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https://issues.apache.org/jira/browse/BEAM-6735?focusedWorklogId=202842&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-202842
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ASF GitHub Bot logged work on BEAM-6735:
----------------------------------------
Author: ASF GitHub Bot
Created on: 22/Feb/19 20:04
Start Date: 22/Feb/19 20:04
Worklog Time Spent: 10m
Work Description: kyle-winkelman commented on pull request #7929:
[BEAM-6735] Add noSpilling option to WriteFiles.
URL: https://github.com/apache/beam/pull/7929
Construct a simplified pipeline in the event that the number of writers
isn't prohibitive. User must opt into this by using FileIO, TextIO, or
WriteFiles withNoSpilling.
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Issue Time Tracking
-------------------
Worklog Id: (was: 202842)
Time Spent: 10m
Remaining Estimate: 0h
> WriteFiles with runner-determined sharding is forced to handle spilling
> -----------------------------------------------------------------------
>
> Key: BEAM-6735
> URL: https://issues.apache.org/jira/browse/BEAM-6735
> Project: Beam
> Issue Type: Improvement
> Components: sdk-java-core
> Reporter: Kyle Winkelman
> Priority: Major
> Time Spent: 10m
> Remaining Estimate: 0h
>
> As a result of BEAM-2302, files in excess of WriteFiles
> maxNumWritersPerBundle are shuffled to be written later. The downside to this
> is that even if you can guarantee that maxNumWritersPerBundle is high enough
> to handle all writes you still have to pay the overhead of this write now
> being a MultiOutput ParDo.
> e.g. In the Spark Runner when a ParDo has multiple outputs the returned data
> is cached and if using the disableCache pipeline option it would cause
> recalculation and all the temp files would be written again.
> I'm sure that the Spark Runner is not the only runner that would benefit from
> an optional setting for WriteFiles that would skip this spilling and simplify
> the pipeline.
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