Thanks! This works with the exception that I have to use the reduceWindow() method when summing up my the content of the window. There still seems to be some work to do.
With the finished Api will I be able to switch from event-time to processing- or ingestion-time without having to adjust my code? Best, Alex Aljoscha Krettek <aljos...@apache.org> schrieb am Mi., 7. Okt. 2015, 17:23: > Hi, > right now, the 0.10-SNAPSHOT is in a bit of a weird state. We still have > the old windowing API in there alongside the new one. To make your example > use the new API that actually uses the timestamps and watermarks you would > use the following code: > > env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime) > val stream = env.addSource(SourceWithEventTime) > > stream > .timeWindowAll(Time.of(5,TimeUnit.SECONDS)) > // or .windowAll(SlidingTimeWindows.of(Time.of(5, TimeUnit.SECONDS))) > .sum(0) > .print() > > the version for keyed streams would be: > stream > .keyBy(...) > .timeWindow(Time.of(5,TimeUnit.SECONDS)) > // or .window(SlidingTimeWindows.of(Time.of(5, TimeUnit.SECONDS))) > .sum(0) > .print() > > I hope this helps. :D > > Cheers, > Aljoscha > > > On Wed, 7 Oct 2015 at 16:54 Alexander Kolb < > alexander.k...@mni.fh-giessen.de> wrote: > >> Hi Guys, >> >> I'm trying to use the event-time windowing feature. But the windowing >> does not work as expected. >> >> What I've been doing is to write my own source which implements the >> EventTimeSourceFunction and uses the collectWithTimeStamp method. >> Additionally I'm emitting a watermark after each element. >> >> My job to test this looks like this: >> >> env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime) >> val stream = env.addSource(SourceWithEventTime) >> >> stream >> .window(Time.of(5,TimeUnit.SECONDS)) >> .sum(0) >> .flatten() >> .print() >> >> env.execute() >> >> The Input are some tuples with TimeStamps set 10 seconds apart: >> >> value: (1,test) timestamp: 1444228980390 >> value: (2,foo) timestamp: 1444228990390 >> value: (3,bar) timestamp: 1444229000390 >> >> What I'm expecting is that each tuple goes into a separate window. >> The actual output is the sum of all tuples, hence all tuples are >> collected in the same window. >> >> Thanks in advance! >> Alex >> >> >>
