Sounds to me like you want a pooled set of streams for processing your 
events, with the restriction that events with the same ID must go into the 
same stream?

If that's the case, a FlexiRoute with a fixed set of downstreams should do 
the job. Then all you need is a way of consistently selecting a downstream 
based on event ID (e.g. hashcode modulo n) - this will be more extensible 
than storing a map with every event ID you encounter.

On Monday, 20 July 2015 16:03:10 UTC+1, Gabriel Volpe wrote:
>
> I don't understand how the FlexiRoute could be the solution. Could you 
> expand the case further?
>
> Actually, I'm solving the problem using only Akka Actors and it's quite 
> easy. I have a Controller Actor which has a Map[Long, ActorRef] 
> corresponding to the Event ID and the Processor Actor (child).
>
> Whenever the Controller receives an event, it checks if the ID already 
> exists in the map and it sends a message to the Processor. If the ID does 
> not exists, it creates another processor actor only for this Event ID. The 
> only problem with this approach is that I have to control the back-pressure 
> manually, that's why I'm trying Akka Streams.
>
> Thanks,
> Gabriel.
>
> El lunes, 20 de julio de 2015, 14:51:35 (UTC+1), Konrad Malawski escribió:
>>
>> I think you might want to use a FlexiRoute 
>> http://doc.akka.io/docs/akka-stream-and-http-experimental/1.0/scala/stream-customize.html#Using_FlexiRoute
>> And in it you'd decide "which way the element should go".
>> You'd have 2 outputs from it, one being the async path, and the other one 
>> the other path.
>> After done with the event (via one of these Flows), you'd add a Merge at 
>> the end of them and thus be able to still consume it using one sink.
>>
>> Maybe I missed something in your requirements?
>>
>> On Fri, Jul 17, 2015 at 4:57 PM, Gabriel Volpe <[email protected]> 
>> wrote:
>>
>>> Hi all, this is my case:
>>>
>>> I have a queue (Rabbit MQ) producing Json data with the following 
>>> format: 
>>>
>>> { "id": 123, "message": "hello" }
>>> { "id": 876, "message": "shutdown" }
>>> { "id": 123, "message": "bye" }
>>>
>>> And I have a respective Consumer. What I want to do is to distribute the 
>>> load depending on the *id* field. I mean, if the id already appeared 
>>> before I want to respect the order, if not I want to process the event in 
>>> parallel. This would be the Flow:
>>>
>>> case class Event(id: Long, message: String)
>>>
>>> val queue = Source(rabbitQueueConnection).mapAsync(100)(d => Future(
>>> fromJson(d.message.body.utf8String)))
>>> val processor = Flow[Try[Option[Event]]] filter (_.isSuccess) map (_.get
>>> ) filter (_.isDefined) map (_.get)
>>> val out = Sink.ignore
>>>
>>> queue ~> processor ~> out
>>>
>>> I've been playing around 
>>> <https://github.com/gvolpe/events-processor-prototype/blob/master/src/main/scala/com/gvolpe/prototypes/processor/flows/ConsumerProcessorFlow.scala>
>>>  
>>> but I don't know how to do this.
>>>
>>> Any ideas?
>>>
>>> Thanks,
>>> Gabriel.
>>>
>>> -- 
>>> >>>>>>>>>> Read the docs: http://akka.io/docs/
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>>
>>
>>
>> -- 
>> Cheers,
>> Konrad 'ktoso' Malawski
>> Akka <http://akka.io/> @ Typesafe <http://typesafe.com/>
>>  
>

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