Any other opinion on this?
Thanks :) Aris ________________________________ From: aris kol <gizera...@hotmail.com> Sent: Sunday, August 28, 2016 12:04 AM To: user@flink.apache.org Subject: Re: Accessing state in connected streams In the implementation I am passing just one CoFlatMapFunction, where flatMap1, which operates on EventA, just emits a None (doesn't do anything practically) and flatMap2 tries to access the state and throws the NPE. It wouldn't make sense to use a mapper in this context, I would still want to flatten afterwards before pushing dowstream. Aris ________________________________ From: Sameer W <sam...@axiomine.com> Sent: Saturday, August 27, 2016 11:40 PM To: user@flink.apache.org Subject: Re: Accessing state in connected streams Ok sorry about that :-). I misunderstood as I am not familiar with Scala code. Just curious though how are you passing two MapFunction's to the flatMap function on the connected stream. The interface of ConnectedStream requires just one CoMap function- https://ci.apache.org/projects/flink/flink-docs-master/api/java/org/apache/flink/streaming/api/datastream/ConnectedStreams.html Sameer On Sat, Aug 27, 2016 at 6:13 PM, aris kol <gizera...@hotmail.com<mailto:gizera...@hotmail.com>> wrote: Let's say I have two types sharing the same trait trait Event { def id: Id } case class EventA(id: Id, info: InfoA) extends Event case class EventB(id: Id, info: InfoB) extends Event Each of these events gets pushed to a Kafka topic and gets consumed by a stream in Flink. Let's say I have two streams Events of type A create state: val typeAStream = env.addSource(...) .flatMap(someUnmarshallerForA) .keyBy(_.id) .mapWithState(...) val typeBStream = env.addSource(...) .flatMap(someUnmarshallerForB) .keyBy(_.id) I want now to process the events in typeBStream using the information stored in the State of typeAStream. One approach would be to use the same stream for the two topics and then pattern match, but Event subclasses may grow in numbers and may have different loads, thus I may want to keep things separate. Would something along the lines of: typeAStream.connect(typeBStream). flatMap( new IdentityFlatMapFunction(), new SomeRichFlatMapFunctionForEventB[EventB, O] with StateFulFuntion[EventB, O, G[EventA]] { ... } ) work? I tried this approach and I ended up in a NPE because the state object was not initialized (meaning it was not there). Thanks, Aris
