Hi, Alternatively if you would like to create continuous aggregates per key you can use ds.groupBy().reduce(..), or use one of the stateful functions in the scala api such as mapWithState.
For a rolling average per key you can check this exmple: https://github.com/gyfora/summer-school/blob/master/flink/src/main/scala/summerschool/FlinkKafkaExample.scala Cheers, Gyula On Fri, Aug 21, 2015 at 3:28 PM Aljoscha Krettek <aljos...@apache.org> wrote: > Hi, > with the current API this should do what you are after: > > val input = ... > > val result = input > .window(...) > .groupBy(...) > .reduceWindow( /* your reduce function */ ) > > With the reduce function you should be able to implement any custom > aggregations. You can also use foldWindow() if you want to do a functional > fold over the window. > > I hope this helps. > > Cheers, > Aljoscha > > On Fri, 21 Aug 2015 at 14:51 Philipp Goetze <philipp.goe...@tu-ilmenau.de> > wrote: > >> Hello community, >> >> how do I define a custom aggregate function in Flink Streaming (Scala)? >> Could you please provide an example on how to do that? >> >> Thank you and best regards, >> Philipp >> >
