Github user mwws commented on a diff in the pull request:

    https://github.com/apache/spark/pull/8760#discussion_r42199960
  
    --- Diff: 
core/src/main/scala/org/apache/spark/scheduler/BlacklistTracker.scala ---
    @@ -0,0 +1,243 @@
    +/*
    + * 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.util.concurrent.TimeUnit
    +
    +import scala.collection.mutable
    +
    +import org.apache.spark.SparkConf
    +import org.apache.spark.Success
    +import org.apache.spark.TaskEndReason
    +import org.apache.spark.annotation.DeveloperApi
    +import org.apache.spark.util.SystemClock
    +import org.apache.spark.util.ThreadUtils
    +import org.apache.spark.util.Utils
    +
    +
    +/**
    + * BlacklistTracker is design to track problematic executors and node on 
application level.
    + * It is shared by all TaskSet, so that once a new TaskSet coming, it 
could be benefit from
    + * previous experience of other TaskSet.
    + *
    + * Once task finished, the callback method in TaskSetManager should update
    + * executorIdToFailureStatus Map.
    + */
    +private[spark] class BlacklistTracker(sparkConf: SparkConf) extends 
WithCache{
    +  // maintain a ExecutorId --> FailureStatus HashMap
    +  private val executorIdToFailureStatus: mutable.HashMap[String, 
FailureStatus] = mutable.HashMap()
    +
    +  // Apply Strategy pattern here to change different blacklist detection 
logic
    +  private val strategy = BlacklistStrategy(sparkConf)
    +
    +  // A daemon thread to expire blacklist executor periodically
    +  private val scheduler = 
ThreadUtils.newDaemonSingleThreadScheduledExecutor(
    +      "spark-scheduler-blacklist-expire-timer")
    +
    +  private val clock = new SystemClock()
    +
    +  private val enableBlacklistSpeculate = sparkConf.getBoolean(
    +    "spark.scheduler.blacklist.speculate", false)
    +
    +  private val recoverPeriod = sparkConf.getLong(
    +    "spark.scheduler.blacklist.recoverPeriod", 60L)
    +
    +  def start(): Unit = {
    +    val scheduleTask = new Runnable() {
    +      override def run(): Unit = {
    +        
Utils.logUncaughtExceptions(expireExecutorsInBlackList(executorIdToFailureStatus))
    +      }
    +    }
    +    scheduler.scheduleAtFixedRate(scheduleTask, 0L, recoverPeriod, 
TimeUnit.SECONDS)
    +  }
    +
    +  def stop(): Unit = {
    +    scheduler.shutdown()
    +    scheduler.awaitTermination(10, TimeUnit.SECONDS)
    +  }
    +
    +  // The actual implementation is delegated to strategy
    +  private def expireExecutorsInBlackList(
    +      executorIdToFailureStatus: mutable.HashMap[String, FailureStatus]): 
Unit = synchronized {
    +    strategy.expireExecutorsInBlackList(executorIdToFailureStatus)
    +
    +    invalidAllCache()
    +  }
    +
    +  def updateFailureExecutors(info: TaskInfo, reason: TaskEndReason) : Unit 
= synchronized {
    +    reason match {
    +      // If task succeeding, remove related record from 
executorIdToFailureStatus
    +      case Success =>
    +        removeFailureExecutorsForTaskId(info.executorId, info.taskId)
    +
    +      // If task failing, update latest failure time and failedTaskIds
    +      case _ =>
    +        val executorId = info.executorId
    +        executorIdToFailureStatus.get(executorId) match {
    +          case Some(failureStatus) =>
    +            failureStatus.updatedTime = clock.getTimeMillis()
    +            val failedTimes = 
failureStatus.numFailuresPerTask.getOrElse(info.taskId, 0) + 1
    +            failureStatus.numFailuresPerTask.update(info.taskId, 
failedTimes)
    +          case None =>
    +            val failedTasks = mutable.HashMap(info.taskId -> 1)
    +            val failureStatus = new FailureStatus(
    +              clock.getTimeMillis(),
    +              info.host,
    +              failedTasks)
    +            executorIdToFailureStatus.update(executorId, failureStatus)
    +        }
    +        invalidAllCache()
    +    }
    +  }
    +
    +  // remove the executorId from executorIdToFailureStatus
    +  def removeFailureExecutors(executorId: String) : Unit = synchronized {
    +    executorIdToFailureStatus.remove(executorId)
    +    invalidAllCache()
    +  }
    +
    +  // remove the failure record related to given taskId from 
executorIdToFailureStatus. If the
    +  // number of records of given executorId becomes 0, remove the completed 
executorId.
    +  def removeFailureExecutorsForTaskId(
    +      executorId: String,
    +      taskId: Long) : Unit = synchronized {
    +    executorIdToFailureStatus.get(executorId).map(fs => {
    +      fs.numFailuresPerTask.remove(taskId)
    +      if(fs.numFailuresPerTask.isEmpty){
    +        executorIdToFailureStatus.remove(executorId)
    +      }
    +      invalidAllCache()
    +    })
    +  }
    +
    +  def executorIsBlacklisted(
    +      executorId: String,
    +      sched: TaskSchedulerImpl,
    +      taskId: Long) : Boolean = {
    +
    +    executorBlacklist(sched, taskId).contains(executorId)
    +  }
    +
    +  // If the node is in blacklist, all executors allocated on that node will
    +  // also be put into  executor blacklist.
    +  // By default it's turned off, user can enable it in sparkConf.
    +  private def speculationFailedExecutor(
    +      sched: TaskSchedulerImpl): Set[String] = {
    +    if (!enableBlacklistSpeculate) {
    +      Set.empty[String]
    +    } else {
    +      nodeBlacklist().flatMap(sched.getExecutorsAliveOnHost(_)
    +        .getOrElse(Set.empty[String])).toSet
    +    }
    +  }
    +
    +  def executorBlacklist(
    +      sched: TaskSchedulerImpl,
    +      taskId: Long): Set[String] = synchronized {
    +    if (!isBlacklistExecutorCacheValid) {
    +      reEvaluateExecutorBlacklistAndUpdateCache(sched, taskId)
    +    } else {
    +      getExecutorBlacklistFromCache(taskId).getOrElse {
    +        reEvaluateExecutorBlacklistAndUpdateCache(sched, taskId)
    +      }
    +    }
    +  }
    +
    +  private def reEvaluateExecutorBlacklistAndUpdateCache(
    +      sched: TaskSchedulerImpl,
    +      taskId: Long): Set[String] = {
    +    val executors = speculationFailedExecutor(sched) ++
    +      strategy.getExecutorBlacklist(executorIdToFailureStatus, taskId)
    +    updateBlacklistExecutorCache(taskId, executors)
    +    executors
    +  }
    +
    +  // The actual implementation is delegated to strategy
    +  def nodeBlacklist(): Set[String] = synchronized {
    +    if (isBlacklistNodeCacheValid) {
    +      getNodeBlacklistFromCache
    +    } else {
    +      val nodes = strategy.getNodeBlacklist(executorIdToFailureStatus)
    +      updateBlacklistNodeCache(nodes)
    +      nodes
    +    }
    +  }
    +}
    +
    +// Hide cache details in this trait to make code clean and avoid operation 
mistake
    +trait WithCache {
    --- End diff --
    
    Sure, will do


---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at infrastruct...@apache.org or file a JIRA ticket
with INFRA.
---

---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org

Reply via email to