Future Composition with Scala and Akka

Scala is functional and object-oriented language, which runs on the JVM. For concurrent and/or parallel programming it is a suitable choice along with the Akka framework, which provides a rich toolset for all kind of concurrent tasks. In this post I want to show a little example how to schedule a logfile-search job on multiple files/servers with Futures and Actors.


I created my setup with the Typesafe Activator Hello-Akka template. This results in a build.sbt file with the following content:

name := """hello-akka"""

version := "1.0"

scalaVersion := "2.10.2"

libraryDependencies ++= Seq(
  "com.typesafe.akka" %% "akka-actor" % "2.2.0",
  "com.typesafe.akka" %% "akka-testkit" % "2.2.0",
  "" % "guava" % "14.0.1",
  "org.scalatest" % "scalatest_2.10" % "1.9.1" % "test",
  "junit" % "junit" % "4.11" % "test",
  "com.novocode" % "junit-interface" % "0.7" % "test->default"

testOptions += Tests.Argument(TestFrameworks.JUnit, "-v")

Scala build-in Futures

Scala has already a build-in support for Futures. The implementation is based on java.util.concurrent. Let’s implement a Future which runs our log search.

import scala.concurrent._
import scala.concurrent.duration._
import scala.concurrent.ExecutionContext.Implicits._

object LogSearch extends App {

println("Starting log search")

val searchFuture = future {
  Thread sleep 1000
  "Found something"

println("Blocking for results")
  val result = Await result (searchFuture, 5 seconds)
  println(s"Found $result")

This is all we need to run our task in another thread. The implicit import from ExecutionContext provides a default ExecutionContext which handles the threads the future is running on. After creating the future we wait with a blocking call Await result for our results. So far nothing too fancy.

Future composition

There are a lot of examples where the for-yield syntax is used to compose future results. In our case we have a dynamic list of futures: the log search results from each server.

For testing future capabilities we will create a list of futures from a list of ints which represent the time the task will run. Types are just for clarification.

val tasks = List(3000, 1200, 1800, 600, 250, 1000, 1100, 8000, 550)
val taskFutures: List[Future[String]] = tasks map { ms =>
  future {
    Thread sleep ms
    s"Task with $ms ms"

In the end, we want a List[String] as a result. This is done with the Futures companion object.

val searchFuture: Future[List[String]] = Future sequence taskFutures

And finally we can wait for our results with

val result = Await result (searchFuture, 2 seconds)

However this will throw a TimeoutException, as some of our tasks run more than 2 seconds. Of course we could increase the timeout, but there error could always happen again, when a server is down. Another approach would be to handle the exception and return an error. However all other results would be lost.

Future – Timeout fallback

No problem, we generate a fallback, which will return a default value if the operation takes, too long. A very naive implementation for our fallback could look like this

def fallback[A](default: A, timeout: Duration): Future[A] = future {
  Thread sleep timeout.toMillis

The fallback future will return after the executing thread has sleeped for the timeout duration. The calling code now looks like this.

val timeout = 2 seconds
val tasks = List(3000, 1200, 1800, 600, 250, 1000, 1100, 8000, 550)
val taskFutures: List[Future[String]] = tasks map { ms =>
val search = future {
  Thread sleep ms
  s"Task with $ms ms"

Future firstCompletedOf Seq(search,
  fallback(s"timeout $ms", timeout))

val searchFuture: Future[List[String]] = Future sequence taskFutures

println("Blocking for results")
val result = Await result (searchFuture, timeout * tasks.length)
println(s"Found $result")

The important call here is Future firstCompletedOf Seq(..) which produces a future returning the result of the first finished future.

This implementation is very bad as discussed here. In short: We are wasting CPU time by putting threads to sleep. Also the blocking call timeout is more or less a guess. With a one-thread scheduler it can actually take more time.

Futures and Akka

Now let’s do this more performant and more robust. Our main goal is to get rid of the poor fallback implementation, which was blocking a complete thread. The idea is now to schedule the fallback feature after a given duration. By this you have all threads working on real, while the fallback future execution time is almost zero. Java has a ScheduledExecutorService on it’s own or you can use a different implementation, a HashedWheelTimer, by Netty. Akka used to use the HashWheelTimer, but has now a own implementation.

So let’s start with the actor.

import akka.pattern.{ after, ask, pipe }
import akka.util.Timeout

class LogSearchActor extends Actor {

  def receive = {
    case Search(worktimes, timeout) =>
      // Doing all the work in one actor using futures
      val searchFutures = worktimes map { worktime =>
      val searchFuture = search(worktime)
      val fallback = after(timeout, context.system.scheduler) {
          Future successful s"$worktime ms > $timeout" 
        Future firstCompletedOf Seq(searchFuture, fallback)

      // Pipe future results to sender
      (Future sequence searchFutures) pipeTo sender

  def search(worktime: Int): Future[String] = future {
      Thread sleep worktime
      s"found something in $worktime ms"

case class Search(worktime: List[Int], timeout: FiniteDuration)

The important part is the after method call. You give it a duration after which the future should be executed and as a second parameter the scheduler, which is the default one of the actor system in our case. The third parameter is the future which should get executed. I use the Future success companion method to return a single string.

The rest of the code is almost identical. PipeTo is a akka pattern to return results of a future to the sender. Nothing fancy here.

Now how to call all this. First the code

object LogSearch extends App {

println("Starting actor system")
val system = ActorSystem("futures")

println("Starting log search")
try {
  // timeout for each search task
  val fallbackTimeout = 2 seconds

  // timeout use with akka.patterns.ask
  implicit val timeout = new Timeout(5 seconds)

  require(fallbackTimeout < timeout.duration) 

  // Create SearchActor 
  val search = system.actorOf(Props[LogSearchActor]) 

  // Test worktimes for search 
  val worktimes = List(1000, 1500, 1200, 800, 2000, 600, 3500, 8000, 250) 

  // Asking for results 
  val futureResults = (search ? Search(worktimes, fallbackTimeout)) 
    // Cast to correct type 
    // In case something went wrong 
    .recover { 
       case e: TimeoutException => List("timeout")
       case e: Exception => List(e getMessage)
  // Callback (non-blocking)
  .onComplete {
      case Success(results) =>
         println(":: Results ::")
         results foreach (r => println(s" $r"))
         system shutdown ()
      case Failure(t) =>
         t printStackTrace ()
      system shutdown ()

} catch {
  case t: Throwable =>
  t printStackTrace ()
  system shutdown ()

  // Await end of programm
  system awaitTermination (20 seconds)

The comments should explain most of the parts. This example is completly asynchronous and works with callbacks. Of course you can use the Await result call as before.



Reference: Future Composition with Scala and Akka from our JCG partner Nepomuk Seiler at the blog.

Nepomuk Seiler

Nepomuk Seiler is a information sience student at the Ludwigs-Maximilians-University Munich. He uses Scala for machine learning tasks and web development with play. Also he provided some small contributions to the Eclipse community.
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