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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.scheduler.local
import java.nio.ByteBuffer
import akka.actor.{Actor, ActorRef, Props}
import org.apache.spark.{Logging, SparkContext, SparkEnv, TaskState}
import org.apache.spark.TaskState.TaskState
import org.apache.spark.executor.{Executor, ExecutorBackend}
import org.apache.spark.scheduler.{SchedulerBackend, TaskSchedulerImpl, WorkerOffer}
private case class ReviveOffers()
private case class StatusUpdate(taskId: Long, state: TaskState, serializedData: ByteBuffer)
private case class KillTask(taskId: Long)
/**
* Calls to LocalBackend are all serialized through LocalActor. Using an actor makes the calls on
* LocalBackend asynchronous, which is necessary to prevent deadlock between LocalBackend
* and the ClusterScheduler.
*/
private[spark] class LocalActor(
scheduler: TaskSchedulerImpl,
executorBackend: LocalBackend,
private val totalCores: Int) extends Actor with Logging {
private var freeCores = totalCores
private val localExecutorId = "localhost"
private val localExecutorHostname = "localhost"
val executor = new Executor(
localExecutorId, localExecutorHostname, scheduler.conf.getAll, isLocal = true)
def receive = {
case ReviveOffers =>
reviveOffers()
case StatusUpdate(taskId, state, serializedData) =>
scheduler.statusUpdate(taskId, state, serializedData)
if (TaskState.isFinished(state)) {
freeCores += 1
reviveOffers()
}
case KillTask(taskId) =>
executor.killTask(taskId)
}
def reviveOffers() {
val offers = Seq(new WorkerOffer(localExecutorId, localExecutorHostname, freeCores))
for (task <- scheduler.resourceOffers(offers).flatten) {
freeCores -= 1
executor.launchTask(executorBackend, task.taskId, task.serializedTask)
}
}
}
/**
* LocalBackend is used when running a local version of Spark where the executor, backend, and
* master all run in the same JVM. It sits behind a ClusterScheduler and handles launching tasks
* on a single Executor (created by the LocalBackend) running locally.
*/
private[spark] class LocalBackend(scheduler: TaskSchedulerImpl, val totalCores: Int)
extends SchedulerBackend with ExecutorBackend {
var localActor: ActorRef = null
override def start() {
localActor = SparkEnv.get.actorSystem.actorOf(
Props(new LocalActor(scheduler, this, totalCores)),
"LocalBackendActor")
}
override def stop() {
}
override def reviveOffers() {
localActor ! ReviveOffers
}
override def defaultParallelism() = totalCores
override def killTask(taskId: Long, executorId: String) {
localActor ! KillTask(taskId)
}
override def statusUpdate(taskId: Long, state: TaskState, serializedData: ByteBuffer) {
localActor ! StatusUpdate(taskId, state, serializedData)
}
}
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