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[SPARK-5336][YARN]spark.executor.cores must not be less than spark.task.cpus #4123

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[SPARK-5336][YARN]spark.executor.cores must not be less than spark.task.cpus #4123

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3112af9
spark.executor.cores must not be less than spark.task.cpus
WangTaoTheTonic Jan 20, 2015
d03d6fa
import ordering should be alphabetical'
WangTaoTheTonic Jan 21, 2015
9632d3a
minor comment fix
WangTaoTheTonic Jan 21, 2015
6c9676a
Update ClientArguments.scala
WangTaoTheTonic Jan 21, 2015
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2 changes: 1 addition & 1 deletion core/src/main/scala/org/apache/spark/ExecutorAllocationManager.scala
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Expand Up @@ -158,7 +158,7 @@ private[spark] class ExecutorAllocationManager(
"shuffle service. You may enable this through spark.shuffle.service.enabled.")
}
if (tasksPerExecutor == 0) {
throw new SparkException("spark.executor.cores must not be less than spark.task.cpus.cores")
throw new SparkException("spark.executor.cores must not be less than spark.task.cpus.")
}
}

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2 changes: 1 addition & 1 deletion core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala
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Expand Up @@ -168,7 +168,7 @@ private[spark] class TaskSchedulerImpl(
if (!hasLaunchedTask) {
logWarning("Initial job has not accepted any resources; " +
"check your cluster UI to ensure that workers are registered " +
"and have sufficient memory")
"and have sufficient resources")
} else {
this.cancel()
}
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10 changes: 7 additions & 3 deletions yarn/src/main/scala/org/apache/spark/deploy/yarn/ClientArguments.scala
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Expand Up @@ -19,9 +19,9 @@ package org.apache.spark.deploy.yarn

import scala.collection.mutable.ArrayBuffer

import org.apache.spark.SparkConf
import org.apache.spark.{SparkConf, SparkException}
import org.apache.spark.deploy.yarn.YarnSparkHadoopUtil._
import org.apache.spark.util.{Utils, IntParam, MemoryParam}
import org.apache.spark.util.{IntParam, MemoryParam, Utils}

// TODO: Add code and support for ensuring that yarn resource 'tasks' are location aware !
private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf) {
Expand Down Expand Up @@ -95,6 +95,10 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf)
throw new IllegalArgumentException(
"You must specify at least 1 executor!\n" + getUsageMessage())
}
if (executorCores < sparkConf.getInt("spark.task.cpus", 1)) {
throw new SparkException("Executor cores must not be less than " +
"spark.task.cpus.")
}
if (isClusterMode) {
for (key <- Seq(amMemKey, amMemOverheadKey, amCoresKey)) {
if (sparkConf.contains(key)) {
Expand Down Expand Up @@ -222,7 +226,7 @@ private[spark] class ClientArguments(args: Array[String], sparkConf: SparkConf)
| --arg ARG Argument to be passed to your application's main class.
| Multiple invocations are possible, each will be passed in order.
| --num-executors NUM Number of executors to start (Default: 2)
| --executor-cores NUM Number of cores for the executors (Default: 1).
| --executor-cores NUM Number of cores per executor (Default: 1).
| --driver-memory MEM Memory for driver (e.g. 1000M, 2G) (Default: 512 Mb)
| --driver-cores NUM Number of cores used by the driver (Default: 1).
| --executor-memory MEM Memory per executor (e.g. 1000M, 2G) (Default: 1G)
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