Fetching contributors…
Cannot retrieve contributors at this time
158 lines (142 sloc) 7.07 KB
* 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
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* See the License for the specific language governing permissions and
* limitations under the License.
package org.apache.spark.scheduler
import scala.collection.mutable.{HashMap, HashSet}
import org.apache.spark.SparkConf
import org.apache.spark.internal.Logging
import org.apache.spark.internal.config
import org.apache.spark.util.Clock
* Handles blacklisting executors and nodes within a taskset. This includes blacklisting specific
* (task, executor) / (task, nodes) pairs, and also completely blacklisting executors and nodes
* for the entire taskset.
* It also must store sufficient information in task failures for application level blacklisting,
* which is handled by [[BlacklistTracker]]. Note that BlacklistTracker does not know anything
* about task failures until a taskset completes successfully.
* THREADING: This class is a helper to [[TaskSetManager]]; as with the methods in
* [[TaskSetManager]] this class is designed only to be called from code with a lock on the
* TaskScheduler (e.g. its event handlers). It should not be called from other threads.
private[scheduler] class TaskSetBlacklist(
private val listenerBus: LiveListenerBus,
val conf: SparkConf,
val stageId: Int,
val stageAttemptId: Int,
val clock: Clock) extends Logging {
* A map from each executor to the task failures on that executor. This is used for blacklisting
* within this taskset, and it is also relayed onto [[BlacklistTracker]] for app-level
* blacklisting if this taskset completes successfully.
val execToFailures = new HashMap[String, ExecutorFailuresInTaskSet]()
* Map from node to all executors on it with failures. Needed because we want to know about
* executors on a node even after they have died. (We don't want to bother tracking the
* node -> execs mapping in the usual case when there aren't any failures).
private val nodeToExecsWithFailures = new HashMap[String, HashSet[String]]()
private val nodeToBlacklistedTaskIndexes = new HashMap[String, HashSet[Int]]()
private val blacklistedExecs = new HashSet[String]()
private val blacklistedNodes = new HashSet[String]()
private var latestFailureReason: String = null
* Get the most recent failure reason of this TaskSet.
* @return
def getLatestFailureReason: String = {
* Return true if this executor is blacklisted for the given task. This does *not*
* need to return true if the executor is blacklisted for the entire stage, or blacklisted
* for the entire application. That is to keep this method as fast as possible in the inner-loop
* of the scheduler, where those filters will have already been applied.
def isExecutorBlacklistedForTask(executorId: String, index: Int): Boolean = {
execToFailures.get(executorId).exists { execFailures =>
execFailures.getNumTaskFailures(index) >= MAX_TASK_ATTEMPTS_PER_EXECUTOR
def isNodeBlacklistedForTask(node: String, index: Int): Boolean = {
* Return true if this executor is blacklisted for the given stage. Completely ignores whether
* the executor is blacklisted for the entire application (or anything to do with the node the
* executor is on). That is to keep this method as fast as possible in the inner-loop of the
* scheduler, where those filters will already have been applied.
def isExecutorBlacklistedForTaskSet(executorId: String): Boolean = {
def isNodeBlacklistedForTaskSet(node: String): Boolean = {
private[scheduler] def updateBlacklistForFailedTask(
host: String,
exec: String,
index: Int,
failureReason: String): Unit = {
latestFailureReason = failureReason
val execFailures = execToFailures.getOrElseUpdate(exec, new ExecutorFailuresInTaskSet(host))
execFailures.updateWithFailure(index, clock.getTimeMillis())
// check if this task has also failed on other executors on the same host -- if its gone
// over the limit, blacklist this task from the entire host.
val execsWithFailuresOnNode = nodeToExecsWithFailures.getOrElseUpdate(host, new HashSet())
execsWithFailuresOnNode += exec
val failuresOnHost = execsWithFailuresOnNode.toIterator.flatMap { exec =>
execToFailures.get(exec).map { failures =>
// We count task attempts here, not the number of unique executors with failures. This is
// because jobs are aborted based on the number task attempts; if we counted unique
// executors, it would be hard to config to ensure that you try another
// node before hitting the max number of task failures.
if (failuresOnHost >= MAX_TASK_ATTEMPTS_PER_NODE) {
nodeToBlacklistedTaskIndexes.getOrElseUpdate(host, new HashSet()) += index
// Check if enough tasks have failed on the executor to blacklist it for the entire stage.
val numFailures = execFailures.numUniqueTasksWithFailures
if (numFailures >= MAX_FAILURES_PER_EXEC_STAGE) {
if (blacklistedExecs.add(exec)) {
logInfo(s"Blacklisting executor ${exec} for stage $stageId")
// This executor has been pushed into the blacklist for this stage. Let's check if it
// pushes the whole node into the blacklist.
val blacklistedExecutorsOnNode =
val now = clock.getTimeMillis()
SparkListenerExecutorBlacklistedForStage(now, exec, numFailures, stageId, stageAttemptId))
val numFailExec = blacklistedExecutorsOnNode.size
if (blacklistedNodes.add(host)) {
logInfo(s"Blacklisting ${host} for stage $stageId")
SparkListenerNodeBlacklistedForStage(now, host, numFailExec, stageId, stageAttemptId))