作者 | 李杰 移动云，Apache DolphinScheduler
在现代数据驱动的企业中，工作流调度系统是数据管道（Data Pipeline）的“中枢神经”。从 ETL 任务到机器学习训练，从报表生成到实时监控，几乎所有关键业务都依赖于一个稳定、高效、易扩展的调度引擎。
笔者认为 Apache DolphinScheduler 3.1.9 是稳定且广泛使用的版本，故本系列文章将深入其源码核心，剖析其架构设计、模块划分与关键实现机制，帮助开发者理解 Master 和 Worker “如何工作”，并为进一步二次开发或性能优化打下基础。
我们之前解读了 Apache DolphinScheduler 3.1.9版本源码的 Master server 启动流程 ，感兴趣的可以去查看。本文是 Apache DolphinScheduler 3.1.9 版本源码解读的第二篇：Worker Server 启动流程源码解读以及相关流程设计。结尾处附有相关流程图，供大家参考。
public void run() { // 1. rpc启动 this.workerRpcServer.start(); // 忽略，因为workerRpcServer初始化时包含workerRpcClient初始化的功能 this.workerRpcClient.start(); // 2. 任务插件初始化 this.taskPluginManager.loadPlugin(); this.workerRegistryClient.setRegistryStoppable(this); // 3. worker 注册 this.workerRegistryClient.start(); // 4. worker管理线程，不断从任务队列中waitSubmitQueue领取任务，提交到线程池处理 this.workerManagerThread.start(); // 5. 消息重试线程。负责轮询通过RPC发送服务，如当task在运行中，若未收到master的ack信息，会周期给master发送“运行中”信号 this.messageRetryRunner.start(); ... } public void start() { LOGGER.info("Worker rpc server starting"); NettyServerConfig serverConfig = new NettyServerConfig(); serverConfig.setListenPort(workerConfig.getListenPort()); this.nettyRemotingServer = new NettyRemotingServer(serverConfig); // 接收派发任务请求。然后将任务放置到任务队列waitSubmitQueue中，等待workerManagerThread去处理 this.nettyRemotingServer.registerProcessor(CommandType.TASK_DISPATCH_REQUEST, taskDispatchProcessor); // 停止任务请求 this.nettyRemotingServer.registerProcessor(CommandType.TASK_KILL_REQUEST, taskKillProcessor); // 接收任务运行中的ack请求 this.nettyRemotingServer.registerProcessor(CommandType.TASK_EXECUTE_RUNNING_ACK, taskExecuteRunningAckProcessor); // 接收任务结果的ack请求 this.nettyRemotingServer.registerProcessor(CommandType.TASK_EXECUTE_RESULT_ACK, taskExecuteResultAckProcessor); this.nettyRemotingServer.registerProcessor(CommandType.TASK_REJECT_ACK, taskRejectAckProcessor); this.nettyRemotingServer.registerProcessor(CommandType.PROCESS_HOST_UPDATE_REQUEST, hostUpdateProcessor); this.nettyRemotingServer.registerProcessor(CommandType.TASK_SAVEPOINT_REQUEST, taskSavePointProcessor); // logger server this.nettyRemotingServer.registerProcessor(CommandType.GET_APP_ID_REQUEST, loggerRequestProcessor); this.nettyRemotingServer.registerProcessor(CommandType.GET_LOG_BYTES_REQUEST, loggerRequestProcessor); this.nettyRemotingServer.registerProcessor(CommandType.ROLL_VIEW_LOG_REQUEST, loggerRequestProcessor); this.nettyRemotingServer.registerProcessor(CommandType.VIEW_WHOLE_LOG_REQUEST, loggerRequestProcessor); this.nettyRemotingServer.registerProcessor(CommandType.REMOVE_TAK_LOG_REQUEST, loggerRequestProcessor); this.nettyRemotingServer.start(); LOGGER.info("Worker rpc server started"); } 此处以TASK_DISPATCH_REQUEST为例进行描述。当有任务从master派发请求时，worker会接受TASK_DISPATCH_REQUEST的RPC请求，然后触发process处理器taskDispatchProcessor(org.apache.dolphinscheduler.server.worker.processor.TaskDispatchProcessor#process)的处理:
public void process(Channel channel, Command command) { ... TaskExecutionContext taskExecutionContext = taskDispatchCommand.getTaskExecutionContext(); ... // set cache, it will be used when kill task TaskExecutionContextCacheManager.cacheTaskExecutionContext(taskExecutionContext); // 设置执行任务的worker地址 taskExecutionContext.setHost(workerConfig.getWorkerAddress()); // 设置任务执行日志的目录 taskExecutionContext.setLogPath(LogUtils.getTaskLogPath(taskExecutionContext)); // 构建任务执行线程。整个任务执行需要依赖该线程 WorkerDelayTaskExecuteRunnable workerTaskExecuteRunnable = WorkerTaskExecuteRunnableFactoryBuilder .createWorkerDelayTaskExecuteRunnableFactory( taskExecutionContext, workerConfig, workflowMasterAddress, workerMessageSender, alertClientService, taskPluginManager, storageOperate) .createWorkerTaskExecuteRunnable(); // submit task to manager // 提交到一个task队列，然后有消费者消费该队列 boolean offer = workerManager.offer(workerTaskExecuteRunnable); ... } 最终会提交给waitSubmitQueue队列，后续有消费者不断进行消费。
public boolean offer(WorkerDelayTaskExecuteRunnable workerDelayTaskExecuteRunnable) { if (workerConfig.getTaskExecuteThreadsFullPolicy() == TaskExecuteThreadsFullPolicy.CONTINUE) { return waitSubmitQueue.offer(workerDelayTaskExecuteRunnable); } if (waitSubmitQueue.size() > workerExecThreads) { logger.warn("Wait submit queue is full, will retry submit task later"); WorkerServerMetrics.incWorkerSubmitQueueIsFullCount(); // if waitSubmitQueue is full, it will wait 1s, then try add ThreadUtils.sleep(Constants.SLEEP_TIME_MILLIS); if (waitSubmitQueue.size() > workerExecThreads) { return false; } } return waitSubmitQueue.offer(workerDelayTaskExecuteRunnable); } public void start() { try { // 1、将worker信息注册至注册中心(本文以zookeeper为例) registry(); // 2、监听自身与注册中心的连接情况； registryClient.addConnectionStateListener( new WorkerConnectionStateListener(workerConfig, registryClient, workerConnectStrategy)); } catch (Exception ex) { throw new RegistryException("Worker registry client start up error", ex); } } public void run() { Thread.currentThread().setName("Worker-Execute-Manager-Thread"); while (!ServerLifeCycleManager.isStopped()) { try { if (!ServerLifeCycleManager.isRunning()) { Thread.sleep(Constants.SLEEP_TIME_MILLIS); } // 1、如果任务线程池线程个数够用，则处理任务 if (this.getThreadPoolQueueSize() <= workerExecThreads) { // 消费task队列并且执行任务执行线程 final WorkerDelayTaskExecuteRunnable workerDelayTaskExecuteRunnable = waitSubmitQueue.take(); workerExecService.submit(workerDelayTaskExecuteRunnable); } else { // 2、若线程池资源紧张，则进行循环等待 WorkerServerMetrics.incWorkerOverloadCount(); logger.info("Exec queue is full, waiting submit queue {}, waiting exec queue size {}", this.getWaitSubmitQueueSize(), this.getThreadPoolQueueSize()); ThreadUtils.sleep(Constants.SLEEP_TIME_MILLIS); } } catch (Exception e) { logger.error("An unexpected interrupt is happened, " + "the exception will be ignored and this thread will continue to run", e); } } } workerDelayTaskExecuteRunnable核心内容：
public void run() { ... // 初始化任务，如任务启动时间等 initializeTask(); ... // 任务执行前的操作 beforeExecute(); // 任务回调，如更改任务的appId。可以先忽略 TaskCallBack taskCallBack = TaskCallbackImpl.builder().workerMessageSender(workerMessageSender) .masterAddress(masterAddress).build(); // 执行任务，等待结果 executeTask(taskCallBack); // 任务执行后的操作 afterExecute(); ... } 初始化：
protected void initializeTask() { logger.info("Begin to initialize task"); // 设置任务启动时间 Date taskStartTime = new Date(); taskExecutionContext.setStartTime(taskStartTime); logger.info("Set task startTime: {}", taskStartTime); // 获取环境变量，默认从dolphinscheduler_env.sh获取 String systemEnvPath = CommonUtils.getSystemEnvPath(); taskExecutionContext.setEnvFile(systemEnvPath); logger.info("Set task envFile: {}", systemEnvPath); String taskAppId = String.format("%s_%s", taskExecutionContext.getProcessInstanceId(), taskExecutionContext.getTaskInstanceId()); taskExecutionContext.setTaskAppId(taskAppId); logger.info("Set task appId: {}", taskAppId); logger.info("End initialize task"); } 执行前：
protected void beforeExecute() { // 设置任务状态为运行中 taskExecutionContext.setCurrentExecutionStatus(TaskExecutionStatus.RUNNING_EXECUTION); // 向master发送“运行中”信号，且将任务的关键信息一起发送，如任务执行节点、任务日志目录等 workerMessageSender.sendMessageWithRetry(taskExecutionContext, masterAddress, CommandType.TASK_EXECUTE_RUNNING); logger.info("Set task status to {}", TaskExecutionStatus.RUNNING_EXECUTION); // 查看租户是否存在 TaskExecutionCheckerUtils.checkTenantExist(workerConfig, taskExecutionContext); logger.info("TenantCode:{} check success", taskExecutionContext.getTenantCode()); // 创建任务执行目录(是一个本地的临时目录) TaskExecutionCheckerUtils.createProcessLocalPathIfAbsent(taskExecutionContext); logger.info("ProcessExecDir:{} check success", taskExecutionContext.getExecutePath()); // 从存储介质下载文件资源(如从hdfs下载aa.jar) TaskExecutionCheckerUtils.downloadResourcesIfNeeded(storageOperate, taskExecutionContext, logger); logger.info("Resources:{} check success", taskExecutionContext.getResources()); TaskChannel taskChannel = taskPluginManager.getTaskChannelMap().get(taskExecutionContext.getTaskType()); if (null == taskChannel) { throw new TaskPluginException(String.format("%s task plugin not found, please check config file.", taskExecutionContext.getTaskType())); } // 利用task插件创建任务信息，此处的task是是具体的任务类型，如shell、spark等 task = taskChannel.createTask(taskExecutionContext); if (task == null) { throw new TaskPluginException(String.format("%s task is null, please check the task plugin is correct", taskExecutionContext.getTaskType())); } logger.info("Task plugin: {} create success", taskExecutionContext.getTaskType()); // 任务参数准备。如将shell任务执行脚本解析出来、将spark任务的jar包、main类解析出来 task.init(); logger.info("Success initialized task plugin instance success"); task.getParameters().setVarPool(taskExecutionContext.getVarPool()); logger.info("Success set taskVarPool: {}", taskExecutionContext.getVarPool()); } 任务的具体执行。如shell任务的具体执行过程：
public void handle(TaskCallBack taskCallBack) throws TaskException { try { // construct process // 利用shell任务内容在执行目录生成一个脚本文件 String command = buildCommand(); // 执行脚本等待结果 TaskResponse commandExecuteResult = shellCommandExecutor.run(command); // 设置执行情况 setExitStatusCode(commandExecuteResult.getExitStatusCode()); // 设置进程id setProcessId(commandExecuteResult.getProcessId()); shellParameters.dealOutParam(shellCommandExecutor.getVarPool()); } catch (InterruptedException e) { Thread.currentThread().interrupt(); logger.error("The current Shell task has been interrupted", e); setExitStatusCode(EXIT_CODE_FAILURE); throw new TaskException("The current Shell task has been interrupted", e); } catch (Exception e) { logger.error("shell task error", e); setExitStatusCode(EXIT_CODE_FAILURE); throw new TaskException("Execute shell task error", e); } } 执行后：
protected void afterExecute() throws TaskException { if (task == null) { throw new TaskException("The current task instance is null"); } // 发送告警相关信息 sendAlertIfNeeded(); // 往master发送任务结果 sendTaskResult(); TaskExecutionContextCacheManager.removeByTaskInstanceId(taskExecutionContext.getTaskInstanceId()); logger.info("Remove the current task execute context from worker cache"); // 清理任务执行目录 clearTaskExecPathIfNeeded(); } 官网描述了很多流程图，如master、worker容错机制流程图、分布式锁实现流程图等，详见：https://dolphinscheduler.apache.org/zh-cn/docs/3.1.9/contribute/architecture-design 与 https://dolphinscheduler.apache.org/zh-cn/docs/3.1.9/architecture/design
本文补充任务派发与任务停止流程图，且只描述正常的实例启动、停止流程，不包含实例容错恢复场景，不包含相关锁以及并发场景。
以上是笔者对 Apache DolphinScheduler 3.1.9 版本特性与架构的初步理解，基于个人学习与实践整理而成。由于水平有限，文中难免存在理解偏差或疏漏之处，恳请各位读者不吝指正。如有不同见解，欢迎交流讨论，共同进步。
如果你对 Apache DolphinScheduler 的源码有兴趣，可以深入研究其任务调度策略的细节部分，或者根据自身业务场景进行二次开发，充分发挥 DolphinScheduler 的调度能力。
