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https://issues.apache.org/jira/browse/BEAM-12685?focusedWorklogId=633757&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-633757
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ASF GitHub Bot logged work on BEAM-12685:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 04/Aug/21 18:47
Start Date: 04/Aug/21 18:47
Worklog Time Spent: 10m
Work Description: pabloem commented on pull request #15246:
URL: https://github.com/apache/beam/pull/15246#issuecomment-892889266
hmmm I think we usually try to avoid giving this kind of knob to users,
because it's easy for these parameters to become obsolete, and hardcoded in
legacy pipelines.. I'm wondering - do you think there's another way of
accomplishing this?
In Dataflow we have GroupIntoBatches.withAutoSharding, which provides a
sharding parameter that scales automatically with the number of workers.
Perhaps this would help?
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Issue Time Tracking
-------------------
Worklog Id: (was: 633757)
Remaining Estimate: 1h 20m (was: 1.5h)
Time Spent: 40m (was: 0.5h)
> Allow managed thread count in AvroIO
> ------------------------------------
>
> Key: BEAM-12685
> URL: https://issues.apache.org/jira/browse/BEAM-12685
> Project: Beam
> Issue Type: Improvement
> Components: io-java-files
> Reporter: Dylan Hercher
> Priority: P2
> Original Estimate: 2h
> Time Spent: 40m
> Remaining Estimate: 1h 20m
>
> During execution, the `ReadAllViaFileBasedSource` runs ReShuffle and creates
> an un-grouped set of file range readers. This can easily cause OOM issues
> when the number of groups changes as there is no limit to the number of
> concurrent file reads.
>
> Using Reshuffle.viaRandomKeys.withNumBuckets instead will allow the same
> default behavior, but lets the user configure the number of readers as and
> when needed.
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