So, you are saying that I can do the join with a regular stream by using the union transformation? For that, I would need to know which data belongs to which stream. I can add some tags to the streamed data so that I would know by which order I should join the elements. This was what you were proposing right? The only drawback, I think, is that tuples in both upstreams would have to be scanned 2 times: 1 time for performing the union, and then again to perform the join in a custom function.
Thanks! On Fri, Feb 3, 2017 at 2:48 PM, Aljoscha Krettek <aljos...@apache.org> wrote: > Hi, > I'm afraid that's not possible but you can use a regular stream and do the > join yourself. What the code for JoinedStreams essentially does is take two > streams, map them to a common data type, union them and then perform a > normal window operation. > > The code for this is in CoGroupedStreams (as the general case of a join) > and JoinedStreams. > > Cheers, > Aljoscha > > On Mon, 30 Jan 2017 at 17:38 Saiph Kappa <saiph.ka...@gmail.com> wrote: > >> Hi all, >> >> Is it possible to specify allowed lateness for a window join like the >> following one: >> >> val tweetsAndWarning = >> warningsPerStock.join(tweetsPerStock).where(_.symbol).equalTo(_.symbol) >> .window(SlidingEventTimeWindows.of(Time.of(windowDurationSec, >> TimeUnit.SECONDS), Time.of(windowDurationSec, >> TimeUnit.SECONDS))) >> .apply((c1, c2) => (c1.count, c2.count)) >> >> >> I think it is related with these: >> https://cwiki.apache.org/confluence/display/FLINK/ >> Streaming+Window+Join+Rework >> https://issues.apache.org/jira/browse/FLINK-3109 >> >> >> Thanks! >> >
