span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> num, slots;</span><br><span class="line"> <span class="keyword">long</span> <span class="keyword">long</span> now, ttl_sum;</span><br><span class="line"> <span class="keyword">int</span> ttl_samples;</span><br><span class="line"> iteration++;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* If there is nothing to expire try next DB ASAP. */</span></span><br><span class="line"> <span class="keyword">if</span> ((num = dictSize(db->expires)) == <span class="number">0</span>) {</span><br><span class="line"> db->avg_ttl = <span class="number">0</span>;</span><br><span class="line"> <span class="keyword">break</span>;</span><br><span class="line"> }</span><br><span class="line"> slots = dictSlots(db->expires);</span><br><span class="line"> now = mstime();</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* When there are less than 1% filled slots, sampling the key</span></span><br><span class="line"><span class="comment"> * space is expensive, so stop here waiting for better times...</span></span><br><span class="line"><span class="comment"> * The dictionary will be resized asap. */</span></span><br><span class="line"> <span class="keyword">if</span> (num && slots > DICT_HT_INITIAL_SIZE &&</span><br><span class="line"> (num*<span class="number">100</span>/slots < <span class="number">1</span>)) <span class="keyword">break</span>;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* The main collection cycle. Sample random keys among keys</span></span><br><span class="line"><span class="comment"> * with an expire set, checking for expired ones. */</span></span><br><span class="line"> expired = <span class="number">0</span>;</span><br><span class="line"> sampled = <span class="number">0</span>;</span><br><span class="line"> ttl_sum = <span class="number">0</span>;</span><br><span class="line"> ttl_samples = <span class="number">0</span>;</span><br><span class="line"></span><br><span class="line"> <span class="keyword">if</span> (num > config_keys_per_loop)</span><br><span class="line"> num = config_keys_per_loop;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Here we access the low level representation of the hash table</span></span><br><span class="line"><span class="comment"> * for speed concerns: this makes this code coupled with dict.c,</span></span><br><span class="line"><span class="comment"> * but it hardly changed in ten years.</span></span><br><span class="line"><span class="comment"> *</span></span><br><span class="line"><span class="comment"> * Note that certain places of the hash table may be empty,</span></span><br><span class="line"><span class="comment"> * so we want also a stop condition about the number of</span></span><br><span class="line"><span class="comment"> * buckets that we scanned. However scanning for free buckets</span></span><br><span class="line"><span class="comment"> * is very fast: we are in the cache line scanning a sequential</span></span><br><span class="line"><span class="comment"> * array of NULL pointers, so we can scan a lot more buckets</span></span><br><span class="line"><span class="comment"> * than keys in the same time. */</span></span><br><span class="line"> <span class="keyword">long</span> max_buckets = num*<span class="number">20</span>;</span><br><span class="line"> <span class="keyword">long</span> checked_buckets = <span class="number">0</span>;</span><br><span class="line"></span><br><span class="line"> <span class="keyword">while</span> (sampled < num && checked_buckets < max_buckets) {</span><br><span class="line"> <span class="keyword">for</span> (<span class="keyword">int</span> table = <span class="number">0</span>; table < <span class="number">2</span>; table++) {</span><br><span class="line"> <span class="keyword">if</span> (table == <span class="number">1</span> && !dictIsRehashing(db->expires)) <span class="keyword">break</span>;</span><br><span class="line"></span><br><span class="line"> <span class="keyword">unsigned</span> <span class="keyword">long</span> idx = db->expires_cursor;</span><br><span class="line"> idx &= db->expires->ht[table].sizemask;</span><br><span class="line"> dictEntry *de = db->expires->ht[table].table[idx];</span><br><span class="line"> <span class="keyword">long</span> <span class="keyword">long</span> ttl;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Scan the current bucket of the current table. */</span></span><br><span class="line"> checked_buckets++;</span><br><span class="line"> <span class="keyword">while</span>(de) {</span><br><span class="line"> <span class="comment">/* Get the next entry now since this entry may get</span></span><br><span class="line"><span class="comment"> * deleted. */</span></span><br><span class="line"> dictEntry *e = de;</span><br><span class="line"> de = de->next;</span><br><span class="line"></span><br><span class="line"> ttl = dictGetSignedIntegerVal(e)-now;</span><br><span class="line"> <span class="keyword">if</span> (activeExpireCycleTryExpire(db,e,now)) expired++;</span><br><span class="line"> <span class="keyword">if</span> (ttl > <span class="number">0</span>) {</span><br><span class="line"> <span class="comment">/* We want the average TTL of keys yet</span></span><br><span class="line"><span class="comment"> * not expired. */</span></span><br><span class="line"> ttl_sum += ttl;</span><br><span class="line"> ttl_samples++;</span><br><span class="line"> }</span><br><span class="line"> sampled++;</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"> db->expires_cursor++;</span><br><span class="line"> }</span><br><span class="line"> total_expired += expired;</span><br><span class="line"> total_sampled += sampled;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Update the average TTL stats for this database. */</span></span><br><span class="line"> <span class="keyword">if</span> (ttl_samples) {</span><br><span class="line"> <span class="keyword">long</span> <span class="keyword">long</span> avg_ttl = ttl_sum/ttl_samples;</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Do a simple running average with a few samples.</span></span><br><span class="line"><span class="comment"> * We just use the current estimate with a weight of 2%</span></span><br><span class="line"><span class="comment"> * and the previous estimate with a weight of 98%. */</span></span><br><span class="line"> <span class="keyword">if</span> (db->avg_ttl == <span class="number">0</span>) db->avg_ttl = avg_ttl;</span><br><span class="line"> db->avg_ttl = (db->avg_ttl/<span class="number">50</span>)*<span class="number">49</span> + (avg_ttl/<span class="number">50</span>);</span><br><span class="line"> }</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* We can't block forever here even if there are many keys to</span></span><br><span class="line"><span class="comment"> * expire. So after a given amount of milliseconds return to the</span></span><br><span class="line"><span class="comment"> * caller waiting for the other active expire cycle. */</span></span><br><span class="line"> <span class="keyword">if</span> ((iteration & <span class="number">0xf</span>) == <span class="number">0</span>) { <span class="comment">/* check once every 16 iterations. */</span></span><br><span class="line"> elapsed = ustime()-start;</span><br><span class="line"> <span class="keyword">if</span> (elapsed > timelimit) {</span><br><span class="line"> timelimit_exit = <span class="number">1</span>;</span><br><span class="line"> server.stat_expired_time_cap_reached_count++;</span><br><span class="line"> <span class="keyword">break</span>;</span><br><span class="line"> }</span><br><span class="line"> }</span><br><span class="line"> <span class="comment">/* We don't repeat the cycle for the current database if there are</span></span><br><span class="line"><span class="comment"> * an acceptable amount of stale keys (logically expired but yet</span></span><br><span class="line"><span class="comment"> * not reclained). */</span></span><br><span class="line"> } <span class="keyword">while</span> ((expired*<span class="number">100</span>/sampled) > config_cycle_acceptable_stale);</span><br><span class="line"> }</span><br><span class="line"></span><br><span class="line"> elapsed = ustime()-start;</span><br><span class="line"> server.stat_expire_cycle_time_used += elapsed;</span><br><span class="line"> latencyAddSampleIfNeeded(<span class="string">"expire-cycle"</span>,elapsed/<span class="number">1000</span>);</span><br><span class="line"></span><br><span class="line"> <span class="comment">/* Update our estimate of keys existing but yet to be expired.</span></span><br><span class="line"><span class="comment"> * Running average with this sample accounting for 5%. */</span></span><br><span class="line"> <span class="keyword">double</span> current_perc;</span><br><span class="line"> <span class="keyword">if</span> (total_sampled) {</span><br><span class="line"> current_perc = (<span class="keyword">double</span>)total_expired/total_sampled;</span><br><span class="line"> } <span class="keyword">else</span></span><br><span class="line"> current_perc = <span class="number">0</span>;</span><br><span class="line"> server.stat_expired_stale_perc = (current_perc*<span class="number">0.05</span>)+</span><br><span class="line"> (server.stat_expired_stale_perc*<span class="number">0.95</span>);</span><br><span class="line">}</span><br></pre></td></tr></table></figure>
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<p>执行定期清除分成两种类型，快和慢，分别由<code>beforeSleep</code>和<code>databasesCron</code>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</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></pre></td><td class="code"><pre><span class="line">onfig_cycle_fast_duration = ACTIVE_EXPIRE_CYCLE_FAST_DURATION +</span><br><span class="line"> ACTIVE_EXPIRE_CYCLE_FAST_DURATION/<span class="number">4</span>*effort</span><br></pre></td></tr></table></figure>
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<p>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</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">config_keys_per_loop = ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP +</span><br><span class="line"> ACTIVE_EXPIRE_CYCLE_KEYS_PER_LOOP/<span class="number">4</span>*effort</span><br><span class="line">``` </span><br><span class="line">控制，慢速的执行时长是</span><br><span class="line">```C</span><br><span class="line">config_cycle_slow_time_perc = ACTIVE_EXPIRE_CYCLE_SLOW_TIME_PERC +</span><br><span class="line"> <span class="number">2</span>*effort</span><br><span class="line">timelimit = config_cycle_slow_time_perc*<span class="number">1000000</span>/server.hz/<span class="number">100</span>;</span><br></pre></td></tr></table></figure>
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<p>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</p>
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href="/tags/%E5%B8%83%E9%9A%86%E8%BF%87%E6%BB%A4%E5%99%A8/" rel="tag">布隆过滤器</a><span class="tag-list-count">1</span></li><li class="tag-list-item"><a class="tag-list-link" href="/tags/%E5%B9%B2%E6%B4%BB/" rel="tag">干活</a><span class="tag-list-count">5</span></li><li class="tag-list-item"><a class="tag-list-link" href="/tags/%E5%B9%B4%E4%B8%AD%E6%80%BB%E7%BB%93/" rel="tag">年中总结</a><span class="tag-list-count">1</span></li><li class="tag-list-item"><a class="tag-list-link" href="/tags/%E5%B9%B4%E7%BB%88%E6%80%BB%E7%BB%93/" rel="tag">年终总结</a><span class="tag-list-count">1</span></li><li class="tag-list-item"><a class="tag-list-link" href="/tags/%E5%B9%B6%E5%8F%91/" rel="tag">并发</a><span class="tag-list-count">1</span></li><li class="tag-list-item"><a class="tag-list-link" href="/tags/%E5%B9%B8%E7%A6%8F%E4%BA%86%E5%90%97/" rel="tag">幸福了吗</a><span class="tag-list-count">1</span></li><li class="tag-list-item"><a class="tag-list-link" href="/tags/%E5%B9%BB%E8%AF%BB/" rel="tag">幻读</a><span 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class="tag-list-count">1</span></li><li class="tag-list-item"><a class="tag-list-link" href="/tags/%E8%B7%91%E6%AD%A5/" rel="tag">跑步</a><span class="tag-list-count">6</span></li><li class="tag-list-item"><a class="tag-list-link" href="/tags/%E8%BD%AC%E4%B9%89/" rel="tag">转义</a><span class="tag-list-count">1</span></li><li class="tag-list-item"><a class="tag-list-link" href="/tags/%E8%BF%90%E5%8A%A8/" rel="tag">运动</a><span class="tag-list-count">6</span></li><li class="tag-list-item"><a class="tag-list-link" href="/tags/%E9%80%92%E5%BD%92/" rel="tag">递归</a><span class="tag-list-count">1</span></li><li class="tag-list-item"><a class="tag-list-link" href="/tags/%E9%A2%98%E8%A7%A3/" rel="tag">题解</a><span class="tag-list-count">8</span></li></ul>
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(function() {
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function leancloudSelector(url) {
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url = encodeURI(url);
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Counter('get', '/classes/Counter?where=' + encodeURIComponent(JSON.stringify({ url: { '$in': entries } })))
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for (let url of entries) {
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leancloudSelector(url).innerText = target ? target.time : 0;
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let { app_id, app_key, server_url } = {"enable":true,"app_id":"ysza182Vghlqjdt7QiwGLLJy-gzGzoHsz","app_key":"s9GDqbn7gnGGkusf66YRVccw","server_url":"https://leancloud.cn","security":true};
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function fetchData(api_server) {
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return fetch(`${api_server}/1.1${url}`, {
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method,
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headers: {
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'X-LC-Id' : app_id,
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'X-LC-Key' : app_key,
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'Content-Type': 'application/json',
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},
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body: JSON.stringify(data)
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});
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};
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if (CONFIG.page.isPost) {
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if (CONFIG.hostname !== location.hostname) return;
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addCount(Counter);
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} else if (document.querySelectorAll('.post-title-link').length >= 1) {
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showTime(Counter);
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}
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}
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let api_server = app_id.slice(-9) !== '-MdYXbMMI' ? server_url : `https://${app_id.slice(0, 8).toLowerCase()}.api.lncldglobal.com`;
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if (api_server) {
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fetchData(api_server);
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} else {
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fetch('https://app-router.leancloud.cn/2/route?appId=' + app_id)
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.then(response => response.json())
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fetchData('https://' + api_server);
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