spark TaskResult 源码

spark TaskResult 代码

文件路径：/core/src/main/scala/org/apache/spark/scheduler/TaskResult.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.scheduler

import java.io._
import java.nio.ByteBuffer

import scala.collection.mutable.ArrayBuffer

import org.apache.spark.SparkEnv
import org.apache.spark.metrics.ExecutorMetricType
import org.apache.spark.serializer.SerializerInstance
import org.apache.spark.storage.BlockId
import org.apache.spark.util.{AccumulatorV2, Utils}

// Task result. Also contains updates to accumulator variables and executor metric peaks.
private[spark] sealed trait TaskResult[T]

/** A reference to a DirectTaskResult that has been stored in the worker's BlockManager. */
private[spark] case class IndirectTaskResult[T](blockId: BlockId, size: Int)
  extends TaskResult[T] with Serializable

/** A TaskResult that contains the task's return value, accumulator updates and metric peaks. */
private[spark] class DirectTaskResult[T](
    var valueBytes: ByteBuffer,
    var accumUpdates: Seq[AccumulatorV2[_, _]],
    var metricPeaks: Array[Long])
  extends TaskResult[T] with Externalizable {

  private var valueObjectDeserialized = false
  private var valueObject: T = _

  def this() = this(null.asInstanceOf[ByteBuffer], null,
    new Array[Long](ExecutorMetricType.numMetrics))

  override def writeExternal(out: ObjectOutput): Unit = Utils.tryOrIOException {
    out.writeInt(valueBytes.remaining)
    Utils.writeByteBuffer(valueBytes, out)
    out.writeInt(accumUpdates.size)
    accumUpdates.foreach(out.writeObject)
    out.writeInt(metricPeaks.length)
    metricPeaks.foreach(out.writeLong)
  }

  override def readExternal(in: ObjectInput): Unit = Utils.tryOrIOException {
    val blen = in.readInt()
    val byteVal = new Array[Byte](blen)
    in.readFully(byteVal)
    valueBytes = ByteBuffer.wrap(byteVal)

    val numUpdates = in.readInt
    if (numUpdates == 0) {
      accumUpdates = Seq.empty
    } else {
      val _accumUpdates = new ArrayBuffer[AccumulatorV2[_, _]]
      for (i <- 0 until numUpdates) {
        _accumUpdates += in.readObject.asInstanceOf[AccumulatorV2[_, _]]
      }
      accumUpdates = _accumUpdates.toSeq
    }

    val numMetrics = in.readInt
    if (numMetrics == 0) {
      metricPeaks = Array.empty
    } else {
      metricPeaks = new Array[Long](numMetrics)
      (0 until numMetrics).foreach { i =>
        metricPeaks(i) = in.readLong
      }
    }
    valueObjectDeserialized = false
  }

  /**
   * When `value()` is called at the first time, it needs to deserialize `valueObject` from
   * `valueBytes`. It may cost dozens of seconds for a large instance. So when calling `value` at
   * the first time, the caller should avoid to block other threads.
   *
   * After the first time, `value()` is trivial and just returns the deserialized `valueObject`.
   */
  def value(resultSer: SerializerInstance = null): T = {
    if (valueObjectDeserialized) {
      valueObject
    } else {
      // This should not run when holding a lock because it may cost dozens of seconds for a large
      // value
      val ser = if (resultSer == null) SparkEnv.get.serializer.newInstance() else resultSer
      valueObject = ser.deserialize(valueBytes)
      valueObjectDeserialized = true
      valueObject
    }
  }
}

相关信息

spark 源码目录

相关文章

spark AccumulableInfo 源码

spark ActiveJob 源码

spark AsyncEventQueue 源码

spark BarrierJobAllocationFailed 源码

spark DAGScheduler 源码

spark DAGSchedulerEvent 源码

spark DAGSchedulerSource 源码

spark EventLoggingListener 源码

spark ExecutorDecommissionInfo 源码

spark ExecutorFailuresInTaskSet 源码