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Posted to issues@flink.apache.org by "Rong Rong (JIRA)" <ji...@apache.org> on 2019/02/15 21:54:00 UTC
[jira] [Updated] (FLINK-11454) Support MergedStream operation
[ https://issues.apache.org/jira/browse/FLINK-11454?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Rong Rong updated FLINK-11454:
------------------------------
Description:
{{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:
{{slideOver}} and {{apply}} can be combined into a {{OVER AGGREGATE}} implementation similar to the one in TableAPI.
was:
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:
`slideOver` and `apply` can be combined into a `OVER AGGREGATE` implementation similar to the one in TableAPI.
> 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:
> {{slideOver}} and {{apply}} can be combined into a {{OVER AGGREGATE}} implementation similar to the one in TableAPI.
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