本文主要是介绍源码- Spark中Worker源码分析（二），希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！
继续前一篇的内容。前一篇内容为：
Spark中Worker源码分析（一）http://www.cnblogs.com/yourarebest/p/5300202.html
4.receive方法，
receive方法主要分为以下14种情况：
（1）worker向master注册成功后，详见代码
（2）worker向master发送心跳消息，如果还没有注册到master上，该消息将被忽略，详见代码
（3）worker的工作空间的清理，详见代码
（4）更换master，详见代码
（5）worker注册失败，详见代码
（6）再次连接worker，详见代码
（7）创建executor，详见代码
（8）executor的转态发生改变时，详见代码
（9）kill executor，详见代码
（10）创建driver，详见代码
（11）kill driver，详见代码
（12）driver的状态发生变化时，详见代码
（13）将worker注册到master上，详见代码
（14）app执行完毕，详见代码
worker与master相关的交互为（1）（2）（4）（6）（13）
worker与driver相关的交互为（10）（11）（12）
worker与executor相关的交互为（3）（7）（8）（9）（14），需要说明的是（3）（14）它们的完成都与executor有着密切的联系。
<code>
override def receive: PartialFunction[Any, Unit] = {
//(1)注册成功的Woker
case RegisteredWorker(masterRef, masterWebUiUrl) =>
logInfo("Successfully registered with master " + masterRef.address.toSparkURL)
registered = true
changeMaster(masterRef, masterWebUiUrl)
//守护线程15s发送一次心跳消息
forwordMessageScheduler.scheduleAtFixedRate(new Runnable {
override def run(): Unit = Utils.tryLogNonFatalError {
self.send(SendHeartbeat)
}
}, 0, HEARTBEAT_MILLIS, TimeUnit.MILLISECONDS)
//如果允许清理
if (CLEANUP_ENABLED) {
logInfo(s"Worker cleanup enabled; old application directories will be deleted in: $workDir")
forwordMessageScheduler.scheduleAtFixedRate(new Runnable {
override def run(): Unit = Utils.tryLogNonFatalError {
//守护线程30min清理app文件夹
self.send(WorkDirCleanup)
}
}, CLEANUP_INTERVAL_MILLIS, CLEANUP_INTERVAL_MILLIS, TimeUnit.MILLISECONDS)
}
//（2）worker向master发送心跳消息，如果还没有注册到master上，该消息将被忽略
case SendHeartbeat =>
if (connected) { sendToMaster(Heartbeat(workerId, self)) }
//（3）worker的工作空间的清理
case WorkDirCleanup =>
//为了加快独立将来独立线程的清理工作，不要占用worker rpcEndpoint的端口号，拷贝ids所以它可以被清理线程使用
val appIds = executors.values.map(_.appId).toSet
val cleanupFuture = concurrent.future {
val appDirs = workDir.listFiles()
if (appDirs == null) {
throw new IOException("ERROR: Failed to list files in " + appDirs)
}
appDirs.filter { dir =>
//目录正在被app使用-当清理时检查app是否在运行
val appIdFromDir = dir.getName
val isAppStillRunning = appIds.contains(appIdFromDir)
dir.isDirectory && !isAppStillRunning &&
!Utils.doesDirectoryContainAnyNewFiles(dir, APP_DATA_RETENTION_SECONDS)
}.foreach { dir =>
logInfo(s"Removing directory: ${dir.getPath}")
Utils.deleteRecursively(dir)
}
}(cleanupThreadExecutor)
cleanupFuture.onFailure {
case e: Throwable =>
logError("App dir cleanup failed: " + e.getMessage, e)
}(cleanupThreadExecutor)
//（4）更换master
case MasterChanged(masterRef, masterWebUiUrl) =>
logInfo("Master has changed, new master is at " + masterRef.address.toSparkURL)
changeMaster(masterRef, masterWebUiUrl)
val execs = executors.values.
map(e => new ExecutorDescription(e.appId, e.execId, e.cores, e.state))
masterRef.send(WorkerSchedulerStateResponse(workerId, execs.toList, drivers.keys.toSeq))
//（5）worker注册失败
case RegisterWorkerFailed(message) =>
if (!registered) {
logError("Worker registration failed: " + message)
System.exit(1)
}
//（6）再次连接Worker
case ReconnectWorker(masterUrl) =>
logInfo(s"Master with url $masterUrl requested this worker to reconnect.")
//再次将worker注册到masters上
registerWithMaster()
//（7）创建Executor
case LaunchExecutor(masterUrl, appId, execId, appDesc, cores_, memory_) =>if (masterUrl != activeMasterUrl) {
logWarning("Invalid Master (" + masterUrl + ") attempted to launch executor.")
} else {
try {
logInfo("Asked to launch executor %s/%d for %s".format(appId, execId, appDesc.name))
//创建executor的工作目录
val executorDir = new File(workDir, appId + "/" + execId)
if (!executorDir.mkdirs()) {
throw new IOException("Failed to create directory " + executorDir)
}
//为executors创建本地目录，通过SPARK_EXECUTOR_DIRS环境变量设置，当app执行完后并删除
val appLocalDirs = appDirectories.get(appId).getOrElse {
Utils.getOrCreateLocalRootDirs(conf).map { dir =>
val appDir = Utils.createDirectory(dir, namePrefix = "executor")
Utils.chmod700(appDir)
appDir.getAbsolutePath()
}.toSeq
}
appDirectories(appId) = appLocalDirs
val manager = new ExecutorRunner(
appId,
execId,
appDesc.copy(command = Worker.maybeUpdateSSLSettings(appDesc.command, conf)),
cores_,
memory_,
self,
workerId,
host,
webUi.boundPort,
publicAddress,
sparkHome,
executorDir,
workerUri,
conf,
appLocalDirs, ExecutorState.LOADING)
executors(appId + "/" + execId) = manager
manager.start()
coresUsed += cores_
memoryUsed += memory_
sendToMaster(ExecutorStateChanged(appId, execId, manager.state, None, None))
} catch {
case e: Exception => {
logError(s"Failed to launch executor $appId/$execId for ${appDesc.name}.", e)
if (executors.contains(appId + "/" + execId)) {
executors(appId + "/" + execId).kill()
executors -= appId + "/" + execId
}
sendToMaster(ExecutorStateChanged(appId, execId, ExecutorState.FAILED,
Some(e.toString), None))
}
}
}
//（8）executor的转态发生改变时
case executorStateChanged @ ExecutorStateChanged(appId, execId, state, message, exitStatus) =>
handleExecutorStateChanged(executorStateChanged)
//（9）kill executor
case KillExecutor(masterUrl, appId, execId) =>
if (masterUrl != activeMasterUrl) {
logWarning("Invalid Master (" + masterUrl + ") attempted to launch executor " + execId)
} else {
val fullId = appId + "/" + execId
executors.get(fullId) match {
case Some(executor) =>
logInfo("Asked to kill executor " + fullId)
executor.kill()
case None =>
logInfo("Asked to kill unknown executor " + fullId)
}
}
//（10）创建Driver
case LaunchDriver(driverId, driverDesc) => {
logInfo(s"Asked to launch driver $driverId")
val driver = new DriverRunner(
conf,
driverId,
workDir,
sparkHome,
driverDesc.copy(command = Worker.maybeUpdateSSLSettings(driverDesc.command, conf)),
self,
workerUri,
securityMgr)
drivers(driverId) = driver
driver.start(
coresUsed += driverDesc.cores
memoryUsed += driverDesc.mem
}
//（11）kill Driver
case KillDriver(driverId) => {
logInfo(s"Asked to kill driver $driverId")
drivers.get(driverId) match {
case Some(runner) =>
runner.kill()
case None =>
logError(s"Asked to kill unknown driver $driverId")
}
}
//（12）driver的状态发生变化时
case driverStateChanged @ DriverStateChanged(driverId, state, exception) => {
handleDriverStateChanged(driverStateChanged)
}
//（13）将worker注册到master上
case ReregisterWithMaster =>
reregisterWithMaster()
//（14）app执行完毕
case ApplicationFinished(id) =>
finishedApps += id
//删除执行完的app在执行过程中创建的本地文件
maybeCleanupApplication(id)
}
</code>
这篇关于源码- Spark中Worker源码分析（二）的文章就介绍到这儿，希望我们推荐的文章对编程师们有所帮助！
