Spark-源码-Spark-StartAll Master Worler启动流程

Posted 2021-01-20 chinashenkai

Spark start-all>>



"""Master启动流程"""


Master类
class Master(
    host: String,
    port: Int,
    webUiPort: Int,
    val securityMgr: SecurityManager,
    val conf: SparkConf) extends Actor with ActorLogReceive with Logging with LeaderElectable







Master端
def main(){
	val (actorSystem, _, _, _) = startSystemAndActor(args.host, args.port, args.webUiPort, conf)
    actorSystem.awaitTermination()
}

Master端
def startSystemAndActor(System, Int, Int, Option[Int]) = {
	//调用AkkaUtils创建ActorSystem
	val (actorSystem, boundPort) = AkkaUtils.createActorSystem(systemName, host, port, conf = conf,
	  securityManager = securityMgr)
	//创建属于Master的actor, 在创建actor的同时, 会使用classOf[Master]初始化Master
	val actor = actorSystem.actorOf(Props(classOf[Master], host, boundPort, webUiPort, securityMgr, conf), actorName)
}

Master端
"""初始化Master时由于Master继承了 trait Actor 重写了preStart方法, 
Actor的初始化会启动preStart方法 因此找到Master的 override def preStart()
preStart属于生命周期方法, 在构造器之后, receiver之前"""
override def preStart() {
	// 启动一个定时器, 定时检查超时的Worker, WORKER_TIMEOUT:每六十秒检查一次, 
	// self:先对着自己来一下(检查)试试
	context.system.scheduler.schedule(0 millis, WORKER_TIMEOUT millis, self, CheckForWorkerTimeOut)
 	// 调用 timeOutDeadWorkers() 方法,
 	override def receiveWithLogging = { 
	 	case CheckForWorkerTimeOut => {
	      timeOutDeadWorkers()
	    }
	}

	// 用来检查并移除所有超时的workers
	def timeOutDeadWorkers(){
		// 事实上是移除了一个存有WorkInfo的HashSet[WrokInfo]中的对象
		val toRemove = workers.filter(_.lastHeartbeat < currentTime - WORKER_TIMEOUT_MS).toArray
		for (worker <- toRemove) {
	      if (worker.state != WorkerState.DEAD) {
	        removeWorker(worker)
	      }
	    }
	}

	def removeWorker(worker: WorkerInfo){
		// 删除内存里的workInfo
		idToWorker -= worker.id
	    addressToWorker -= worker.endpoint.address
	}
}
    
"""之后执行receive方法(1.3版本), 在后来的1.6版本中叫 def receive: PartialFunction[Any, Unit]"""
Master端
override def receiveWithLogging () {}
会不断的接收actor发送过来的请求




"""Worker启动流程"""

Worker类
class Worker(
    host: String,
    port: Int,
    webUiPort: Int,
    cores: Int,
    memory: Int,
    masterAkkaUrls: Array[String],
    actorSystemName: String,
    actorName: String,
    workDirPath: String = null,
    val conf: SparkConf,
    val securityMgr: SecurityManager)
  extends Actor

def preStart() => {
  registerWithMaster()
}

// 向Master注册的方法
def registerWithMaster() {
  	// 向所有的Master注册Worker
  	tryRegisterAllMasters()
  	
  	// 其中内容
  	def tryRegisterAllMasters()=>{
	  	// 通过Master的Url获取Master的actor
		val actor = context.actorSelection(masterAkkaUrl)
		// 向Master发送注册信息
	    actor ! RegisterWorker(workerId, host, port, cores, memory, webUi.boundPort, publicAddress)
	}	
 }

Master端
// 接收Worker发送的注册信息
override def receiveWithLogging = {
	case RegisterWorker(id, workerHost, workerPort, cores, memory, workerUiPort, publicAddress) =>{
		// 判断是否是StandBy状态, doNothing
		idToWorker.contains(id), 已经注册过, doNothing
		
		正常情况下(Active状态, 且没有注册过):{
			// 把发送来的 WorkerInfo 添加到 Master的 WorkerInfo中
			val worker = new WorkerInfo(id, workerHost, workerPort, cores, memory, sender, workerUiPort, publicAddress)
		}
		// 如果将Worker Info存入内存成功, 则调用持久化引擎, 将信息存入磁盘中, 
		// 目的是防止数据丢失. 如果Master宕机, 内存中会丢失数据, 
		// 切换状态(Standby和Active)后, 需要切换的节点拿不到WorkerInfo, Worker会再次注册, 非常消耗资源, 存在磁盘则可以直接去磁盘拿取数据不需要重新注册
		if (registerWorker(worker)) {
	      persistenceEngine.addWorker(worker)
	      sender ! RegisteredWorker(masterUrl, masterWebUiUrl)
	      schedule()
	    }

		// 向worker响应注册成功信息
		sender ! RegisteredWorker(masterUrl, masterWebUiUrl)
		// 开始调度资源, 调度资源不仅仅是集群启动的时候调动资源, 运行Job的时候也会调度资源, 其有两种方式 一种是尽量分散, 一种是尽量集中
		schedule()
	}
}

Worker端
// 接收注册成功的信息, 其实是将 Active Master 的Url和rWebUiUrl传回并更新, 之后向他发送心跳~
def receiveWithLogging() = {
	case RegisteredWorker(masterUrl, masterWebUiUrl) =>{
		//更新MasterUrl
		changeMaster(masterUrl, masterWebUiUrl)
		//向Master发送心跳信息, HEARTBEAT_MILLIS =15秒, 每十五秒发送一次心跳信息, 发送逻辑为 SendHeartbeat
  		context.system.scheduler.schedule(0 millis, HEARTBEAT_MILLIS millis, self, SendHeartbeat)
	}

  	//向Master发送心跳信息, 实际上是将自己的WorkerId发送给Master
  	case SendHeartbeat =>
    	if (connected) { master ! Heartbeat(workerId) }
}

Master端 
def receiveWithLogging() = {
	case Heartbeat(workerId) => {
		//正常情况下, 更新上次心跳时间
		workerInfo.lastHeartbeat = System.currentTimeMillis()
		//启动完成
	}
}