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Posted to issues@flink.apache.org by "Aljoscha Krettek (JIRA)" <ji...@apache.org> on 2016/04/12 12:45:25 UTC

[jira] [Commented] (FLINK-3581) Add Special Aligned Event-Time WindowOperator

    [ https://issues.apache.org/jira/browse/FLINK-3581?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15236977#comment-15236977 ] 

Aljoscha Krettek commented on FLINK-3581:
-----------------------------------------

I decided to change the scope of this issue since I discovered while implementing and thinking about this that an aligned Trigger only makes sense for very special cases. The one case we have is aligned triggering of sliding windows or tumbling windows. This is easier to do in a specialized operator that uses the partitioned state. The partitioned state still has to be enhanced to allow iterating over all keys, but this is not too hard to do.

[~StephanEwen] should we also add a special Aligned Processing-Time operator that uses the partitioned state abstraction? This would have the same performance for tumbling windows as the current {{*AlignedProcessingTimeWindowOperator}} operators. For sliding windows, however, performance would regress because there is no easy way to do lock-step traversal of the keyed panes.

> Add Special Aligned Event-Time WindowOperator
> ---------------------------------------------
>
>                 Key: FLINK-3581
>                 URL: https://issues.apache.org/jira/browse/FLINK-3581
>             Project: Flink
>          Issue Type: Improvement
>          Components: Streaming
>            Reporter: Aljoscha Krettek
>            Assignee: Aljoscha Krettek
>
> The current Window Trigger is per key. Meaning every window has a (logical) Trigger for every key in the window, i.e. there will be state and time triggers per key per window.
> For some types of windows, i.e. based on time it is possible to use a single Trigger to fire for all keys at the same time. In that case we would save a lot of space on state and timers. Which makes state snapshots a lot smaller.



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