spark ReceivedBlockTracker 源码

  • 2022-10-20
  • 浏览 (278)

spark ReceivedBlockTracker 代码

文件路径:/streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceivedBlockTracker.scala

/*
 * 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 java.nio.ByteBuffer

import scala.collection.JavaConverters._
import scala.collection.mutable
import scala.util.control.NonFatal

import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs.Path

import org.apache.spark.SparkConf
import org.apache.spark.internal.Logging
import org.apache.spark.network.util.JavaUtils
import org.apache.spark.streaming.Time
import org.apache.spark.streaming.util.{WriteAheadLog, WriteAheadLogUtils}
import org.apache.spark.util.{Clock, Utils}

/** Trait representing any event in the ReceivedBlockTracker that updates its state. */
private[streaming] sealed trait ReceivedBlockTrackerLogEvent

private[streaming] case class BlockAdditionEvent(receivedBlockInfo: ReceivedBlockInfo)
  extends ReceivedBlockTrackerLogEvent
private[streaming] case class BatchAllocationEvent(time: Time, allocatedBlocks: AllocatedBlocks)
  extends ReceivedBlockTrackerLogEvent
private[streaming] case class BatchCleanupEvent(times: Seq[Time])
  extends ReceivedBlockTrackerLogEvent

/** Class representing the blocks of all the streams allocated to a batch */
private[streaming]
case class AllocatedBlocks(streamIdToAllocatedBlocks: Map[Int, Seq[ReceivedBlockInfo]]) {
  def getBlocksOfStream(streamId: Int): Seq[ReceivedBlockInfo] = {
    streamIdToAllocatedBlocks.getOrElse(streamId, Seq.empty)
  }
}

/**
 * Class that keep track of all the received blocks, and allocate them to batches
 * when required. All actions taken by this class can be saved to a write ahead log
 * (if a checkpoint directory has been provided), so that the state of the tracker
 * (received blocks and block-to-batch allocations) can be recovered after driver failure.
 *
 * Note that when any instance of this class is created with a checkpoint directory,
 * it will try reading events from logs in the directory.
 */
private[streaming] class ReceivedBlockTracker(
    conf: SparkConf,
    hadoopConf: Configuration,
    streamIds: Seq[Int],
    clock: Clock,
    recoverFromWriteAheadLog: Boolean,
    checkpointDirOption: Option[String])
  extends Logging {

  private type ReceivedBlockQueue = mutable.Queue[ReceivedBlockInfo]

  private val streamIdToUnallocatedBlockQueues = new mutable.HashMap[Int, ReceivedBlockQueue]
  private val timeToAllocatedBlocks = new mutable.HashMap[Time, AllocatedBlocks]
  private val writeAheadLogOption = createWriteAheadLog()

  private var lastAllocatedBatchTime: Time = null

  // Recover block information from write ahead logs
  if (recoverFromWriteAheadLog) {
    recoverPastEvents()
  }

  /** Add received block. This event will get written to the write ahead log (if enabled). */
  def addBlock(receivedBlockInfo: ReceivedBlockInfo): Boolean = {
    try {
      val writeResult = writeToLog(BlockAdditionEvent(receivedBlockInfo))
      if (writeResult) {
        synchronized {
          getReceivedBlockQueue(receivedBlockInfo.streamId) += receivedBlockInfo
        }
        logDebug(s"Stream ${receivedBlockInfo.streamId} received " +
          s"block ${receivedBlockInfo.blockStoreResult.blockId}")
      } else {
        logDebug(s"Failed to acknowledge stream ${receivedBlockInfo.streamId} receiving " +
          s"block ${receivedBlockInfo.blockStoreResult.blockId} in the Write Ahead Log.")
      }
      writeResult
    } catch {
      case NonFatal(e) =>
        logError(s"Error adding block $receivedBlockInfo", e)
        false
    }
  }

  /**
   * Allocate all unallocated blocks to the given batch.
   * This event will get written to the write ahead log (if enabled).
   */
  def allocateBlocksToBatch(batchTime: Time): Unit = synchronized {
    if (lastAllocatedBatchTime == null || batchTime > lastAllocatedBatchTime) {
      // We explicitly create an ArrayBuffer here because at least as of Scala 2.11 and 2.12
      // a mutable.Queue fails serialization with a StackOverflow error if it has more than
      // a few thousand elements.  So we explicitly allocate a collection for serialization which
      // we know doesn't have this issue.  (See SPARK-26734).
      val streamIdToBlocks = streamIds.map { streamId =>
        val blocks = mutable.ArrayBuffer[ReceivedBlockInfo]()
        blocks ++= getReceivedBlockQueue(streamId).clone()
        (streamId, blocks.toSeq)
      }.toMap
      val allocatedBlocks = AllocatedBlocks(streamIdToBlocks)
      if (writeToLog(BatchAllocationEvent(batchTime, allocatedBlocks))) {
        streamIds.foreach(getReceivedBlockQueue(_).clear())
        timeToAllocatedBlocks.put(batchTime, allocatedBlocks)
        lastAllocatedBatchTime = batchTime
      } else {
        logInfo(s"Possibly processed batch $batchTime needs to be processed again in WAL recovery")
      }
    } else {
      // This situation occurs when:
      // 1. WAL is ended with BatchAllocationEvent, but without BatchCleanupEvent,
      // possibly processed batch job or half-processed batch job need to be processed again,
      // so the batchTime will be equal to lastAllocatedBatchTime.
      // 2. Slow checkpointing makes recovered batch time older than WAL recovered
      // lastAllocatedBatchTime.
      // This situation will only occurs in recovery time.
      logInfo(s"Possibly processed batch $batchTime needs to be processed again in WAL recovery")
    }
  }

  /** Get the blocks allocated to the given batch. */
  def getBlocksOfBatch(batchTime: Time): Map[Int, Seq[ReceivedBlockInfo]] = synchronized {
    timeToAllocatedBlocks.get(batchTime).map { _.streamIdToAllocatedBlocks }.getOrElse(Map.empty)
  }

  /** Get the blocks allocated to the given batch and stream. */
  def getBlocksOfBatchAndStream(batchTime: Time, streamId: Int): Seq[ReceivedBlockInfo] = {
    synchronized {
      timeToAllocatedBlocks.get(batchTime).map {
        _.getBlocksOfStream(streamId)
      }.getOrElse(Seq.empty)
    }
  }

  /** Check if any blocks are left to be allocated to batches. */
  def hasUnallocatedReceivedBlocks: Boolean = synchronized {
    !streamIdToUnallocatedBlockQueues.values.forall(_.isEmpty)
  }

  /**
   * Get blocks that have been added but not yet allocated to any batch. This method
   * is primarily used for testing.
   */
  def getUnallocatedBlocks(streamId: Int): Seq[ReceivedBlockInfo] = synchronized {
    getReceivedBlockQueue(streamId).toSeq
  }

  /**
   * Clean up block information of old batches. If waitForCompletion is true, this method
   * returns only after the files are cleaned up.
   */
  def cleanupOldBatches(cleanupThreshTime: Time, waitForCompletion: Boolean): Unit = synchronized {
    require(cleanupThreshTime.milliseconds < clock.getTimeMillis())
    val timesToCleanup = timeToAllocatedBlocks.keys.filter { _ < cleanupThreshTime }.toSeq
    logInfo(s"Deleting batches: ${timesToCleanup.mkString(" ")}")
    if (writeToLog(BatchCleanupEvent(timesToCleanup))) {
      timeToAllocatedBlocks --= timesToCleanup
      writeAheadLogOption.foreach(_.clean(cleanupThreshTime.milliseconds, waitForCompletion))
    } else {
      logWarning("Failed to acknowledge batch clean up in the Write Ahead Log.")
    }
  }

  /** Stop the block tracker. */
  def stop(): Unit = {
    writeAheadLogOption.foreach { _.close() }
  }

  /**
   * Recover all the tracker actions from the write ahead logs to recover the state (unallocated
   * and allocated block info) prior to failure.
   */
  private def recoverPastEvents(): Unit = synchronized {
    // Insert the recovered block information
    def insertAddedBlock(receivedBlockInfo: ReceivedBlockInfo): Unit = {
      logTrace(s"Recovery: Inserting added block $receivedBlockInfo")
      receivedBlockInfo.setBlockIdInvalid()
      getReceivedBlockQueue(receivedBlockInfo.streamId) += receivedBlockInfo
    }

    // Insert the recovered block-to-batch allocations and removes them from queue of
    // received blocks.
    def insertAllocatedBatch(batchTime: Time, allocatedBlocks: AllocatedBlocks): Unit = {
      logTrace(s"Recovery: Inserting allocated batch for time $batchTime to " +
        s"${allocatedBlocks.streamIdToAllocatedBlocks}")
      allocatedBlocks.streamIdToAllocatedBlocks.foreach {
        case (streamId, allocatedBlocksInStream) =>
          getReceivedBlockQueue(streamId).dequeueAll(allocatedBlocksInStream.toSet)
      }
      timeToAllocatedBlocks.put(batchTime, allocatedBlocks)
      lastAllocatedBatchTime = batchTime
    }

    // Cleanup the batch allocations
    def cleanupBatches(batchTimes: Seq[Time]): Unit = {
      logTrace(s"Recovery: Cleaning up batches $batchTimes")
      timeToAllocatedBlocks --= batchTimes
    }

    writeAheadLogOption.foreach { writeAheadLog =>
      logInfo(s"Recovering from write ahead logs in ${checkpointDirOption.get}")
      writeAheadLog.readAll().asScala.foreach { byteBuffer =>
        logInfo("Recovering record " + byteBuffer)
        Utils.deserialize[ReceivedBlockTrackerLogEvent](
          JavaUtils.bufferToArray(byteBuffer), Thread.currentThread().getContextClassLoader) match {
          case BlockAdditionEvent(receivedBlockInfo) =>
            insertAddedBlock(receivedBlockInfo)
          case BatchAllocationEvent(time, allocatedBlocks) =>
            insertAllocatedBatch(time, allocatedBlocks)
          case BatchCleanupEvent(batchTimes) =>
            cleanupBatches(batchTimes)
        }
      }
    }
  }

  /** Write an update to the tracker to the write ahead log */
  private[streaming] def writeToLog(record: ReceivedBlockTrackerLogEvent): Boolean = {
    if (isWriteAheadLogEnabled) {
      logTrace(s"Writing record: $record")
      try {
        writeAheadLogOption.get.write(ByteBuffer.wrap(Utils.serialize(record)),
          clock.getTimeMillis())
        true
      } catch {
        case NonFatal(e) =>
          logWarning(s"Exception thrown while writing record: $record to the WriteAheadLog.", e)
          false
      }
    } else {
      true
    }
  }

  /** Get the queue of received blocks belonging to a particular stream */
  private def getReceivedBlockQueue(streamId: Int): ReceivedBlockQueue = {
    streamIdToUnallocatedBlockQueues.getOrElseUpdate(streamId, new ReceivedBlockQueue)
  }

  /** Optionally create the write ahead log manager only if the feature is enabled */
  private def createWriteAheadLog(): Option[WriteAheadLog] = {
    checkpointDirOption.map { checkpointDir =>
      val logDir = ReceivedBlockTracker.checkpointDirToLogDir(checkpointDirOption.get)
      WriteAheadLogUtils.createLogForDriver(conf, logDir, hadoopConf)
    }
  }

  /** Check if the write ahead log is enabled. This is only used for testing purposes. */
  private[streaming] def isWriteAheadLogEnabled: Boolean = writeAheadLogOption.nonEmpty
}

private[streaming] object ReceivedBlockTracker {
  def checkpointDirToLogDir(checkpointDir: String): String = {
    new Path(checkpointDir, "receivedBlockMetadata").toString
  }
}

相关信息

spark 源码目录

相关文章

spark BatchInfo 源码

spark ExecutorAllocationManager 源码

spark InputInfoTracker 源码

spark Job 源码

spark JobGenerator 源码

spark JobScheduler 源码

spark JobSet 源码

spark OutputOperationInfo 源码

spark RateController 源码

spark ReceivedBlockInfo 源码

0  赞