[ https://issues.apache.org/jira/browse/SPARK-27192?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen resolved SPARK-27192. ------------------------------- Resolution: Fixed Issue resolved by pull request 24261 [https://github.com/apache/spark/pull/24261] > spark.task.cpus should be less or equal than spark.task.cpus when use static > executor allocation > ------------------------------------------------------------------------------------------------ > > Key: SPARK-27192 > URL: https://issues.apache.org/jira/browse/SPARK-27192 > Project: Spark > Issue Type: Improvement > Components: Spark Core > Affects Versions: 2.2.0, 2.3.0, 2.4.0 > Reporter: Lijia Liu > Assignee: Lijia Liu > Priority: Minor > Fix For: 3.0.0 > > > When use dynamic executor allocation, if we set spark.executor.cores small > than spark.task.cpus, exception will be thrown as follows: > '''spark.executor.cores must not be < spark.task.cpus''' > But, if dynamic executor allocation not enabled, spark will hang when submit > new job for TaskSchedulerImpl will not schedule a task in a executor which > available cores is small than > spark.task.cpus.See > [https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/scheduler/TaskSchedulerImpl.scala#L351] > So, when start task scheduler, spark.task.cpus should be check. > reproduce > $SPARK_HOME/bin/spark-shell --conf spark.task.cpus=2 --master local[1] > scala> sc.parallelize(1 to 9).collect -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org