Hi,
I think it is currently the right approach. I hope that we can in the
future provide APIs to make such cases more pleasant to implement.
Cheers,
Aljoscha
On Wed, 25 May 2016 at 22:13 prateekarora <prateek.arora...@gmail.com>
wrote:
> Hi
>
> I am trying to port my spark application in flink.
>
> In spark i have used below command to join multiple stream :
>
> val stream=stream1.join(stream2).join(stream3).join(stream4)
>
>
> As per my understanding flink required window operation because flink
> don't
> works on RDD like spark.
>
> so i tried below code to port my spark code in flink . but i don't know its
> a right approach or right way to implement join between multiple stream .
>
> val stream_join_1 =
>
> stream1.join(stream2).where(_.getField(0).toString()).equalTo(_.getField(0).toString()).window(TumblingEventTimeWindows.of(Time.milliseconds(windowSize))).apply{
> (l, r) =>
>
>
> (l.getField(0).toString(),(l.getField(1).toString(),r.getField(1).toString()))
> }
>
> val stream_join_2 =
>
> stream3.join(stream4).where(_.getField(0).toString()).equalTo(_.getField(0).toString()).window(TumblingEventTimeWindows.of(Time.milliseconds(windowSize))).apply{
> (l, r) =>
>
>
> (l.getField(0).toString(),(l.getField(1).toString(),r.getField(1).toString()))
> }
>
> val stream =
>
> stream_join_1.join(stream_join_2).where(_._1).equalTo(_._1).window(TumblingEventTimeWindows.of(Time.milliseconds(windowSize))).apply{
> (l, r) =>
> (l._1,(((l._2._1,l._2._2),r._2._1),r._2._2))
> }
>
>
> please help me to find out right approach .
>
>
> Regards
> Prateek
>
>
>
> --
> View this message in context:
> http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/How-to-perform-multiple-stream-join-functionality-tp7184.html
> Sent from the Apache Flink User Mailing List archive. mailing list archive
> at Nabble.com.
>
