Assume I have three methods in an Akka actor that I need to invoke from an actor client:
class MyActor extends Actor {
def receive = {
case req1: Request1 => sender ! method1()
case req2: Request2 => sender ! method2()
case req3: Request3 => sender ! method3()
}
}
I need to invoke these methods in different combinations, for example:
method1, method2
method3
method1, method2, method3
I could have in the client the following method to invoke method1:
def invokeMethod1 () {
val system = ActorSystem("system")
implicit val timeout = Timeout(120 seconds)
val actor = system.actorOf(Props[MyActor], name = "myactor")
val future = actor ? Request1
val result = Await.result(future, timeout.duration)
}
What is the best strategy to invoke methods in different combinations? should I have a invokeMethod1, invokeMethod2 and invokeMethod3 (note that each one initializes the actor system)? Or should I combine in the actor itself the methods, for example method1and2? Is there any other preferred way?
i recommend use to for-loop ,
def invokeMetod1:Future[Int] = ???
def invokeMetod2:Future[Int] = ???
def invokeMetod3:Future[Int] = ???
val a =
for{
_1 <- invokeMetod1
_3 <- invokeMetod3
_2 <- invokeMetod2
}yield
_1 + _2 + _3
it can sequential execution (invokeMetod1 and then invokeMetod3 and then invokeMetod2)
Related
I have an app that generate reports, with akka-http + akka-actors + akka-camel + akka-streams. When a post request arrives , the ActiveMqProducerActor enqueue the request into ActiveMq Broker. Then the ActiveMqConsumerActor consumes the message and start the task using akka-streams(in this actor i need the materializer) .
The main class create the ActorSystem and the ActorMaterializer, but i dont know how is the correct way to "inject" the materializer into the akka-actor
object ReportGeneratorApplication extends App {
implicit val system: ActorSystem = ActorSystem()
implicit val executor = system.dispatcher
implicit val materializer = ActorMaterializer()
val camelExtension: Camel = CamelExtension(system);
val amqc: ActiveMQComponent = ActiveMQComponent.activeMQComponent(env.getString("jms.url"))
amqc.setUsePooledConnection(true)
amqc.setAsyncConsumer(true)
amqc.setTrustAllPackages(true)
amqc.setConcurrentConsumers(1)
camelExtension.context.addComponent("jms", amqc);
val jmsProducer: ActorRef = system.actorOf(Props[ActiveMQProducerActor])
//Is this the correct way to pass the materializer?
val jmsConsumer: ActorRef = system.actorOf(Props(new ActiveMQConsumerActor()(materializer)), name = "jmsConsumer")
val endpoint: ReportEndpoint = new ReportEndpoint(jmsProducer);
Http().bindAndHandle(endpoint.routes, "localhost", 8881)
}
The ReportEndPoint class, that have the jmsProducerActor . Mongo is a trait with CRUD methods. JsonSupport(==SprayJsonSupport)
class ReportEndpoint(jmsProducer: ActorRef)
(implicit val system:ActorSystem,
implicit val executor: ExecutionContext,
implicit val materializer : ActorMaterializer)
extends JsonSupport with Mongo {
val routes =
pathPrefix("reports"){
post {
path("generate"){
entity(as[DataRequest]) { request =>
val id = java.util.UUID.randomUUID.toString
// **Enqueue the request into ActiveMq**
jmsProducer ! request
val future: Future[Seq[Completed]] = insertReport(request)
complete {
future.map[ToResponseMarshallable](r => r.head match {
case r : Completed => println(r); s"Reporte Generado con id $id"
case _ => HttpResponse(StatusCodes.InternalServerError, entity = "Error al generar reporte")
})
}
}
}
} ....
The idea of ActiveMqConsumerActor, is send the messages, with streams and backpressure, one by one,because ReportBuilderActor makes many mongo operations (and the datacenter it`s not very good).
//Is this the correct way to pass the materializer??
class ActiveMQConsumerActor (implicit materializer : ActorMaterializer) extends Consumer with Base {
override def endpointUri: String = env.getString("jms.queue")
val log = Logging(context.system, this)
val reportActor: ActorRef = context.actorOf(Props(new ReportBuilderActor()(materializer)), name = "reportActor")
override def receive: Receive = {
case msg: CamelMessage => msg.body match {
case data: DataRequest => {
//I need only one task running
Source.single(data).buffer(1, OverflowStrategy.backpressure).to(Sink.foreach(d => reportActor ! d)).run()
}
case _ => log.info("Invalid")
}
case _ => UnhandledMessage
}
}
Is a good idea have implicit values in companion objects?
Thanks!!
I have the following code that I need to run around 100 times:
val system = ActorSystem("mySystem")
val myActorObject = system.actorOf(Props[MyActorClass], name = "myactor")
implicit val timeout = Timeout(60 seconds)
val future = myActorObject ? Request1
val result = Await.result(future, timeout.duration)
Question is: assuming the first two statements can be called just once, should I cache these variables or Akka does it?
Do not make the actor system creation and actor creation part of repetitive code. Once the actor is created. Using the ActorRef can be done as many times as possible.
val system = ActorSystem("mySystem")
val myActorObject = system.actorOf(Props[MyActorClass], name = "myactor")
Something like this
val futureList = for(_ <- 1 to 1000) yield {
implicit val timeout = Timeout(60 seconds)
val future = myActorObject ? Request1
}
val finalF = Future.sequence(futureList)
val result = Await.result(future, timeout.duration)
In play! (+2.5.x) you can get the system by injection. e.g.
#Singleton
class MyController #Inject() (system: ActorSystem) extends Controller {
val myActor = system.actorOf(MyActorClass.props, "myactor")
//...
}
Then you could have an end point to call the actor as many times as you want, for example
def sayHello(name: String) = Action.async {
(myActor ? name).map { message => Ok(message) }
}
The code inside your actor could be something like this
class MyActorClass extends Actor {
def receive = {
case name: String => sender() ! s"hello $name"
}
}
object MyActorClass {
def props: Props = Props(classOf[MyActorClass ])
}
I want to write some function that can return different Class objects according to the arguments.
For example, I have some classes that extends akka Actor, and I want to get their classes by passing different Int values. The code below is not correct, but I think you can understand what I mean:
def createActor(num: Int): Unit {
val c: Class = o.getActorClass(num)
system.actorOf(Props[c]) ! "hello"
}
object o {
val m: Map[Int, Class] = Map(1->classOf[Actor1], 2->classOf[Actor2])
def getActorClass(num: Int): Class {
m(num)
}
}
Hope my question is understandable. Thank you!
If you simply return the ActorRef, you should be fine.
def createActor(num: Int): ActorRef = {
val c = o.getActorClass(num)
val actor = system.actorOf(Props(c))
actor ! "hello"
actor
}
I would create a generator method for creating a new mapping under a given actor system like so:
def newMapping(sys: ActorSystem, mappings: (Int, Props)*) = {
assert(sys != null)
val m = mappings.toMap
(i: Int) => sys.actorOf(m(i))
}
Then you can create different mappings with different ActorSystems and ultimately get the effect you desire:
val sys = ActorSystem("sys1")
val myMapping = newMapping(sys, 1 -> Props[Class1], 2 -> Props[Class2])
val actor1 = myMapping(1)
val actor2 = myMapping(2)
I need to create an akka.stream.scaladsl.Source[T, Unit] from a collection of Future[T].
E.g., having a collection of futures returning integers,
val f1: Future[Int] = ???
val f2: Future[Int] = ???
val fN: Future[Int] = ???
val futures = List(f1, f2, fN)
how to create a
val source: Source[Int, Unit] = ???
from it.
I cannot use Future.sequence combinator, since then I would wait for each future to complete before getting anything from the source. I want to get results in any order as soon as any future completes.
I understand that Source is a purely functional API and it should not run anything before somehow materializing it. So, my idea is to use an Iterator (which is lazy) to create a source:
Source { () =>
new Iterator[Future[Int]] {
override def hasNext: Boolean = ???
override def next(): Future[Int] = ???
}
}
But that would be a source of futures, not of actual values. I could also block on next using Await.result(future) but I'm not sure which tread pool's thread will be blocked. Also this will call futures sequentially, while I need parallel execution.
UPDATE 2: it turned out there was a much easier way to do it (thanks to Viktor Klang):
Source(futures).mapAsync(1)(identity)
UPDATE: here is what I've got based on #sschaef answer:
def futuresToSource[T](futures: Iterable[Future[T]])(implicit ec: ExecutionContext): Source[T, Unit] = {
def run(actor: ActorRef): Unit = {
futures.foreach { future =>
future.onComplete {
case Success(value) =>
actor ! value
case Failure(NonFatal(t)) =>
actor ! Status.Failure(t) // to signal error
}
}
Future.sequence(futures).onSuccess { case _ =>
actor ! Status.Success(()) // to signal stream's end
}
}
Source.actorRef[T](futures.size, OverflowStrategy.fail).mapMaterializedValue(run)
}
// ScalaTest tests follow
import scala.concurrent.ExecutionContext.Implicits.global
implicit val system = ActorSystem()
implicit val materializer = ActorMaterializer()
"futuresToSource" should "convert futures collection to akka-stream source" in {
val f1 = Future(1)
val f2 = Future(2)
val f3 = Future(3)
whenReady {
futuresToSource(List(f1, f2, f3)).runFold(Seq.empty[Int])(_ :+ _)
} { results =>
results should contain theSameElementsAs Seq(1, 2, 3)
}
}
it should "fail on future failure" in {
val f1 = Future(1)
val f2 = Future(2)
val f3 = Future.failed(new RuntimeException("future failed"))
whenReady {
futuresToSource(List(f1, f2, f3)).runWith(Sink.ignore).failed
} { t =>
t shouldBe a [RuntimeException]
t should have message "future failed"
}
}
Creating a source of Futures and then "flatten" it via mapAsync:
scala> Source(List(f1,f2,fN)).mapAsync(1)(identity)
res0: akka.stream.scaladsl.Source[Int,Unit] = akka.stream.scaladsl.Source#3e10d804
One of the easiest ways to feed a Source is through an Actor:
import scala.concurrent.Future
import akka.actor._
import akka.stream._
import akka.stream.scaladsl._
implicit val system = ActorSystem("MySystem")
def run(actor: ActorRef): Unit = {
import system.dispatcher
Future { Thread.sleep(100); actor ! 1 }
Future { Thread.sleep(200); actor ! 2 }
Future { Thread.sleep(300); actor ! 3 }
}
val source = Source
.actorRef[Int](0, OverflowStrategy.fail)
.mapMaterializedValue(ref ⇒ run(ref))
implicit val m = ActorMaterializer()
source runForeach { int ⇒
println(s"received: $int")
}
The Actor is created through the Source.actorRef method and made available through the mapMaterializedValue method. run simply takes the Actor and sends all the completed values to it, which can then be accessed through source. In the example above, the values are sent directly in the Future, but this can of course be done everywhere (for example in the onComplete call on the Future).
I have an existing API which returns a Future. Now introducing an Actor for one of the use cases and trying to continue using same service API from it. From below you can see MyService.saveValues return future.
object MyActor {
implicit val ec = scala.concurrent.ExecutionContext.Implicits.global
implicit val timeout = Timeout(1 second)
case class SampleMessage(list: List[String])
val actorSystem = //get actorSystem that was created at the startup
def saveMessage(list: List[String]) ={
val res = (actorSystem.actorOf(Props[MyActor]) ? SaveMyMessage(list) ).mapTo[Future[\/[Throwable,String]]
//res map{ r=>
//}
}
}
class MyActor extends Actor {
import MyActor._
def receive = {
case SaveMyMessage(list) =>
val originalSender = sender
val res : Future[\/[Throwable,String] ] = MyService.saveValues(list)
originalSender ! res
}
}
As you can see in def saveMessage I am using ask to wait for a result from an actor. However ask also creates its own future so result (val res) in saveMessage becomes Future[Future[T]] which looks annoying. What's the best way to deal with this scenario?
pipeTo forwards the result of a Future to an ActorRef.
import akka.pattern.pipe
val originalSender = sender
val res : Future[\/[Throwable,String] ] = MyService.saveValues(list)
res pipeTo originalSender
If saveValues throws, your future never complete and will end up timing something out though.
If you ever end up with Future[Future[A]], but want Future[A] as a result of sequencing/traversing or something, you can always "flatMap that shit."
import ExecutionContext.Implicits.global
val foo: Future[Future[Int]] = ???
val bar: Future[Int] = foo.flatMap(identity)
If you already depend on scalaz (and scalaz.contrib if on scalaz 7.0.x), you can use join defined in monad syntax.
import scalaz.syntax.monad._
import scalaz.contrib.std.scalaFuture._
val bar2: Future[Int] = foo.join