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From mwws <...@git.apache.org>
Subject [GitHub] spark pull request: [Spark-8426] [scheduler] enhance blacklist mec...
Date Thu, 05 Nov 2015 02:38:15 GMT
Github user mwws commented on a diff in the pull request:

    https://github.com/apache/spark/pull/8760#discussion_r43970555
  
    --- Diff: core/src/main/scala/org/apache/spark/scheduler/BlacklistStrategy.scala ---
    @@ -0,0 +1,145 @@
    +/*
    + * 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 scala.collection.mutable
    +import org.apache.spark.Logging
    +import org.apache.spark.SparkConf
    +import org.apache.spark.util.SystemClock
    +import org.apache.spark.util.Clock
    +
    +/**
    + * The interface to determine executor blacklist and node blacklist.
    + */
    +private [scheduler] trait BlacklistStrategy {
    +  /** Defined a time interval to expire failure information of executors */
    +  val expireTimeInMilliseconds: Long
    +
    +  /** Return executors in blacklist which are related to given taskIndex */
    +  def getExecutorBlacklist(
    +      executorIdToFailureStatus: mutable.HashMap[String, FailureStatus],
    +      taskIndex: Int, clock: Clock): Set[String]
    +
    +  /** Return all nodes in blacklist */
    +  def getNodeBlacklist(
    +      executorIdToFailureStatus: mutable.HashMap[String, FailureStatus]): Set[String]
    +
    +  /**
    +   * Default implementation to remove failure executors from HashMap based on given time
period.
    +   * The return value identity whether or not it updated anything
    +   */
    +  def expireExecutorsInBlackList(
    +      executorIdToFailureStatus: mutable.HashMap[String, FailureStatus], clock: Clock):
Boolean = {
    +    val now = clock.getTimeMillis()
    +    val expiredKey = executorIdToFailureStatus.filter {
    +      case (executorid, failureStatus) => {
    +        (now - failureStatus.updatedTime) >= expireTimeInMilliseconds
    +      }
    +    }.keySet
    +
    +    if (expiredKey.isEmpty) {
    +      false
    +    } else {
    +      executorIdToFailureStatus --= expiredKey
    +      true
    +    }
    +  }
    +}
    +
    +/**
    + * This strategy is simply based on given threshold and is taskId unrelated. An executor
will be
    + * in blacklist, if it failed more than "maxFailureTaskNumber" times. A node will be
in blacklist,
    + * if there are more than "maxBlackExecutorNumber" executors on it in executor blacklist.
    + *
    + * In this case, provided taskId will be ignored. The benefit for taskId unrelated strategy
is that
    + * different taskSets can learn experience from other taskSet to avoid allocating tasks
on
    + * problematic executors.
    + */
    +private[scheduler] class SimpleStrategy(
    +    maxFailureTaskNumber: Int,
    +    maxBlackExecutorNumber: Int,
    +    val expireTimeInMilliseconds: Long
    +  )extends BlacklistStrategy {
    +
    +  private def getSelectedExecutorMap(
    +      executorIdToFailureStatus: mutable.HashMap[String, FailureStatus]) = {
    +    executorIdToFailureStatus.filter{
    +      case (id, failureStatus) => failureStatus.totalNumFailures > maxFailureTaskNumber
    +    }
    +  }
    +
    +  // As this is a taskId unrelated strategy, the input taskId will be ignored
    +  def getExecutorBlacklist(
    +      executorIdToFailureStatus: mutable.HashMap[String, FailureStatus],
    +      taskIndex: Int, clock: Clock): Set[String] = {
    +    getSelectedExecutorMap(executorIdToFailureStatus).keys.toSet
    +  }
    +
    +  def getNodeBlacklist(
    +      executorIdToFailureStatus: mutable.HashMap[String, FailureStatus]): Set[String]
= {
    +    getSelectedExecutorMap(executorIdToFailureStatus)
    +      .groupBy{case (id, failureStatus) => failureStatus.host}
    +      .filter {case (host, executorIdToFailureStatus) =>
    +        executorIdToFailureStatus.size > maxBlackExecutorNumber}
    +      .keys.toSet
    +  }
    +}
    +
    +/**
    + * This strategy is applied as default to keep the same semantics as original. It's an
taskId
    + * related strategy. If an executor failed running "task A", then we think this executor
is
    + * blacked for "task A". And we think the executor is still healthy for other task. node
blacklist
    + * is always empty.
    + *
    + * It was the standard behavior before spark 1.6
    + */
    +private[scheduler] class DefaultStrategy(
    +    val expireTimeInMilliseconds: Long) extends BlacklistStrategy {
    +  def getExecutorBlacklist(
    +      executorIdToFailureStatus: mutable.HashMap[String, FailureStatus],
    +      taskIndex: Int, clock: Clock): Set[String] = {
    +    executorIdToFailureStatus.filter{
    +      case (_, failureStatus) => failureStatus.numFailuresPerTask.keySet.contains(taskIndex)
&&
    +        clock.getTimeMillis() - failureStatus.updatedTime < expireTimeInMilliseconds
    +    }.keys.toSet
    +  }
    +
    +  def getNodeBlacklist(
    +      executorIdToFailureStatus: mutable.HashMap[String, FailureStatus]): Set[String]
=
    +        Set.empty[String]
    +}
    +
    +/**
    + * Create BlacklistStrategy instance according to SparkConf
    + */
    +private[scheduler] object BlacklistStrategy {
    +  def apply(sparkConf: SparkConf): BlacklistStrategy = {
    +    val timeout = sparkConf.getLong("spark.scheduler.executorTaskBlacklistTime", 0L)
    --- End diff --
    
    use *getTimeAsMs* instead and I think time unit could be automatically converted "s <-->
ms <--> us " by this method, so it's not necessary to divide 1000 here.


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