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https://issues.apache.org/jira/browse/FLINK-8951?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17321603#comment-17321603
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Flink Jira Bot commented on FLINK-8951:
---------------------------------------
This issue and all of its Sub-Tasks have not been updated for 180 days. So, it
has been labeled "stale-minor". If you are still affected by this bug or are
still interested in this issue, please give an update and remove the label. In
7 days the issue will be closed automatically.
> Support OVER windows PARTITION BY (rounded) timestamp
> -----------------------------------------------------
>
> Key: FLINK-8951
> URL: https://issues.apache.org/jira/browse/FLINK-8951
> Project: Flink
> Issue Type: New Feature
> Components: Table SQL / API
> Reporter: Fabian Hueske
> Assignee: TANG Wen-hui
> Priority: Minor
> Labels: stale-minor
>
> There are a few interesting use cases that can be addressed by queries that
> follow the following pattern
> {code:sql}
> SELECT sensorId COUNT(*) OVER (PARTITION BY CEIL(rowtime TO HOUR) ORDER BY
> temp ROWS BETWEEN UNBOUNDED preceding AND CURRENT ROW) FROM sensors
> {code}
> Such queries can be used to compute rolling cascading (tumbling) windows with
> aggregates that are reset in regular intervals. This can be useful for TOP-K
> per minute/hour/day queries.
> Right now, such {{OVER}} windows are not supported, because we require that
> the {{ORDER BY}} clause is defined on a timestamp (time indicator) attribute.
> In order to support this kind of queries, we would require that the
> {{PARTITION BY}} clause contains a timestamp (time indicator) attribute or a
> function that is defined on it and which is monotonicity preserving. Once the
> optimizer identifies this case, it could translate the query into a special
> time-partitioned OVER window operator.
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