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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.streaming.scheduler
import scala.collection.mutable.Queue
import org.apache.spark.annotation.DeveloperApi
import org.apache.spark.util.Distribution
/**
* :: DeveloperApi ::
* Base trait for events related to StreamingListener
*/
@DeveloperApi
sealed trait StreamingListenerEvent
@DeveloperApi
case class StreamingListenerBatchSubmitted(batchInfo: BatchInfo) extends StreamingListenerEvent
@DeveloperApi
case class StreamingListenerBatchCompleted(batchInfo: BatchInfo) extends StreamingListenerEvent
@DeveloperApi
case class StreamingListenerBatchStarted(batchInfo: BatchInfo) extends StreamingListenerEvent
@DeveloperApi
case class StreamingListenerOutputOperationStarted(outputOperationInfo: OutputOperationInfo)
extends StreamingListenerEvent
@DeveloperApi
case class StreamingListenerOutputOperationCompleted(outputOperationInfo: OutputOperationInfo)
extends StreamingListenerEvent
@DeveloperApi
case class StreamingListenerReceiverStarted(receiverInfo: ReceiverInfo)
extends StreamingListenerEvent
@DeveloperApi
case class StreamingListenerReceiverError(receiverInfo: ReceiverInfo)
extends StreamingListenerEvent
@DeveloperApi
case class StreamingListenerReceiverStopped(receiverInfo: ReceiverInfo)
extends StreamingListenerEvent
/**
* :: DeveloperApi ::
* A listener interface for receiving information about an ongoing streaming
* computation.
*/
@DeveloperApi
trait StreamingListener {
/** Called when a receiver has been started */
def onReceiverStarted(receiverStarted: StreamingListenerReceiverStarted) { }
/** Called when a receiver has reported an error */
def onReceiverError(receiverError: StreamingListenerReceiverError) { }
/** Called when a receiver has been stopped */
def onReceiverStopped(receiverStopped: StreamingListenerReceiverStopped) { }
/** Called when a batch of jobs has been submitted for processing. */
def onBatchSubmitted(batchSubmitted: StreamingListenerBatchSubmitted) { }
/** Called when processing of a batch of jobs has started. */
def onBatchStarted(batchStarted: StreamingListenerBatchStarted) { }
/** Called when processing of a batch of jobs has completed. */
def onBatchCompleted(batchCompleted: StreamingListenerBatchCompleted) { }
/** Called when processing of a job of a batch has started. */
def onOutputOperationStarted(
outputOperationStarted: StreamingListenerOutputOperationStarted) { }
/** Called when processing of a job of a batch has completed. */
def onOutputOperationCompleted(
outputOperationCompleted: StreamingListenerOutputOperationCompleted) { }
}
/**
* :: DeveloperApi ::
* A simple StreamingListener that logs summary statistics across Spark Streaming batches
* @param numBatchInfos Number of last batches to consider for generating statistics (default: 10)
*/
@DeveloperApi
class StatsReportListener(numBatchInfos: Int = 10) extends StreamingListener {
// Queue containing latest completed batches
val batchInfos = new Queue[BatchInfo]()
override def onBatchCompleted(batchStarted: StreamingListenerBatchCompleted) {
batchInfos.enqueue(batchStarted.batchInfo)
if (batchInfos.size > numBatchInfos) batchInfos.dequeue()
printStats()
}
def printStats() {
showMillisDistribution("Total delay: ", _.totalDelay)
showMillisDistribution("Processing time: ", _.processingDelay)
}
def showMillisDistribution(heading: String, getMetric: BatchInfo => Option[Long]) {
org.apache.spark.scheduler.StatsReportListener.showMillisDistribution(
heading, extractDistribution(getMetric))
}
def extractDistribution(getMetric: BatchInfo => Option[Long]): Option[Distribution] = {
Distribution(batchInfos.flatMap(getMetric(_)).map(_.toDouble))
}
}
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