Can Scala actors process multiple messages simultaneously?

Actors process one message at a time. The classic pattern to process multiple messages is to have one coordinator actor front for a pool of consumer actors. If you use react then the consumer pool can be large but will still only use a small number of JVM threads. Here’s an example where I create a pool of 10 consumers and one coordinator to front for them.

import scala.actors.Actor
import scala.actors.Actor._

case class Request(sender : Actor, payload : String)
case class Ready(sender : Actor)
case class Result(result : String)
case object Stop

def consumer(n : Int) = actor {
  loop {
    react {
      case Ready(sender) => 
        sender ! Ready(self)
      case Request(sender, payload) =>
        println("request to consumer " + n + " with " + payload)
        // some silly computation so the process takes awhile
        val result = ((payload + payload + payload) map {case '0' => 'X'; case '1' => "-"; case c => c}).mkString
        sender ! Result(result)
        println("consumer " + n + " is done processing " + result )
      case Stop => exit
    }
  }
}

// a pool of 10 consumers
val consumers = for (n <- 0 to 10) yield consumer(n)

val coordinator = actor {
  loop {
     react {
        case msg @ Request(sender, payload) =>
           consumers foreach {_ ! Ready(self)}
           react {
              // send the request to the first available consumer
              case Ready(consumer) => consumer ! msg
           }
         case Stop => 
           consumers foreach {_ ! Stop} 
           exit
     }
  }
}

// a little test loop - note that it's not doing anything with the results or telling the coordinator to stop
for (i <- 0 to 1000) coordinator ! Request(self, i.toString)

This code tests to see which consumer is available and sends a request to that consumer. Alternatives are to just randomly assign to consumers or to use a round robin scheduler.

Depending on what you are doing, you might be better served with Scala’s Futures. For instance, if you don’t really need actors then all of the above machinery could be written as

import scala.actors.Futures._

def transform(payload : String) = {      
  val result = ((payload + payload + payload) map {case '0' => 'X'; case '1' => "-"; case c => c}).mkString
  println("transformed " + payload + " to " + result )
  result
}

val results = for (i <- 0 to 1000) yield future(transform(i.toString))

I think that the answer is that an Actor cannot handle messages aynchronously. If you have an Actor which should be listening to messages where these messages can be handled asynchronously, then it could be written like this:

val actor_ = actor {

  loop {
    react {
      case msg =>
        //create a new actor to execute the work. The framework can then 
        //manage the resources effectively
        actor {
          //do work here
        }
      }
    }
  }