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7.53c-.34.3-.13.87.33.87H5v7c0 .55.45 1 1 1h3c.55 0 1-.45 1-1z" fill="currentColor"></path></svg></a></li><li class="breadcrumbs__item"><span class="breadcrumbs__link">最佳实践</span><meta itemprop="position" content="1"></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link" itemprop="name">基本最佳实践</span><meta itemprop="position" content="2"></li></ul></nav><span class="theme-doc-version-badge badge badge--secondary">版本:5.0</span><div class="tocCollapsible_ETCw theme-doc-toc-mobile tocMobile_ITEo"><button type="button" class="clean-btn tocCollapsibleButton_TO0P">本页总览</button></div><div class="theme-doc-markdown markdown"><h1>基本最佳实践</h1><h2 class="anchor anchorWithStickyNavbar_LWe7" id="生产者">生产者<a href="#生产者" class="hash-link" aria-label="生产者的直接链接" title="生产者的直接链接"></a></h2><h3 class="anchor anchorWithStickyNavbar_LWe7" id="发送消息注意事项">发送消息注意事项<a href="#发送消息注意事项" class="hash-link" aria-label="发送消息注意事项的直接链接" title="发送消息注意事项的直接链接"></a></h3><h4 class="anchor anchorWithStickyNavbar_LWe7" id="tag的使用">Tag的使用<a href="#tag的使用" class="hash-link" aria-label="Tag的使用的直接链接" title="Tag的使用的直接链接"></a></h4><p>一个应用尽可能用一个Topic,而消息子类型则可以用tags来标识。tags可以由应用自由设置,只有生产者在发送消息设置了tags,消费方在订阅消息时才可以利用tags通过broker做消息过滤,5.x SDK 可以调用messageBuilder.setTag(&quot;messageTag&quot;),历史版本可以调用 message.setTags(&quot;messageTag&quot;)。 </p><h4 class="anchor anchorWithStickyNavbar_LWe7" id="keys的使用">Keys的使用<a href="#keys的使用" class="hash-link" aria-label="Keys的使用的直接链接" title="Keys的使用的直接链接"></a></h4><p>每个消息在业务层面一般建议映射到业务的唯一标识并设置到keys字段,方便将来定位消息丢失问题。服务器会为每个消息创建索引(哈希索引),应用可以通过topic、key来查询这条消息内容,以及消息被谁消费。由于是哈希索引,请务必保证key尽可能唯一,这样可以避免潜在的哈希冲突。常见的设置策略使用订单Id、用户Id、请求Id等比较离散的唯一标识来处理。</p><h4 class="anchor anchorWithStickyNavbar_LWe7" id="日志的打印">日志的打印<a href="#日志的打印" class="hash-link" aria-label="日志的打印的直接链接" title="日志的打印的直接链接"></a></h4><p>消息发送成功或者失败要打印消息日志,用于业务排查问题。Send消息方法只要不抛异常,就代表发送成功。</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="消息发送失败处理方式">消息发送失败处理方式<a href="#消息发送失败处理方式" class="hash-link" aria-label="消息发送失败处理方式的直接链接" title="消息发送失败处理方式的直接链接"></a></h3><p>Producer的send方法本身支持内部重试,5.x SDK的重试逻辑参考<a href="/zh/docs/featureBehavior/05sendretrypolicy">发送重试策略</a></p><p>以上策略也是在一定程度上保证了消息可以发送成功。如果业务要求消息发送不能丢,仍然需要对可能出现的异常做兜底,比如调用send同步方法发送失败时,则尝试将消息存储到db,然后由后台线程定时重试,确保消息一定到达Broker。</p><p>上述DB重试方式为什么没有集成到MQ客户端内部做,而是要求应用自己去完成,主要基于以下几点考虑:首先,MQ的客户端设计为无状态模式,方便任意的水平扩展,且对机器资源的消耗仅仅是cpu、内存、网络。其次,如果MQ客户端内部集成一个KV存储模块,那么数据只有同步落盘才能较可靠,而同步落盘本身性能开销较大,所以通常会采用异步落盘,又由于应用关闭过程不受MQ运维人员控制,可能经常会发生 kill -9 这样暴力方式关闭,造成数据没有及时落盘而丢失。第三,Producer所在机器的可靠性较低,一般为虚拟机,不适合存储重要数据。综上,建议重试过程交由应用来控制。</p><h2 class="anchor anchorWithStickyNavbar_LWe7" id="消费者">消费者<a href="#消费者" class="hash-link" aria-label="消费者的直接链接" title="消费者的直接链接"></a></h2><h3 class="anchor anchorWithStickyNavbar_LWe7" id="消费过程幂等">消费过程幂等<a href="#消费过程幂等" class="hash-link" aria-label="消费过程幂等的直接链接" title="消费过程幂等的直接链接"></a></h3><p>RocketMQ 无法避免消息重复(Exactly-Once),所以如果业务对消费重复非常敏感,务必要在业务层面进行去重处理。可以借助关系数据库进行去重。首先需要确定消息的唯一键,可以是msgId,也可以是消息内容中的唯一标识字段,例如订单Id等。在消费之前判断唯一键是否在关系数据库中存在。如果不存在则插入,并消费,否则跳过。(实际过程要考虑原子性问题,判断是否存在可以尝试插入,如果报主键冲突,则插入失败,直接跳过)</p><p>msgId一定是全局唯一标识符,但是实际使用中,可能会存在相同的消息有两个不同msgId的情况(消费者主动重发、因客户端重投机制导致的重复等),这种情况就需要使业务字段进行重复消费。</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="消费速度慢的处理方式">消费速度慢的处理方式<a href="#消费速度慢的处理方式" class="hash-link" aria-label="消费速度慢的处理方式的直接链接" title="消费速度慢的处理方式的直接链接"></a></h3><h3 class="anchor anchorWithStickyNavbar_LWe7" id="提高消费并行度">提高消费并行度<a href="#提高消费并行度" class="hash-link" aria-label="提高消费并行度的直接链接" title="提高消费并行度的直接链接"></a></h3><p>绝大部分消息消费行为都属于 IO 密集型,即可能是操作数据库,或者调用 RPC,这类消费行为的消费速度在于后端数据库或者外系统的吞吐量,通过增加消费并行度,可以提高总的消费吞吐量,但是并行度增加到一定程度,反而会下降。所以,应用必须要设置合理的并行度。 如下有几种修改消费并行度的方法:</p><ul><li>同一个 ConsumerGroup 下,通过增加 Consumer 实例数量来提高并行度。可以通过加机器,或者在已有机器启动多个进程的方式。</li><li>提高单个 Consumer 的消费并行线程,5.x PushConsumer SDK 可以通过PushConsumerBuilder.setConsumptionThreadCount() 设置线程数,SimpleConsumer可以由业务线程自由增加并发,底层线程安全;历史版本SDK PushConsumer可以通过修改参数 consumeThreadMin、consumeThreadMax实现。</li></ul><h3 class="anchor anchorWithStickyNavbar_LWe7" id="批量方式消费">批量方式消费<a href="#批量方式消费" class="hash-link" aria-label="批量方式消费的直接链接" title="批量方式消费的直接链接"></a></h3><p>某些业务流程如果支持批量方式消费,则可以很大程度上提高消费吞吐量,例如订单扣款类应用,一次处理一个订单耗时 1 s,一次处理 10 个订单可能也只耗时 2 s,这样即可大幅度提高消费的吞吐量。建议使用5.x SDK的SimpleConsumer,每次接口调用设置批次大小,一次性拉取消费多条消息。</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="重置位点跳过非重要消息">重置位点跳过非重要消息<a href="#重置位点跳过非重要消息" class="hash-link" aria-label="重置位点跳过非重要消息的直接链接" title="重置位点跳过非重要消息的直接链接"></a></h3><p>发生消息堆积时,如果消费速度一直追不上发送速度,如果业务对数据要求不高的话,可以选择丢弃不重要的消息。建议使用重置位点功能直接调整消费位点到指定时刻或者指定位置。</p><h4 class="anchor anchorWithStickyNavbar_LWe7" id="优化每条消息消费过程">优化每条消息消费过程<a href="#优化每条消息消费过程" class="hash-link" aria-label="优化每条消息消费过程的直接链接" title="优化每条消息消费过程的直接链接"></a></h4><p>举例如下,某条消息的消费过程如下:</p><ul><li>根据消息从 DB 查询【数据 1】</li><li>根据消息从 DB 查询【数据 2】</li><li>复杂的业务计算</li><li>向 DB 插入【数据 3】</li><li>向 DB 插入【数据 4】</li></ul><p>这条消息的消费过程中有4次与 DB的 交互,如果按照每次 5ms 计算,那么总共耗时 20ms,假设业务计算耗时 5ms,那么总过耗时 25ms,所以如果能把 4 次 DB 交互优化为 2 次,那么总耗时就可以优化到 15ms,即总体性能提高了 40%。所以应用如果对时延敏感的话,可以把DB部署在SSD硬盘,相比于SCSI磁盘,前者的RT会小很多。</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="消费打印日志">消费打印日志<a href="#消费打印日志" class="hash-link" aria-label="消费打印日志的直接链接" title="消费打印日志的直接链接"></a></h3><p>如果消息量较少,建议在消费入口方法打印消息,消费耗时等,方便后续排查问题。</p><div class="language-java codeBlockContainer_Ckt0 theme-code-block" style="--prism-color:#393A34;--prism-background-color:#f6f8fa"><div class="codeBlockContent_biex"><pre tabindex="0" class="prism-code language-java codeBlock_bY9V thin-scrollbar"><code class="codeBlockLines_e6Vv"><span class="token-line" style="color:#393A34"><span class="token plain"> new MessageListener() {</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain"> @Override</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain"> public ConsumeResult consume(MessageView messageView) {</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain"> LOGGER.info(&quot;Consume message={}&quot;, messageView);</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain"> //Do your consume process</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain"> return ConsumeResult.SUCCESS;</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain"> }</span><br></span><span class="token-line" style="color:#393A34"><span class="token plain"> }</span><br></span></code></pre><div class="buttonGroup__atx"><button type="button" aria-label="复制代码到剪贴板" title="复制" class="clean-btn"><span class="copyButtonIcons_eSgA" aria-hidden="true"><svg viewBox="0 0 24 24" class="copyButtonIcon_y97N"><path fill="currentColor" d="M19,21H8V7H19M19,5H8A2,2 0 0,0 6,7V21A2,2 0 0,0 8,23H19A2,2 0 0,0 21,21V7A2,2 0 0,0 19,5M16,1H4A2,2 0 0,0 2,3V17H4V3H16V1Z"></path></svg><svg viewBox="0 0 24 24" class="copyButtonSuccessIcon_LjdS"><path fill="currentColor" d="M21,7L9,19L3.5,13.5L4.91,12.09L9,16.17L19.59,5.59L21,7Z"></path></svg></span></button></div></div></div><p>如果能打印每条消息消费耗时,那么在排查消费慢等线上问题时,会更方便。但如果线上环境TPS很高,不建议开启,避免日志太多影响性能。</p><h2 class="anchor anchorWithStickyNavbar_LWe7" id="broker">Broker<a href="#broker" class="hash-link" aria-label="Broker的直接链接" title="Broker的直接链接"></a></h2><h3 class="anchor anchorWithStickyNavbar_LWe7" id="broker-角色">Broker 角色<a href="#broker-角色" class="hash-link" aria-label="Broker 角色的直接链接" title="Broker 角色的直接链接"></a></h3><p> Broker 角色分为 ASYNC_MASTER(异步主机)、SYNC_MASTER(同步主机)以及SLAVE(从机)。如果对消息的可靠性要求比较严格,可以采用 SYNC_MASTER加SLAVE的部署方式。如果对消息可靠性要求不高,可以采用ASYNC_MASTER加SLAVE的部署方式。如果只是测试方便,则可以选择仅ASYNC_MASTER或仅SYNC_MASTER的部署方式。</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="flushdisktype">FlushDiskType<a href="#flushdisktype" class="hash-link" aria-label="FlushDiskType的直接链接" title="FlushDiskType的直接链接"></a></h3><p> SYNC_FLUSH(同步刷新)相比于ASYNC_FLUSH(异步处理)会损失很多性能,但是也更可靠,所以需要根据实际的业务场景做好权衡。</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="broker-配置">Broker 配置<a href="#broker-配置" class="hash-link" aria-label="Broker 配置的直接链接" title="Broker 配置的直接链接"></a></h3><table><thead><tr><th>参数名</th><th>默认值</th><th>说明</th></tr></thead><tbody><tr><td>listenPort</td><td>10911</td><td>接受客户端连接的监听端口</td></tr><tr><td>namesrvAddr</td><td>null</td><td>nameServer 地址</td></tr><tr><td>brokerIP1</td><td>网卡的 InetAddress</td><td>当前 broker 监听的 IP</td></tr><tr><td>brokerIP2</td><td>跟 brokerIP1 一样</td><td>存在主从 broker 时,如果在 broker 主节点上配置了 brokerIP2 属性,broker 从节点会连接主节点配置的 brokerIP2 进行同步</td></tr><tr><td>brokerName</td><td>null</td><td>broker 的名称</td></tr><tr><td>brokerClusterName</td><td>DefaultCluster</td><td>本 broker 所属的 Cluser 名称</td></tr><tr><td>brokerId</td><td>0</td><td>broker id, 0 表示 master, 其他的正整数表示 slave</td></tr><tr><td>storePathCommitLog</td><td>$HOME/store/commitlog/</td><td>存储 commit log 的路径</td></tr><tr><td>storePathConsumerQueue</td><td>$HOME/store/consumequeue/</td><td>存储 consume queue 的路径</td></tr><tr><td>mapedFileSizeCommitLog</td><td>1024 <!-- -->*<!-- --> 1024 <!-- -->*<!-- --> 1024(1G)</td><td>commit log 的映射文件大小</td></tr><tr><td>deleteWhen</td><td>04</td><td>在每天的什么时间删除已经超过文件保留时间的 commit log</td></tr><tr><td>fileReservedTime</td><td>72</td><td>以小时计算的文件保留时间</td></tr><tr><td>brokerRole</td><td>ASYNC_MASTER</td><td>SYNC_MASTER/ASYNC_MASTER/SLAVE</td></tr><tr><td>flushDiskType</td><td>ASYNC_FLUSH</td><td>SYNC_FLUSH/ASYNC_FLUSH SYNC_FLUSH 模式下的 broker 保证在收到确认生产者之前将消息刷盘。ASYNC_FLUSH 模式下的 broker 则利用刷盘一组消息的模式,可以取得更好的性能。</td></tr></tbody></table></div><footer class="theme-doc-footer docusaurus-mt-lg"><div class="theme-doc-footer-edit-meta-row row"><div class="col"><a href="https://github.com/apache/rocketmq-site/tree/new-official-website/versioned_docs/version-5.0/06-bestPractice/01bestpractice.md" target="_blank" rel="noreferrer noopener" 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table-of-contents__left-border"><li><a href="#生产者" class="table-of-contents__link toc-highlight">生产者</a><ul><li><a href="#发送消息注意事项" class="table-of-contents__link toc-highlight">发送消息注意事项</a></li><li><a href="#消息发送失败处理方式" class="table-of-contents__link toc-highlight">消息发送失败处理方式</a></li></ul></li><li><a href="#消费者" class="table-of-contents__link toc-highlight">消费者</a><ul><li><a href="#消费过程幂等" class="table-of-contents__link toc-highlight">消费过程幂等</a></li><li><a href="#消费速度慢的处理方式" class="table-of-contents__link toc-highlight">消费速度慢的处理方式</a></li><li><a href="#提高消费并行度" class="table-of-contents__link toc-highlight">提高消费并行度</a></li><li><a href="#批量方式消费" class="table-of-contents__link toc-highlight">批量方式消费</a></li><li><a href="#重置位点跳过非重要消息" class="table-of-contents__link toc-highlight">重置位点跳过非重要消息</a></li><li><a href="#消费打印日志" class="table-of-contents__link toc-highlight">消费打印日志</a></li></ul></li><li><a href="#broker" class="table-of-contents__link toc-highlight">Broker</a><ul><li><a 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