org.apache.spark.scheduler.JobWaiter.scala Maven / Gradle / Ivy
/*
* 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
import java.util.concurrent.atomic.AtomicInteger
import scala.concurrent.{Future, Promise}
import org.apache.spark.internal.Logging
/**
* An object that waits for a DAGScheduler job to complete. As tasks finish, it passes their
* results to the given handler function.
*/
private[spark] class JobWaiter[T](
dagScheduler: DAGScheduler,
val jobId: Int,
totalTasks: Int,
resultHandler: (Int, T) => Unit)
extends JobListener with Logging {
private val finishedTasks = new AtomicInteger(0)
// If the job is finished, this will be its result. In the case of 0 task jobs (e.g. zero
// partition RDDs), we set the jobResult directly to JobSucceeded.
private val jobPromise: Promise[Unit] =
if (totalTasks == 0) Promise.successful(()) else Promise()
def jobFinished: Boolean = jobPromise.isCompleted
def completionFuture: Future[Unit] = jobPromise.future
/**
* Sends a signal to the DAGScheduler to cancel the job. The cancellation itself is handled
* asynchronously. After the low level scheduler cancels all the tasks belonging to this job, it
* will fail this job with a SparkException.
*/
def cancel() {
dagScheduler.cancelJob(jobId, None)
}
override def taskSucceeded(index: Int, result: Any): Unit = {
// resultHandler call must be synchronized in case resultHandler itself is not thread safe.
synchronized {
resultHandler(index, result.asInstanceOf[T])
}
if (finishedTasks.incrementAndGet() == totalTasks) {
jobPromise.success(())
}
}
override def jobFailed(exception: Exception): Unit = {
if (!jobPromise.tryFailure(exception)) {
logWarning("Ignore failure", exception)
}
}
}