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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.spark.deploy.worker
import java.io.File
import java.io.IOException
import java.text.SimpleDateFormat
import java.util.{UUID, Date}
import scala.collection.JavaConversions._
import scala.collection.mutable.{HashMap, HashSet}
import scala.concurrent.duration._
import scala.language.postfixOps
import scala.util.Random
import akka.actor._
import akka.remote.{DisassociatedEvent, RemotingLifecycleEvent}
import org.apache.spark.{Logging, SecurityManager, SparkConf}
import org.apache.spark.deploy.{Command, ExecutorDescription, ExecutorState}
import org.apache.spark.deploy.DeployMessages._
import org.apache.spark.deploy.master.{DriverState, Master}
import org.apache.spark.deploy.worker.ui.WorkerWebUI
import org.apache.spark.metrics.MetricsSystem
import org.apache.spark.util.{ActorLogReceive, AkkaUtils, SignalLogger, Utils}
/**
* @param masterAkkaUrls Each url should be a valid akka url.
*/
private[worker] 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 with ActorLogReceive with Logging {
import context.dispatcher
Utils.checkHost(host, "Expected hostname")
assert (port > 0)
// For worker and executor IDs
private def createDateFormat = new SimpleDateFormat("yyyyMMddHHmmss")
// Send a heartbeat every (heartbeat timeout) / 4 milliseconds
private val HEARTBEAT_MILLIS = conf.getLong("spark.worker.timeout", 60) * 1000 / 4
// Model retries to connect to the master, after Hadoop's model.
// The first six attempts to reconnect are in shorter intervals (between 5 and 15 seconds)
// Afterwards, the next 10 attempts are between 30 and 90 seconds.
// A bit of randomness is introduced so that not all of the workers attempt to reconnect at
// the same time.
private val INITIAL_REGISTRATION_RETRIES = 6
private val TOTAL_REGISTRATION_RETRIES = INITIAL_REGISTRATION_RETRIES + 10
private val FUZZ_MULTIPLIER_INTERVAL_LOWER_BOUND = 0.500
private val REGISTRATION_RETRY_FUZZ_MULTIPLIER = {
val randomNumberGenerator = new Random(UUID.randomUUID.getMostSignificantBits)
randomNumberGenerator.nextDouble + FUZZ_MULTIPLIER_INTERVAL_LOWER_BOUND
}
private val INITIAL_REGISTRATION_RETRY_INTERVAL = (math.round(10 *
REGISTRATION_RETRY_FUZZ_MULTIPLIER)).seconds
private val PROLONGED_REGISTRATION_RETRY_INTERVAL = (math.round(60
* REGISTRATION_RETRY_FUZZ_MULTIPLIER)).seconds
private val CLEANUP_ENABLED = conf.getBoolean("spark.worker.cleanup.enabled", false)
// How often worker will clean up old app folders
private val CLEANUP_INTERVAL_MILLIS =
conf.getLong("spark.worker.cleanup.interval", 60 * 30) * 1000
// TTL for app folders/data; after TTL expires it will be cleaned up
private val APP_DATA_RETENTION_SECS =
conf.getLong("spark.worker.cleanup.appDataTtl", 7 * 24 * 3600)
private val testing: Boolean = sys.props.contains("spark.testing")
private var master: ActorSelection = null
private var masterAddress: Address = null
private var activeMasterUrl: String = ""
private[worker] var activeMasterWebUiUrl : String = ""
private val akkaUrl = AkkaUtils.address(
AkkaUtils.protocol(context.system),
actorSystemName,
host,
port,
actorName)
@volatile private var registered = false
@volatile private var connected = false
private val workerId = generateWorkerId()
private val sparkHome =
if (testing) {
assert(sys.props.contains("spark.test.home"), "spark.test.home is not set!")
new File(sys.props("spark.test.home"))
} else {
new File(sys.env.get("SPARK_HOME").getOrElse("."))
}
var workDir: File = null
val finishedExecutors = new HashMap[String, ExecutorRunner]
val drivers = new HashMap[String, DriverRunner]
val executors = new HashMap[String, ExecutorRunner]
val finishedDrivers = new HashMap[String, DriverRunner]
val appDirectories = new HashMap[String, Seq[String]]
val finishedApps = new HashSet[String]
// The shuffle service is not actually started unless configured.
private val shuffleService = new StandaloneWorkerShuffleService(conf, securityMgr)
private val publicAddress = {
val envVar = conf.getenv("SPARK_PUBLIC_DNS")
if (envVar != null) envVar else host
}
private var webUi: WorkerWebUI = null
private var connectionAttemptCount = 0
private val metricsSystem = MetricsSystem.createMetricsSystem("worker", conf, securityMgr)
private val workerSource = new WorkerSource(this)
private var registrationRetryTimer: Option[Cancellable] = None
var coresUsed = 0
var memoryUsed = 0
def coresFree: Int = cores - coresUsed
def memoryFree: Int = memory - memoryUsed
private def createWorkDir() {
workDir = Option(workDirPath).map(new File(_)).getOrElse(new File(sparkHome, "work"))
try {
// This sporadically fails - not sure why ... !workDir.exists() && !workDir.mkdirs()
// So attempting to create and then check if directory was created or not.
workDir.mkdirs()
if ( !workDir.exists() || !workDir.isDirectory) {
logError("Failed to create work directory " + workDir)
System.exit(1)
}
assert (workDir.isDirectory)
} catch {
case e: Exception =>
logError("Failed to create work directory " + workDir, e)
System.exit(1)
}
}
override def preStart() {
assert(!registered)
logInfo("Starting Spark worker %s:%d with %d cores, %s RAM".format(
host, port, cores, Utils.megabytesToString(memory)))
logInfo(s"Running Spark version ${org.apache.spark.SPARK_VERSION}")
logInfo("Spark home: " + sparkHome)
createWorkDir()
context.system.eventStream.subscribe(self, classOf[RemotingLifecycleEvent])
shuffleService.startIfEnabled()
webUi = new WorkerWebUI(this, workDir, webUiPort)
webUi.bind()
registerWithMaster()
metricsSystem.registerSource(workerSource)
metricsSystem.start()
// Attach the worker metrics servlet handler to the web ui after the metrics system is started.
metricsSystem.getServletHandlers.foreach(webUi.attachHandler)
}
private def changeMaster(url: String, uiUrl: String) {
// activeMasterUrl it's a valid Spark url since we receive it from master.
activeMasterUrl = url
activeMasterWebUiUrl = uiUrl
master = context.actorSelection(
Master.toAkkaUrl(activeMasterUrl, AkkaUtils.protocol(context.system)))
masterAddress = Master.toAkkaAddress(activeMasterUrl, AkkaUtils.protocol(context.system))
connected = true
// Cancel any outstanding re-registration attempts because we found a new master
registrationRetryTimer.foreach(_.cancel())
registrationRetryTimer = None
}
private def tryRegisterAllMasters() {
for (masterAkkaUrl <- masterAkkaUrls) {
logInfo("Connecting to master " + masterAkkaUrl + "...")
val actor = context.actorSelection(masterAkkaUrl)
actor ! RegisterWorker(workerId, host, port, cores, memory, webUi.boundPort, publicAddress)
}
}
/**
* Re-register with the master because a network failure or a master failure has occurred.
* If the re-registration attempt threshold is exceeded, the worker exits with error.
* Note that for thread-safety this should only be called from the actor.
*/
private def reregisterWithMaster(): Unit = {
Utils.tryOrExit {
connectionAttemptCount += 1
if (registered) {
registrationRetryTimer.foreach(_.cancel())
registrationRetryTimer = None
} else if (connectionAttemptCount <= TOTAL_REGISTRATION_RETRIES) {
logInfo(s"Retrying connection to master (attempt # $connectionAttemptCount)")
/**
* Re-register with the active master this worker has been communicating with. If there
* is none, then it means this worker is still bootstrapping and hasn't established a
* connection with a master yet, in which case we should re-register with all masters.
*
* It is important to re-register only with the active master during failures. Otherwise,
* if the worker unconditionally attempts to re-register with all masters, the following
* race condition may arise and cause a "duplicate worker" error detailed in SPARK-4592:
*
* (1) Master A fails and Worker attempts to reconnect to all masters
* (2) Master B takes over and notifies Worker
* (3) Worker responds by registering with Master B
* (4) Meanwhile, Worker's previous reconnection attempt reaches Master B,
* causing the same Worker to register with Master B twice
*
* Instead, if we only register with the known active master, we can assume that the
* old master must have died because another master has taken over. Note that this is
* still not safe if the old master recovers within this interval, but this is a much
* less likely scenario.
*/
if (master != null) {
master ! RegisterWorker(
workerId, host, port, cores, memory, webUi.boundPort, publicAddress)
} else {
// We are retrying the initial registration
tryRegisterAllMasters()
}
// We have exceeded the initial registration retry threshold
// All retries from now on should use a higher interval
if (connectionAttemptCount == INITIAL_REGISTRATION_RETRIES) {
registrationRetryTimer.foreach(_.cancel())
registrationRetryTimer = Some {
context.system.scheduler.schedule(PROLONGED_REGISTRATION_RETRY_INTERVAL,
PROLONGED_REGISTRATION_RETRY_INTERVAL, self, ReregisterWithMaster)
}
}
} else {
logError("All masters are unresponsive! Giving up.")
System.exit(1)
}
}
}
private def registerWithMaster() {
// DisassociatedEvent may be triggered multiple times, so don't attempt registration
// if there are outstanding registration attempts scheduled.
registrationRetryTimer match {
case None =>
registered = false
tryRegisterAllMasters()
connectionAttemptCount = 0
registrationRetryTimer = Some {
context.system.scheduler.schedule(INITIAL_REGISTRATION_RETRY_INTERVAL,
INITIAL_REGISTRATION_RETRY_INTERVAL, self, ReregisterWithMaster)
}
case Some(_) =>
logInfo("Not spawning another attempt to register with the master, since there is an" +
" attempt scheduled already.")
}
}
override def receiveWithLogging: PartialFunction[Any, Unit] = {
case RegisteredWorker(masterUrl, masterWebUiUrl) =>
logInfo("Successfully registered with master " + masterUrl)
registered = true
changeMaster(masterUrl, masterWebUiUrl)
context.system.scheduler.schedule(0 millis, HEARTBEAT_MILLIS millis, self, SendHeartbeat)
if (CLEANUP_ENABLED) {
logInfo(s"Worker cleanup enabled; old application directories will be deleted in: $workDir")
context.system.scheduler.schedule(CLEANUP_INTERVAL_MILLIS millis,
CLEANUP_INTERVAL_MILLIS millis, self, WorkDirCleanup)
}
case SendHeartbeat =>
if (connected) { master ! Heartbeat(workerId) }
case WorkDirCleanup =>
// Spin up a separate thread (in a future) to do the dir cleanup; don't tie up worker actor
val cleanupFuture = concurrent.future {
val appDirs = workDir.listFiles()
if (appDirs == null) {
throw new IOException("ERROR: Failed to list files in " + appDirs)
}
appDirs.filter { dir =>
// the directory is used by an application - check that the application is not running
// when cleaning up
val appIdFromDir = dir.getName
val isAppStillRunning = executors.values.map(_.appId).contains(appIdFromDir)
dir.isDirectory && !isAppStillRunning &&
!Utils.doesDirectoryContainAnyNewFiles(dir, APP_DATA_RETENTION_SECS)
}.foreach { dir =>
logInfo(s"Removing directory: ${dir.getPath}")
Utils.deleteRecursively(dir)
}
}
cleanupFuture onFailure {
case e: Throwable =>
logError("App dir cleanup failed: " + e.getMessage, e)
}
case MasterChanged(masterUrl, masterWebUiUrl) =>
logInfo("Master has changed, new master is at " + masterUrl)
changeMaster(masterUrl, masterWebUiUrl)
val execs = executors.values.
map(e => new ExecutorDescription(e.appId, e.execId, e.cores, e.state))
sender ! WorkerSchedulerStateResponse(workerId, execs.toList, drivers.keys.toSeq)
case Heartbeat =>
logInfo(s"Received heartbeat from driver ${sender.path}")
case RegisterWorkerFailed(message) =>
if (!registered) {
logError("Worker registration failed: " + message)
System.exit(1)
}
case ReconnectWorker(masterUrl) =>
logInfo(s"Master with url $masterUrl requested this worker to reconnect.")
registerWithMaster()
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))
// Create the executor's working directory
val executorDir = new File(workDir, appId + "/" + execId)
if (!executorDir.mkdirs()) {
throw new IOException("Failed to create directory " + executorDir)
}
// Create local dirs for the executor. These are passed to the executor via the
// SPARK_EXECUTOR_DIRS environment variable, and deleted by the Worker when the
// application finishes.
val appLocalDirs = appDirectories.get(appId).getOrElse {
Utils.getOrCreateLocalRootDirs(conf).map { dir =>
Utils.createDirectory(dir, namePrefix = "executor").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,
akkaUrl,
conf,
appLocalDirs, ExecutorState.LOADING)
executors(appId + "/" + execId) = manager
manager.start()
coresUsed += cores_
memoryUsed += memory_
master ! 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
}
master ! ExecutorStateChanged(appId, execId, ExecutorState.FAILED,
Some(e.toString), None)
}
}
}
case ExecutorStateChanged(appId, execId, state, message, exitStatus) =>
master ! ExecutorStateChanged(appId, execId, state, message, exitStatus)
val fullId = appId + "/" + execId
if (ExecutorState.isFinished(state)) {
executors.get(fullId) match {
case Some(executor) =>
logInfo("Executor " + fullId + " finished with state " + state +
message.map(" message " + _).getOrElse("") +
exitStatus.map(" exitStatus " + _).getOrElse(""))
executors -= fullId
finishedExecutors(fullId) = executor
coresUsed -= executor.cores
memoryUsed -= executor.memory
case None =>
logInfo("Unknown Executor " + fullId + " finished with state " + state +
message.map(" message " + _).getOrElse("") +
exitStatus.map(" exitStatus " + _).getOrElse(""))
}
maybeCleanupApplication(appId)
}
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)
}
}
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,
akkaUrl)
drivers(driverId) = driver
driver.start()
coresUsed += driverDesc.cores
memoryUsed += driverDesc.mem
}
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")
}
}
case DriverStateChanged(driverId, state, exception) => {
state match {
case DriverState.ERROR =>
logWarning(s"Driver $driverId failed with unrecoverable exception: ${exception.get}")
case DriverState.FAILED =>
logWarning(s"Driver $driverId exited with failure")
case DriverState.FINISHED =>
logInfo(s"Driver $driverId exited successfully")
case DriverState.KILLED =>
logInfo(s"Driver $driverId was killed by user")
case _ =>
logDebug(s"Driver $driverId changed state to $state")
}
master ! DriverStateChanged(driverId, state, exception)
val driver = drivers.remove(driverId).get
finishedDrivers(driverId) = driver
memoryUsed -= driver.driverDesc.mem
coresUsed -= driver.driverDesc.cores
}
case x: DisassociatedEvent if x.remoteAddress == masterAddress =>
logInfo(s"$x Disassociated !")
masterDisconnected()
case RequestWorkerState =>
sender ! WorkerStateResponse(host, port, workerId, executors.values.toList,
finishedExecutors.values.toList, drivers.values.toList,
finishedDrivers.values.toList, activeMasterUrl, cores, memory,
coresUsed, memoryUsed, activeMasterWebUiUrl)
case ReregisterWithMaster =>
reregisterWithMaster()
case ApplicationFinished(id) =>
finishedApps += id
maybeCleanupApplication(id)
}
private def masterDisconnected() {
logError("Connection to master failed! Waiting for master to reconnect...")
connected = false
registerWithMaster()
}
private def maybeCleanupApplication(id: String): Unit = {
val shouldCleanup = finishedApps.contains(id) && !executors.values.exists(_.appId == id)
if (shouldCleanup) {
finishedApps -= id
appDirectories.remove(id).foreach { dirList =>
logInfo(s"Cleaning up local directories for application $id")
dirList.foreach { dir =>
Utils.deleteRecursively(new File(dir))
}
}
}
}
private def generateWorkerId(): String = {
"worker-%s-%s-%d".format(createDateFormat.format(new Date), host, port)
}
override def postStop() {
metricsSystem.report()
registrationRetryTimer.foreach(_.cancel())
executors.values.foreach(_.kill())
drivers.values.foreach(_.kill())
shuffleService.stop()
webUi.stop()
metricsSystem.stop()
}
}
private[deploy] object Worker extends Logging {
def main(argStrings: Array[String]) {
SignalLogger.register(log)
val conf = new SparkConf
val args = new WorkerArguments(argStrings, conf)
val (actorSystem, _) = startSystemAndActor(args.host, args.port, args.webUiPort, args.cores,
args.memory, args.masters, args.workDir)
actorSystem.awaitTermination()
}
def startSystemAndActor(
host: String,
port: Int,
webUiPort: Int,
cores: Int,
memory: Int,
masterUrls: Array[String],
workDir: String,
workerNumber: Option[Int] = None,
conf: SparkConf = new SparkConf): (ActorSystem, Int) = {
// The LocalSparkCluster runs multiple local sparkWorkerX actor systems
val systemName = "sparkWorker" + workerNumber.map(_.toString).getOrElse("")
val actorName = "Worker"
val securityMgr = new SecurityManager(conf)
val (actorSystem, boundPort) = AkkaUtils.createActorSystem(systemName, host, port,
conf = conf, securityManager = securityMgr)
val masterAkkaUrls = masterUrls.map(Master.toAkkaUrl(_, AkkaUtils.protocol(actorSystem)))
actorSystem.actorOf(Props(classOf[Worker], host, boundPort, webUiPort, cores, memory,
masterAkkaUrls, systemName, actorName, workDir, conf, securityMgr), name = actorName)
(actorSystem, boundPort)
}
def isUseLocalNodeSSLConfig(cmd: Command): Boolean = {
val pattern = """\-Dspark\.ssl\.useNodeLocalConf\=(.+)""".r
val result = cmd.javaOpts.collectFirst {
case pattern(_result) => _result.toBoolean
}
result.getOrElse(false)
}
def maybeUpdateSSLSettings(cmd: Command, conf: SparkConf): Command = {
val prefix = "spark.ssl."
val useNLC = "spark.ssl.useNodeLocalConf"
if (isUseLocalNodeSSLConfig(cmd)) {
val newJavaOpts = cmd.javaOpts
.filter(opt => !opt.startsWith(s"-D$prefix")) ++
conf.getAll.collect { case (key, value) if key.startsWith(prefix) => s"-D$key=$value" } :+
s"-D$useNLC=true"
cmd.copy(javaOpts = newJavaOpts)
} else {
cmd
}
}
}
|