True, at this point it does not pre-aggregate in parallel, that is actually a feature on the list but not yet added...
On Fri, Feb 26, 2016 at 7:08 PM, Saiph Kappa <[email protected]> wrote: > That code will not run in parallel right? So, a map-reduce task would > yield better performance no? > > > > On Fri, Feb 26, 2016 at 6:06 PM, Stephan Ewen <[email protected]> wrote: > >> Then go for: >> >> input.timeWindowAll(Time.seconds(10)).fold(0, new >> FoldFunction<Tuple2<Integer, Integer>, Integer>() { @Override public >> Integer fold(Integer integer, Tuple2<Integer, Integer> o) throws Exception >> { return integer + 1; } }); >> >> Try to explore the API a bit, most things should be quite intuitive. >> There are also some docs: >> https://ci.apache.org/projects/flink/flink-docs-release-0.10/apis/streaming_guide.html#windows-on-unkeyed-data-streams >> >> On Fri, Feb 26, 2016 at 4:07 PM, Saiph Kappa <[email protected]> >> wrote: >> >>> Why the ".keyBy"? I don't want to count tuples by Key. I simply want to >>> count all tuples that are contained in a window. >>> >>> On Fri, Feb 26, 2016 at 9:14 AM, Till Rohrmann <[email protected]> >>> wrote: >>> >>>> Hi Saiph, >>>> >>>> you can do it the following way: >>>> >>>> input.keyBy(0).timeWindow(Time.seconds(10)).fold(0, new >>>> FoldFunction<Tuple2<Integer, Integer>, Integer>() { >>>> @Override >>>> public Integer fold(Integer integer, Tuple2<Integer, Integer> o) >>>> throws Exception { >>>> return integer + 1; >>>> } >>>> }); >>>> >>>> Cheers, >>>> Till >>>> >>>> >>>> On Thu, Feb 25, 2016 at 7:58 PM, Saiph Kappa <[email protected]> >>>> wrote: >>>> >>>>> Hi, >>>>> >>>>> In Flink Stream what's the best way of counting the number of tuples >>>>> within a window of 10 seconds? Using a map-reduce task? Asking because in >>>>> spark there is the method rawStream.countByWindow(Seconds(x)). >>>>> >>>>> Thanks. >>>>> >>>> >>>> >>> >> >
