spark BarrierTaskContext 源码

  • 2022-10-20
  • 浏览 (263)

spark BarrierTaskContext 代码

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

import java.util.{Properties, Timer, TimerTask}

import scala.collection.JavaConverters._
import scala.concurrent.duration._
import scala.util.{Failure, Success => ScalaSuccess, Try}

import org.apache.spark.annotation.{Experimental, Since}
import org.apache.spark.executor.TaskMetrics
import org.apache.spark.internal.Logging
import org.apache.spark.memory.TaskMemoryManager
import org.apache.spark.metrics.source.Source
import org.apache.spark.resource.ResourceInformation
import org.apache.spark.rpc.{RpcEndpointRef, RpcTimeout}
import org.apache.spark.shuffle.FetchFailedException
import org.apache.spark.util._

/**
 * :: Experimental ::
 * A [[TaskContext]] with extra contextual info and tooling for tasks in a barrier stage.
 * Use [[BarrierTaskContext#get]] to obtain the barrier context for a running barrier task.
 */
@Experimental
@Since("2.4.0")
class BarrierTaskContext private[spark] (
    taskContext: TaskContext) extends TaskContext with Logging {

  import BarrierTaskContext._

  // Find the driver side RPCEndpointRef of the coordinator that handles all the barrier() calls.
  private val barrierCoordinator: RpcEndpointRef = {
    val env = SparkEnv.get
    RpcUtils.makeDriverRef("barrierSync", env.conf, env.rpcEnv)
  }

  // Local barrierEpoch that identify a barrier() call from current task, it shall be identical
  // with the driver side epoch.
  private var barrierEpoch = 0

  private def runBarrier(message: String, requestMethod: RequestMethod.Value): Array[String] = {
    logInfo(s"Task $taskAttemptId from Stage $stageId(Attempt $stageAttemptNumber) has entered " +
      s"the global sync, current barrier epoch is $barrierEpoch.")
    logTrace("Current callSite: " + Utils.getCallSite())

    val startTime = System.currentTimeMillis()
    val timerTask = new TimerTask {
      override def run(): Unit = {
        logInfo(s"Task $taskAttemptId from Stage $stageId(Attempt $stageAttemptNumber) waiting " +
          s"under the global sync since $startTime, has been waiting for " +
          s"${MILLISECONDS.toSeconds(System.currentTimeMillis() - startTime)} seconds, " +
          s"current barrier epoch is $barrierEpoch.")
      }
    }
    // Log the update of global sync every 60 seconds.
    timer.schedule(timerTask, 60000, 60000)

    try {
      val abortableRpcFuture = barrierCoordinator.askAbortable[Array[String]](
        message = RequestToSync(numPartitions, stageId, stageAttemptNumber, taskAttemptId,
          barrierEpoch, partitionId, message, requestMethod),
        // Set a fixed timeout for RPC here, so users shall get a SparkException thrown by
        // BarrierCoordinator on timeout, instead of RPCTimeoutException from the RPC framework.
        timeout = new RpcTimeout(365.days, "barrierTimeout"))

      // Wait the RPC future to be completed, but every 1 second it will jump out waiting
      // and check whether current spark task is killed. If killed, then throw
      // a `TaskKilledException`, otherwise continue wait RPC until it completes.

      while (!abortableRpcFuture.future.isCompleted) {
        try {
          // wait RPC future for at most 1 second
          Thread.sleep(1000)
        } catch {
          case _: InterruptedException => // task is killed by driver
        } finally {
          Try(taskContext.killTaskIfInterrupted()) match {
            case ScalaSuccess(_) => // task is still running healthily
            case Failure(e) => abortableRpcFuture.abort(e)
          }
        }
      }
      // messages which consist of all barrier tasks' messages. The future will return the
      // desired messages if it is completed successfully. Otherwise, exception could be thrown.
      val messages = abortableRpcFuture.future.value.get.get

      barrierEpoch += 1
      logInfo(s"Task $taskAttemptId from Stage $stageId(Attempt $stageAttemptNumber) finished " +
        "global sync successfully, waited for " +
        s"${MILLISECONDS.toSeconds(System.currentTimeMillis() - startTime)} seconds, " +
        s"current barrier epoch is $barrierEpoch.")
      messages
    } catch {
      case e: SparkException =>
        logInfo(s"Task $taskAttemptId from Stage $stageId(Attempt $stageAttemptNumber) failed " +
          "to perform global sync, waited for " +
          s"${MILLISECONDS.toSeconds(System.currentTimeMillis() - startTime)} seconds, " +
          s"current barrier epoch is $barrierEpoch.")
        throw e
    } finally {
      timerTask.cancel()
      timer.purge()
    }
  }

  /**
   * :: Experimental ::
   * Sets a global barrier and waits until all tasks in this stage hit this barrier. Similar to
   * MPI_Barrier function in MPI, the barrier() function call blocks until all tasks in the same
   * stage have reached this routine.
   *
   * CAUTION! In a barrier stage, each task must have the same number of barrier() calls, in all
   * possible code branches. Otherwise, you may get the job hanging or a SparkException after
   * timeout. Some examples of '''misuses''' are listed below:
   * 1. Only call barrier() function on a subset of all the tasks in the same barrier stage, it
   * shall lead to timeout of the function call.
   * {{{
   *   rdd.barrier().mapPartitions { iter =>
   *       val context = BarrierTaskContext.get()
   *       if (context.partitionId() == 0) {
   *           // Do nothing.
   *       } else {
   *           context.barrier()
   *       }
   *       iter
   *   }
   * }}}
   *
   * 2. Include barrier() function in a try-catch code block, this may lead to timeout of the
   * second function call.
   * {{{
   *   rdd.barrier().mapPartitions { iter =>
   *       val context = BarrierTaskContext.get()
   *       try {
   *           // Do something that might throw an Exception.
   *           doSomething()
   *           context.barrier()
   *       } catch {
   *           case e: Exception => logWarning("...", e)
   *       }
   *       context.barrier()
   *       iter
   *   }
   * }}}
   */
  @Experimental
  @Since("2.4.0")
  def barrier(): Unit = runBarrier("", RequestMethod.BARRIER)

  /**
   * :: Experimental ::
   * Blocks until all tasks in the same stage have reached this routine. Each task passes in
   * a message and returns with a list of all the messages passed in by each of those tasks.
   *
   * CAUTION! The allGather method requires the same precautions as the barrier method
   *
   * The message is type String rather than Array[Byte] because it is more convenient for
   * the user at the cost of worse performance.
   */
  @Experimental
  @Since("3.0.0")
  def allGather(message: String): Array[String] = runBarrier(message, RequestMethod.ALL_GATHER)

  /**
   * :: Experimental ::
   * Returns [[BarrierTaskInfo]] for all tasks in this barrier stage, ordered by partition ID.
   */
  @Experimental
  @Since("2.4.0")
  def getTaskInfos(): Array[BarrierTaskInfo] = {
    val addressesStr = Option(taskContext.getLocalProperty("addresses")).getOrElse("")
    addressesStr.split(",").map(_.trim()).map(new BarrierTaskInfo(_))
  }

  // delegate methods

  override def isCompleted(): Boolean = taskContext.isCompleted()

  override def isInterrupted(): Boolean = taskContext.isInterrupted()

  override def addTaskCompletionListener(listener: TaskCompletionListener): this.type = {
    taskContext.addTaskCompletionListener(listener)
    this
  }

  override def addTaskFailureListener(listener: TaskFailureListener): this.type = {
    taskContext.addTaskFailureListener(listener)
    this
  }

  override def stageId(): Int = taskContext.stageId()

  override def stageAttemptNumber(): Int = taskContext.stageAttemptNumber()

  override def partitionId(): Int = taskContext.partitionId()

  override def numPartitions(): Int = taskContext.numPartitions()

  override def attemptNumber(): Int = taskContext.attemptNumber()

  override def taskAttemptId(): Long = taskContext.taskAttemptId()

  override def getLocalProperty(key: String): String = taskContext.getLocalProperty(key)

  override def taskMetrics(): TaskMetrics = taskContext.taskMetrics()

  override def getMetricsSources(sourceName: String): Seq[Source] = {
    taskContext.getMetricsSources(sourceName)
  }

  override def cpus(): Int = taskContext.cpus()

  override def resources(): Map[String, ResourceInformation] = taskContext.resources()

  override def resourcesJMap(): java.util.Map[String, ResourceInformation] = {
    resources().asJava
  }

  override private[spark] def killTaskIfInterrupted(): Unit = taskContext.killTaskIfInterrupted()

  override private[spark] def getKillReason(): Option[String] = taskContext.getKillReason()

  override private[spark] def taskMemoryManager(): TaskMemoryManager = {
    taskContext.taskMemoryManager()
  }

  override private[spark] def registerAccumulator(a: AccumulatorV2[_, _]): Unit = {
    taskContext.registerAccumulator(a)
  }

  override private[spark] def setFetchFailed(fetchFailed: FetchFailedException): Unit = {
    taskContext.setFetchFailed(fetchFailed)
  }

  override private[spark] def markInterrupted(reason: String): Unit = {
    taskContext.markInterrupted(reason)
  }

  override private[spark] def markTaskFailed(error: Throwable): Unit = {
    taskContext.markTaskFailed(error)
  }

  override private[spark] def markTaskCompleted(error: Option[Throwable]): Unit = {
    taskContext.markTaskCompleted(error)
  }

  override private[spark] def fetchFailed: Option[FetchFailedException] = {
    taskContext.fetchFailed
  }

  override private[spark] def getLocalProperties: Properties = taskContext.getLocalProperties
}

@Experimental
@Since("2.4.0")
object BarrierTaskContext {
  /**
   * :: Experimental ::
   * Returns the currently active BarrierTaskContext. This can be called inside of user functions to
   * access contextual information about running barrier tasks.
   */
  @Experimental
  @Since("2.4.0")
  def get(): BarrierTaskContext = TaskContext.get().asInstanceOf[BarrierTaskContext]

  private val timer = new Timer("Barrier task timer for barrier() calls.")

}

相关信息

spark 源码目录

相关文章

spark Aggregator 源码

spark BarrierCoordinator 源码

spark BarrierTaskInfo 源码

spark ContextAwareIterator 源码

spark ContextCleaner 源码

spark Dependency 源码

spark ErrorClassesJSONReader 源码

spark ExecutorAllocationClient 源码

spark ExecutorAllocationManager 源码

spark FutureAction 源码

0  赞