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From Robert Metzger <rmetz...@apache.org>
Subject Re: PartitionedState and watermark of Window coGroup()
Date Wed, 14 Dec 2016 14:45:26 GMT
Hi,
elements are coGrouped on the specified key. So only elements with the same
key in both streams end up in the same group.

Yes, the watermark uses the minimum of both streams.




On Tue, Dec 13, 2016 at 7:02 PM, Sendoh <unicorn.banachi@gmail.com> wrote:

> Hi Flink users,
>
> I'm a bit confused about how these two work when writing trigger for window
> coGroup().
>
> Stream1.assignTimestampsAndWatermarks(new EventWatermark())
>                 .coGroup(Stream2.assignTimestampsAndWatermarks(new
> EventWatermark()))
>                 .where(new JSONKey("key")).equalTo(new JSONKey("key"))
>
> .window(TumblingEventTimeWindows.of(Time.days(7))).trigger(new
> CoGroupTrigger())
>                 .apply(new CoGroupFunction<JSONObject, JSONObject,
> JSONObject>() {
> ...
> ...
> }
>
> The documentation describes(
> https://github.com/apache/flink/blob/master/flink-
> streaming-scala/src/main/scala/org/apache/flink/streaming/api/scala/
> CoGroupedStreams.scala#L37)
> *A streaming co-group operation is evaluated over elements in a window.*
>
> Does it mean elements are not keyed by the joined key?
>
> Another question is does the watermark take the minimum timestamps of two
> streams (or keyed streams, if elements are keyed)?
>
> Our trigger is going to fire the window when watermark has passed two keyed
> streams' timestamps, because one stream is much smaller and consumed much
> faster. A similar trigger has been implemented for keyed stream, which
> means
> if we cannot make coGroup() behave as expected, we can still union those
> two
> streams into one stream and use similar solution.
>
> Best,
>
> Sendoh
>
>
>
>
> --
> View this message in context: http://apache-flink-user-
> mailing-list-archive.2336050.n4.nabble.com/PartitionedState-and-
> watermark-of-Window-coGroup-tp10620.html
> Sent from the Apache Flink User Mailing List archive. mailing list archive
> at Nabble.com.
>

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