concurrency - Can Scala actors process multiple messages simultaneously?

Question

The reply to a recent question of mine indicated that an actor processed its messages one at a time. Is this true? I see nothing that explicitly says that (in Programming in Scala), which contains the following snippet (pp. 593)

If [the react method] finds a message that can be handled, [it] will schedule the handling of that message for later execution and throw an exception

(Emphasis my own). Two related (and mutually exclusive) questions:

1. Assuming an actor could process multiple messages simulatenously, how can I force an actor to process messages 1 at a time (if this is what I wish to do)? (using receive?)
2. Assuming an actor processes messages one at a time, how would I best implement an actor which in fact could process messages concurrently

edit: doing a bit of testing seems to bear out that I am wrong and that actors are indeed sequential. So it's question #2 which I need answering

Answer 1

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))