小记--------spark的Master主备切换机制原理分析及源码分析

Master类位置所在：spark-core_2.11-2.1.0.jar的org.apache.spark.deploy.master下的Master类

/**
*完成Master的主备切换，从字面意思来看，其实就是完成Master的恢复
/
private def completeRecovery() {
  // Ensure "only-once" recovery semantics using a short synchronization period.
  if (state != RecoveryState.RECOVERING) { return }
  state = RecoveryState.COMPLETING_RECOVERY
 
  //将Application和Worker，过滤出来目前状态还是UNKNOWN的
  //然后遍历，分别调用removeWorkers和finishApplication方法，对可能已经出现故障，或者甚至已经死掉的Application和Worker，进行清理
  // 清理的机制：1.从内存缓存结构中移除；2.从相关的组件的内存缓存中移除；3.从持久化存储中移除
  // Kill off any workers and apps that didn\'t respond to us.
  workers.filter(_.state == WorkerState.UNKNOWN).foreach(removeWorker)//清理worker的信息
  apps.filter(_.state == ApplicationState.UNKNOWN).foreach(finishApplication)//清理Application信息
 
  // 如果Driver为空的话，重新尝试启动Driver
  // Reschedule drivers which were not claimed by any workers
  drivers.filter(_.worker.isEmpty).foreach { d =>
    logWarning(s"Driver ${d.id} was not found after master recovery")
    if (d.desc.supervise) {
      logWarning(s"Re-launching ${d.id}")
      relaunchDriver(d)
    } else {
      removeDriver(d.id, DriverState.ERROR, None)
      logWarning(s"Did not re-launch ${d.id} because it was not supervised")
    }
  }
 
 
  state = RecoveryState.ALIVE
  schedule()    //资源组件发送改变时（Application、Worker）执行重新调度
  logInfo("Recovery complete - resuming operations!")
}