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https://issues.apache.org/jira/browse/BEAM-8191?focusedWorklogId=329824&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-329824
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ASF GitHub Bot logged work on BEAM-8191:
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Author: ASF GitHub Bot
Created on: 17/Oct/19 12:53
Start Date: 17/Oct/19 12:53
Worklog Time Spent: 10m
Work Description: RyanSkraba commented on pull request #9544: [BEAM-8191]
Fixes potentially large number of tasks on Spark after Flatten.pCollections()
URL: https://github.com/apache/beam/pull/9544#discussion_r335985096
##########
File path:
runners/spark/src/main/java/org/apache/beam/runners/spark/translation/SparkBatchPortablePipelineTranslator.java
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@@ -353,6 +353,11 @@ public void setName(String name) {
index++;
}
unionRDD = context.getSparkContext().union(rdds);
+
+ Partitioner partitioner = getPartitioner(context);
Review comment:
This *does* sound like a good idea! I linked your JIRA to
https://issues.apache.org/jira/browse/BEAM-8384 . Before adding some a new
pipeline option, it would be great if there were a better "overall" view of how
the SparkRunner is managing parallelism.
This seems like it would be a good area to collaborate.
I apologize for forgetting to add this comment to your PR earlier :/
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Issue Time Tracking
-------------------
Worklog Id: (was: 329824)
Time Spent: 1h 50m (was: 1h 40m)
> Multiple Flatten.pCollections() transforms generate an overwhelming number of
> tasks
> -----------------------------------------------------------------------------------
>
> Key: BEAM-8191
> URL: https://issues.apache.org/jira/browse/BEAM-8191
> Project: Beam
> Issue Type: Bug
> Components: runner-spark
> Affects Versions: 2.12.0, 2.14.0, 2.15.0
> Reporter: Peter Backx
> Assignee: Peter Backx
> Priority: Major
> Time Spent: 1h 50m
> Remaining Estimate: 0h
>
> The Flatten.pCollections() is translated into a Spark union operation. The
> resulting RDD will have the sum of the partitions in the originating RDDs.
> If you flatten 2 PCollections with each 10 partitions, the result will have
> 20 partitions.
> This is ok in small pipelins, but in our main pipeline, this means the number
> of tasks grows out of hand quite easily (over 500k tasks in one stage). This
> overloads the driver and crashes the process.
> I have created a small repro case:
> [https://github.com/pbackx/beam-flatmap-test]
>
> A possible solution is to add a coalesce call after the union. We have been
> testing this and it seems to do exactly what we want, but I'm not sure if
> this fix is applicable for all cases.
> I will open a PR for this so that you can review my proposed change and
> discuss whether or not it's a good idea.
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