[akka-user] Streams M4: Reasons behind the new MAT type parameter/why does .to default to Keep.left?

2015-03-02 Thread Giovanni Alberto Caporaletti
I'm trying to better understand the new api.  If I got it right, the new 
type parameter of the various stream components represents the type of 
what's materialized by that component when the stream is run 
(materialized).  E.g.: A Source(actorProducerProps) has the actorRef as its 
materialization.

Now I have two questions:
1) In which cases could it be useful to know the materialization type of 
intermediate components? I mean, as a stream consumer (i.e. client, in a 
generic sense), if someone gives me a Source[T,M], I should only know that 
it produces T elements, the M type looks like implementation detail. What 
am I missing?
2) Why does .to default to Keep.left? Aren't we almost always interested in 
the materialized result of Sinks (right)? I see a lot of [T, Unit] around.



Thanks!
G

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[akka-user] [Streams 1.0-M4] Using Balance to partition to independent sinks

2015-03-02 Thread rmarsch
Hi,

I have a use case that I believe Akka Streams may be well suited for, but 
I'm not clearly seeing how to implement part of it from reading the 
documentation.

I have a single, finite input source from an iterator stream. I want to use 
Balance to split this stream into N partitions and then be able to feed 
these stream partitions each into a RunnableFlow that would be executed on 
its own node in a distributed system.

in ~ balance.out(0) ~ sink0
 balance.out(1) ~ sink1
 ...
 balance.out(n) ~ sinkN

I have some rough code sketched together, but I think I'm missing some 
concepts to tie everything together. Runtime complains about the inlet for 
the UniformInOutShape which I'm assuming is what I have in the inputGraph. 
Any nudge in the right direction would be appreciated:


val iteratorBuilder: () = Iterator[T] = ???


val inputGraph: Graph[UniformFanOutShape[T,T], Unit] = FlowGraph.partial() { 
implicit builder : FlowGraph.Builder =
  import FlowGraph.Implicits._

  val stream: SourceShape[T] = builder.add(Source(iteratorBuilder))
  val balance = builder.add(Balance[T](numPartitions))

  stream ~ balance

  balance
}

partitions = (0 until numPartitions).map(i = {
  val sink : Sink[T, Future[Stream[T]]] = Sink.fold(Stream.empty[T]) { (v, e) 
= v.+:(e) }

  val outFlow: RunnableFlow[Future[Stream[T]]] = FlowGraph.closed(sink) { 
implicit builder : FlowGraph.Builder = sink =
import FlowGraph.Implicits._
val balance = builder.add(inputGraph)

balance.out(i) ~ sink
  }

  new Partition(i, outFlow)
  }).toArray

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[akka-user] GSOC(2015)

2015-03-02 Thread adam kozuch
Hello,
I would like to ask if anyone from Akka Team would like to be Google Summer 
of Code mentor this year?

Cheers, 
Adam Kozuch

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Re: [akka-user] [Streams 1.0-M4] From Source[Future[T], Unit] to Source[T, Unit]?

2015-03-02 Thread Jim Hazen
I think the answer is in the {Scala, Java}Docs of mapAsync:

Transform this stream by applying the given function to each of the 
 elements as they pass through this processing step. The function returns a 
 Future and the value of that future will be emitted downstreams. As many 
 futures as requested elements by downstream may run in parallel and may 
 complete in any order, but the elements that are emitted downstream are in 
 the same order as received from upstream.


The section on rate goes into greater 
detail: 
http://doc.akka.io/docs/akka-stream-and-http-experimental/1.0-M4/scala/stream-rate.html

You can either go with the default demand as specified by your 
Materialization settings, use the default settings (default values in 
reference.conf), or manually specify a buffer downstream from your source 
to have greater control over buffering and generated demand.

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[akka-user] [Streams 1.0-M4] Compatibility with Akka-2.4-SNAPSHOT?

2015-03-02 Thread Jim Hazen
Are these 1.0-M4 modules intended to be compatible with akka-2.4-SNAPSHOT?

I'm having trouble passing a custom materializer to an 
IncommingConnection.handleWithAsyncHandler().  The default materializer 
seems to work fine, but I wanted to play with buffer sizes.

implicit val materializer = ActorFlowMaterializer()
val matSettings = materializer.settings.withInputBuffer(16, 32)


Http().bind(interface = 0.0.0.0, 5001).runForeach { conn =
  conn.handleWithAsyncHandler(r = 
Future(HttpResponse()))(ActorFlowMaterializer(matSettings))
}.onComplete(_ = actorSystem.terminate())


The fails at runtime with:

java.lang.NoSuchMethodError: 
akka.pattern.AskableActorRef$.$qmark$extension(Lakka/actor/ActorRef;Ljava/lang/Object;Lakka/util/Timeout;)Lscala/concurrent/Future;
at 
akka.stream.impl.ActorFlowMaterializerImpl.actorOf(ActorFlowMaterializerImpl.scala:185)
at 
akka.stream.impl.ActorFlowMaterializerImpl$$anon$2.processorFor(ActorFlowMaterializerImpl.scala:92)
at 
akka.stream.impl.ActorFlowMaterializerImpl$$anon$2.materializeAtomic(ActorFlowMaterializerImpl.scala:77)
at 
akka.stream.impl.MaterializerSession$$anonfun$materializeModule$1.apply(StreamLayout.scala:336)
at 
akka.stream.impl.MaterializerSession$$anonfun$materializeModule$1.apply(StreamLayout.scala:334)


I couldn't find akka-stream or akka-http modules as part of the akka-2.4 
distribution.  Is there a better way to experiment with akka-streams and 
akka-http with akka-2.4?  Aside from tweaking the handler's materializer, 
is there another way to control the amount of buffering/demand generated by 
the handleWith* constructs?

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Re: [akka-user] Dead letter JournalProtocol#WriteMessageSuccessful

2015-03-02 Thread Björn Antonsson
Hi Anders,

How are you stopping your actor. There is a difference between 
system.stop(actorRef) and actorRef ! PoisonPill.

Calling stop is more direct and will as you say send a message, but that is an 
internal system message that will cut the line and be processed before normal 
actor messages.

If you on the other hand sends the actor a PoisonPill, it will process all 
messages that it has in the inbox up until the PoisonPill, and then shut down. 
Please note that there can of course be messages enqueued after the PoisonPill 
that won't be handled.

B/

On 27 February 2015 at 13:26:30, Anders Båtstrand (ander...@gmail.com) wrote:

Dear users

Sometimes I find dead letter JournalProtocol#WriteMessageSuccessful in my logs, 
after I have stopped my actor.

As I understand it, stop involves a message send, so all write operations 
should be finished before the actor is stopped. How is it still possible to get 
this message AFTER my actor is gone?

Regards, Anders
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Re: [akka-user] [Java 1.7.0_60][Play 2.3.5][AKKA 2.3.4] Suggestions for AKKA clustering approach in auto-scaled system.

2015-03-02 Thread Björn Antonsson
Hi Anupam,

Have you looked at the Reactivve Maps, Activator Tutorial 
http://typesafe.com/activator/template/reactive-maps ? It has the Play web 
front end talking to the back end using akka clustering.

B/

On 27 February 2015 at 16:20:11, Anupam Sharma (anu.lnmiit.1...@gmail.com) 
wrote:

Could you please suggest some appropriate AKKA clustering mechanism for the 
AKKA actor system ( description of which is given right after) used in

conjunction with play framework.

Description of our system.

We have several AKKA actors(different actors for database interaction, XMPP 
interaction and some for supervision), which are fired once we get a  
web-service request

on play-framework. We will be getting very few requests on play-framework and 
it will respond asynchronously to those and handover the lengthy handling of 
request to AKKA system. AKKA system should take some minutes to process one 
request fully.

We get our web service requests at elastic load balancer which sprays the 
requests to instances running play server at its disposal. Play server running 
instances are 

part of a auto scaling group with minimum instances set to 2 ( More instances 
are spawned automatically if needed. ).

Why We need AKKA Clustering approach 

We need AKKA clustering approach to scale AKKA system independently. If we just 
use Play framework's AKKA system we will be just putting the load on

current instance ( instance which is running the play framework) while other 
instances may have not have any load.

Thanks,

Anupam

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Re: [akka-user] Advice on connecting spark-shell to a containerized standalone master

2015-03-02 Thread Björn Antonsson
Hi Simeon,

What you are experiencing is this the issue where the local address used to 
bind the akka actor system inside the docker container doesn't match up with 
the external address that is exposed by the host running docker, and that you 
are trying to connect to. Akka will then refuse to accept the incoming 
connection and messages, since they are clearly meant for another system with 
another address.

This has been fixed in this ticket https://github.com/akka/akka/issues/15007 
for Akka 2.4.x, but the feature is not available for 2.3.x.

B/

On 27 February 2015 at 21:02:07, Simeon Fitch (fi...@datamininglab.com) wrote:

I’m attempting to deploy Spark in stand-alone mode using Docker containers on 
CoreOS. I’ve got the master running fine, can connect to the web UI fine, but 
when I attempt to connect to it from  
spark-shell, from a non-local machine, the connection negotiation never 
completes.

I’m launching the shell like this:  
spark-shell --master spark://172.17.8.102:7077. Here’s what I see on the 
master, right after I launch the  
spark-shell, but the connection never completes..


Feb 26 16:00:09 core-02 docker[26172]: 15/02/26 16:00:09 ERROR EndpointWriter: 
dropping message [class akka.actor.ActorSelectionMessage] for non-local 
recipient [Actor[akka.tcp://sparkMaster@172.17.8.102:7077/]] arriving at 
[akka.tcp://sparkMaster@172.17.8.102:7077] inbound addresses are 
[akka.tcp://sparkMaster@a9dcfc43a383:7077]

Feb 26 16:00:28 core-02 docker[26172]: 15/02/26 16:00:28 ERROR EndpointWriter: 
dropping message [class akka.actor.ActorSelectionMessage] for non-local 
recipient [Actor[akka.tcp://sparkMaster@172.17.8.102:7077/]] arriving at 
[akka.tcp://sparkMaster@172.17.8.102:7077] inbound addresses are 
[akka.tcp://sparkMaster@a9dcfc43a383:7077]

Feb 26 16:01:09 core-02 docker[26172]: 15/02/26 16:01:09 INFO Master: 
akka.tcp://sparkdri...@xyz.com:55541 got disassociated, removing it.  

Feb 26 16:01:09 core-02 docker[26172]: 15/02/26 16:01:09 WARN 
ReliableDeliverySupervisor: Association with remote system 
[akka.tcp://sparkdri...@xyz.com:55541] has failed, address is now gated for 
[5000] ms. Reason is: [Disassociated].  

Feb 26 16:01:09 core-02 docker[26172]: 15/02/26 16:01:09 INFO Master: 
akka.tcp://sparkdri...@xyz.com:55541 got disassociated, removing it.

The fact that something is logged immediately after  
spark-shell is launched indicates to me that packets are getting from the 
remote client to the master, but the connection negotiation never finishes.

Can someone give me some hints as to what I might be doing wrong here?

Thanks,

Simeon

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[akka-user] Re: unstashAll() not queuing messages until actor death

2015-03-02 Thread Sam Halliday
Grr, so it seems that TestActorRef really is incompatible with Stash.

  http://stackoverflow.com/questions/18335127

This is a real shame.

On Monday, 2 March 2015 12:35:22 UTC, Sam Halliday wrote:

 Wow, I think I figured this out... and it's quite scary.

 Stash needs an unbounded mailbox. I didn't quite pick up on this because 
 somebody in our team had made the default dispatcher an unbounded mailbox 
 at some point and now there is no going back.

 Then when I wanted to use TestActorRef, it blew up when I tried to create 
 my actor because it uses an unbounded mailbox, so I had to give it a 
 bounded mailbox to pass the test.

 *That seems to have disabled Stash without any warning* for this Actor.

 There seems to be several funky things going on here:

 1. why doesn't initialisation blow up when I have an Actor with Stash used 
 with an unbounded mailbox?
 2. why is TestActorRef enforcing that unbounded mailboxes cannot be used? 
 --- doesn't this mean that TestActorRef cannot be used to test an Actor 
 with Stash?



 On Monday, 2 March 2015 12:13:40 UTC, Sam Halliday wrote:

 Looks like I'm seeing the same thing as

   https://groups.google.com/d/msg/akka-user/Vb2dQtZX6DI/lZtEvg8DwkkJ

 but I see the Awaken message immediately ... which means the 
 `unstashAll` simply hasn't added anything onto the actor queue (until after 
 the actor dies?)

 On Monday, 2 March 2015 12:05:52 UTC, Sam Halliday wrote:

 Hi all,

 I have an Actor which is using Stash and is working through two 
 different Receive behaviours with context.become. Messages are stashed 
 until we're ready to receive them.

 I've used context.become(), stash() and unstashAll() several times, so 
 I'm pretty familiar with them, but I'm seeing a bizarre behaviour in this 
 Actor and I was wondering if I'm using it wrong in a subtle way.

 In the part of the Actor code that is causing the problem, I am doing 
 this:

   def catchUp: Receive = LoggingReceive {
 case item: PublishItem =
   stash()
 case event: Event =
   context.become(republishing)
   unstashAll()
   }

   def republishing: Receive = LoggingReceive {
 case event: PublishItem =
   downstream ! event
 case e: Event = // ignore leftover messages from the dying loader
   }


 In my test I send a bunch of PublishItem's, then send the Event that 
 changes the behaviour. Then I assert that 'downstream' receives all the 
 backlogged PublishItems.

 However, what I'm actually seeing are handled events for the 
 PublishItem and Event into the catchUp behaviour. Then I see the test 
 timing out waiting for the PublishItem to appear in downstream and then 
 (the really weird bit) the actor is stopped and AFTER this actor stops, all 
 the PublishItems show up in the dead letters mailbox.

 Any ideas?

 As a workaround, I am managing my own stash as a Queue, but this sucks 
 because my stashed messages arrive after other messages that are already 
 queued and that breaks the assumed logic of the whole actor.

 I'm using akka 2.3.9 on scala 2.11.5

 Best regards,
 Sam



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Re: [akka-user] [Streams 1.0-M4] From Source[Future[T], Unit] to Source[T, Unit]?

2015-03-02 Thread Luis Ángel Vicente Sánchez
You should use mapAsync instead of map.
On 2 Mar 2015 18:03, kermitas kermi...@gmail.com wrote:

 Hello,

 as an input I have

 Source[PageDetails, Unit]

 and I also have method which transform PageDetails to
 Future[CategoryVector]:

 def categorizePage(page: PageDetails): Future[CategoryVector]

 By using map method I can change Source[PageDetails, Unit] to
 Source[Future[CategoryVector], Unit]:

 val sourceOfPageDetails: Source[PageDetails, Unit] = ...
 val notSomethingThatIWant: Source[Future[CategoryVector], Unit]
 = sourceOfPageDetails.map(categorizePage)

 ... but as an output I need Source[CategoryVector, Unit] (not Source[
 *Future[*CategoryVector*]*, Unit]) :/.

 How can I solve this problem?

 Thanks,
 Arthur.

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[akka-user] [Streams 1.0-M4] From Source[Future[T], Unit] to Source[T, Unit]?

2015-03-02 Thread kermitas
Hello,

as an input I have

Source[PageDetails, Unit]

and I also have method which transform PageDetails to Future[CategoryVector]
:

def categorizePage(page: PageDetails): Future[CategoryVector]

By using map method I can change Source[PageDetails, Unit] to Source[Future[
CategoryVector], Unit]: 

val sourceOfPageDetails: Source[PageDetails, Unit] = ...
val notSomethingThatIWant: Source[Future[CategoryVector], Unit] 
= sourceOfPageDetails.map(categorizePage)

... but as an output I need Source[CategoryVector, Unit] (not Source[
*Future[*CategoryVector*]*, Unit]) :/.

How can I solve this problem?

Thanks,
Arthur.

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[akka-user] Re: Akka Cluster (and Cluster Client) on Kubernetes

2015-03-02 Thread Jim Hazen
Might want to look at this thread. 
 https://groups.google.com/forum/#!topic/akka-user/wyA4xNfM5LM

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[akka-user] Re: Akka Cluster (and Cluster Client) on Kubernetes

2015-03-02 Thread Jim Hazen
Lol.  Or not, since you're the OP.  Oh well, need more coffee.

On Monday, March 2, 2015 at 10:52:29 AM UTC-8, Jim Hazen wrote:

 Might want to look at this thread.  
 https://groups.google.com/forum/#!topic/akka-user/wyA4xNfM5LM


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[akka-user] Akka Cluster (and Cluster Client) on Kubernetes

2015-03-02 Thread Ashley Aitken

Howdy All,

Has anyone had any experience getting an Akka Cluster and Cluster Client 
running on Kubernetes, e.g. on Google Container Engine (GCE)?

I note the problem with Akka dropping messages when the host IP address 
doesn't match the container virtual IP address.

I note the solution in Akka 2.4.

I would most appreciate anyone confirming if they have an Akka Cluster 
running on Kubernetes (on GCE or not) and sharing any tips / hints.

Thanks in advance,
Ashley.

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Re: [akka-user] [Streams 1.0-M4] From Source[Future[T], Unit] to Source[T, Unit]?

2015-03-02 Thread kermitas
THANK YOU Luis!! :) That is what I needed.

Let's imagine that I have just one stream run in one JVM. Do you know how 
many futures will be evaluated and wait for completion? You know, I can not 
have billion of futures in memory :/. Will this be auto-regulated by back 
pressure of if not then where I can configure maximal number of futures?

Thanks!

W dniu poniedziałek, 2 marca 2015 19:32:32 UTC+1 użytkownik Luis Ángel 
Vicente Sánchez napisał:

 You should use mapAsync instead of map.
 On 2 Mar 2015 18:03, kermitas kerm...@gmail.com javascript: wrote:

 Hello,

 as an input I have

 Source[PageDetails, Unit]

 and I also have method which transform PageDetails to 
 Future[CategoryVector]:

 def categorizePage(page: PageDetails): Future[CategoryVector]

 By using map method I can change Source[PageDetails, Unit] to 
 Source[Future[CategoryVector], Unit]: 

 val sourceOfPageDetails: Source[PageDetails, Unit] = ...
 val notSomethingThatIWant: Source[Future[CategoryVector], Unit] 
 = sourceOfPageDetails.map(categorizePage)

 ... but as an output I need Source[CategoryVector, Unit] (not Source[
 *Future[*CategoryVector*]*, Unit]) :/.

 How can I solve this problem?

 Thanks,
 Arthur.

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