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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
import java.util.concurrent.Semaphore
import scala.concurrent.Await
import scala.concurrent.duration.Duration
import scala.concurrent.future
import scala.concurrent.ExecutionContext.Implicits.global
import org.scalatest.{BeforeAndAfter, FunSuite}
import org.scalatest.matchers.ShouldMatchers
import org.apache.spark.SparkContext._
import org.apache.spark.scheduler.{SparkListenerTaskStart, SparkListener}
/**
* Test suite for cancelling running jobs. We run the cancellation tasks for single job action
* (e.g. count) as well as multi-job action (e.g. take). We test the local and cluster schedulers
* in both FIFO and fair scheduling modes.
*/
class JobCancellationSuite extends FunSuite with ShouldMatchers with BeforeAndAfter
with LocalSparkContext {
override def afterEach() {
super.afterEach()
resetSparkContext()
System.clearProperty("spark.scheduler.mode")
}
test("local mode, FIFO scheduler") {
System.setProperty("spark.scheduler.mode", "FIFO")
sc = new SparkContext("local[2]", "test")
testCount()
testTake()
// Make sure we can still launch tasks.
assert(sc.parallelize(1 to 10, 2).count === 10)
}
test("local mode, fair scheduler") {
System.setProperty("spark.scheduler.mode", "FAIR")
val xmlPath = getClass.getClassLoader.getResource("fairscheduler.xml").getFile()
System.setProperty("spark.scheduler.allocation.file", xmlPath)
sc = new SparkContext("local[2]", "test")
testCount()
testTake()
// Make sure we can still launch tasks.
assert(sc.parallelize(1 to 10, 2).count === 10)
}
test("cluster mode, FIFO scheduler") {
System.setProperty("spark.scheduler.mode", "FIFO")
sc = new SparkContext("local-cluster[2,1,512]", "test")
testCount()
testTake()
// Make sure we can still launch tasks.
assert(sc.parallelize(1 to 10, 2).count === 10)
}
test("cluster mode, fair scheduler") {
System.setProperty("spark.scheduler.mode", "FAIR")
val xmlPath = getClass.getClassLoader.getResource("fairscheduler.xml").getFile()
System.setProperty("spark.scheduler.allocation.file", xmlPath)
sc = new SparkContext("local-cluster[2,1,512]", "test")
testCount()
testTake()
// Make sure we can still launch tasks.
assert(sc.parallelize(1 to 10, 2).count === 10)
}
test("job group") {
sc = new SparkContext("local[2]", "test")
// Add a listener to release the semaphore once any tasks are launched.
val sem = new Semaphore(0)
sc.dagScheduler.addSparkListener(new SparkListener {
override def onTaskStart(taskStart: SparkListenerTaskStart) {
sem.release()
}
})
// jobA is the one to be cancelled.
val jobA = future {
sc.setJobGroup("jobA", "this is a job to be cancelled")
sc.parallelize(1 to 10000, 2).map { i => Thread.sleep(10); i }.count()
}
sc.clearJobGroup()
val jobB = sc.parallelize(1 to 100, 2).countAsync()
// Block until both tasks of job A have started and cancel job A.
sem.acquire(2)
sc.cancelJobGroup("jobA")
val e = intercept[SparkException] { Await.result(jobA, Duration.Inf) }
assert(e.getMessage contains "cancel")
// Once A is cancelled, job B should finish fairly quickly.
assert(jobB.get() === 100)
}
test("two jobs sharing the same stage") {
// sem1: make sure cancel is issued after some tasks are launched
// sem2: make sure the first stage is not finished until cancel is issued
val sem1 = new Semaphore(0)
val sem2 = new Semaphore(0)
sc = new SparkContext("local[2]", "test")
sc.dagScheduler.addSparkListener(new SparkListener {
override def onTaskStart(taskStart: SparkListenerTaskStart) {
sem1.release()
}
})
// Create two actions that would share the some stages.
val rdd = sc.parallelize(1 to 10, 2).map { i =>
sem2.acquire()
(i, i)
}.reduceByKey(_+_)
val f1 = rdd.collectAsync()
val f2 = rdd.countAsync()
// Kill one of the action.
future {
sem1.acquire()
f1.cancel()
sem2.release(10)
}
// Expect both to fail now.
// TODO: update this test when we change Spark so cancelling f1 wouldn't affect f2.
intercept[SparkException] { f1.get() }
intercept[SparkException] { f2.get() }
}
def testCount() {
// Cancel before launching any tasks
{
val f = sc.parallelize(1 to 10000, 2).map { i => Thread.sleep(10); i }.countAsync()
future { f.cancel() }
val e = intercept[SparkException] { f.get() }
assert(e.getMessage.contains("cancelled") || e.getMessage.contains("killed"))
}
// Cancel after some tasks have been launched
{
// Add a listener to release the semaphore once any tasks are launched.
val sem = new Semaphore(0)
sc.dagScheduler.addSparkListener(new SparkListener {
override def onTaskStart(taskStart: SparkListenerTaskStart) {
sem.release()
}
})
val f = sc.parallelize(1 to 10000, 2).map { i => Thread.sleep(10); i }.countAsync()
future {
// Wait until some tasks were launched before we cancel the job.
sem.acquire()
f.cancel()
}
val e = intercept[SparkException] { f.get() }
assert(e.getMessage.contains("cancelled") || e.getMessage.contains("killed"))
}
}
def testTake() {
// Cancel before launching any tasks
{
val f = sc.parallelize(1 to 10000, 2).map { i => Thread.sleep(10); i }.takeAsync(5000)
future { f.cancel() }
val e = intercept[SparkException] { f.get() }
assert(e.getMessage.contains("cancelled") || e.getMessage.contains("killed"))
}
// Cancel after some tasks have been launched
{
// Add a listener to release the semaphore once any tasks are launched.
val sem = new Semaphore(0)
sc.dagScheduler.addSparkListener(new SparkListener {
override def onTaskStart(taskStart: SparkListenerTaskStart) {
sem.release()
}
})
val f = sc.parallelize(1 to 10000, 2).map { i => Thread.sleep(10); i }.takeAsync(5000)
future {
sem.acquire()
f.cancel()
}
val e = intercept[SparkException] { f.get() }
assert(e.getMessage.contains("cancelled") || e.getMessage.contains("killed"))
}
}
}
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