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itemtype="https://schema.org/ListItem" class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link" itemprop="name">RocketMQ Connect 概览</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>RocketMQ Connect 概览</h1><p>RocketMQ Connect是RocketMQ数据集成重要组件，可将各种系统中的数据通过高效，可靠，流的方式，流入流出到RocketMQ，它是独立于RocketMQ的，一个单独的分布式、可扩展、可容错系统， | |
| 它具备低延时，高可靠性，高性能，低代码，扩展性强等特点，可以实现各种异构数据系统的连接，以及构建数据管道，ETL，CDC，数据湖等能力。</p><p><img loading="lazy" alt="RocketMQ Connect Overview" src="/zh/assets/images/overview-195cf6b6249dc8488e721970527cc533.png" width="721" height="482" class="img_ev3q"></p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="connector工作原理">Connector工作原理<a href="#connector工作原理" class="hash-link" aria-label="Connector工作原理的直接链接" title="Connector工作原理的直接链接"></a></h3><p>RocketMQ Connect是一个独立的的分布式，可伸缩，容错的系统，它主要为RocketMQ提供与各种外部系统的数据的流入流出能力。用户不需要编程，只需要简单的配置即可使用RocketMQ Connect，例如从MySQL同步数据到RocketMQ，只需要配置同步所需的MySQL的账号密码，链接地址，和需要同步的数据库，表名就可以了。</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="connector的使用场景">Connector的使用场景<a href="#connector的使用场景" class="hash-link" aria-label="Connector的使用场景的直接链接" title="Connector的使用场景的直接链接"></a></h3><h5 class="anchor anchorWithStickyNavbar_LWe7" id="构建流式数据管道">构建流式数据管道<a href="#构建流式数据管道" class="hash-link" aria-label="构建流式数据管道的直接链接" title="构建流式数据管道的直接链接"></a></h5><p><img loading="lazy" alt="RocketMQ Connect使用场景" src="/zh/assets/images/scene-3406354e6f18c416f4676634945f8fdd.png" width="493" height="228" class="img_ev3q"></p><p>在业务系统中，利用MySQL完善的事务支持，处理数据的增删改，使用ElasticSearch，Solr等实现强大的搜索能力,或者将产生的业务数据同步到数据分析系统，数据湖中（例如hudi），对数据进一步处理从而让数据产生更高的价值。使用RocketMQ Connect很容易实现这样的数据管道的能力，只需要配置3个任务，第一个是从MySQL获取数据的任务，第二，三个是从RocketMQ消费数据到ElasticSearch，Hudi的任务，配置3个任务就实现了从MySQL到ElasticSearch，MySQL到hudi的两条数据管道，既可以满足业务对事务、搜索的需求，也可以用于构建数据湖。</p><h5 class="anchor anchorWithStickyNavbar_LWe7" id="cdc">CDC<a href="#cdc" class="hash-link" aria-label="CDC的直接链接" title="CDC的直接链接"></a></h5><p>CDC作为ETL模式之一，可以近乎实时的捕获增量数据库INSERT、UPDATE，DELETE变化，RocketMQ Connect流试数据传输，具备高可用，低延时等特性，通过Connector很容易实现CDC。</p><h3 class="anchor anchorWithStickyNavbar_LWe7" id="connector-部署">Connector 部署<a href="#connector-部署" class="hash-link" aria-label="Connector 部署的直接链接" title="Connector 部署的直接链接"></a></h3><p>创建Connector，一般通过配置即可完成，Connector包含逻辑的Connector连接器和执行数据复制的Task(即物理线程)，如下图所示，两个Connector连接器和它们对应的运行Task任务。</p><p><img loading="lazy" alt="RocketMQ Connect任务模型1" src="data:image/png;base64,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" width="471" height="231" class="img_ev3q"></p><p>一个Connector也可以同时运行多个任务，提高Connector的并行度，例如下图所示的Hudi Sink Connector有2个任务，每个任务处理不同的分片数据，从而Connector的并行度，进而提高处理性能。</p><p><img loading="lazy" alt="RocketMQ Connect任务模型2" src="data:image/png;base64,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" width="481" height="231" class="img_ev3q"></p><p>RocketMQ Connect Worker支持两种运行模式，集群和单机 | |
| 集群模式，顾名思义，由多个Worker节点组成，推荐最少有2个Worker节点，组成高可用集群。集群间的配置信息，offset信息，status信息则通过指定的RocketMQ Topic进行存储，新增Worker节点也会获取到集群中的这些配置，offset，status信息，并且触发负载均衡，重新分配集群中的任务，使集群达到均衡的状态，减少Woker节点或者Worker宕机也会触发负载均衡，从而保障集群中所有的任务都可以均衡的在集群中存活的节点中正常运行。</p><p><img loading="lazy" alt="RocketMQ Connect部署模型集群" src="/zh/assets/images/deploy3-879eb285035b5f869646a5707885d874.png" width="781" height="431" class="img_ev3q"></p><p>单机模式，Connector任务运行在单机上，Worker本身没有高可用，任务offset信息持久化在本地。适合一些对高可没有什么要求或者不需要Worker保障高可用的场景，例如部署在k8s集群中，由k8s集群保障高可用。</p><p><img loading="lazy" alt="RocketMQ Connect部署模型单机" 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" 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