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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.yarn
import java.net.Socket
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.net.NetUtils
import org.apache.hadoop.yarn.api._
import org.apache.hadoop.yarn.api.records._
import org.apache.hadoop.yarn.api.protocolrecords._
import org.apache.hadoop.yarn.conf.YarnConfiguration
import org.apache.hadoop.yarn.util.{ConverterUtils, Records}
import akka.actor._
import akka.remote._
import akka.actor.Terminated
import org.apache.spark.{SparkConf, SparkContext, Logging}
import org.apache.spark.util.{Utils, AkkaUtils}
import org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend
import org.apache.spark.scheduler.SplitInfo
import org.apache.hadoop.yarn.client.api.AMRMClient
import org.apache.hadoop.yarn.client.api.AMRMClient.ContainerRequest
class WorkerLauncher(args: ApplicationMasterArguments, conf: Configuration, sparkConf: SparkConf)
extends Logging {
def this(args: ApplicationMasterArguments, sparkConf: SparkConf) =
this(args, new Configuration(), sparkConf)
def this(args: ApplicationMasterArguments) = this(args, new SparkConf())
private var appAttemptId: ApplicationAttemptId = _
private var reporterThread: Thread = _
private val yarnConf: YarnConfiguration = new YarnConfiguration(conf)
private var yarnAllocator: YarnAllocationHandler = _
private var driverClosed:Boolean = false
private var amClient: AMRMClient[ContainerRequest] = _
val actorSystem: ActorSystem = AkkaUtils.createActorSystem("sparkYarnAM", Utils.localHostName, 0,
conf = sparkConf)._1
var actor: ActorRef = _
// This actor just working as a monitor to watch on Driver Actor.
class MonitorActor(driverUrl: String) extends Actor {
var driver: ActorSelection = _
override def preStart() {
logInfo("Listen to driver: " + driverUrl)
driver = context.actorSelection(driverUrl)
// Send a hello message thus the connection is actually established, thus we can monitor Lifecycle Events.
driver ! "Hello"
context.system.eventStream.subscribe(self, classOf[RemotingLifecycleEvent])
}
override def receive = {
case x: DisassociatedEvent =>
logInfo(s"Driver terminated or disconnected! Shutting down. $x")
driverClosed = true
}
}
def run() {
amClient = AMRMClient.createAMRMClient()
amClient.init(yarnConf)
amClient.start()
appAttemptId = getApplicationAttemptId()
registerApplicationMaster()
waitForSparkMaster()
// Allocate all containers
allocateWorkers()
// Launch a progress reporter thread, else app will get killed after expiration (def: 10mins) timeout
// ensure that progress is sent before YarnConfiguration.RM_AM_EXPIRY_INTERVAL_MS elapse.
val timeoutInterval = yarnConf.getInt(YarnConfiguration.RM_AM_EXPIRY_INTERVAL_MS, 120000)
// must be <= timeoutInterval/ 2.
// On other hand, also ensure that we are reasonably responsive without causing too many requests to RM.
// so atleast 1 minute or timeoutInterval / 10 - whichever is higher.
val interval = math.min(timeoutInterval / 2, math.max(timeoutInterval / 10, 60000L))
reporterThread = launchReporterThread(interval)
// Wait for the reporter thread to Finish.
reporterThread.join()
finishApplicationMaster(FinalApplicationStatus.SUCCEEDED)
actorSystem.shutdown()
logInfo("Exited")
System.exit(0)
}
private def getApplicationAttemptId(): ApplicationAttemptId = {
val envs = System.getenv()
val containerIdString = envs.get(ApplicationConstants.Environment.CONTAINER_ID.name())
val containerId = ConverterUtils.toContainerId(containerIdString)
val appAttemptId = containerId.getApplicationAttemptId()
logInfo("ApplicationAttemptId: " + appAttemptId)
appAttemptId
}
private def registerApplicationMaster(): RegisterApplicationMasterResponse = {
logInfo("Registering the ApplicationMaster")
// TODO:(Raymond) Find out Spark UI address and fill in here?
amClient.registerApplicationMaster(Utils.localHostName(), 0, "")
}
private def waitForSparkMaster() {
logInfo("Waiting for Spark driver to be reachable.")
var driverUp = false
val hostport = args.userArgs(0)
val (driverHost, driverPort) = Utils.parseHostPort(hostport)
while(!driverUp) {
try {
val socket = new Socket(driverHost, driverPort)
socket.close()
logInfo("Driver now available: %s:%s".format(driverHost, driverPort))
driverUp = true
} catch {
case e: Exception =>
logError("Failed to connect to driver at %s:%s, retrying ...".
format(driverHost, driverPort))
Thread.sleep(100)
}
}
sparkConf.set("spark.driver.host", driverHost)
sparkConf.set("spark.driver.port", driverPort.toString)
val driverUrl = "akka.tcp://spark@%s:%s/user/%s".format(
driverHost, driverPort.toString, CoarseGrainedSchedulerBackend.ACTOR_NAME)
actor = actorSystem.actorOf(Props(new MonitorActor(driverUrl)), name = "YarnAM")
}
private def allocateWorkers() {
// Fixme: should get preferredNodeLocationData from SparkContext, just fake a empty one for now.
val preferredNodeLocationData: scala.collection.Map[String, scala.collection.Set[SplitInfo]] =
scala.collection.immutable.Map()
yarnAllocator = YarnAllocationHandler.newAllocator(
yarnConf,
amClient,
appAttemptId,
args,
preferredNodeLocationData,
sparkConf)
logInfo("Allocating " + args.numWorkers + " workers.")
// Wait until all containers have finished
// TODO: This is a bit ugly. Can we make it nicer?
// TODO: Handle container failure
yarnAllocator.addResourceRequests(args.numWorkers)
while (yarnAllocator.getNumWorkersRunning < args.numWorkers) {
yarnAllocator.allocateResources()
Thread.sleep(100)
}
logInfo("All workers have launched.")
}
// TODO: We might want to extend this to allocate more containers in case they die !
private def launchReporterThread(_sleepTime: Long): Thread = {
val sleepTime = if (_sleepTime <= 0) 0 else _sleepTime
val t = new Thread {
override def run() {
while (!driverClosed) {
val missingWorkerCount = args.numWorkers - yarnAllocator.getNumWorkersRunning -
yarnAllocator.getNumPendingAllocate
if (missingWorkerCount > 0) {
logInfo("Allocating %d containers to make up for (potentially) lost containers".
format(missingWorkerCount))
yarnAllocator.addResourceRequests(missingWorkerCount)
}
sendProgress()
Thread.sleep(sleepTime)
}
}
}
// setting to daemon status, though this is usually not a good idea.
t.setDaemon(true)
t.start()
logInfo("Started progress reporter thread - sleep time : " + sleepTime)
t
}
private def sendProgress() {
logDebug("Sending progress")
// simulated with an allocate request with no nodes requested ...
yarnAllocator.allocateResources()
}
def finishApplicationMaster(status: FinalApplicationStatus) {
logInfo("finish ApplicationMaster with " + status)
amClient.unregisterApplicationMaster(status, "" /* appMessage */ , "" /* appTrackingUrl */)
}
}
object WorkerLauncher {
def main(argStrings: Array[String]) {
val args = new ApplicationMasterArguments(argStrings)
new WorkerLauncher(args).run()
}
}
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