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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
import scala.collection.mutable.{Buffer, HashSet}
import org.scalatest.{BeforeAndAfter, BeforeAndAfterAll, FunSuite}
import org.scalatest.matchers.ShouldMatchers
import org.apache.spark.{LocalSparkContext, SparkContext}
import org.apache.spark.SparkContext._
class SparkListenerSuite extends FunSuite with LocalSparkContext with ShouldMatchers
with BeforeAndAfter with BeforeAndAfterAll {
/** Length of time to wait while draining listener events. */
val WAIT_TIMEOUT_MILLIS = 10000
before {
sc = new SparkContext("local", "SparkListenerSuite")
}
override def afterAll {
System.clearProperty("spark.akka.frameSize")
}
test("basic creation of StageInfo") {
val listener = new SaveStageInfo
sc.addSparkListener(listener)
val rdd1 = sc.parallelize(1 to 100, 4)
val rdd2 = rdd1.map(x => x.toString)
rdd2.setName("Target RDD")
rdd2.count
assert(sc.dagScheduler.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS))
listener.stageInfos.size should be {1}
val first = listener.stageInfos.head
first.rddName should be {"Target RDD"}
first.numTasks should be {4}
first.numPartitions should be {4}
first.submissionTime should be ('defined)
first.completionTime should be ('defined)
first.taskInfos.length should be {4}
}
test("StageInfo with fewer tasks than partitions") {
val listener = new SaveStageInfo
sc.addSparkListener(listener)
val rdd1 = sc.parallelize(1 to 100, 4)
val rdd2 = rdd1.map(x => x.toString)
sc.runJob(rdd2, (items: Iterator[String]) => items.size, Seq(0, 1), true)
assert(sc.dagScheduler.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS))
listener.stageInfos.size should be {1}
val first = listener.stageInfos.head
first.numTasks should be {2}
first.numPartitions should be {4}
}
test("local metrics") {
val listener = new SaveStageInfo
sc.addSparkListener(listener)
sc.addSparkListener(new StatsReportListener)
//just to make sure some of the tasks take a noticeable amount of time
val w = {i:Int =>
if (i == 0)
Thread.sleep(100)
i
}
val d = sc.parallelize(0 to 1e4.toInt, 64).map{i => w(i)}
d.count()
assert(sc.dagScheduler.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS))
listener.stageInfos.size should be (1)
val d2 = d.map{i => w(i) -> i * 2}.setName("shuffle input 1")
val d3 = d.map{i => w(i) -> (0 to (i % 5))}.setName("shuffle input 2")
val d4 = d2.cogroup(d3, 64).map{case(k,(v1,v2)) => w(k) -> (v1.size, v2.size)}
d4.setName("A Cogroup")
d4.collectAsMap()
assert(sc.dagScheduler.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS))
listener.stageInfos.size should be (4)
listener.stageInfos.foreach { stageInfo =>
/* small test, so some tasks might take less than 1 millisecond, but average should be greater
* than 0 ms. */
checkNonZeroAvg(stageInfo.taskInfos.map{_._1.duration}, stageInfo + " duration")
checkNonZeroAvg(
stageInfo.taskInfos.map{_._2.executorRunTime.toLong},
stageInfo + " executorRunTime")
checkNonZeroAvg(
stageInfo.taskInfos.map{_._2.executorDeserializeTime.toLong},
stageInfo + " executorDeserializeTime")
if (stageInfo.rddName == d4.name) {
checkNonZeroAvg(
stageInfo.taskInfos.map{_._2.shuffleReadMetrics.get.fetchWaitTime},
stageInfo + " fetchWaitTime")
}
stageInfo.taskInfos.foreach { case (taskInfo, taskMetrics) =>
taskMetrics.resultSize should be > (0l)
if (stageInfo.rddName == d2.name || stageInfo.rddName == d3.name) {
taskMetrics.shuffleWriteMetrics should be ('defined)
taskMetrics.shuffleWriteMetrics.get.shuffleBytesWritten should be > (0l)
}
if (stageInfo.rddName == d4.name) {
taskMetrics.shuffleReadMetrics should be ('defined)
val sm = taskMetrics.shuffleReadMetrics.get
sm.totalBlocksFetched should be > (0)
sm.localBlocksFetched should be > (0)
sm.remoteBlocksFetched should be (0)
sm.remoteBytesRead should be (0l)
sm.remoteFetchTime should be (0l)
}
}
}
}
test("onTaskGettingResult() called when result fetched remotely") {
val listener = new SaveTaskEvents
sc.addSparkListener(listener)
// Make a task whose result is larger than the akka frame size
System.setProperty("spark.akka.frameSize", "1")
val akkaFrameSize =
sc.env.actorSystem.settings.config.getBytes("akka.remote.netty.message-frame-size").toInt
val result = sc.parallelize(Seq(1), 1).map(x => 1.to(akkaFrameSize).toArray).reduce((x,y) => x)
assert(result === 1.to(akkaFrameSize).toArray)
assert(sc.dagScheduler.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS))
val TASK_INDEX = 0
assert(listener.startedTasks.contains(TASK_INDEX))
assert(listener.startedGettingResultTasks.contains(TASK_INDEX))
assert(listener.endedTasks.contains(TASK_INDEX))
}
test("onTaskGettingResult() not called when result sent directly") {
val listener = new SaveTaskEvents
sc.addSparkListener(listener)
// Make a task whose result is larger than the akka frame size
val result = sc.parallelize(Seq(1), 1).map(x => 2 * x).reduce((x, y) => x)
assert(result === 2)
assert(sc.dagScheduler.listenerBus.waitUntilEmpty(WAIT_TIMEOUT_MILLIS))
val TASK_INDEX = 0
assert(listener.startedTasks.contains(TASK_INDEX))
assert(listener.startedGettingResultTasks.isEmpty == true)
assert(listener.endedTasks.contains(TASK_INDEX))
}
def checkNonZeroAvg(m: Traversable[Long], msg: String) {
assert(m.sum / m.size.toDouble > 0.0, msg)
}
class SaveStageInfo extends SparkListener {
val stageInfos = Buffer[StageInfo]()
override def onStageCompleted(stage: StageCompleted) {
stageInfos += stage.stage
}
}
class SaveTaskEvents extends SparkListener {
val startedTasks = new HashSet[Int]()
val startedGettingResultTasks = new HashSet[Int]()
val endedTasks = new HashSet[Int]()
override def onTaskStart(taskStart: SparkListenerTaskStart) {
startedTasks += taskStart.taskInfo.index
}
override def onTaskEnd(taskEnd: SparkListenerTaskEnd) {
endedTasks += taskEnd.taskInfo.index
}
override def onTaskGettingResult(taskGettingResult: SparkListenerTaskGettingResult) {
startedGettingResultTasks += taskGettingResult.taskInfo.index
}
}
}
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