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[SPARK-17675][CORE] Expand Blacklist for TaskSets
## What changes were proposed in this pull request? This is a step along the way to SPARK-8425. To enable incremental review, the first step proposed here is to expand the blacklisting within tasksets. In particular, this will enable blacklisting for * (task, executor) pairs (this already exists via an undocumented config) * (task, node) * (taskset, executor) * (taskset, node) Adding (task, node) is critical to making spark fault-tolerant of one-bad disk in a cluster, without requiring careful tuning of "spark.task.maxFailures". The other additions are also important to avoid many misleading task failures and long scheduling delays when there is one bad node on a large cluster. Note that some of the code changes here aren't really required for just this -- they put pieces in place for SPARK-8425 even though they are not used yet (eg. the `BlacklistTracker` helper is a little out of place, `TaskSetBlacklist` holds onto a little more info than it needs to for just this change, and `ExecutorFailuresInTaskSet` is more complex than it needs to be). ## How was this patch tested? Added unit tests, run tests via jenkins. Author: Imran Rashid <[email protected]> Author: mwws <[email protected]> Closes apache#15249 from squito/taskset_blacklist_only.
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core/src/main/scala/org/apache/spark/scheduler/BlacklistTracker.scala
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/* | ||
* 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. | ||
*/ | ||
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package org.apache.spark.scheduler | ||
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import org.apache.spark.SparkConf | ||
import org.apache.spark.internal.Logging | ||
import org.apache.spark.internal.config | ||
import org.apache.spark.util.Utils | ||
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private[scheduler] object BlacklistTracker extends Logging { | ||
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private val DEFAULT_TIMEOUT = "1h" | ||
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/** | ||
* Returns true if the blacklist is enabled, based on checking the configuration in the following | ||
* order: | ||
* 1. Is it specifically enabled or disabled? | ||
* 2. Is it enabled via the legacy timeout conf? | ||
* 3. Default is off | ||
*/ | ||
def isBlacklistEnabled(conf: SparkConf): Boolean = { | ||
conf.get(config.BLACKLIST_ENABLED) match { | ||
case Some(enabled) => | ||
enabled | ||
case None => | ||
// if they've got a non-zero setting for the legacy conf, always enable the blacklist, | ||
// otherwise, use the default. | ||
val legacyKey = config.BLACKLIST_LEGACY_TIMEOUT_CONF.key | ||
conf.get(config.BLACKLIST_LEGACY_TIMEOUT_CONF).exists { legacyTimeout => | ||
if (legacyTimeout == 0) { | ||
logWarning(s"Turning off blacklisting due to legacy configuration: $legacyKey == 0") | ||
false | ||
} else { | ||
logWarning(s"Turning on blacklisting due to legacy configuration: $legacyKey > 0") | ||
true | ||
} | ||
} | ||
} | ||
} | ||
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def getBlacklistTimeout(conf: SparkConf): Long = { | ||
conf.get(config.BLACKLIST_TIMEOUT_CONF).getOrElse { | ||
conf.get(config.BLACKLIST_LEGACY_TIMEOUT_CONF).getOrElse { | ||
Utils.timeStringAsMs(DEFAULT_TIMEOUT) | ||
} | ||
} | ||
} | ||
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/** | ||
* Verify that blacklist configurations are consistent; if not, throw an exception. Should only | ||
* be called if blacklisting is enabled. | ||
* | ||
* The configuration for the blacklist is expected to adhere to a few invariants. Default | ||
* values follow these rules of course, but users may unwittingly change one configuration | ||
* without making the corresponding adjustment elsewhere. This ensures we fail-fast when | ||
* there are such misconfigurations. | ||
*/ | ||
def validateBlacklistConfs(conf: SparkConf): Unit = { | ||
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def mustBePos(k: String, v: String): Unit = { | ||
throw new IllegalArgumentException(s"$k was $v, but must be > 0.") | ||
} | ||
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Seq( | ||
config.MAX_TASK_ATTEMPTS_PER_EXECUTOR, | ||
config.MAX_TASK_ATTEMPTS_PER_NODE, | ||
config.MAX_FAILURES_PER_EXEC_STAGE, | ||
config.MAX_FAILED_EXEC_PER_NODE_STAGE | ||
).foreach { config => | ||
val v = conf.get(config) | ||
if (v <= 0) { | ||
mustBePos(config.key, v.toString) | ||
} | ||
} | ||
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val timeout = getBlacklistTimeout(conf) | ||
if (timeout <= 0) { | ||
// first, figure out where the timeout came from, to include the right conf in the message. | ||
conf.get(config.BLACKLIST_TIMEOUT_CONF) match { | ||
case Some(t) => | ||
mustBePos(config.BLACKLIST_TIMEOUT_CONF.key, timeout.toString) | ||
case None => | ||
mustBePos(config.BLACKLIST_LEGACY_TIMEOUT_CONF.key, timeout.toString) | ||
} | ||
} | ||
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val maxTaskFailures = conf.get(config.MAX_TASK_FAILURES) | ||
val maxNodeAttempts = conf.get(config.MAX_TASK_ATTEMPTS_PER_NODE) | ||
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if (maxNodeAttempts >= maxTaskFailures) { | ||
throw new IllegalArgumentException(s"${config.MAX_TASK_ATTEMPTS_PER_NODE.key} " + | ||
s"( = ${maxNodeAttempts}) was >= ${config.MAX_TASK_FAILURES.key} " + | ||
s"( = ${maxTaskFailures} ). Though blacklisting is enabled, with this configuration, " + | ||
s"Spark will not be robust to one bad node. Decrease " + | ||
s"${config.MAX_TASK_ATTEMPTS_PER_NODE.key}, increase ${config.MAX_TASK_FAILURES.key}, " + | ||
s"or disable blacklisting with ${config.BLACKLIST_ENABLED.key}") | ||
} | ||
} | ||
} |
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core/src/main/scala/org/apache/spark/scheduler/ExecutorFailuresInTaskSet.scala
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/* | ||
* 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 | ||
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import scala.collection.mutable.HashMap | ||
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/** | ||
* Small helper for tracking failed tasks for blacklisting purposes. Info on all failures on one | ||
* executor, within one task set. | ||
*/ | ||
private[scheduler] class ExecutorFailuresInTaskSet(val node: String) { | ||
/** | ||
* Mapping from index of the tasks in the taskset, to the number of times it has failed on this | ||
* executor. | ||
*/ | ||
val taskToFailureCount = HashMap[Int, Int]() | ||
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def updateWithFailure(taskIndex: Int): Unit = { | ||
val prevFailureCount = taskToFailureCount.getOrElse(taskIndex, 0) | ||
taskToFailureCount(taskIndex) = prevFailureCount + 1 | ||
} | ||
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def numUniqueTasksWithFailures: Int = taskToFailureCount.size | ||
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/** | ||
* Return the number of times this executor has failed on the given task index. | ||
*/ | ||
def getNumTaskFailures(index: Int): Int = { | ||
taskToFailureCount.getOrElse(index, 0) | ||
} | ||
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override def toString(): String = { | ||
s"numUniqueTasksWithFailures = $numUniqueTasksWithFailures; " + | ||
s"tasksToFailureCount = $taskToFailureCount" | ||
} | ||
} |
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