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Posted to reviews@spark.apache.org by blyncsy-david-lewis <gi...@git.apache.org> on 2017/10/08 18:28:24 UTC
[GitHub] spark pull request #19456: [SPARK] [Scheduler] Configurable default scheduli...
GitHub user blyncsy-david-lewis opened a pull request:
https://github.com/apache/spark/pull/19456
[SPARK] [Scheduler] Configurable default scheduling mode
Pulling default values for scheduling mode from spark conf.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/blyncsy-david-lewis/spark master
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/19456.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 #19456
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commit f55ced3899cb80e23617dcacc3c548a88873f4c0
Author: David Lewis <da...@blyncsy.com>
Date: 2017-10-08T18:25:19Z
allowing configuration of default scheduling mode and properties
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[GitHub] spark issue #19456: [SPARK] [Scheduler] Configurable default scheduling mode
Posted by jiangxb1987 <gi...@git.apache.org>.
Github user jiangxb1987 commented on the issue:
https://github.com/apache/spark/pull/19456
Could you elaborate on the scenario that you should need to make these settings configurable?
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[GitHub] spark issue #19456: [SPARK] [Scheduler] Configurable default scheduling mode
Posted by blyncsy-david-lewis <gi...@git.apache.org>.
Github user blyncsy-david-lewis commented on the issue:
https://github.com/apache/spark/pull/19456
I have a multiuser application where I use the userId as the name of the scheduling pool so that users are balanced equally by spark and within a user's workload I can set the scheduling mode to FAIR (or whatever I want). It is unreasonable to specify xml for each user and restart spark, so this patch allows me to specify the default configuration used by undefined pools.
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[GitHub] spark pull request #19456: [SPARK] [Scheduler] Configurable default scheduli...
Posted by asfgit <gi...@git.apache.org>.
Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/19456
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[GitHub] spark issue #19456: [SPARK] [Scheduler] Configurable default scheduling mode
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/19456
Can one of the admins verify this patch?
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[GitHub] spark issue #19456: [SPARK] [Scheduler] Configurable default scheduling mode
Posted by HyukjinKwon <gi...@git.apache.org>.
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/19456
ping @blyncsy-david-lewis for @varuvish 's comment. Otherwise let me propose to close it for now.
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[GitHub] spark issue #19456: [SPARK] [Scheduler] Configurable default scheduling mode
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/19456
Can one of the admins verify this patch?
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[GitHub] spark issue #19456: [SPARK] [Scheduler] Configurable default scheduling mode
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/19456
Can one of the admins verify this patch?
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[GitHub] spark issue #19456: [SPARK] [Scheduler] Configurable default scheduling mode
Posted by varuvish <gi...@git.apache.org>.
Github user varuvish commented on the issue:
https://github.com/apache/spark/pull/19456
Can you guarantee that your users share an even workload? With this setup you could potentially have a user with a high workload using 1/#users resources. Wouldn't using the queue feature be better?
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[GitHub] spark issue #19456: [SPARK] [Scheduler] Configurable default scheduling mode
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/19456
Can one of the admins verify this patch?
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[GitHub] spark issue #19456: [SPARK] [Scheduler] Configurable default scheduling mode
Posted by AmplabJenkins <gi...@git.apache.org>.
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/19456
Can one of the admins verify this patch?
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