[
https://issues.apache.org/jira/browse/FLINK-11454?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16769779#comment-16769779
]
Rong Rong commented on FLINK-11454:
-----------------------------------
Initial thought was to use the {{[Proctime/Rowtime][Bounded/Unbounded]Over}}
operator in TableAPI to implement this.
However, this will involve a migration from the TabelAPI to the DataStream API.
Wasn't sure if this is worth some discussion first before I dive into the
implementation. Any suggestions are welcome [~fhueske] [~aljoscha]
> Support MergedStream operation
> ------------------------------
>
> Key: FLINK-11454
> URL: https://issues.apache.org/jira/browse/FLINK-11454
> Project: Flink
> Issue Type: Sub-task
> Components: DataStream API
> Reporter: Rong Rong
> Assignee: Rong Rong
> Priority: Major
>
> Following SlicedStream, the mergedStream operator merges results from sliced
> stream and produces windowing results.
> {code:java}
> val slicedStream: SlicedStream = inputStream
> .keyBy("key")
> .sliceWindow(Time.seconds(5L)) // new “slice window” concept: to
> combine
> // tumble results based on discrete
> // non-overlapping windows.
> .aggregate(aggFunc)
> val mergedStream1: MergedStream = slicedStream
> .slideOver(Time.second(10L)) // combine slice results with same
>
> // windowing function, equivalent to
> // WindowOperator with an aggregate
> state
> // and derived aggregate function.
> val mergedStream2: MergedStream = slicedStream
> .slideOver(Count.of(5))
> .apply(windowFunction) // apply a different window function
> over
> // the sliced results.{code}
> MergedStream are produced by MergeOperator.
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
