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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 javax.annotation.concurrent.GuardedBy
import scala.collection.mutable
import scala.collection.mutable.ArrayBuffer
import scala.ref.WeakReference
import scala.util.control.NonFatal
import org.scalatest.Matchers
import org.scalatest.exceptions.TestFailedException
import org.apache.spark.AccumulatorParam.StringAccumulatorParam
import org.apache.spark.scheduler._
import org.apache.spark.serializer.JavaSerializer
import org.apache.spark.util.{AccumulatorContext, AccumulatorMetadata, AccumulatorV2, LongAccumulator}
class AccumulatorSuite extends SparkFunSuite with Matchers with LocalSparkContext {
import AccumulatorSuite.createLongAccum
override def afterEach(): Unit = {
try {
AccumulatorContext.clear()
} finally {
super.afterEach()
}
}
implicit def setAccum[A]: AccumulableParam[mutable.Set[A], A] =
new AccumulableParam[mutable.Set[A], A] {
def addInPlace(t1: mutable.Set[A], t2: mutable.Set[A]) : mutable.Set[A] = {
t1 ++= t2
t1
}
def addAccumulator(t1: mutable.Set[A], t2: A) : mutable.Set[A] = {
t1 += t2
t1
}
def zero(t: mutable.Set[A]) : mutable.Set[A] = {
new mutable.HashSet[A]()
}
}
test("accumulator serialization") {
val ser = new JavaSerializer(new SparkConf).newInstance()
val acc = createLongAccum("x")
acc.add(5)
assert(acc.value == 5)
assert(acc.isAtDriverSide)
// serialize and de-serialize it, to simulate sending accumulator to executor.
val acc2 = ser.deserialize[LongAccumulator](ser.serialize(acc))
// value is reset on the executors
assert(acc2.localValue == 0)
assert(!acc2.isAtDriverSide)
acc2.add(10)
// serialize and de-serialize it again, to simulate sending accumulator back to driver.
val acc3 = ser.deserialize[LongAccumulator](ser.serialize(acc2))
// value is not reset on the driver
assert(acc3.value == 10)
assert(acc3.isAtDriverSide)
}
test ("basic accumulation") {
sc = new SparkContext("local", "test")
val acc: Accumulator[Int] = sc.accumulator(0)
val d = sc.parallelize(1 to 20)
d.foreach{x => acc += x}
acc.value should be (210)
val longAcc = sc.accumulator(0L)
val maxInt = Integer.MAX_VALUE.toLong
d.foreach{x => longAcc += maxInt + x}
longAcc.value should be (210L + maxInt * 20)
}
test("value not assignable from tasks") {
sc = new SparkContext("local", "test")
val acc: Accumulator[Int] = sc.accumulator(0)
val d = sc.parallelize(1 to 20)
an [Exception] should be thrownBy {d.foreach{x => acc.value = x}}
}
test ("add value to collection accumulators") {
val maxI = 1000
for (nThreads <- List(1, 10)) { // test single & multi-threaded
sc = new SparkContext("local[" + nThreads + "]", "test")
val acc: Accumulable[mutable.Set[Any], Any] = sc.accumulable(new mutable.HashSet[Any]())
val d = sc.parallelize(1 to maxI)
d.foreach {
x => acc += x
}
val v = acc.value.asInstanceOf[mutable.Set[Int]]
for (i <- 1 to maxI) {
v should contain(i)
}
resetSparkContext()
}
}
test("value not readable in tasks") {
val maxI = 1000
for (nThreads <- List(1, 10)) { // test single & multi-threaded
sc = new SparkContext("local[" + nThreads + "]", "test")
val acc: Accumulable[mutable.Set[Any], Any] = sc.accumulable(new mutable.HashSet[Any]())
val d = sc.parallelize(1 to maxI)
an [SparkException] should be thrownBy {
d.foreach {
x => acc.value += x
}
}
resetSparkContext()
}
}
test ("collection accumulators") {
val maxI = 1000
for (nThreads <- List(1, 10)) {
// test single & multi-threaded
sc = new SparkContext("local[" + nThreads + "]", "test")
val setAcc = sc.accumulableCollection(mutable.HashSet[Int]())
val bufferAcc = sc.accumulableCollection(mutable.ArrayBuffer[Int]())
val mapAcc = sc.accumulableCollection(mutable.HashMap[Int, String]())
val d = sc.parallelize((1 to maxI) ++ (1 to maxI))
d.foreach {
x => {setAcc += x; bufferAcc += x; mapAcc += (x -> x.toString)}
}
// Note that this is typed correctly -- no casts necessary
setAcc.value.size should be (maxI)
bufferAcc.value.size should be (2 * maxI)
mapAcc.value.size should be (maxI)
for (i <- 1 to maxI) {
setAcc.value should contain(i)
bufferAcc.value should contain(i)
mapAcc.value should contain (i -> i.toString)
}
resetSparkContext()
}
}
test ("localValue readable in tasks") {
val maxI = 1000
for (nThreads <- List(1, 10)) { // test single & multi-threaded
sc = new SparkContext("local[" + nThreads + "]", "test")
val acc: Accumulable[mutable.Set[Any], Any] = sc.accumulable(new mutable.HashSet[Any]())
val groupedInts = (1 to (maxI/20)).map {x => (20 * (x - 1) to 20 * x).toSet}
val d = sc.parallelize(groupedInts)
d.foreach {
x => acc.localValue ++= x
}
acc.value should be ( (0 to maxI).toSet)
resetSparkContext()
}
}
test ("garbage collection") {
// Create an accumulator and let it go out of scope to test that it's properly garbage collected
sc = new SparkContext("local", "test")
var acc: Accumulable[mutable.Set[Any], Any] = sc.accumulable(new mutable.HashSet[Any]())
val accId = acc.id
val ref = WeakReference(acc)
// Ensure the accumulator is present
assert(ref.get.isDefined)
// Remove the explicit reference to it and allow weak reference to get garbage collected
acc = null
System.gc()
assert(ref.get.isEmpty)
AccumulatorContext.remove(accId)
assert(!AccumulatorContext.get(accId).isDefined)
}
test("get accum") {
// Don't register with SparkContext for cleanup
var acc = createLongAccum("a")
val accId = acc.id
val ref = WeakReference(acc)
assert(ref.get.isDefined)
// Remove the explicit reference to it and allow weak reference to get garbage collected
acc = null
System.gc()
assert(ref.get.isEmpty)
// Getting a garbage collected accum should throw error
intercept[IllegalAccessError] {
AccumulatorContext.get(accId)
}
// Getting a normal accumulator. Note: this has to be separate because referencing an
// accumulator above in an `assert` would keep it from being garbage collected.
val acc2 = createLongAccum("b")
assert(AccumulatorContext.get(acc2.id) === Some(acc2))
// Getting an accumulator that does not exist should return None
assert(AccumulatorContext.get(100000).isEmpty)
}
test("string accumulator param") {
val acc = new Accumulator("", StringAccumulatorParam, Some("darkness"))
assert(acc.value === "")
acc.setValue("feeds")
assert(acc.value === "feeds")
acc.add("your")
assert(acc.value === "your") // value is overwritten, not concatenated
acc += "soul"
assert(acc.value === "soul")
acc ++= "with"
assert(acc.value === "with")
acc.merge("kindness")
assert(acc.value === "kindness")
}
}
private[spark] object AccumulatorSuite {
import InternalAccumulator._
/**
* Create a long accumulator and register it to [[AccumulatorContext]].
*/
def createLongAccum(
name: String,
countFailedValues: Boolean = false,
initValue: Long = 0,
id: Long = AccumulatorContext.newId()): LongAccumulator = {
val acc = new LongAccumulator
acc.setValue(initValue)
acc.metadata = AccumulatorMetadata(id, Some(name), countFailedValues)
AccumulatorContext.register(acc)
acc
}
/**
* Make an [[AccumulableInfo]] out of an [[Accumulable]] with the intent to use the
* info as an accumulator update.
*/
def makeInfo(a: AccumulatorV2[_, _]): AccumulableInfo = a.toInfo(Some(a.localValue), None)
/**
* Run one or more Spark jobs and verify that in at least one job the peak execution memory
* accumulator is updated afterwards.
*/
def verifyPeakExecutionMemorySet(
sc: SparkContext,
testName: String)(testBody: => Unit): Unit = {
val listener = new SaveInfoListener
sc.addSparkListener(listener)
testBody
// wait until all events have been processed before proceeding to assert things
sc.listenerBus.waitUntilEmpty(10 * 1000)
val accums = listener.getCompletedStageInfos.flatMap(_.accumulables.values)
val isSet = accums.exists { a =>
a.name == Some(PEAK_EXECUTION_MEMORY) && a.value.exists(_.asInstanceOf[Long] > 0L)
}
if (!isSet) {
throw new TestFailedException(s"peak execution memory accumulator not set in '$testName'", 0)
}
}
}
/**
* A simple listener that keeps track of the TaskInfos and StageInfos of all completed jobs.
*/
private class SaveInfoListener extends SparkListener {
type StageId = Int
type StageAttemptId = Int
private val completedStageInfos = new ArrayBuffer[StageInfo]
private val completedTaskInfos =
new mutable.HashMap[(StageId, StageAttemptId), ArrayBuffer[TaskInfo]]
// Callback to call when a job completes. Parameter is job ID.
@GuardedBy("this")
private var jobCompletionCallback: () => Unit = null
private val jobCompletionSem = new Semaphore(0)
private var exception: Throwable = null
def getCompletedStageInfos: Seq[StageInfo] = completedStageInfos.toArray.toSeq
def getCompletedTaskInfos: Seq[TaskInfo] = completedTaskInfos.values.flatten.toSeq
def getCompletedTaskInfos(stageId: StageId, stageAttemptId: StageAttemptId): Seq[TaskInfo] =
completedTaskInfos.getOrElse((stageId, stageAttemptId), Seq.empty[TaskInfo])
/**
* If `jobCompletionCallback` is set, block until the next call has finished.
* If the callback failed with an exception, throw it.
*/
def awaitNextJobCompletion(): Unit = {
if (jobCompletionCallback != null) {
jobCompletionSem.acquire()
if (exception != null) {
throw exception
}
}
}
/**
* Register a callback to be called on job end.
* A call to this should be followed by [[awaitNextJobCompletion]].
*/
def registerJobCompletionCallback(callback: () => Unit): Unit = {
jobCompletionCallback = callback
}
override def onJobEnd(jobEnd: SparkListenerJobEnd): Unit = {
if (jobCompletionCallback != null) {
try {
jobCompletionCallback()
} catch {
// Store any exception thrown here so we can throw them later in the main thread.
// Otherwise, if `jobCompletionCallback` threw something it wouldn't fail the test.
case NonFatal(e) => exception = e
} finally {
jobCompletionSem.release()
}
}
}
override def onStageCompleted(stageCompleted: SparkListenerStageCompleted): Unit = {
completedStageInfos += stageCompleted.stageInfo
}
override def onTaskEnd(taskEnd: SparkListenerTaskEnd): Unit = {
completedTaskInfos.getOrElseUpdate(
(taskEnd.stageId, taskEnd.stageAttemptId), new ArrayBuffer[TaskInfo]) += taskEnd.taskInfo
}
}
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