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Posted to issues@flink.apache.org by "ASF GitHub Bot (JIRA)" <ji...@apache.org> on 2014/07/06 20:20:33 UTC
[jira] [Commented] (FLINK-1003) Spread out scheduling strategy
[ https://issues.apache.org/jira/browse/FLINK-1003?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14053170#comment-14053170 ]
ASF GitHub Bot commented on FLINK-1003:
---------------------------------------
GitHub user tillrohrmann opened a pull request:
https://github.com/apache/incubator-flink/pull/60
[FLINK-1003] Added spread out scheduling strategy
The spread out scheduling strategy tries to keep the work load among the instances balanced. The scheduling strategy can be specified by the configuration parameter ```jobmanager.scheduling-strategy```. Valid options are ```SpreadOut``` and ```FillFirst```. The latter strategy is the old and default strategy.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/tillrohrmann/incubator-flink FLINK-1003
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/incubator-flink/pull/60.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #60
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commit 7800b3becdf3551e69a2f950412476cf65b8534f
Author: Till Rohrmann <ti...@gmail.com>
Date: 2014-07-06T17:24:10Z
Added spread out scheduling strategy
commit e8b573d9721eb78477e154bc050dabb015a0fade
Author: Till Rohrmann <ti...@gmail.com>
Date: 2014-07-06T18:16:06Z
minor fixes
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> Spread out scheduling strategy
> ------------------------------
>
> Key: FLINK-1003
> URL: https://issues.apache.org/jira/browse/FLINK-1003
> Project: Flink
> Issue Type: Improvement
> Reporter: Till Rohrmann
>
> Currently the Flink scheduler tries to fill one instance completely before the tasks are deployed to another instance. This is a good behaviour in multi-user and multi-job scenarios but it wastes resources if one wants to use the complete cluster. Therefore, another scheduling strategy where the load among the different instances is kept balanced might be useful. This spread out strategy will deploy the tasks such that the overall work is equally distributed.
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