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<!DOCTYPE HTML>
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单机的Redis存在四大问题：
Redis持久化Redis有两种持久化方案：
RDB持久化
AOF持久化
1.1.RDB持久化RDB全称Redis Database Bac">
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<h1 id="分布式缓存"><a href="#分布式缓存" class="headerlink" title="分布式缓存"></a>分布式缓存</h1><p>– 基于Redis集群解决单机Redis存在的问题</p>
<p>单机的Redis存在四大问题：</p>
<p><img src="/redis02-distributed-caching/image-20210725144240631.png" alt="image-20210725144240631"></p>
<h1 id="Redis持久化"><a href="#Redis持久化" class="headerlink" title="Redis持久化"></a>Redis持久化</h1><p>Redis有两种持久化方案：</p>
<ul>
<li>RDB持久化</li>
<li>AOF持久化</li>
</ul>
<h2 id="1-1-RDB持久化"><a href="#1-1-RDB持久化" class="headerlink" title="1.1.RDB持久化"></a>1.1.RDB持久化</h2><p>RDB全称Redis Database Backup file（Redis数据备份文件），也被叫做Redis数据快照。简单来说就是把内存中的所有数据都记录到磁盘中。当Redis实例故障重启后，从磁盘读取快照文件，恢复数据。快照文件称为RDB文件，默认是保存在当前运行目录。</p>
<h3 id="1-1-1-执行时机"><a href="#1-1-1-执行时机" class="headerlink" title="1.1.1.执行时机"></a>1.1.1.执行时机</h3><p>RDB持久化在四种情况下会执行：</p>
<ul>
<li>执行save命令</li>
<li>执行bgsave命令</li>
<li>Redis停机时</li>
<li>触发RDB条件时</li>
</ul>
<p><strong>1）save命令</strong></p>
<p>执行下面的命令，可以立即执行一次RDB：</p>
<p><img src="/redis02-distributed-caching/image-20210725144536958.png" alt="image-20210725144536958"></p>
<p>save命令会导致主进程执行RDB，这个过程中其它所有命令都会被阻塞。只有在数据迁移时可能用到。</p>
<p><strong>2）bgsave命令</strong></p>
<p>下面的命令可以异步执行RDB：</p>
<p><img src="/redis02-distributed-caching/image-20210725144725943.png" alt="image-20210725144725943"></p>
<p>这个命令执行后会开启独立进程完成RDB，主进程可以持续处理用户请求，不受影响。</p>
<p><strong>3）停机时</strong></p>
<p>Redis停机时会执行一次save命令，实现RDB持久化。</p>
<p><strong>4）触发RDB条件</strong></p>
<p>Redis内部有触发RDB的机制，可以在redis.conf文件中找到，格式如下：</p>
<pre class="line-numbers language-properties"><code class="language-properties"><span class="token comment" spellcheck="true"># 900秒内，如果至少有1个key被修改，则执行bgsave ， 如果是save "" 则表示禁用RDB</span>
<span class="token attr-name">save</span> <span class="token attr-value">900 1 </span>
<span class="token attr-name">save</span> <span class="token attr-value">300 10 </span>
<span class="token attr-name">save</span> <span class="token attr-value">60 10000 </span><span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span></span></code></pre>
<p>RDB的其它配置也可以在redis.conf文件中设置：</p>
<pre class="line-numbers language-properties"><code class="language-properties"><span class="token comment" spellcheck="true"># 是否压缩 ,建议不开启，压缩也会消耗cpu，磁盘的话不值钱</span>
<span class="token attr-name">rdbcompression</span> <span class="token attr-value">yes</span>
<span class="token comment" spellcheck="true"># RDB文件名称</span>
<span class="token attr-name">dbfilename</span> <span class="token attr-value">dump.rdb </span>
<span class="token comment" spellcheck="true"># 文件保存的路径目录</span>
<span class="token attr-name">dir</span> <span class="token attr-value">./ </span><span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span><span></span><span></span><span></span><span></span></span></code></pre>
<h3 id="1-1-2-RDB原理"><a href="#1-1-2-RDB原理" class="headerlink" title="1.1.2.RDB原理"></a>1.1.2.RDB原理</h3><p>bgsave开始时会fork主进程得到子进程，子进程共享主进程的内存数据。完成fork后读取内存数据并写入 RDB 文件。</p>
<p>fork采用的是copy-on-write技术：</p>
<ul>
<li>当主进程执行读操作时，访问共享内存；</li>
<li>当主进程执行写操作时，则会拷贝一份数据，执行写操作。</li>
</ul>
<p><img src="/redis02-distributed-caching/image-20210725151319695.png" alt="image-20210725151319695"></p>
<h3 id="1-1-3-小结"><a href="#1-1-3-小结" class="headerlink" title="1.1.3.小结"></a>1.1.3.小结</h3><p>RDB方式bgsave的基本流程？</p>
<ul>
<li>fork主进程得到一个子进程，共享内存空间</li>
<li>子进程读取内存数据并写入新的RDB文件</li>
<li>用新RDB文件替换旧的RDB文件</li>
</ul>
<p>RDB会在什么时候执行？save 60 1000代表什么含义？</p>
<ul>
<li>默认是服务停止时</li>
<li>代表60秒内至少执行1000次修改则触发RDB</li>
</ul>
<p>RDB的缺点？</p>
<ul>
<li>RDB执行间隔时间长，两次RDB之间写入数据有丢失的风险</li>
<li>fork子进程、压缩、写出RDB文件都比较耗时</li>
</ul>
<h2 id="1-2AOF持久化"><a href="#1-2AOF持久化" class="headerlink" title="1.2AOF持久化"></a>1.2AOF持久化</h2><h3 id="1-2-1-AOF原理"><a href="#1-2-1-AOF原理" class="headerlink" title="1.2.1.AOF原理"></a>1.2.1.AOF原理</h3><p>AOF全称为Append Only File（追加文件）。Redis处理的每一个写命令都会记录在AOF文件，可以看做是命令日志文件。</p>
<p><img src="/redis02-distributed-caching/image-20210725151543640.png" alt="image-20210725151543640"></p>
<h3 id="1-2-2-AOF配置"><a href="#1-2-2-AOF配置" class="headerlink" title="1.2.2.AOF配置"></a>1.2.2.AOF配置</h3><p>AOF默认是关闭的，需要修改redis.conf配置文件来开启AOF：</p>
<pre class="line-numbers language-properties"><code class="language-properties"><span class="token comment" spellcheck="true"># 是否开启AOF功能，默认是no</span>
<span class="token attr-name">appendonly</span> <span class="token attr-value">yes</span>
<span class="token comment" spellcheck="true"># AOF文件的名称</span>
<span class="token attr-name">appendfilename</span> <span class="token attr-value">"appendonly.aof"</span><span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span></span></code></pre>
<p>AOF的命令记录的频率也可以通过redis.conf文件来配：</p>
<pre class="line-numbers language-properties"><code class="language-properties"><span class="token comment" spellcheck="true"># 表示每执行一次写命令，立即记录到AOF文件</span>
<span class="token attr-name">appendfsync</span> <span class="token attr-value">always </span>
<span class="token comment" spellcheck="true"># 写命令执行完先放入AOF缓冲区，然后表示每隔1秒将缓冲区数据写到AOF文件，是默认方案</span>
<span class="token attr-name">appendfsync</span> <span class="token attr-value">everysec </span>
<span class="token comment" spellcheck="true"># 写命令执行完先放入AOF缓冲区，由操作系统决定何时将缓冲区内容写回磁盘</span>
<span class="token attr-name">appendfsync</span> <span class="token attr-value">no</span><span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span><span></span><span></span></span></code></pre>
<p>三种策略对比：</p>
<p><img src="/redis02-distributed-caching/image-20210725151654046.png" alt="image-20210725151654046"></p>
<h3 id="1-2-3-AOF文件重写"><a href="#1-2-3-AOF文件重写" class="headerlink" title="1.2.3.AOF文件重写"></a>1.2.3.AOF文件重写</h3><p>因为是记录命令，AOF文件会比RDB文件大的多。而且AOF会记录对同一个key的多次写操作，但只有最后一次写操作才有意义。通过执行bgrewriteaof命令，可以让AOF文件执行重写功能，用最少的命令达到相同效果。</p>
<p><img src="/redis02-distributed-caching/image-20210725151729118.png" alt="image-20210725151729118"></p>
<p>如图，AOF原本有三个命令，但是<code>set num 123 和 set num 666</code>都是对num的操作，第二次会覆盖第一次的值，因此第一个命令记录下来没有意义。</p>
<p>所以重写命令后，AOF文件内容就是：<code>mset name jack num 666</code></p>
<p>Redis也会在触发阈值时自动去重写AOF文件。阈值也可以在redis.conf中配置：</p>
<pre class="line-numbers language-properties"><code class="language-properties"><span class="token comment" spellcheck="true"># AOF文件比上次文件 增长超过多少百分比则触发重写</span>
<span class="token attr-name">auto-aof-rewrite-percentage</span> <span class="token attr-value">100</span>
<span class="token comment" spellcheck="true"># AOF文件体积最小多大以上才触发重写 </span>
<span class="token attr-name">auto-aof-rewrite-min-size</span> <span class="token attr-value">64mb </span><span aria-hidden="true" class="line-numbers-rows"><span></span><span></span><span></span><span></span></span></code></pre>
<h2 id="1-3-RDB与AOF对比"><a href="#1-3-RDB与AOF对比" class="headerlink" title="1.3.RDB与AOF对比"></a>1.3.RDB与AOF对比</h2><p>RDB和AOF各有自己的优缺点，如果对数据安全性要求较高，在实际开发中往往会<strong>结合</strong>两者来使用。</p>
<p><img src="/redis02-distributed-caching/image-20210725151940515.png" alt="image-20210725151940515"></p>
<h1 id="Redis主从"><a href="#Redis主从" class="headerlink" title="Redis主从"></a>Redis主从</h1><h2 id="主从数据同步原理"><a href="#主从数据同步原理" class="headerlink" title="主从数据同步原理"></a>主从数据同步原理</h2><p>开启主从关系</p>
<p>有临时和永久两种模式：</p>
<ul>
<li><p>修改配置文件（永久生效）</p>
<ul>
<li>在redis.conf中添加一行配置：<code>slaveof <masterip> <masterport></code></li>
</ul>
</li>
<li><p>使用redis-cli客户端连接到redis服务，执行slaveof命令（重启后失效）：</p>
<pre class="line-numbers language-sh"><code class="language-sh">slaveof <masterip> <masterport><span aria-hidden="true" class="line-numbers-rows"><span></span></span></code></pre>
</li>
</ul>
<p><strong><font color="red">注意</font></strong>：在5.0以后新增命令replicaof，与salveof效果一致。</p>
<h3 id="全量同步"><a href="#全量同步" class="headerlink" title="全量同步"></a>全量同步</h3><p>主从第一次建立连接时，会执行<strong>全量同步</strong>，将master节点的所有数据都拷贝给slave节点，流程：</p>
<p><img src="/redis02-distributed-caching/image-20210725152222497.png" alt="image-20210725152222497"></p>
<p>这里有一个问题，master如何得知salve是第一次来连接呢？？</p>
<p>有几个概念，可以作为判断依据：</p>
<ul>
<li><strong>Replication Id</strong>：简称replid，是数据集的标记，id一致则说明是同一数据集。每一个master都有唯一的replid，slave则会继承master节点的replid</li>
<li><strong>offset</strong>：偏移量，随着记录在repl_baklog中的数据增多而逐渐增大。slave完成同步时也会记录当前同步的offset。如果slave的offset小于master的offset，说明slave数据落后于master，需要更新。</li>
</ul>
<p>因此slave做数据同步，必须向master声明自己的replication id 和offset，master才可以判断到底需要同步哪些数据。</p>
<p>因为slave原本也是一个master，有自己的replid和offset，当第一次变成slave，与master建立连接时，发送的replid和offset是自己的replid和offset。</p>
<p>master判断发现slave发送来的replid与自己的不一致，说明这是一个全新的slave，就知道要做全量同步了。</p>
<p>master会将自己的replid和offset都发送给这个slave，slave保存这些信息。以后slave的replid就与master一致了。</p>
<p>因此，<strong>master判断一个节点是否是第一次同步的依据，就是看replid是否一致</strong>。</p>
<p>如图：</p>
<p><img src="/redis02-distributed-caching/image-20210725152700914.png" alt="image-20210725152700914"></p>
<p>完整流程描述：</p>
<ul>
<li>slave节点请求增量同步</li>
<li>master节点判断replid，发现不一致，拒绝增量同步</li>
<li>master将完整内存数据生成RDB，发送RDB到slave</li>
<li>slave清空本地数据，加载master的RDB</li>
<li>master将RDB期间的命令记录在repl_baklog，并持续将log中的命令发送给slave</li>
<li>slave执行接收到的命令，保持与master之间的同步</li>
</ul>
<h3 id="增量同步"><a href="#增量同步" class="headerlink" title="增量同步"></a>增量同步</h3><p>全量同步需要先做RDB，然后将RDB文件通过网络传输个slave，成本太高了。因此除了第一次做全量同步，其它大多数时候slave与master都是做<strong>增量同步</strong>。</p>
<p>什么是增量同步？就是只更新slave与master存在差异的部分数据。如图：</p>
<p><img src="/redis02-distributed-caching/image-20210725153201086.png" alt="image-20210725153201086"></p>
<p>那么master怎么知道slave与自己的数据差异在哪里呢?</p>
<h3 id="repl-backlog原理"><a href="#repl-backlog原理" class="headerlink" title="repl_backlog原理"></a>repl_backlog原理</h3><p>master怎么知道slave与自己的数据差异在哪里呢?</p>
<p>这就要说到全量同步时的repl_baklog文件了。</p>
<p>这个文件是一个固定大小的数组，只不过数组是环形，也就是说<strong>角标到达数组末尾后，会再次从0开始读写</strong>，这样数组头部的数据就会被覆盖。</p>
<p>repl_baklog中会记录Redis处理过的命令日志及offset，包括master当前的offset，和slave已经拷贝到的offset：</p>
<p><img src="/redis02-distributed-caching/image-20210725153359022.png" alt="image-20210725153359022"> </p>
<p>slave与master的offset之间的差异，就是salve需要增量拷贝的数据了。</p>
<p>随着不断有数据写入，master的offset逐渐变大，slave也不断的拷贝，追赶master的offset：</p>
<p><img src="/redis02-distributed-caching/image-20210725153524190.png" alt="image-20210725153524190"> </p>
<p>直到数组被填满：</p>
<p><img src="/redis02-distributed-caching/image-20210725153715910.png" alt="image-20210725153715910"> </p>
<p>此时，如果有新的数据写入，就会覆盖数组中的旧数据。不过，旧的数据只要是绿色的，说明是已经被同步到slave的数据，即便被覆盖了也没什么影响。因为未同步的仅仅是红色部分。</p>
<p>但是，如果slave出现网络阻塞，导致master的offset远远超过了slave的offset： </p>
<p><img src="/redis02-distributed-caching/image-20210725153937031.png" alt="image-20210725153937031"> </p>
<p>如果master继续写入新数据，其offset就会覆盖旧的数据，直到将slave现在的offset也覆盖：</p>
<p><img src="/redis02-distributed-caching/image-20210725154155984.png" alt="image-20210725154155984"> </p>
<p>棕色框中的红色部分，就是尚未同步，但是却已经被覆盖的数据。此时如果slave恢复，需要同步，却发现自己的offset都没有了，无法完成增量同步了。只能做全量同步。</p>
<p><img src="/redis02-distributed-caching/image-20210725154216392.png" alt="image-20210725154216392"></p>
<h2 id="主从同步优化"><a href="#主从同步优化" class="headerlink" title="主从同步优化"></a>主从同步优化</h2><p>主从同步可以保证主从数据的一致性，非常重要。</p>
<p>可以从以下几个方面来优化Redis主从就集群：</p>
<ul>
<li>在master中配置repl-diskless-sync yes启用无磁盘复制，避免全量同步时的磁盘IO。</li>
<li>Redis单节点上的内存占用不要太大，减少RDB导致的过多磁盘IO</li>
<li>适当提高repl_baklog的大小，发现slave宕机时尽快实现故障恢复，尽可能避免全量同步</li>
<li>限制一个master上的slave节点数量，如果实在是太多slave，则可以采用主-从-从链式结构，减少master压力</li>
</ul>
<p>主从从架构图：</p>
<p><img src="/redis02-distributed-caching/image-20210725154405899.png" alt="image-20210725154405899"></p>
<h2 id="小结"><a href="#小结" class="headerlink" title="小结"></a>小结</h2><p>简述全量同步和增量同步区别？</p>
<ul>
<li>全量同步：master将完整内存数据生成RDB，发送RDB到slave。后续命令则记录在repl_baklog，逐个发送给slave。</li>
<li>增量同步：slave提交自己的offset到master，master获取repl_baklog中从offset之后的命令给slave</li>
</ul>
<p>什么时候执行全量同步？</p>
<ul>
<li>slave节点第一次连接master节点时</li>
<li>slave节点断开时间太久，repl_baklog中的offset已经被覆盖时</li>
</ul>
<p>什么时候执行增量同步？</p>
<ul>
<li>slave节点断开又恢复，并且在repl_baklog中能找到offset时</li>
</ul>
<h1 id="Redis哨兵"><a href="#Redis哨兵" class="headerlink" title="Redis哨兵"></a>Redis哨兵</h1><p>Redis提供了哨兵（Sentinel）机制来实现主从集群的自动故障恢复。</p>
<h2 id="哨兵原理"><a href="#哨兵原理" class="headerlink" title="哨兵原理"></a>哨兵原理</h2><h3 id="集群结构和作用"><a href="#集群结构和作用" class="headerlink" title="集群结构和作用"></a>集群结构和作用</h3><h1 id="搭建哨兵集群"><a href="#搭建哨兵集群" class="headerlink" title="搭建哨兵集群"></a>搭建哨兵集群</h1><h2 id="集群结构"><a href="#集群结构" class="headerlink" title="集群结构"></a>集群结构</h2><p>这里我们搭建一个三节点形成的Sentinel集群，来监管之前的Redis主从集群。如图：</p>
<p><img src="/redis02-distributed-caching/image-20210701215227018.png" alt="image-20210701215227018"></p>
<p>三个sentinel实例信息如下：</p>
<table>
<thead>
<tr>
<th>节点</th>
<th align="center">IP</th>
<th align="center">PORT</th>
</tr>
</thead>
<tbody><tr>
<td>s1</td>
<td align="center">192.168.150.101</td>
<td align="center">27001</td>
</tr>
<tr>
<td>s2</td>
<td align="center">192.168.150.101</td>
<td align="center">27002</td>
</tr>
<tr>
<td>s3</td>