FSM
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FSM

Overview

The FSM (Finite State Machine) is available as a mixin for the akka Actor and is best described in the Erlang design principles

A FSM can be described as a set of relations of the form:

State(S) x Event(E) -> Actions (A), State(S')

These relations are interpreted as meaning:

If we are in state S and the event E occurs, we should perform the actions A and make a transition to the state S'.

A Simple Example

To demonstrate most of the features of the FSM trait, consider an actor which shall receive and queue messages while they arrive in a burst and send them on after the burst ended or a flush request is received.

First, consider all of the below to use these import statements:

import akka.actor.{ Actor, ActorRef, FSM }
import scala.concurrent.duration._

The contract of our “Buncher” actor is that it accepts or produces the following messages:

// received events
case class SetTarget(ref: ActorRef)
case class Queue(obj: Any)
case object Flush

// sent events
case class Batch(obj: immutable.Seq[Any])

SetTarget is needed for starting it up, setting the destination for the Batches to be passed on; Queue will add to the internal queue while Flush will mark the end of a burst.

// states
sealed trait State
case object Idle extends State
case object Active extends State

sealed trait Data
case object Uninitialized extends Data
case class Todo(target: ActorRef, queue: immutable.Seq[Any]) extends Data

The actor can be in two states: no message queued (aka Idle) or some message queued (aka Active). It will stay in the active state as long as messages keep arriving and no flush is requested. The internal state data of the actor is made up of the target actor reference to send the batches to and the actual queue of messages.

Now let’s take a look at the skeleton for our FSM actor:

class Buncher extends FSM[State, Data] {

  startWith(Idle, Uninitialized)

  when(Idle) {
    case Event(SetTarget(ref), Uninitialized) =>
      stay using Todo(ref, Vector.empty)
  }

  // transition elided ...

  when(Active, stateTimeout = 1 second) {
    case Event(Flush | StateTimeout, t: Todo) =>
      goto(Idle) using t.copy(queue = Vector.empty)
  }

  // unhandled elided ...

  initialize()
}

The basic strategy is to declare the actor, mixing in the FSM trait and specifying the possible states and data values as type parameters. Within the body of the actor a DSL is used for declaring the state machine:

  • startWith defines the initial state and initial data
  • then there is one when(<state>) { ... } declaration per state to be handled (could potentially be multiple ones, the passed PartialFunction will be concatenated using orElse)
  • finally starting it up using initialize, which performs the transition into the initial state and sets up timers (if required).

In this case, we start out in the Idle and Uninitialized state, where only the SetTarget() message is handled; stay prepares to end this event’s processing for not leaving the current state, while the using modifier makes the FSM replace the internal state (which is Uninitialized at this point) with a fresh Todo() object containing the target actor reference. The Active state has a state timeout declared, which means that if no message is received for 1 second, a FSM.StateTimeout message will be generated. This has the same effect as receiving the Flush command in this case, namely to transition back into the Idle state and resetting the internal queue to the empty vector. But how do messages get queued? Since this shall work identically in both states, we make use of the fact that any event which is not handled by the when() block is passed to the whenUnhandled() block:

whenUnhandled {
  // common code for both states
  case Event(Queue(obj), t @ Todo(_, v)) =>
    goto(Active) using t.copy(queue = v :+ obj)

  case Event(e, s) =>
    log.warning("received unhandled request {} in state {}/{}", e, stateName, s)
    stay
}

The first case handled here is adding Queue() requests to the internal queue and going to the Active state (this does the obvious thing of staying in the Active state if already there), but only if the FSM data are not Uninitialized when the Queue() event is received. Otherwise—and in all other non-handled cases—the second case just logs a warning and does not change the internal state.

The only missing piece is where the Batches are actually sent to the target, for which we use the onTransition mechanism: you can declare multiple such blocks and all of them will be tried for matching behavior in case a state transition occurs (i.e. only when the state actually changes).

onTransition {
  case Active -> Idle =>
    stateData match {
      case Todo(ref, queue) => ref ! Batch(queue)
    }
}

The transition callback is a partial function which takes as input a pair of states—the current and the next state. The FSM trait includes a convenience extractor for these in form of an arrow operator, which conveniently reminds you of the direction of the state change which is being matched. During the state change, the old state data is available via stateData as shown, and the new state data would be available as nextStateData.

To verify that this buncher actually works, it is quite easy to write a test using the Testing Actor Systems, which is conveniently bundled with ScalaTest traits into AkkaSpec:

import akka.actor.Props
import scala.collection.immutable

class FSMDocSpec extends MyFavoriteTestFrameWorkPlusAkkaTestKit {

  // fsm code elided ...

  "simple finite state machine" must {

    "demonstrate NullFunction" in {
      class A extends FSM[Int, Null] {
        val SomeState = 0
        when(SomeState)(FSM.NullFunction)
      }
    }

    "batch correctly" in {
      val buncher = system.actorOf(Props(classOf[Buncher], this))
      buncher ! SetTarget(testActor)
      buncher ! Queue(42)
      buncher ! Queue(43)
      expectMsg(Batch(immutable.Seq(42, 43)))
      buncher ! Queue(44)
      buncher ! Flush
      buncher ! Queue(45)
      expectMsg(Batch(immutable.Seq(44)))
      expectMsg(Batch(immutable.Seq(45)))
    }

    "not batch if uninitialized" in {
      val buncher = system.actorOf(Props(classOf[Buncher], this))
      buncher ! Queue(42)
      expectNoMsg
    }
  }
}

Reference

The FSM Trait and Object

The FSM trait inherits directly from Actor, when you extend FSM you must be aware that an actor is actually created:

class Buncher extends FSM[State, Data] {

  // fsm body ...

  initialize()
}

Note

The FSM trait defines a receive method which handles internal messages and passes everything else through to the FSM logic (according to the current state). When overriding the receive method, keep in mind that e.g. state timeout handling depends on actually passing the messages through the FSM logic.

The FSM trait takes two type parameters:

  1. the supertype of all state names, usually a sealed trait with case objects extending it,
  2. the type of the state data which are tracked by the FSM module itself.

Note

The state data together with the state name describe the internal state of the state machine; if you stick to this scheme and do not add mutable fields to the FSM class you have the advantage of making all changes of the internal state explicit in a few well-known places.

Defining States

A state is defined by one or more invocations of the method

when(<name>[, stateTimeout = <timeout>])(stateFunction).

The given name must be an object which is type-compatible with the first type parameter given to the FSM trait. This object is used as a hash key, so you must ensure that it properly implements equals and hashCode; in particular it must not be mutable. The easiest fit for these requirements are case objects.

If the stateTimeout parameter is given, then all transitions into this state, including staying, receive this timeout by default. Initiating the transition with an explicit timeout may be used to override this default, see Initiating Transitions for more information. The state timeout of any state may be changed during action processing with setStateTimeout(state, duration). This enables runtime configuration e.g. via external message.

The stateFunction argument is a PartialFunction[Event, State], which is conveniently given using the partial function literal syntax as demonstrated below:

when(Idle) {
  case Event(SetTarget(ref), Uninitialized) =>
    stay using Todo(ref, Vector.empty)
}

when(Active, stateTimeout = 1 second) {
  case Event(Flush | StateTimeout, t: Todo) =>
    goto(Idle) using t.copy(queue = Vector.empty)
}

The Event(msg: Any, data: D) case class is parameterized with the data type held by the FSM for convenient pattern matching.

Warning

It is required that you define handlers for each of the possible FSM states, otherwise there will be failures when trying to switch to undeclared states.

It is recommended practice to declare the states as objects extending a sealed trait and then verify that there is a when clause for each of the states. If you want to leave the handling of a state “unhandled” (more below), it still needs to be declared like this:

when(SomeState)(FSM.NullFunction)

Defining the Initial State

Each FSM needs a starting point, which is declared using

startWith(state, data[, timeout])

The optionally given timeout argument overrides any specification given for the desired initial state. If you want to cancel a default timeout, use Duration.Inf.

Unhandled Events

If a state doesn't handle a received event a warning is logged. If you want to do something else in this case you can specify that with whenUnhandled(stateFunction):

whenUnhandled {
  case Event(x: X, data) =>
    log.info("Received unhandled event: " + x)
    stay
  case Event(msg, _) =>
    log.warning("Received unknown event: " + msg)
    goto(Error)
}

Within this handler the state of the FSM may be queried using the stateName method.

IMPORTANT: This handler is not stacked, meaning that each invocation of whenUnhandled replaces the previously installed handler.

Initiating Transitions

The result of any stateFunction must be a definition of the next state unless terminating the FSM, which is described in Termination from Inside. The state definition can either be the current state, as described by the stay directive, or it is a different state as given by goto(state). The resulting object allows further qualification by way of the modifiers described in the following:

  • forMax(duration)

    This modifier sets a state timeout on the next state. This means that a timer is started which upon expiry sends a StateTimeout message to the FSM. This timer is canceled upon reception of any other message in the meantime; you can rely on the fact that the StateTimeout message will not be processed after an intervening message.

    This modifier can also be used to override any default timeout which is specified for the target state. If you want to cancel the default timeout, use Duration.Inf.

  • using(data)

    This modifier replaces the old state data with the new data given. If you follow the advice above, this is the only place where internal state data are ever modified.

  • replying(msg)

    This modifier sends a reply to the currently processed message and otherwise does not modify the state transition.

All modifiers can be chained to achieve a nice and concise description:

when(SomeState) {
  case Event(msg, _) =>
    goto(Processing) using (newData) forMax (5 seconds) replying (WillDo)
}

The parentheses are not actually needed in all cases, but they visually distinguish between modifiers and their arguments and therefore make the code even more pleasant to read for foreigners.

Note

Please note that the return statement may not be used in when blocks or similar; this is a Scala restriction. Either refactor your code using if () ... else ... or move it into a method definition.

Monitoring Transitions

Transitions occur "between states" conceptually, which means after any actions you have put into the event handling block; this is obvious since the next state is only defined by the value returned by the event handling logic. You do not need to worry about the exact order with respect to setting the internal state variable, as everything within the FSM actor is running single-threaded anyway.

Internal Monitoring

Up to this point, the FSM DSL has been centered on states and events. The dual view is to describe it as a series of transitions. This is enabled by the method

onTransition(handler)

which associates actions with a transition instead of with a state and event. The handler is a partial function which takes a pair of states as input; no resulting state is needed as it is not possible to modify the transition in progress.

onTransition {
  case Idle -> Active => setTimer("timeout", Tick, 1 second, true)
  case Active -> _    => cancelTimer("timeout")
  case x -> Idle      => log.info("entering Idle from " + x)
}

The convenience extractor -> enables decomposition of the pair of states with a clear visual reminder of the transition's direction. As usual in pattern matches, an underscore may be used for irrelevant parts; alternatively you could bind the unconstrained state to a variable, e.g. for logging as shown in the last case.

It is also possible to pass a function object accepting two states to onTransition, in case your transition handling logic is implemented as a method:

onTransition(handler _)

def handler(from: StateType, to: StateType) {
  // handle it here ...
}

The handlers registered with this method are stacked, so you can intersperse onTransition blocks with when blocks as suits your design. It should be noted, however, that all handlers will be invoked for each transition, not only the first matching one. This is designed specifically so you can put all transition handling for a certain aspect into one place without having to worry about earlier declarations shadowing later ones; the actions are still executed in declaration order, though.

Note

This kind of internal monitoring may be used to structure your FSM according to transitions, so that for example the cancellation of a timer upon leaving a certain state cannot be forgot when adding new target states.

External Monitoring

External actors may be registered to be notified of state transitions by sending a message SubscribeTransitionCallBack(actorRef). The named actor will be sent a CurrentState(self, stateName) message immediately and will receive Transition(actorRef, oldState, newState) messages whenever a new state is reached. External monitors may be unregistered by sending UnsubscribeTransitionCallBack(actorRef) to the FSM actor.

Stopping a listener without unregistering will not remove the listener from the subscription list; use UnsubscribeTransitionCallback before stopping the listener.

Transforming State

The partial functions supplied as argument to the when() blocks can be transformed using Scala’s full supplement of functional programming tools. In order to retain type inference, there is a helper function which may be used in case some common handling logic shall be applied to different clauses:

when(SomeState)(transform {
  case Event(bytes: ByteString, read) => stay using (read + bytes.length)
} using {
  case s @ FSM.State(state, read, timeout, stopReason, replies) if read > 1000 =>
    goto(Processing)
})

It goes without saying that the arguments to this method may also be stored, to be used several times, e.g. when applying the same transformation to several when() blocks:

val processingTrigger: PartialFunction[State, State] = {
  case s @ FSM.State(state, read, timeout, stopReason, replies) if read > 1000 =>
    goto(Processing)
}

when(SomeState)(transform {
  case Event(bytes: ByteString, read) => stay using (read + bytes.length)
} using processingTrigger)

Timers

Besides state timeouts, FSM manages timers identified by String names. You may set a timer using

setTimer(name, msg, interval, repeat)

where msg is the message object which will be sent after the duration interval has elapsed. If repeat is true, then the timer is scheduled at fixed rate given by the interval parameter. Any existing timer with the same name will automatically be canceled before adding the new timer.

Timers may be canceled using

cancelTimer(name)

which is guaranteed to work immediately, meaning that the scheduled message will not be processed after this call even if the timer already fired and queued it. The status of any timer may be inquired with

isTimerActive(name)

These named timers complement state timeouts because they are not affected by intervening reception of other messages.

Termination from Inside

The FSM is stopped by specifying the result state as

stop([reason[, data]])

The reason must be one of Normal (which is the default), Shutdown or Failure(reason), and the second argument may be given to change the state data which is available during termination handling.

Note

It should be noted that stop does not abort the actions and stop the FSM immediately. The stop action must be returned from the event handler in the same way as a state transition (but note that the return statement may not be used within a when block).

when(Error) {
  case Event("stop", _) =>
    // do cleanup ...
    stop()
}

You can use onTermination(handler) to specify custom code that is executed when the FSM is stopped. The handler is a partial function which takes a StopEvent(reason, stateName, stateData) as argument:

onTermination {
  case StopEvent(FSM.Normal, state, data)         => // ...
  case StopEvent(FSM.Shutdown, state, data)       => // ...
  case StopEvent(FSM.Failure(cause), state, data) => // ...
}

As for the whenUnhandled case, this handler is not stacked, so each invocation of onTermination replaces the previously installed handler.

Termination from Outside

When an ActorRef associated to a FSM is stopped using the stop method, its postStop hook will be executed. The default implementation by the FSM trait is to execute the onTermination handler if that is prepared to handle a StopEvent(Shutdown, ...).

Warning

In case you override postStop and want to have your onTermination handler called, do not forget to call super.postStop.

Testing and Debugging Finite State Machines

During development and for trouble shooting FSMs need care just as any other actor. There are specialized tools available as described in Testing Finite State Machines and in the following.

Event Tracing

The setting akka.actor.debug.fsm in Configuration enables logging of an event trace by LoggingFSM instances:

import akka.actor.LoggingFSM
class MyFSM extends LoggingFSM[StateType, Data] {
  // body elided ...
}

This FSM will log at DEBUG level:

  • all processed events, including StateTimeout and scheduled timer messages
  • every setting and cancellation of named timers
  • all state transitions

Life cycle changes and special messages can be logged as described for Actors.

Rolling Event Log

The LoggingFSM trait adds one more feature to the FSM: a rolling event log which may be used during debugging (for tracing how the FSM entered a certain failure state) or for other creative uses:

import akka.actor.LoggingFSM
class MyFSM extends LoggingFSM[StateType, Data] {
  override def logDepth = 12
  onTermination {
    case StopEvent(FSM.Failure(_), state, data) =>
      val lastEvents = getLog.mkString("\n\t")
      log.warning("Failure in state " + state + " with data " + data + "\n" +
        "Events leading up to this point:\n\t" + lastEvents)
  }
  // ...
}

The logDepth defaults to zero, which turns off the event log.

Warning

The log buffer is allocated during actor creation, which is why the configuration is done using a virtual method call. If you want to override with a val, make sure that its initialization happens before the initializer of LoggingFSM runs, and do not change the value returned by logDepth after the buffer has been allocated.

The contents of the event log are available using method getLog, which returns an IndexedSeq[LogEntry] where the oldest entry is at index zero.

Examples

A bigger FSM example contrasted with Actor's become/unbecome can be found in the Typesafe Activator template named Akka FSM in Scala

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