Hi, this is not supported by the DSL layer. What you would need to do, is to add a custom stateful transform() operator after there window (`stream.groupByKey().aggregate().toStream().transform().to()`), that buffers the output and remembers the latest result. Second, you would schedule a punctuation that emit the data whenever you want.
Hope this helps. -Matthias On 8/31/17 9:52 PM, Praveen wrote: > Hi, > > I have a use case where I want to schedule processing of events in the > future. I am not really sure if this a proper use of stream processing > application. But I was looking at KTable and kafka streams api to see if > this was possible. > > So far the pattern I have is: > FEED -> changelog stream -> groupByKey() -> window -> write to > different kafka topic > > The window here i believe would be the TumblingWindow for my use case. I'd > like to write back to a kafka topic only after the window retention ends. > The documentation > <http://docs.confluent.io/current/streams/developer-guide.html#writing-streams-back-to-kafka> > says that streams may only be written "continuously" to the kafka topic. Is > that the case? > > - Praveen >
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