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https://issues.apache.org/jira/browse/BEAM-5519?focusedWorklogId=230106&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-230106
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ASF GitHub Bot logged work on BEAM-5519:
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Author: ASF GitHub Bot
Created on: 19/Apr/19 12:54
Start Date: 19/Apr/19 12:54
Worklog Time Spent: 10m
Work Description: kyle-winkelman commented on issue #6511: [BEAM-5519]
Remove call to groupByKey in Spark Streaming.
URL: https://github.com/apache/beam/pull/6511#issuecomment-484887010
Rebased.
One other option I have come up with regarding the performance tests is to
alter the Nexmark BoundedEventSource so that it splits properly. For example if
it returns that the estimatedSizeBytes is 100 and the Spark Runner asks for
desiredBundleSizeBytes of 10 then we split it into 10 equal pieces (instead of
always splitting on numEventGenerators). This will unfortunately impact all
batch performance numbers so I don't really want to do it, but it seems like it
might be the best way.
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Issue Time Tracking
-------------------
Worklog Id: (was: 230106)
Time Spent: 5h (was: 4h 50m)
> Spark Streaming Duplicated Encoding/Decoding Effort
> ---------------------------------------------------
>
> Key: BEAM-5519
> URL: https://issues.apache.org/jira/browse/BEAM-5519
> Project: Beam
> Issue Type: Bug
> Components: runner-spark
> Reporter: Kyle Winkelman
> Assignee: Kyle Winkelman
> Priority: Major
> Labels: spark, spark-streaming, triaged
> Fix For: 2.13.0
>
> Time Spent: 5h
> Remaining Estimate: 0h
>
> When using the SparkRunner in streaming mode. There is a call to groupByKey
> followed by a call to updateStateByKey. BEAM-1815 fixed an issue where this
> used to cause 2 shuffles but it still causes 2 encode/decode cycles.
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