[
https://issues.apache.org/jira/browse/FLINK-8951?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16596447#comment-16596447
]
Sergey Tsvetkov commented on FLINK-8951:
----------------------------------------
I'd like to give this one a try.
> 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 API & SQL
> Reporter: Fabian Hueske
> Priority: 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.
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
