Thanks. I was able to quickly build a simple example out of this. Also saw the issue with punctuate and your “tick” feed recommendation for now.
- Praveen On Fri, Sep 1, 2017 at 9:48 AM, Matthias J. Sax <matth...@confluent.io> wrote: > 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 > > > >
