Github user squito commented on a diff in the pull request:
https://github.com/apache/spark/pull/6870#discussion_r33729664
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/ExecutorBlacklistTracker.scala
---
@@ -0,0 +1,175 @@
+/*
+ * 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._
+import org.apache.spark.util.{Clock, SystemClock, ThreadUtils, Utils}
+
+/**
+ * ExecutorBlacklistTracker blacklists the executors by tracking the
status of running tasks with
+ * heuristic algorithm.
+ *
+ * A executor will be considered bad enough only when:
+ * 1. The failure task number on this executor is more than
+ * spark.scheduler.blacklist.executorFaultThreshold.
+ * 2. The failure task number on this executor is
+ * spark.scheduler.blacklist.averageBlacklistThreshold more than
average failure task number
+ * of this cluster.
+ *
+ * Also max number of blacklisted executors will not exceed the
+ * spark.scheduler.blacklist.maxBlacklistFraction of whole cluster, and
blacklisted executors
+ * will be forgiven when there is no failure tasks in the
+ * spark.scheduler.blacklist.executorFaultTimeoutWindowInMinutes.
+ */
+private[spark] class ExecutorBlacklistTracker(conf: SparkConf) extends
SparkListener {
+ import ExecutorBlacklistTracker._
+
+ private val maxBlacklistFraction = conf.getDouble(
+ "spark.scheduler.blacklist.maxBlacklistFraction",
MAX_BLACKLIST_FRACTION)
+ private val avgBlacklistThreshold = conf.getDouble(
+ "spark.scheduler.blacklist.averageBlacklistThreshold",
AVERAGE_BLACKLIST_THRESHOLD)
+ private val executorFaultThreshold = conf.getInt(
+ "spark.scheduler.blacklist.executorFaultThreshold",
EXECUTOR_FAULT_THRESHOLD)
+ private val executorFaultTimeoutWindowInMinutes = conf.getInt(
+ "spark.scheduler.blacklist.executorFaultTimeoutWindowInMinutes",
EXECUTOR_FAULT_TIMEOUT_WINDOW)
+
+ // Count the number of executors registered
+ var numExecutorsRegistered: Int = 0
+
+ // Track the number of failure tasks and time of latest failure to
executor id
+ val executorIdToTaskFailures = new mutable.HashMap[String,
ExecutorFailureStatus]()
+
+ // Clock used to update and exclude the executors which are out of time
window.
+ private var clock: Clock = new SystemClock()
+
+ // Executor that handles the scheduling task
+ private val executor =
ThreadUtils.newDaemonSingleThreadScheduledExecutor(
+ "spark-scheduler-blacklist-expire-timer")
+
+ def start(): Unit = {
+ val scheduleTask = new Runnable() {
+ override def run(): Unit = {
+ Utils.logUncaughtExceptions(expireTimeoutExecutorBlacklist())
+ }
+ }
+ executor.scheduleAtFixedRate(scheduleTask, 0L, 60, TimeUnit.SECONDS)
+ }
+
+ def stop(): Unit = {
+ executor.shutdown()
+ executor.awaitTermination(10, TimeUnit.SECONDS)
+ }
+
+ def setClock(newClock: Clock): Unit = {
+ clock = newClock
+ }
+
+ def getExecutorBlacklist: Set[String] = synchronized {
+ executorIdToTaskFailures.filter(_._2.isBlackListed).keys.toSet
--- End diff --
this gets called a lot, and (hopefully) is updated only rarely. It should
probably be computed only when it changes, and then stored. (Also I think the
stored value could probably just be `@volatile`, you wouldn't need to
synchronize ... but I'm not 100% sure ...)
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