原创-Spark源码分析五: Standalone模式下spar

Standalone模式下，spark-submit最后会通过执行org.apache.spark.deploy.ClientApp.start方法注册client rpc客户端，默认调用onStart方法，向Master注册Driver

override def onStart(): Unit = {
    driverArgs.cmd match {
      case "launch" =>
        // TODO: We could add an env variable here and intercept it in `sc.addJar` that would
        //       truncate filesystem paths similar to what YARN does. For now, we just require
        //       people call `addJar` assuming the jar is in the same directory.
        val mainClass = "org.apache.spark.deploy.worker.DriverWrapper"

        val classPathConf = "spark.driver.extraClassPath"
        val classPathEntries = getProperty(classPathConf, conf).toSeq.flatMap { cp =>
          cp.split(java.io.File.pathSeparator)
        }

        val libraryPathConf = "spark.driver.extraLibraryPath"
        val libraryPathEntries = getProperty(libraryPathConf, conf).toSeq.flatMap { cp =>
          cp.split(java.io.File.pathSeparator)
        }

        val extraJavaOptsConf = "spark.driver.extraJavaOptions"
        val extraJavaOpts = getProperty(extraJavaOptsConf, conf)
          .map(Utils.splitCommandString).getOrElse(Seq.empty)

        val sparkJavaOpts = Utils.sparkJavaOpts(conf)
        val javaOpts = sparkJavaOpts ++ extraJavaOpts
        val command = new Command(mainClass,
          Seq("{{WORKER_URL}}", "{{USER_JAR}}", driverArgs.mainClass) ++ driverArgs.driverOptions,
          sys.env, classPathEntries, libraryPathEntries, javaOpts)

        val driverDescription = new DriverDescription(
          driverArgs.jarUrl,
          driverArgs.memory,
          driverArgs.cores,
          driverArgs.supervise,
          command)
        asyncSendToMasterAndForwardReply[SubmitDriverResponse](
          RequestSubmitDriver(driverDescription))

      case "kill" =>
        val driverId = driverArgs.driverId
        asyncSendToMasterAndForwardReply[KillDriverResponse](RequestKillDriver(driverId))
    }
  }

在onstart方法中，执行asyncSendToMasterAndForwardReply方法

 /**
   * Send the message to master and forward the reply to self asynchronously.
   */
  private def asyncSendToMasterAndForwardReply[T: ClassTag](message: Any): Unit = {
    for (masterEndpoint <- masterEndpoints) {
      masterEndpoint.ask[T](message).onComplete {
        case Success(v) => self.send(v)
        case Failure(e) =>
          logWarning(s"Error sending messages to master $masterEndpoint", e)
      }(forwardMessageExecutionContext)
    }
  }

向master发送RequestSubmitDriver请求，Master节点receiveAndReply方法中处理RequestSubmitDriver请求

 override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = {
    case RequestSubmitDriver(description) =>
      if (state != RecoveryState.ALIVE) {
        val msg = s"${Utils.BACKUP_STANDALONE_MASTER_PREFIX}: $state. " +
          "Can only accept driver submissions in ALIVE state."
        context.reply(SubmitDriverResponse(self, false, None, msg))
      } else {
        logInfo("Driver submitted " + description.command.mainClass)
        val driver = createDriver(description)
        persistenceEngine.addDriver(driver)
        waitingDrivers += driver
        drivers.add(driver)
        schedule()

        // TODO: It might be good to instead have the submission client poll the master to determine
        //       the current status of the driver. For now it's simply "fire and forget".

        context.reply(SubmitDriverResponse(self, true, Some(driver.id),
          s"Driver successfully submitted as ${driver.id}"))
      }
}

主要执行流程：

• 判断当前master节点是否是alive
• zk中持久化driver信息
• 加入到待执行waitingDrivers集合中
• 调用schedule()方法开始执行driver

至此通过spark-submit提交任务主要流程结束,主要涉及流程图如下：