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<h2 id="删除策略">删除策略</h2>
<h3 id="定时删除">定时删除</h3>
<ul>
<li>定时删除，CPU 占用大</li>
</ul>
<h3 id="惰性删除">惰性删除</h3>
<ul>
<li>过期数据二次访问后才删除，内存占用大</li>
</ul>
<h3 id="定期删除">定期删除</h3>
<ul>
<li>随机抽查删除，hz 值决定了 CPU 和内存哪个占用大</li>
</ul>
<h3 id="淘汰策略">淘汰策略</h3>
<ul>
<li>
<p>内存不足时按策略删除</p>
<ul>
<li>
<p>maxmemory ?mb 最大可用内存，默认为 0 不限制，一般设置物理机的 50%以上</p>
</li>
<li>
<p>maxmemory-samples count 每次随机删除的数据个数</p>
</li>
<li>
<p>maxmemory-policy policy 删除策略</p>
<ul>
<li>
<p>volatile 易失数据</p>
<ul>
<li>volatile-lru 按最后一次使用时间</li>
<li>volatile-lfu 按最近使用次数</li>
<li>volatile-ttl 按即将过期的数据</li>
<li>volatile-random 随机</li>
</ul>
</li>
<li>
<p>allkeys 全库数据</p>
<ul>
<li>allkeys-lru 按最后一次使用时间</li>
<li>allkeys-lfu 按最近使用次数</li>
<li>allkeys-random 随机</li>
</ul>
</li>
<li>
<p>no-enviction 放弃数据驱逐</p>
</li>
</ul>
</li>
</ul>
</li>
</ul>
<h2 id="主从复制">主从复制</h2>
<h3 id="建立连接的流程">建立连接的流程</h3>
<ul>
<li>设置 master 地址和端口并保存</li>
<li>建立 socket 连接</li>
<li>发送 ping 命令(定时器任务)</li>
<li>身份验证</li>
<li>发送 slave 端口信息</li>
</ul>
<h3 id="数据同步">数据同步</h3>
<ul>
<li>
<p>全量复制</p>
<ul>
<li>发送指令 psync2 <runid> <offset></li>
<li>执行 bgsave</li>
<li>第一个 slave 连接时创建命令缓冲区</li>
<li>生成 RDB 文件通过 socket 发给 slave</li>
<li>接收 RDB，清空数据，执行恢复过程</li>
</ul>
</li>
<li>
<p>部分复制</p>
<ul>
<li>发送命令告知 RDB 已经恢复完成</li>
<li>发送复制缓冲区信息</li>
<li>接收信息，执行 bgrewriteaof，恢复数据</li>
</ul>
</li>
<li>
<p>心跳机制</p>
<ul>
<li>
<p>master 心跳</p>
<ul>
<li>内部指令 PING</li>
<li>周期 repl-ping-slave-period 默认 10 秒</li>
<li>INFO replication 获取 slave 最后一次连接时间间隔，lag 项维持在 0 或 1 视为正常</li>
</ul>
</li>
<li>
<p>slave 心跳</p>
<ul>
<li>内部指令 REPLCONF ACK {offset}</li>
<li>周期 1 秒</li>
<li>汇报 slave 自己的复制偏移量，获取最新的数据变更指令</li>
<li>判断 master 是否在线</li>
</ul>
</li>
</ul>
</li>
<li>
<p>注意事项</p>
<ul>
<li>master 数据同步应避开流量高峰期</li>
<li>复制缓冲区太小会导致数据溢出，出现数据丢失并自动进行二次全量复制，死循环 repl=backlog-size ?mb 建议留下 30%~50%的内存用于执行 bgsave 命令和创建复制缓冲区</li>
<li>避免 slave 同步过程服务器响应阻塞或者数据不同步，建议关闭此期间的对外服务 slave-serve-stale-data yes | no</li>
<li>数据同步阶段，master 主动发送命令给 slave，可以理解为是一个客户端</li>
<li>多个 slave 同时对 master 请求同步，RDB 只会有一份，但是带宽压力变大，可以适量错峰但是 RDB 会有多份</li>
<li>slave 过多可以采用树状结构，但是数据一致性差</li>
</ul>
</li>
</ul>
<h2 id="哨兵模式">哨兵模式</h2>
<h3 id="检测-master-是否宕机，master-宕机后选举-slave-为-master">检测 master 是否宕机，master 宕机后选举 slave 为 master</h3>
<h3 id="建立过程配置">建立过程配置</h3>
<ul>
<li>sentinel monitor master_name master_host master_port sentinel_number 设置监听的主服务器信息，sentinel_number 表示参与投票的哨兵数量</li>
<li>sentinel down-after-milliseconds master_name million_seconds 设置宕机时长，控制是否进行主从切换</li>
<li>sentinel failover-timeout master_name million_seconds 设置故障切换操作的最大超时时长</li>
<li>sentinel parallel-syncs master_name sync_slave_number 设置主从切换后，同时进行数据同步的 slave 数量，越大网络资源要求越高，越小同步时间越长</li>
</ul>
<h3 id="监控阶段">监控阶段</h3>
<ul>
<li>检查各个哨兵是否在线</li>
<li>先向 master 发 info 查询其信息和名下 slave</li>
<li>再向 slave 发 info 查询 slave 具体信息</li>
</ul>
<h3 id="故障转移阶段">故障转移阶段</h3>
<ul>
<li>
<p>单个哨兵监测到 master 无响应（主观下线） SRI_S_DOWN</p>
</li>
<li>
<p>半数哨兵监测到 master 无响应（客观下线） SRI_O_DOWN</p>
</li>
<li>
<p>哨兵选举</p>
</li>
<li>
<p>选举 master 优先级</p>
<ul>
<li>
<p>不在线的</p>
</li>
<li>
<p>响应慢的</p>
</li>
<li>
<p>与原来 master 断开连接时间长的</p>
</li>
<li>
<p>优先原则</p>
<ul>
<li>优先级</li>
<li>offset 偏移量大</li>
<li>runid</li>
</ul>
</li>
</ul>
</li>
</ul>
<h2 id="Cluster-集群">Cluster 集群</h2>
<h3 id="数据存储结构">数据存储结构</h3>
<ul>
<li>
<p>保存流程</p>
<ul>
<li>CRC(key)%16384 计算结果为某台服务器中的槽位地址，该槽位不止存储一个 key，而是大量 key</li>
</ul>
</li>
<li>
<p>查询流程</p>
<ul>
<li>各个数据库相互通信，保存各个库中槽位的编号数据</li>
<li>一次查询命中直接返回</li>
<li>一次未命中，告知具体的位置</li>
</ul>
</li>
</ul>
<h3 id="配置">配置</h3>
<ul>
<li>cluster-enabled yes|no 是否启用 cluster，加入 cluster 节点</li>
<li>cluster-config-file filename cluster 配置文件名，该文件会自动生成，尽量手动命名否则会共用</li>
<li>cluster-node-timeout milliseconds 节点服务响应超时时间</li>
<li>cluster-migration-barrier min_slave_number master 连接的 slave 最小数量</li>
</ul>
<h2 id="企业级解决方案">企业级解决方案</h2>
<h3 id="缓存预热">缓存预热</h3>
<ul>
<li>现象：启动服务器后立刻宕机</li>
<li>解决思路：系统启动前，提前将相关的缓存数据直接加载到缓存系统。避免在用户请求的时候，先查询数据库，然后再将数据缓存的问题！用户直接查询事先被预热的缓存数据！</li>
</ul>
<h3 id="缓存雪崩">缓存雪崩</h3>
<ul>
<li>
<p>现象：短时间范围内，大量 key 集中过期导致一系列宕机</p>
</li>
<li>
<p>解决思路</p>
<ul>
<li>更多的页面静态化处理</li>
<li>构建多级缓存架构<br>
Nginx 缓存+redis 缓存+ehcache 缓存</li>
<li>检测 Mysql 严重耗时业务进行优化<br>
对数据库的瓶颈排查：例如超时查询、耗时较高事务等</li>
<li>预警机制</li>
<li>限流、降级</li>
</ul>
</li>
<li>
<p>具体解决方案</p>
<ul>
<li>切换为 LFU 淘汰策略</li>
<li>调整过期的时间，使其错峰</li>
<li>超热数据暂时使用永久 key</li>
<li>定期维护（自动+人工）<br>
对即将过期数据做访问量分析，确认是否延时，配合访问量统计，做热点数据的延时</li>
<li>加锁：慎用！</li>
</ul>
</li>
</ul>
<h3 id="缓存击穿">缓存击穿</h3>
<ul>
<li>
<p>现象：Redis 中某个高热点 key 过期，该 key 访问量巨大</p>
</li>
<li>
<p>解决方案</p>
<ul>
<li>增加热点 key 的时间</li>
<li>设置热点 key 为永久</li>
<li>高峰期来临前自动刷新有效期</li>
<li>二级缓存，设置不同的过期时间错峰</li>
<li>分布式锁</li>
</ul>
</li>
</ul>
<h3 id="缓存穿透">缓存穿透</h3>
<ul>
<li>
<p>现象：黑客大量访问不存在的数据，跳过 redis 直接攻击数据库</p>
</li>
<li>
<p>解决方案</p>
<ul>
<li>1、对查询结果为 null 的数据进行缓存（长期使用，定期清理），设定短时限，例如 30-60 秒，最高 5 分钟</li>
<li>2、白名单策略<br>
提前预热各种分类数据 id 对应的 bitmaps，id 作为 bitmaps 的 offset，相当于设置了数据白名单。当加载正常数据时放行，加载异常数据时直接拦截（效率偏低）<br>
使用布隆过滤器（有关布隆过滤器的命中问题对当前状况可以忽略）</li>
<li>3、实时监控 redis 命中率，提前预防，使用黑名单进行防控</li>
<li>4、key 加密<br>
问题出现后，临时启动防灾业务 key，对 key 进行业务层传输加密服务，设定校验程序，过来的 key 校验<br>
例如每天随机分配 60 个加密串，挑选 2 到 3 个，混淆到页面数据 id 中，发现访问 key 不满足规则，驳回数据访问</li>
</ul>
</li>
</ul>
</article><div class="post-copyright"><div class="post-copyright__author"><span class="post-copyright-meta"><i class="fas fa-circle-user fa-fw"></i>文章作者: </span><span class="post-copyright-info"><a href="https://sekibetu.com">SekiBetu</a></span></div><div class="post-copyright__type"><span class="post-copyright-meta"><i class="fas fa-square-arrow-up-right fa-fw"></i>文章链接: </span><span class="post-copyright-info"><a href="https://sekibetu.com/redis02.html">https://sekibetu.com/redis02.html</a></span></div><div class="post-copyright__notice"><span class="post-copyright-meta"><i class="fas fa-circle-exclamation fa-fw"></i>版权声明: </span><span class="post-copyright-info">本博客所有文章除特别声明外，均采用 <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/" target="_blank">CC BY-NC-SA 4.0</a> 许可协议。转载请注明来源 <a href="https://sekibetu.com" target="_blank">惜别的秘密基地</a>！</span></div></div><div class="tag_share"><div class="post-meta__tag-list"><a class="post-meta__tags" href="/tags/Redis/">Redis</a></div><div class="post-share"><div class="social-share" data-image="/img/67861832_p0.jpg" data-sites="facebook,twitter,wechat,weibo,qq"></div><link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/[email protected]/sharejs/dist/css/share.min.css" media="print" onload="this.media='all'"><script src="https://cdn.jsdelivr.net/npm/[email protected]/sharejs/dist/js/social-share.min.js" defer></script></div></div><nav class="pagination-post" id="pagination"><a class="pagination-related" href="/mybatis01.html" title="MyBatis如何获取刚刚插入数据的ID"><img class="cover" src="/img/67861832_p0.jpg" onerror="onerror=null;src='/img/Starfetcher.jpg'" alt="cover of previous post"><div class="info"><div class="info-1"><div class="info-item-1">上一篇</div><div class="info-item-2">MyBatis如何获取刚刚插入数据的ID</div></div><div class="info-2"><div class="info-item-1"> 有时业务逻辑中需要获取刚刚插入的数据的自增 ID 值以用于后续使用，MyBatis 提供了 LAST_INSERT_ID() 函数获取该 ID 值： 1234567891011<mapper> <insert id="add" parameterType="pojo"> <!--insert操作结束后查询最后一条插入的数据的ID值并将其赋值给pojo对象中的id属性--> <selectKey resultType="java.lang.Integer" order="AFTER" keyProperty="id"> select LAST_INSERT_ID() </selectKey> insert into table(items) values(#{items}) ...</div></div></div></a><a class="pagination-related" href="/docker01.html" title="Docker笔记(自用)"><img class="cover" src="/img/67861832_p0.jpg" onerror="onerror=null;src='/img/Starfetcher.jpg'" alt="cover of next post"><div class="info text-right"><div class="info-1"><div class="info-item-1">下一篇</div><div class="info-item-2">Docker笔记(自用)</div></div><div class="info-2"><div class="info-item-1">随手记点笔记，不全，自用 Docker 基础命令 服务相关命令 systemctl start docker systemctl stop docker systemctl restart docker systemctl status docker systemctl enable docker 为 docker 服务设置开机自启 镜像相关命令 docker images 查看本地镜像 docker search 镜像名称 搜索镜像 docker pull 镜像名称:版本号 从 docker 仓库拉取某版本的镜像到本地 docker build 创建 dockerfile 镜像 容器相关命令 docker ps -a 查看所有本地容器 举例：docker run -it --name=cl centos:7 /bin/bash 创建一个名为 cl 的 centos7 的容器并以 bash 这个 shell 进入交互式界面 exit 可以退出容器但会使带-t 参数的交互式容器停止，所以要避免-t 参数的使用，但是可以使用^p^q...</div></div></div></a></nav><div class="relatedPosts"><div class="headline"><i class="fas fa-thumbs-up fa-fw"></i><span>相关推荐</span></div><div class="relatedPosts-list"><a class="pagination-related" href="/redis01.html" title="Redis笔记(自用)"><img class="cover" src="/img/67861832_p0.jpg" alt="cover"><div class="info text-center"><div class="info-1"><div class="info-item-1"><i class="far fa-calendar-alt fa-fw"></i> 2020-08-01</div><div class="info-item-2">Redis笔记(自用)</div></div><div class="info-2"><div class="info-item-1">Redis Redis: Remote Dictionary Server 三个特点: Redis 支持数据持久化. 可以将内存中的数据保持在磁盘中, 重启后可再次使用 Redis 支持 key-val, list, set, zset, hash 等数据结构存储 Redis 支持数据备份, master-slave 模式数据备份 零碎基础知识 单进程 (*) 单进程处理客户端的请求, 对读写事件响应是通过 epoll 函数而包装来操作. 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class="item-headline"><i class="fas fa-bullhorn fa-shake"></i><span>公告</span></div><div class="announcement_content">This is my Blog</div></div><div class="sticky_layout"><div class="card-widget" id="card-toc"><div class="item-headline"><i class="fas fa-stream"></i><span>目录</span><span class="toc-percentage"></span></div><div class="toc-content is-expand"><ol class="toc"><li class="toc-item toc-level-2"><a class="toc-link" href="#%E5%88%A0%E9%99%A4%E7%AD%96%E7%95%A5"><span class="toc-number">1.</span> <span class="toc-text">删除策略</span></a><ol class="toc-child"><li class="toc-item toc-level-3"><a class="toc-link" href="#%E5%AE%9A%E6%97%B6%E5%88%A0%E9%99%A4"><span class="toc-number">1.1.</span> <span class="toc-text">定时删除</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E6%83%B0%E6%80%A7%E5%88%A0%E9%99%A4"><span class="toc-number">1.2.</span> <span class="toc-text">惰性删除</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E5%AE%9A%E6%9C%9F%E5%88%A0%E9%99%A4"><span class="toc-number">1.3.</span> <span class="toc-text">定期删除</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E6%B7%98%E6%B1%B0%E7%AD%96%E7%95%A5"><span class="toc-number">1.4.</span> <span class="toc-text">淘汰策略</span></a></li></ol></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%E4%B8%BB%E4%BB%8E%E5%A4%8D%E5%88%B6"><span class="toc-number">2.</span> <span class="toc-text">主从复制</span></a><ol class="toc-child"><li class="toc-item toc-level-3"><a class="toc-link" href="#%E5%BB%BA%E7%AB%8B%E8%BF%9E%E6%8E%A5%E7%9A%84%E6%B5%81%E7%A8%8B"><span class="toc-number">2.1.</span> <span class="toc-text">建立连接的流程</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E6%95%B0%E6%8D%AE%E5%90%8C%E6%AD%A5"><span class="toc-number">2.2.</span> <span class="toc-text">数据同步</span></a></li></ol></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%E5%93%A8%E5%85%B5%E6%A8%A1%E5%BC%8F"><span class="toc-number">3.</span> <span class="toc-text">哨兵模式</span></a><ol class="toc-child"><li class="toc-item toc-level-3"><a class="toc-link" href="#%E6%A3%80%E6%B5%8B-master-%E6%98%AF%E5%90%A6%E5%AE%95%E6%9C%BA%EF%BC%8Cmaster-%E5%AE%95%E6%9C%BA%E5%90%8E%E9%80%89%E4%B8%BE-slave-%E4%B8%BA-master"><span class="toc-number">3.1.</span> <span class="toc-text">检测 master 是否宕机，master 宕机后选举 slave 为 master</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E5%BB%BA%E7%AB%8B%E8%BF%87%E7%A8%8B%E9%85%8D%E7%BD%AE"><span class="toc-number">3.2.</span> <span class="toc-text">建立过程配置</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E7%9B%91%E6%8E%A7%E9%98%B6%E6%AE%B5"><span class="toc-number">3.3.</span> <span class="toc-text">监控阶段</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E6%95%85%E9%9A%9C%E8%BD%AC%E7%A7%BB%E9%98%B6%E6%AE%B5"><span class="toc-number">3.4.</span> <span class="toc-text">故障转移阶段</span></a></li></ol></li><li class="toc-item toc-level-2"><a class="toc-link" href="#Cluster-%E9%9B%86%E7%BE%A4"><span class="toc-number">4.</span> <span class="toc-text">Cluster 集群</span></a><ol class="toc-child"><li class="toc-item toc-level-3"><a class="toc-link" href="#%E6%95%B0%E6%8D%AE%E5%AD%98%E5%82%A8%E7%BB%93%E6%9E%84"><span class="toc-number">4.1.</span> <span class="toc-text">数据存储结构</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E9%85%8D%E7%BD%AE"><span class="toc-number">4.2.</span> <span class="toc-text">配置</span></a></li></ol></li><li class="toc-item toc-level-2"><a class="toc-link" href="#%E4%BC%81%E4%B8%9A%E7%BA%A7%E8%A7%A3%E5%86%B3%E6%96%B9%E6%A1%88"><span class="toc-number">5.</span> <span class="toc-text">企业级解决方案</span></a><ol class="toc-child"><li class="toc-item toc-level-3"><a class="toc-link" href="#%E7%BC%93%E5%AD%98%E9%A2%84%E7%83%AD"><span class="toc-number">5.1.</span> <span class="toc-text">缓存预热</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E7%BC%93%E5%AD%98%E9%9B%AA%E5%B4%A9"><span class="toc-number">5.2.</span> <span class="toc-text">缓存雪崩</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E7%BC%93%E5%AD%98%E5%87%BB%E7%A9%BF"><span class="toc-number">5.3.</span> <span class="toc-text">缓存击穿</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E7%BC%93%E5%AD%98%E7%A9%BF%E9%80%8F"><span class="toc-number">5.4.</span> <span class="toc-text">缓存穿透</span></a></li></ol></li></ol></div></div><div class="card-widget card-recent-post"><div class="item-headline"><i class="fas fa-history"></i><span>最新文章</span></div><div class="aside-list"><div class="aside-list-item no-cover"><div class="content"><a class="title" href="/linus01.html" title="对Linux社区封禁俄罗斯开发者且linus本人支持这一行为的评价">对Linux社区封禁俄罗斯开发者且linus本人支持这一行为的评价</a><time datetime="2024-10-24T13:54:15.000Z" title="发表于 2024-10-24 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