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https://issues.apache.org/jira/browse/FLINK-7799?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17329542#comment-17329542
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Flink Jira Bot commented on FLINK-7799:
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This issue is assigned but has not received an update in 7 days so it has been
labeled "stale-assigned". If you are still working on the issue, please give an
update and remove the label. If you are no longer working on the issue, please
unassign so someone else may work on it. In 7 days the issue will be
automatically unassigned.
> Improve performance of windowed joins
> -------------------------------------
>
> Key: FLINK-7799
> URL: https://issues.apache.org/jira/browse/FLINK-7799
> Project: Flink
> Issue Type: Improvement
> Components: Table SQL / Legacy Planner
> Affects Versions: 1.4.0
> Reporter: Fabian Hueske
> Assignee: Xingcan Cui
> Priority: Minor
> Labels: stale-assigned, stale-minor
>
> The performance of windowed joins can be improved by changing the state
> access patterns.
> Right now, rows are inserted into a MapState with their timestamp as key.
> Since we use a time resolution of 1ms, this means that the full key space of
> the state must be iterated and many map entries must be accessed when joining
> or evicting rows.
> A better strategy would be to block the time into larger intervals and
> register the rows in their respective interval. Another benefit would be that
> we can directly access the state entries because we know exactly which
> timestamps to look up. Hence, we can limit the state access to the relevant
> section during joining and state eviction.
> The good size for intervals needs to be identified and might depend on the
> size of the window.
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