spark BarrierCoordinator 源码
spark BarrierCoordinator 代码
文件路径:/core/src/main/scala/org/apache/spark/BarrierCoordinator.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.{Timer, TimerTask}
import java.util.concurrent.ConcurrentHashMap
import java.util.function.Consumer
import scala.collection.mutable.{ArrayBuffer, HashSet}
import org.apache.spark.internal.Logging
import org.apache.spark.rpc.{RpcCallContext, RpcEnv, ThreadSafeRpcEndpoint}
import org.apache.spark.scheduler.{LiveListenerBus, SparkListener, SparkListenerStageCompleted}
/**
* For each barrier stage attempt, only at most one barrier() call can be active at any time, thus
* we can use (stageId, stageAttemptId) to identify the stage attempt where the barrier() call is
* from.
*/
private case class ContextBarrierId(stageId: Int, stageAttemptId: Int) {
override def toString: String = s"Stage $stageId (Attempt $stageAttemptId)"
}
/**
* A coordinator that handles all global sync requests from BarrierTaskContext. Each global sync
* request is generated by `BarrierTaskContext.barrier()`, and identified by
* stageId + stageAttemptId + barrierEpoch. Reply all the blocking global sync requests upon
* all the requests for a group of `barrier()` calls are received. If the coordinator is unable to
* collect enough global sync requests within a configured time, fail all the requests and return
* an Exception with timeout message.
*/
private[spark] class BarrierCoordinator(
timeoutInSecs: Long,
listenerBus: LiveListenerBus,
override val rpcEnv: RpcEnv) extends ThreadSafeRpcEndpoint with Logging {
// TODO SPARK-25030 Create a Timer() in the mainClass submitted to SparkSubmit makes it unable to
// fetch result, we shall fix the issue.
private lazy val timer = new Timer("BarrierCoordinator barrier epoch increment timer")
// Listen to StageCompleted event, clear corresponding ContextBarrierState.
private val listener = new SparkListener {
override def onStageCompleted(stageCompleted: SparkListenerStageCompleted): Unit = {
val stageInfo = stageCompleted.stageInfo
val barrierId = ContextBarrierId(stageInfo.stageId, stageInfo.attemptNumber)
// Clear ContextBarrierState from a finished stage attempt.
cleanupBarrierStage(barrierId)
}
}
// Record all active stage attempts that make barrier() call(s), and the corresponding internal
// state.
private val states = new ConcurrentHashMap[ContextBarrierId, ContextBarrierState]
override def onStart(): Unit = {
super.onStart()
listenerBus.addToStatusQueue(listener)
}
override def onStop(): Unit = {
try {
states.forEachValue(1, clearStateConsumer)
states.clear()
listenerBus.removeListener(listener)
} finally {
super.onStop()
}
}
/**
* Provide the current state of a barrier() call. A state is created when a new stage attempt
* sends out a barrier() call, and recycled on stage completed.
*
* @param barrierId Identifier of the barrier stage that make a barrier() call.
* @param numTasks Number of tasks of the barrier stage, all barrier() calls from the stage shall
* collect `numTasks` requests to succeed.
*/
private class ContextBarrierState(
val barrierId: ContextBarrierId,
val numTasks: Int) {
// There may be multiple barrier() calls from a barrier stage attempt, `barrierEpoch` is used
// to identify each barrier() call. It shall get increased when a barrier() call succeeds, or
// reset when a barrier() call fails due to timeout.
private var barrierEpoch: Int = 0
// An Array of RPCCallContexts for barrier tasks that have made a blocking runBarrier() call
private val requesters: ArrayBuffer[RpcCallContext] = new ArrayBuffer[RpcCallContext](numTasks)
// Messages from each barrier task that have made a blocking runBarrier() call.
// The messages will be replied to all tasks once sync finished.
private val messages = Array.ofDim[String](numTasks)
// Request methods collected from tasks inside this barrier sync. All tasks should make sure
// that they're calling the same method within the same barrier sync phase. In other words,
// the size of requestMethods should always be 1 for a legitimate barrier sync. Otherwise,
// the barrier sync would fail if the size of requestMethods becomes greater than 1.
private val requestMethods = new HashSet[RequestMethod.Value]
// A timer task that ensures we may timeout for a barrier() call.
private var timerTask: TimerTask = null
// Init a TimerTask for a barrier() call.
private def initTimerTask(state: ContextBarrierState): Unit = {
timerTask = new TimerTask {
override def run(): Unit = state.synchronized {
// Timeout current barrier() call, fail all the sync requests.
requesters.foreach(_.sendFailure(new SparkException("The coordinator didn't get all " +
s"barrier sync requests for barrier epoch $barrierEpoch from $barrierId within " +
s"$timeoutInSecs second(s).")))
cleanupBarrierStage(barrierId)
}
}
}
// Cancel the current active TimerTask and release resources.
private def cancelTimerTask(): Unit = {
if (timerTask != null) {
timerTask.cancel()
timer.purge()
timerTask = null
}
}
// Process the global sync request. The barrier() call succeed if collected enough requests
// within a configured time, otherwise fail all the pending requests.
def handleRequest(requester: RpcCallContext, request: RequestToSync): Unit = synchronized {
val taskId = request.taskAttemptId
val epoch = request.barrierEpoch
val curReqMethod = request.requestMethod
requestMethods.add(curReqMethod)
if (requestMethods.size > 1) {
val error = new SparkException(s"Different barrier sync types found for the " +
s"sync $barrierId: ${requestMethods.mkString(", ")}. Please use the " +
s"same barrier sync type within a single sync.")
(requesters :+ requester).foreach(_.sendFailure(error))
clear()
return
}
// Require the number of tasks is correctly set from the BarrierTaskContext.
require(request.numTasks == numTasks, s"Number of tasks of $barrierId is " +
s"${request.numTasks} from Task $taskId, previously it was $numTasks.")
// Check whether the epoch from the barrier tasks matches current barrierEpoch.
logInfo(s"Current barrier epoch for $barrierId is $barrierEpoch.")
if (epoch != barrierEpoch) {
requester.sendFailure(new SparkException(s"The request to sync of $barrierId with " +
s"barrier epoch $barrierEpoch has already finished. Maybe task $taskId is not " +
"properly killed."))
} else {
// If this is the first sync message received for a barrier() call, start timer to ensure
// we may timeout for the sync.
if (requesters.isEmpty) {
initTimerTask(this)
timer.schedule(timerTask, timeoutInSecs * 1000)
}
// Add the requester to array of RPCCallContexts pending for reply.
requesters += requester
messages(request.partitionId) = request.message
logInfo(s"Barrier sync epoch $barrierEpoch from $barrierId received update from Task " +
s"$taskId, current progress: ${requesters.size}/$numTasks.")
if (requesters.size == numTasks) {
requesters.foreach(_.reply(messages))
// Finished current barrier() call successfully, clean up ContextBarrierState and
// increase the barrier epoch.
logInfo(s"Barrier sync epoch $barrierEpoch from $barrierId received all updates from " +
s"tasks, finished successfully.")
barrierEpoch += 1
requesters.clear()
requestMethods.clear()
cancelTimerTask()
}
}
}
// Cleanup the internal state of a barrier stage attempt.
def clear(): Unit = synchronized {
// The global sync fails so the stage is expected to retry another attempt, all sync
// messages come from current stage attempt shall fail.
barrierEpoch = -1
requesters.clear()
cancelTimerTask()
}
}
// Clean up the [[ContextBarrierState]] that correspond to a specific stage attempt.
private def cleanupBarrierStage(barrierId: ContextBarrierId): Unit = {
val barrierState = states.remove(barrierId)
if (barrierState != null) {
barrierState.clear()
}
}
override def receiveAndReply(context: RpcCallContext): PartialFunction[Any, Unit] = {
case request @ RequestToSync(numTasks, stageId, stageAttemptId, _, _, _, _, _) =>
// Get or init the ContextBarrierState correspond to the stage attempt.
val barrierId = ContextBarrierId(stageId, stageAttemptId)
states.computeIfAbsent(barrierId,
(key: ContextBarrierId) => new ContextBarrierState(key, numTasks))
val barrierState = states.get(barrierId)
barrierState.handleRequest(context, request)
}
private val clearStateConsumer = new Consumer[ContextBarrierState] {
override def accept(state: ContextBarrierState) = state.clear()
}
}
private[spark] sealed trait BarrierCoordinatorMessage extends Serializable
/**
* A global sync request message from BarrierTaskContext. Each request is
* identified by stageId + stageAttemptId + barrierEpoch.
*
* @param numTasks The number of global sync requests the BarrierCoordinator shall receive
* @param stageId ID of current stage
* @param stageAttemptId ID of current stage attempt
* @param taskAttemptId Unique ID of current task
* @param barrierEpoch ID of a runBarrier() call, a task may consist multiple runBarrier() calls
* @param partitionId ID of the current partition the task is assigned to
* @param message Message sent from the BarrierTaskContext
* @param requestMethod The BarrierTaskContext method that was called to trigger BarrierCoordinator
*/
private[spark] case class RequestToSync(
numTasks: Int,
stageId: Int,
stageAttemptId: Int,
taskAttemptId: Long,
barrierEpoch: Int,
partitionId: Int,
message: String,
requestMethod: RequestMethod.Value) extends BarrierCoordinatorMessage
private[spark] object RequestMethod extends Enumeration {
val BARRIER, ALL_GATHER = Value
}
相关信息
相关文章
spark ErrorClassesJSONReader 源码
spark ExecutorAllocationClient 源码
0
赞
- 所属分类: 前端技术
- 本文标签:
热门推荐
-
2、 - 优质文章
-
3、 gate.io
-
8、 golang
-
9、 openharmony
-
10、 Vue中input框自动聚焦