Github user squito commented on a diff in the pull request:
https://github.com/apache/spark/pull/15249#discussion_r82268509
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/TaskSetBlacklist.scala ---
@@ -0,0 +1,135 @@
+/*
+ * 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.{HashMap, HashSet}
+
+import org.apache.spark.SparkConf
+import org.apache.spark.internal.config
+import org.apache.spark.internal.Logging
+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.
+ *
+ * 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(val conf: SparkConf, val
stageId: Int, val clock: Clock)
+ extends Logging {
+
+ private val MAX_TASK_ATTEMPTS_PER_EXECUTOR =
conf.get(config.MAX_TASK_ATTEMPTS_PER_EXECUTOR)
+ private val MAX_TASK_ATTEMPTS_PER_NODE =
conf.get(config.MAX_TASK_ATTEMPTS_PER_NODE)
+ private val MAX_FAILURES_PER_EXEC_STAGE =
conf.get(config.MAX_FAILURES_PER_EXEC_STAGE)
+ private val MAX_FAILED_EXEC_PER_NODE_STAGE =
conf.get(config.MAX_FAILED_EXEC_PER_NODE_STAGE)
+ private val TIMEOUT_MILLIS = BlacklistTracker.getBlacklistTimeout(conf)
+
+ /**
+ * A map from each executor to the task failures on that executor.
+ */
+ val execToFailures: HashMap[String, ExecutorFailuresInTaskSet] = new
HashMap()
+
+ /**
+ * 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: HashMap[String, HashSet[String]] =
new HashMap()
+ private val nodeToBlacklistedTasks: HashMap[String, HashSet[Int]] = new
HashMap()
+ private val blacklistedExecs: HashSet[String] = new HashSet()
+ private val blacklistedNodes: HashSet[String] = new HashSet()
+
+ /**
+ * 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.
+ * 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 = {
+ nodeToBlacklistedTasks.get(node).exists(_.contains(index))
+ }
+
+ /**
+ * Return true if this executor is blacklisted for the given stage.
Completely ignores
+ * 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 = {
+ blacklistedExecs.contains(executorId)
+ }
+
+ def isNodeBlacklistedForTaskSet(node: String): Boolean = {
+ blacklistedNodes.contains(node)
+ }
+
+ private[scheduler] def updateBlacklistForFailedTask(
+ host: String,
+ exec: String,
+ index: Int): Unit = {
+ val execFailures = execToFailures.getOrElseUpdate(exec, new
ExecutorFailuresInTaskSet(host))
+ execFailures.updateWithFailure(
+ taskIndex = index,
+ failureExpiryTime = clock.getTimeMillis() + TIMEOUT_MILLIS)
+
+ // 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
=>
--- End diff --
since `execsWithFailuresOnNode` is a Set, one of the intermediate types is
a Set, and then you collapse some of the failure counts, `Set(1,1)` -->
`Set(1)` so the sum is wrong. It could be `.toSeq` instead, but that would
make an unnecessary intermediate collection. But its not a meaningful
optimization here, if you think `.toSeq` would be more clear.
makes a nice scala puzzler:
```scala
val dictionary = Map(
"a" -> Set("apple", "ant"),
"b" -> Set("banana", "barn")
)
// lets count how many times each letter occurs in all words in our
dictionary
val letters = dictionary.values.flatMap {x => x.flatMap {_.toCharArray} }
val letterCounts = letters.groupBy(identity).mapValues(_.size)
letterCounts.toArray.sorted.foreach{println}
(a,2)
(b,1)
(e,1)
(l,1)
(n,2)
(p,1)
(r,1)
(t,1)
```
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