Akka and the Java Memory Model

A major benefit of using the Lightbend Platform, including Scala and Akka, is that it simplifies the process of writing concurrent software. This article discusses how the Lightbend Platform, and Akka in particular, approaches shared memory in concurrent applications.

The Java Memory Model

Prior to Java 5, the Java Memory Model (JMM) was ill defined. It was possible to get all kinds of strange results when shared memory was accessed by multiple threads, such as:

  • a thread not seeing values written by other threads: a visibility problem
  • a thread observing ‘impossible’ behavior of other threads, caused by instructions not being executed in the order expected: an instruction reordering problem.

With the implementation of JSR 133 in Java 5, a lot of these issues have been resolved. The JMM is a set of rules based on the “happens-before” relation, which constrain when one memory access must happen before another, and conversely, when they are allowed to happen out of order. Two examples of these rules are:

  • The monitor lock rule: a release of a lock happens before every subsequent acquire of the same lock.
  • The volatile variable rule: a write of a volatile variable happens before every subsequent read of the same volatile variable

Although the JMM can seem complicated, the specification tries to find a balance between ease of use and the ability to write performant and scalable concurrent data structures.

Actors and the Java Memory Model

With the Actors implementation in Akka, there are two ways multiple threads can execute actions on shared memory:

  • if a message is sent to an actor (e.g. by another actor). In most cases messages are immutable, but if that message is not a properly constructed immutable object, without a “happens before” rule, it would be possible for the receiver to see partially initialized data structures and possibly even values out of thin air (longs/doubles).
  • if an actor makes changes to its internal state while processing a message, and accesses that state while processing another message moments later. It is important to realize that with the actor model you don’t get any guarantee that the same thread will be executing the same actor for different messages.

To prevent visibility and reordering problems on actors, Akka guarantees the following two “happens before” rules:

  • The actor send rule: the send of the message to an actor happens before the receive of that message by the same actor.
  • The actor subsequent processing rule: processing of one message happens before processing of the next message by the same actor.

In layman’s terms this means that changes to internal fields of the actor are visible when the next message is processed by that actor. So fields in your actor need not be volatile or equivalent.

Both rules only apply for the same actor instance and are not valid if different actors are used.

Futures and the Java Memory Model

The completion of a Future “happens before” the invocation of any callbacks registered to it are executed.

We recommend not to close over non-final fields (final in Java and val in Scala), and if you do choose to close over non-final fields, they must be marked volatile in order for the current value of the field to be visible to the callback.

If you close over a reference, you must also ensure that the instance that is referred to is thread safe. We highly recommend staying away from objects that use locking, since it can introduce performance problems and in the worst case, deadlocks. Such are the perils of synchronized.

Actors and shared mutable state

Since Akka runs on the JVM there are still some rules to be followed.

  • Closing over internal Actor state and exposing it to other threads
import akka.actor.{ Actor, ActorRef }
import akka.pattern.ask
import akka.util.Timeout
import scala.concurrent.Future
import scala.concurrent.duration._
import scala.language.postfixOps
import scala.collection.mutable

case class Message(msg: String)

class EchoActor extends Actor {
  def receive = {
    case msg => sender() ! msg

class CleanUpActor extends Actor {
  def receive = {
    case set: mutable.Set[_] => set.clear()

class MyActor(echoActor: ActorRef, cleanUpActor: ActorRef) extends Actor {
  var state = ""
  val mySet = mutable.Set[String]()

  def expensiveCalculation(actorRef: ActorRef): String = {
    // this is a very costly operation
    "Meaning of life is 42"

  def expensiveCalculation(): String = {
    // this is a very costly operation
    "Meaning of life is 42"

  def receive = {
    case _ =>
      implicit val ec = context.dispatcher
      implicit val timeout = Timeout(5 seconds) // needed for `?` below

      // Example of incorrect approach
      // Very bad: shared mutable state will cause your
      // application to break in weird ways
      Future { state = "This will race" }
      ((echoActor ? Message("With this other one")).mapTo[Message]).foreach { received =>
        state = received.msg

      // Very bad: shared mutable object allows
      // the other actor to mutate your own state,
      // or worse, you might get weird race conditions
      cleanUpActor ! mySet

      // Very bad: "sender" changes for every message,
      // shared mutable state bug
      Future { expensiveCalculation(sender()) }

      // Example of correct approach
      // Completely safe: "self" is OK to close over
      // and it's an ActorRef, which is thread-safe
      Future { expensiveCalculation() }.foreach { self ! _ }

      // Completely safe: we close over a fixed value
      // and it's an ActorRef, which is thread-safe
      val currentSender = sender()
      Future { expensiveCalculation(currentSender) }
  • Messages should be immutable, this is to avoid the shared mutable state trap.
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