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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.executor
import java.nio.ByteBuffer
import akka.actor._
import akka.remote._
import org.apache.spark.{Logging, SparkConf}
import org.apache.spark.TaskState.TaskState
import org.apache.spark.deploy.worker.WorkerWatcher
import org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages._
import org.apache.spark.util.{AkkaUtils, Utils}
private[spark] class CoarseGrainedExecutorBackend(
driverUrl: String,
executorId: String,
hostPort: String,
cores: Int)
extends Actor
with ExecutorBackend
with Logging {
Utils.checkHostPort(hostPort, "Expected hostport")
var executor: Executor = null
var driver: ActorSelection = null
override def preStart() {
logInfo("Connecting to driver: " + driverUrl)
driver = context.actorSelection(driverUrl)
driver ! RegisterExecutor(executorId, hostPort, cores)
context.system.eventStream.subscribe(self, classOf[RemotingLifecycleEvent])
}
override def receive = {
case RegisteredExecutor(sparkProperties) =>
logInfo("Successfully registered with driver")
// Make this host instead of hostPort ?
executor = new Executor(executorId, Utils.parseHostPort(hostPort)._1, sparkProperties)
case RegisterExecutorFailed(message) =>
logError("Slave registration failed: " + message)
System.exit(1)
case LaunchTask(taskDesc) =>
logInfo("Got assigned task " + taskDesc.taskId)
if (executor == null) {
logError("Received LaunchTask command but executor was null")
System.exit(1)
} else {
executor.launchTask(this, taskDesc.taskId, taskDesc.serializedTask)
}
case KillTask(taskId, _) =>
if (executor == null) {
logError("Received KillTask command but executor was null")
System.exit(1)
} else {
executor.killTask(taskId)
}
case x: DisassociatedEvent =>
logError(s"Driver $x disassociated! Shutting down.")
System.exit(1)
case StopExecutor =>
logInfo("Driver commanded a shutdown")
context.stop(self)
context.system.shutdown()
}
override def statusUpdate(taskId: Long, state: TaskState, data: ByteBuffer) {
driver ! StatusUpdate(executorId, taskId, state, data)
}
}
private[spark] object CoarseGrainedExecutorBackend {
def run(driverUrl: String, executorId: String, hostname: String, cores: Int,
workerUrl: Option[String]) {
// Debug code
Utils.checkHost(hostname)
// Create a new ActorSystem to run the backend, because we can't create a SparkEnv / Executor
// before getting started with all our system properties, etc
val (actorSystem, boundPort) = AkkaUtils.createActorSystem("sparkExecutor", hostname, 0,
indestructible = true, conf = new SparkConf)
// set it
val sparkHostPort = hostname + ":" + boundPort
actorSystem.actorOf(
Props(classOf[CoarseGrainedExecutorBackend], driverUrl, executorId, sparkHostPort, cores),
name = "Executor")
workerUrl.foreach{ url =>
actorSystem.actorOf(Props(classOf[WorkerWatcher], url), name = "WorkerWatcher")
}
actorSystem.awaitTermination()
}
def main(args: Array[String]) {
args.length match {
case x if x < 4 =>
System.err.println(
// Worker url is used in spark standalone mode to enforce fate-sharing with worker
"Usage: CoarseGrainedExecutorBackend <driverUrl> <executorId> <hostname> " +
"<cores> [<workerUrl>]")
System.exit(1)
case 4 =>
run(args(0), args(1), args(2), args(3).toInt, None)
case x if x > 4 =>
run(args(0), args(1), args(2), args(3).toInt, Some(args(4)))
}
}
}
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