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https://issues.apache.org/jira/browse/BEAM-11934?focusedWorklogId=565478&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-565478
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ASF GitHub Bot logged work on BEAM-11934:
-----------------------------------------

                Author: ASF GitHub Bot
            Created on: 12/Mar/21 19:38
            Start Date: 12/Mar/21 19:38
    Worklog Time Spent: 10m 
      Work Description: chamikaramj commented on a change in pull request 
#14164:
URL: https://github.com/apache/beam/pull/14164#discussion_r593405175



##########
File path: sdks/java/core/src/main/java/org/apache/beam/sdk/io/WriteFiles.java
##########
@@ -301,6 +321,21 @@
     return toBuilder().setMaxNumWritersPerBundle(-1).build();
   }
 
+  /**
+   * Returns a new {@link WriteFiles} that will write to the current {@link 
FileBasedSink} with
+   * runner-determined sharding for unbounded data specifically. Currently 
manual sharding is
+   * required for writing unbounded data with a fixed number of shards or a 
predefined sharding
+   * function. This option allows the runners to get around that requirement 
and perform automatic
+   * sharding.
+   *
+   * <p>Intended to only be used by runners. Users should use {@link

Review comment:
       Ok, makes sense. I think a PTransformOverride should work for this.




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

    Worklog Id:     (was: 565478)
    Time Spent: 1h 40m  (was: 1.5h)

> GCS streaming file sink uses runner determined sharding
> -------------------------------------------------------
>
>                 Key: BEAM-11934
>                 URL: https://issues.apache.org/jira/browse/BEAM-11934
>             Project: Beam
>          Issue Type: Improvement
>          Components: io-java-files, io-java-gcp
>            Reporter: Siyuan Chen
>            Assignee: Siyuan Chen
>            Priority: P1
>          Time Spent: 1h 40m
>  Remaining Estimate: 0h
>
> Integrate file sink with shardable `GroupIntoBatches` (BEAM-10475) to allow 
> runner determined dynamic sharding for streaming use cases.



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