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Posted to issues@spark.apache.org by "Dongjoon Hyun (Jira)" <ji...@apache.org> on 2020/01/08 17:15:00 UTC
[jira] [Resolved] (SPARK-30445) Accelerator aware scheduling handle
setting configs to 0 better
[ https://issues.apache.org/jira/browse/SPARK-30445?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Dongjoon Hyun resolved SPARK-30445.
-----------------------------------
Fix Version/s: 3.0.0
Resolution: Fixed
Issue resolved by pull request 27118
[https://github.com/apache/spark/pull/27118]
> Accelerator aware scheduling handle setting configs to 0 better
> ---------------------------------------------------------------
>
> Key: SPARK-30445
> URL: https://issues.apache.org/jira/browse/SPARK-30445
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 3.0.0
> Reporter: Thomas Graves
> Assignee: Thomas Graves
> Priority: Major
> Fix For: 3.0.0
>
>
> If you set the resource configs to 0, it errors with divide by zero. While I think ideally the user should just remove the configs we should handle the 0 better.
>
> {color:#1d1c1d}$ spark-submit --conf spark.driver.resource.gpu.amount=0 {color}*--conf spark.executor.resource.gpu.amount=0*{color:#1d1c1d} {color}*--conf spark.task.resource.gpu.amount=0*{color:#1d1c1d} --conf spark.driver.resource.gpu.discoveryScript=/shared/tools/get_gpu_resources.sh --conf spark.executor.resource.gpu.discoveryScript=/shared/tools/get_gpu_resources.sh test.py{color}
> {color:#1d1c1d}20/01/07 05:36:42 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable{color}
> {color:#1d1c1d}Using Spark’s default log4j profile: org/apache/spark/log4j-defaults.properties{color}
> {color:#1d1c1d}20/01/07 05:36:43 INFO SparkContext: {color}*Running Spark version 3.0.0-preview*
> {color:#1d1c1d}20/01/07 05:36:43 INFO ResourceUtils: =============================================================={color}
> {color:#1d1c1d}20/01/07 05:36:43 INFO ResourceUtils: Resources for spark.driver:{color}
> *gpu -> [name: gpu, addresses: 0]*
> {color:#1d1c1d}20/01/07 05:36:43 INFO ResourceUtils: =============================================================={color}
> {color:#1d1c1d}20/01/07 05:36:43 INFO SparkContext: Submitted application: test.py{color}
> {color:#1d1c1d}......{color}
> {color:#1d1c1d}20/01/07 05:36:43 ERROR SparkContext: Error initializing SparkContext.{color}
> *java.lang.ArithmeticException: / by zero*
> {color:#1d1c1d}at org.apache.spark.SparkContext$.$anonfun$createTaskScheduler$3(SparkContext.scala:2793){color}
> {color:#1d1c1d}at org.apache.spark.SparkContext$.$anonfun$createTaskScheduler$3$adapted(SparkContext.scala:2775){color}
> {color:#1d1c1d}at scala.collection.Iterator.foreach(Iterator.scala:941){color}
> {color:#1d1c1d}at scala.collection.Iterator.foreach$(Iterator.scala:941){color}
> {color:#1d1c1d}at scala.collection.AbstractIterator.foreach(Iterator.scala:1429){color}
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