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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 java.util.concurrent.LinkedBlockingQueue
import scala.collection.mutable.{ArrayBuffer, SynchronizedBuffer}
import org.apache.spark.Logging
/** Asynchronously passes SparkListenerEvents to registered SparkListeners. */
private[spark] class SparkListenerBus extends Logging {
private val sparkListeners = new ArrayBuffer[SparkListener] with SynchronizedBuffer[SparkListener]
/* Cap the capacity of the SparkListenerEvent queue so we get an explicit error (rather than
* an OOM exception) if it's perpetually being added to more quickly than it's being drained. */
private val EVENT_QUEUE_CAPACITY = 10000
private val eventQueue = new LinkedBlockingQueue[SparkListenerEvents](EVENT_QUEUE_CAPACITY)
private var queueFullErrorMessageLogged = false
// Create a new daemon thread to listen for events. This thread is stopped when it receives
// a SparkListenerShutdown event, using the stop method.
new Thread("SparkListenerBus") {
setDaemon(true)
override def run() {
while (true) {
val event = eventQueue.take
event match {
case stageSubmitted: SparkListenerStageSubmitted =>
sparkListeners.foreach(_.onStageSubmitted(stageSubmitted))
case stageCompleted: SparkListenerStageCompleted =>
sparkListeners.foreach(_.onStageCompleted(stageCompleted))
case jobStart: SparkListenerJobStart =>
sparkListeners.foreach(_.onJobStart(jobStart))
case jobEnd: SparkListenerJobEnd =>
sparkListeners.foreach(_.onJobEnd(jobEnd))
case taskStart: SparkListenerTaskStart =>
sparkListeners.foreach(_.onTaskStart(taskStart))
case taskGettingResult: SparkListenerTaskGettingResult =>
sparkListeners.foreach(_.onTaskGettingResult(taskGettingResult))
case taskEnd: SparkListenerTaskEnd =>
sparkListeners.foreach(_.onTaskEnd(taskEnd))
case SparkListenerShutdown =>
// Get out of the while loop and shutdown the daemon thread
return
case _ =>
}
}
}
}.start()
def addListener(listener: SparkListener) {
sparkListeners += listener
}
def post(event: SparkListenerEvents) {
val eventAdded = eventQueue.offer(event)
if (!eventAdded && !queueFullErrorMessageLogged) {
logError("Dropping SparkListenerEvent because no remaining room in event queue. " +
"This likely means one of the SparkListeners is too slow and cannot keep up with the " +
"rate at which tasks are being started by the scheduler.")
queueFullErrorMessageLogged = true
}
}
/**
* Waits until there are no more events in the queue, or until the specified time has elapsed.
* Used for testing only. Returns true if the queue has emptied and false is the specified time
* elapsed before the queue emptied.
*/
def waitUntilEmpty(timeoutMillis: Int): Boolean = {
val finishTime = System.currentTimeMillis + timeoutMillis
while (!eventQueue.isEmpty) {
if (System.currentTimeMillis > finishTime) {
return false
}
/* Sleep rather than using wait/notify, because this is used only for testing and wait/notify
* add overhead in the general case. */
Thread.sleep(10)
}
return true
}
def stop(): Unit = post(SparkListenerShutdown)
}
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