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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-17637) Packed scheduling for Spark tasks across executors
Date Fri, 23 Sep 2016 16:20:20 GMT

     [ https://issues.apache.org/jira/browse/SPARK-17637?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-17637:
------------------------------------

    Assignee: Apache Spark

> Packed scheduling for Spark tasks across executors
> --------------------------------------------------
>
>                 Key: SPARK-17637
>                 URL: https://issues.apache.org/jira/browse/SPARK-17637
>             Project: Spark
>          Issue Type: Improvement
>          Components: Scheduler
>            Reporter: Zhan Zhang
>            Assignee: Apache Spark
>            Priority: Minor
>
> Currently Spark scheduler implements round robin scheduling for tasks to executors. Which
is great as it distributes the load evenly across the cluster, but this leads to significant
resource waste in some cases, especially when dynamic allocation is enabled.



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