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https://issues.apache.org/jira/browse/BEAM-11267?focusedWorklogId=512612&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-512612
]
ASF GitHub Bot logged work on BEAM-11267:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 16/Nov/20 21:54
Start Date: 16/Nov/20 21:54
Worklog Time Spent: 10m
Work Description: mxm commented on a change in pull request #13353:
URL: https://github.com/apache/beam/pull/13353#discussion_r524634584
##########
File path:
runners/flink/src/main/java/org/apache/beam/runners/flink/FlinkStreamingTransformTranslators.java
##########
@@ -971,7 +987,9 @@ public void translateNode(
.transform(fullName, outputTypeInfo, (OneInputStreamOperator)
doFnOperator)
.uid(fullName);
- context.setOutputDataStream(context.getOutput(transform), outDataStream);
+ final PCollection<KV<K, Iterable<InputT>>> output =
context.getOutput(transform);
+ context.setOutputDataStream(output, outDataStream);
+ context.setProducer(output, transform);
Review comment:
It would be nice if these explicit calls wouldn't be required. I believe
`context.setOutputDataStream` internally has the current transform available.
So we could perform it internally in the context.
##########
File path:
runners/flink/src/main/java/org/apache/beam/runners/flink/FlinkStreamingTransformTranslators.java
##########
@@ -1127,7 +1148,9 @@ public void translateNode(
keyedWorkItemStream.getExecutionEnvironment().addOperator(rawFlinkTransform);
- context.setOutputDataStream(context.getOutput(transform),
outDataStream);
+ final PCollection<KV<K, OutputT>> output =
context.getOutput(transform);
+ context.setOutputDataStream(output, outDataStream);
+ context.setProducer(output, transform);
Review comment:
Same here.
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Issue Time Tracking
-------------------
Worklog Id: (was: 512612)
Time Spent: 1h 20m (was: 1h 10m)
> Remove unnecessary reshuffle for stateful ParDo after keyed operation
> ---------------------------------------------------------------------
>
> Key: BEAM-11267
> URL: https://issues.apache.org/jira/browse/BEAM-11267
> Project: Beam
> Issue Type: Improvement
> Components: runner-flink
> Reporter: David Morávek
> Assignee: David Morávek
> Priority: P3
> Time Spent: 1h 20m
> Remaining Estimate: 0h
>
> When we have stateful pardo after GBK / Combine, we can safely assume that
> partitioning remains consistent and we can safe an extra shuffle.
> The use case for this are user defined timers / datadriven triggers. This
> code path is stressed for example by
> org.apache.beam.sdk.transforms.ParDoTest.TimerTests#testGbkFollowedByUserTimers.
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