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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-22628) Some situations, the assignment of executors on workers is not what we expected when `spark.deploy.spreadOut=true`.
Date Tue, 28 Nov 2017 11:20:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-22628?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16268583#comment-16268583
] 

Apache Spark commented on SPARK-22628:
--------------------------------------

User '10110346' has created a pull request for this issue:
https://github.com/apache/spark/pull/19832

> Some situations,  the assignment of executors on workers is not what we expected when
`spark.deploy.spreadOut=true`.
> --------------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-22628
>                 URL: https://issues.apache.org/jira/browse/SPARK-22628
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 2.3.0
>            Reporter: liuxian
>
> For example, cluster has 3 workers(workA, workB, workC),  workA has 1 core left, workB
has 1 core left, workC has no cores left.
> User requests 3 executors (spark.cores.max = 3, spark.executor.cores = 1), obviously,
workA  will be assigned one executor ,and workB will be assigned one executor.
> After a moment,if some apps release  cores, and workB has 3 core left, workC has 2 core
left, we should assign one executor on workC,not workB.
> Especially for dynamic executors allocation in standalone mode, this problem is more
serious.



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