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https://issues.apache.org/jira/browse/BEAM-2873?focusedWorklogId=91007&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-91007
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ASF GitHub Bot logged work on BEAM-2873:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 13/Apr/18 22:57
            Start Date: 13/Apr/18 22:57
    Worklog Time Spent: 10m 
      Work Description: robertwb commented on issue #4760: [BEAM-2873] Setting 
number of shards for writes with runner determined sharding
URL: https://github.com/apache/beam/pull/4760#issuecomment-381279762
 
 
   Jenkins: retest this please.

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Issue Time Tracking
-------------------

    Worklog Id:     (was: 91007)
    Time Spent: 3h 10m  (was: 3h)

> Detect number of shards for file sink in Flink Streaming Runner
> ---------------------------------------------------------------
>
>                 Key: BEAM-2873
>                 URL: https://issues.apache.org/jira/browse/BEAM-2873
>             Project: Beam
>          Issue Type: Improvement
>          Components: runner-flink
>            Reporter: Aljoscha Krettek
>            Assignee: Dawid Wysakowicz
>            Priority: Major
>          Time Spent: 3h 10m
>  Remaining Estimate: 0h
>
> [~reuvenlax] mentioned that this is done for the Dataflow Runner and the 
> default behaviour on Flink can be somewhat surprising for users.
> ML entry: https://www.mail-archive.com/dev@beam.apache.org/msg02665.html:
> This is how the file sink has always worked in Beam. If no sharding is 
> specified, then this means runner-determined sharding, and by default that is 
> one file per bundle. If Flink has small bundles, then I suggest using the 
> withNumShards method to explicitly pick the number of output shards.
> The Flink runner can detect that runner-determined sharding has been chosen, 
> and override it with a specific number of shards. For example, the Dataflow 
> streaming runner (which as you mentioned also has small bundles) detects this 
> case and sets the number of out files shards based on the number of workers 
> in the worker pool 
> [Here|https://github.com/apache/beam/blob/9e6530adb00669b7cf0f01cb8b128be0a21fd721/runners/google-cloud-dataflow-java/src/main/java/org/apache/beam/runners/dataflow/DataflowRunner.java#L354]
>  is the code that does this; it should be quite simple to do something 
> similar for Flink, and then there will be no need for users to explicitly 
> call withNumShards themselves.



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