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https://issues.apache.org/jira/browse/FLINK-22587?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17349168#comment-17349168
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Seth Wiesman commented on FLINK-22587:
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Isn’t this expected behavior?
- NeverTrigger should never fire
- ProcessingTimeTrigger is non sensical in a batch context
- Count and Delta triggers only fire if certain semantic requirements are met
If you did want to have those output I think we’d also need to add another side
output for windows that fired incomplete because their results were fired
despite their trigger not running
> Support aggregations in batch mode with DataStream API
> ------------------------------------------------------
>
> Key: FLINK-22587
> URL: https://issues.apache.org/jira/browse/FLINK-22587
> Project: Flink
> Issue Type: Bug
> Components: API / DataStream
> Affects Versions: 1.12.0, 1.13.0
> Reporter: Etienne Chauchot
> Priority: Major
>
> A pipeline like this *in batch mode* would output no data
> {code:java}
> stream.join(otherStream)
> .where(<KeySelector>)
> .equalTo(<KeySelector>)
> .window(GlobalWindows.create())
> .apply(<JoinFunction>)
> {code}
> Indeed the default trigger for GlobalWindow is NeverTrigger which never
> fires. If we set a _EventTimeTrigger_ it will fire with every element as the
> watermark will be set to +INF (batch mode) and will pass the end of the
> global window with each new element. A _ProcessingTimeTrigger_ never fires
> either and all elapsed time or delta based triggers would not be suited for
> batch.
> Same goes for _reduce()_ instead of join().
> So I guess we miss something for batch support with DataStream.
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