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https://issues.apache.org/jira/browse/FLINK-6228?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15956640#comment-15956640
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Fabian Hueske commented on FLINK-6228:
--------------------------------------
I think that use case is not supported yet (but should be at some point).
I think in SQL the query would look as follows:
{code}
SELECT timestamp, orderId, amount, rank() OVER (PARTITION BY CEIL(timestamp TO
MILLISECOND) ORDER BY amount) FROM stream
{code}
So, we would partition on {{timestamp}} and order by {{amount}} and compute the
{{RANK()}} function on each partition.
I'm not sure if the current OVER window implementations are able to execute
your use case.
> Integrating the OVER windows in the Table API
> ---------------------------------------------
>
> Key: FLINK-6228
> URL: https://issues.apache.org/jira/browse/FLINK-6228
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Reporter: sunjincheng
> Assignee: sunjincheng
>
> Syntax:
> {code}
> table
> .overWindows(
> (Rows|Range [ partitionBy value_expression , ... [ n ]] [ orderBy
> order_by_expression]
> (preceding
> UNBOUNDED|value_specification.(rows|milli|second|minute|hour|day|month|year)|CURRENTROW)
> [following
> UNBOUNDED|value_specification.(rows|milli|second|minute|hour|day|month|year)|CURRENTROW]
> as alias,...[n])
> )
> .select( [col1,...[n]], (agg(col1) OVER overWindowAlias, … [n])
> {code}
> Implement restrictions:
> * 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 Before the
> [FLINK-5884|https://issues.apache.org/jira/browse/FLINK-5884] implementation
> orderBy may only have ‘rowtime/’proctime(for stream)/‘specific-time-field(for
> batch).
> * FOLLOWING is not supported.
> I will soon add a user interface design document.
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