Hello John, Thank you for your response,
I am using custom time extractor, in final stage i am persisting streamed data into timeseries database and when i did a double check from there, i confirmed that time calculation seems correct. How about warning message that i mentioned ? How can be possible that i am taking that warning ? I mean that i could not get the point/root cause ... or do i need to pass that message without taking any action ? On 11 May 2020 Mon at 18:33 John Roesler <vvcep...@apache.org> wrote: > Hello Baki, > > It looks like option 2 is really what you want. The purpose of the time > window stores is to allow deleting old data when you need to group by a > time dimension, which naturally results in an infinite key space. > > If you don’t want to wait for the final result, can you just not add the > suppression? It’s only purpose is to _not_ emit any data until _after_ the > grace period expires. Without it, streams will still respect the grace > period by updating the result whenever there is late arriving data. > > Lastly, that is a check for overflow. The timestamp is supposed to be a > timestamp in milliseconds since the epoch. If you’re getting an overflow, > it means your time stamps are from the far future. You might want to > manually inspect them. > > I hope this helps, > John > > > On Sun, May 10, 2020, at 05:29, Baki Hayat wrote: > > Hello Friends, > > > > I wrote into stackoverflow but also i am writing here, > > > > I have couple of questions about window operation, grace period and late > > events. > > > > Could you please check my problem about group by with adding time field > as > > a key or window by and group by without time field ? > > > > Here is detail explanation... > > > > > https://stackoverflow.com/questions/61680407/kafka-streams-groupby-late-event-persistentwindowstore-windowby-with-gra > > >
