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package spark.executor
import java.nio.ByteBuffer
import spark.Logging
import spark.TaskState.TaskState
import spark.util.AkkaUtils
import akka.actor.{ActorRef, Actor, Props}
import java.util.concurrent.{TimeUnit, ThreadPoolExecutor, SynchronousQueue}
import akka.remote.RemoteClientLifeCycleEvent
import spark.scheduler.cluster._
import spark.scheduler.cluster.RegisteredSlave
import spark.scheduler.cluster.LaunchTask
import spark.scheduler.cluster.RegisterSlaveFailed
import spark.scheduler.cluster.RegisterSlave
private[spark] class StandaloneExecutorBackend(
executor: Executor,
masterUrl: String,
slaveId: String,
hostname: String,
cores: Int)
extends Actor
with ExecutorBackend
with Logging {
val threadPool = new ThreadPoolExecutor(
1, 128, 600, TimeUnit.SECONDS, new SynchronousQueue[Runnable])
var master: ActorRef = null
override def preStart() {
try {
logInfo("Connecting to master: " + masterUrl)
master = context.actorFor(masterUrl)
master ! RegisterSlave(slaveId, hostname, cores)
context.system.eventStream.subscribe(self, classOf[RemoteClientLifeCycleEvent])
context.watch(master) // Doesn't work with remote actors, but useful for testing
} catch {
case e: Exception =>
logError("Failed to connect to master", e)
System.exit(1)
}
}
override def receive = {
case RegisteredSlave(sparkProperties) =>
logInfo("Successfully registered with master")
executor.initialize(hostname, sparkProperties)
case RegisterSlaveFailed(message) =>
logError("Slave registration failed: " + message)
System.exit(1)
case LaunchTask(taskDesc) =>
logInfo("Got assigned task " + taskDesc.taskId)
executor.launchTask(this, taskDesc.taskId, taskDesc.serializedTask)
}
override def statusUpdate(taskId: Long, state: TaskState, data: ByteBuffer) {
master ! StatusUpdate(slaveId, taskId, state, data)
}
}
private[spark] object StandaloneExecutorBackend {
def run(masterUrl: String, slaveId: String, hostname: String, cores: Int) {
// 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)
val actor = actorSystem.actorOf(
Props(new StandaloneExecutorBackend(new Executor, masterUrl, slaveId, hostname, cores)),
name = "Executor")
actorSystem.awaitTermination()
}
def main(args: Array[String]) {
if (args.length != 4) {
System.err.println("Usage: StandaloneExecutorBackend <master> <slaveId> <hostname> <cores>")
System.exit(1)
}
run(args(0), args(1), args(2), args(3).toInt)
}
}
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