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https://issues.apache.org/jira/browse/FLINK-5990?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15900788#comment-15900788
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sunjincheng commented on FLINK-5990:
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[~fhueske] I think ROWS Clause {code}OVER ROWS BETWEEN x PRECEDING {code} and
RANGE Clause {code} OVER RANGE BETWEEN x PRECEDING{code} are a little
different. So,I created this JIRA. is that make sense for you?
Best,
SunJincheng
> Add event time OVER ROWS BETWEEN x PRECEDING aggregation to SQL
> ---------------------------------------------------------------
>
> Key: FLINK-5990
> URL: https://issues.apache.org/jira/browse/FLINK-5990
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Reporter: sunjincheng
> Assignee: sunjincheng
>
> The goal of this issue is to add support for OVER ROWS aggregations on event
> time streams to the SQL interface.
> Queries similar to the following should be supported:
> {code}
> SELECT
> a,
> SUM(b) OVER (PARTITION BY c ORDER BY rowTime() ROWS BETWEEN 2 PRECEDING AND
> CURRENT ROW) AS sumB,
> MIN(b) OVER (PARTITION BY c ORDER BY rowTime() ROWS BETWEEN 2 PRECEDING AND
> CURRENT ROW) AS minB
> FROM myStream
> {code}
> The following restrictions should initially apply:
> - All OVER clauses in the same SELECT clause must be exactly the same.
> - The PARTITION BY clause is optional (no partitioning results in single
> threaded execution).
> - The ORDER BY clause may only have rowTime() as parameter. rowTime() is a
> parameterless scalar function that just indicates event time mode.
> - UNBOUNDED PRECEDING is not supported
> - FOLLOWING is not supported.
> The restrictions will be resolved in follow up issues. If we find that some
> of the restrictions are trivial to address, we can add the functionality in
> this issue as well.
> This issue includes:
> - Design of the DataStream operator to compute OVER ROW aggregates
> - Translation from Calcite's RelNode representation (LogicalProject with
> RexOver expression).
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