I'll create a new thread with my last message since it's not completely
related with the original question here.
On Sat, Jan 28, 2017 at 11:55 AM, Matt <dromitl...@gmail.com> wrote:
> Aha, ok, got it!
>
> I just realized that this ConnectedStream I was talking about (A) depends
> on another ConnectedStream (B), which depends on the first one (A). So it's
> even trickier than I first thought.
>
> For instance (simplified):
>
> *predictionStream = **input*
> .connect(*statsStream*)
> .keyBy(...)
> .flatMap(CoFlatMapFunction {
> flatMap1(obj, output) {
> p = prediction(obj)
> * output.collect(p)*
> }
> flatMap2(stat, output) {
> updateModel(stat)
> }
> })
>
> *statsStream = input2*
> .connect(*predictionStream*)
> .keyBy(...)
> .flatMap(CoFlatMapFunction {
> flatMap1(obj2, output) {
> s = getStats(obj2, p)
> * output.collect(s)*
> }
> flatMap2(prediction, output) {
> p = prediction
> }
> })
>
> I'm guessing it should be possible to achieve, one way would be to add a
> sink on statsStream to save the elements into Kafka and read from that
> topic on predictionStream instead of initializing it with a reference of
> statsStream. I would rather avoid writing unnecessarily into kafka.
>
> Is there any other way to achieve this?
>
> Thanks,
> Matt
>
> On Fri, Jan 27, 2017 at 6:35 AM, Timo Walther <twal...@apache.org> wrote:
>
>> Hi Matt,
>>
>> the keyBy() on ConnectedStream has two parameters to specify the key of
>> the left and of the right stream. Same keys end up in the same
>> CoMapFunction/CoFlatMapFunction. If you want to group both streams on a
>> common key, then you can use .union() instead of .connect().
>>
>> I hope that helps.
>>
>> Timo
>>
>>
>> Am 27/01/17 um 07:21 schrieb Matt:
>>
>> Hi all,
>>>
>>> What's the purpose of .keyBy() on ConnectedStream? How does it affect
>>> .map() and .flatMap()?
>>>
>>> I'm not finding a way to group stream elements based on a key, something
>>> like a Window on a normal Stream, but for a ConnectedStream.
>>>
>>> Regards,
>>> Matt
>>>
>>
>>
>>
>
