[jira] [Commented] (SPARK-25073) Spark-submit on Yarn Task : When the yarn.nodemanager.resource.memory-mb and/or yarn.scheduler.maximum-allocation-mb is insufficient, Spark always reports an error req

2018-08-23 Thread Sujith (JIRA)
[ https://issues.apache.org/jira/browse/SPARK-25073?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16590396#comment-16590396 ] Sujith commented on SPARK-25073:  Yes, in the executor memory validation check we are di

[jira] [Commented] (SPARK-25073) Spark-submit on Yarn Task : When the yarn.nodemanager.resource.memory-mb and/or yarn.scheduler.maximum-allocation-mb is insufficient, Spark always reports an error req

2018-08-23 Thread Sean Owen (JIRA)
[ https://issues.apache.org/jira/browse/SPARK-25073?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16590195#comment-16590195 ] Sean Owen commented on SPARK-25073: --- I don't think Spark can necessarily know or analy

[jira] [Commented] (SPARK-25073) Spark-submit on Yarn Task : When the yarn.nodemanager.resource.memory-mb and/or yarn.scheduler.maximum-allocation-mb is insufficient, Spark always reports an error req

2018-08-23 Thread Sujith (JIRA)
[ https://issues.apache.org/jira/browse/SPARK-25073?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16590089#comment-16590089 ] Sujith commented on SPARK-25073: @ [~hyukjin.kwon] [@gatorsmile|https://github.com/gator

[jira] [Commented] (SPARK-25073) Spark-submit on Yarn Task : When the yarn.nodemanager.resource.memory-mb and/or yarn.scheduler.maximum-allocation-mb is insufficient, Spark always reports an error req

2018-08-23 Thread Apache Spark (JIRA)
[ https://issues.apache.org/jira/browse/SPARK-25073?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16590069#comment-16590069 ] Apache Spark commented on SPARK-25073: -- User 'sujith71955' has created a pull reque

[jira] [Commented] (SPARK-25073) Spark-submit on Yarn Task : When the yarn.nodemanager.resource.memory-mb and/or yarn.scheduler.maximum-allocation-mb is insufficient, Spark always reports an error req

2018-08-09 Thread Sujith (JIRA)
[ https://issues.apache.org/jira/browse/SPARK-25073?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16574864#comment-16574864 ] Sujith commented on SPARK-25073: Seems to be you are right, Message is bit misleading to