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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2015/01/22 11:52:34 UTC
[jira] [Commented] (SPARK-5349) Multiple spark shells should be
able to share resources
[ https://issues.apache.org/jira/browse/SPARK-5349?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14287261#comment-14287261 ]
Sean Owen commented on SPARK-5349:
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I think this is a subset of https://issues.apache.org/jira/browse/SPARK-3174 which has been implemented. This is a means to scale up and down the number of executors. It is for YARN, but, I think this issue isn't acute in standalone mode, which is generally not multi-user. The issue is not special to the shell.
> Multiple spark shells should be able to share resources
> -------------------------------------------------------
>
> Key: SPARK-5349
> URL: https://issues.apache.org/jira/browse/SPARK-5349
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 1.2.0
> Reporter: Tobias Bertelsen
>
> The resource requirements of an interactive shell varies heavily. Sometimes heavy commands are executed, and sometimes the user is thinking, getting coffee, interrupted etc...
> A spark shell allocates a fixed number of worker cores (at least in standalone mode). A user thus has the choice to either block other users from the cluster by allocating all cores (default behavior), or restrict him/herself to only a few cores using the option {{--total-executor-cores}}. Either way the cores allocated to the shell has low utilization, since they will be waiting for the user a lot.
> Instead the spark shell allocate resources directly required to run the driver, and request worker cores only when computation is performed on the RDDs.
> This should allow for multiple users, to use an interactive shell concurrently while stille utilizing the entire cluster, when performing heavy operations.
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