Classic FSM
Akka Classic pertains to the original Actor APIs, which have been improved by more type safe and guided Actor APIs. Akka Classic is still fully supported and existing applications can continue to use the classic APIs. It is also possible to use the new Actor APIs together with classic actors in the same ActorSystem, see coexistence. For new projects we recommend using the new Actor API.
For the documentation of the new API of this feature and for new projects see fsm.
Dependency
The Akka dependencies are available from Akka’s library repository. To access them there, you need to configure the URL for this repository.
- sbt
resolvers += "Akka library repository".at("https://repo.akka.io/maven")
- Maven
<project> ... <repositories> <repository> <id>akka-repository</id> <name>Akka library repository</name> <url>https://repo.akka.io/maven</url> </repository> </repositories> </project>
- Gradle
repositories { mavenCentral() maven { url "https://repo.akka.io/maven" } }
To use Finite State Machine actors, you must add the following dependency in your project:
- sbt
val AkkaVersion = "2.9.7" libraryDependencies += "com.typesafe.akka" %% "akka-actor" % AkkaVersion
- Maven
<properties> <scala.binary.version>2.13</scala.binary.version> </properties> <dependencyManagement> <dependencies> <dependency> <groupId>com.typesafe.akka</groupId> <artifactId>akka-bom_${scala.binary.version}</artifactId> <version>2.9.7</version> <type>pom</type> <scope>import</scope> </dependency> </dependencies> </dependencyManagement> <dependencies> <dependency> <groupId>com.typesafe.akka</groupId> <artifactId>akka-actor_${scala.binary.version}</artifactId> </dependency> </dependencies>
- Gradle
def versions = [ ScalaBinary: "2.13" ] dependencies { implementation platform("com.typesafe.akka:akka-bom_${versions.ScalaBinary}:2.9.7") implementation "com.typesafe.akka:akka-actor_${versions.ScalaBinary}" }
Overview
The FSM (Finite State Machine) is available as a mixin for the an abstract base class that implements an 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
traitAbstractFSM
class, 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:
- Scala
-
source
import akka.actor.{ ActorRef, FSM } import scala.concurrent.duration._
- Java
-
source
import akka.actor.AbstractFSM; import akka.actor.ActorRef; import akka.japi.pf.UnitMatch; import java.util.Arrays; import java.util.LinkedList; import java.util.List; import java.time.Duration;
The contract of our “Buncher” actor is that it accepts or produces the following messages:
- Scala
-
source
// received events final case class SetTarget(ref: ActorRef) final case class Queue(obj: Any) case object Flush // sent events final case class Batch(obj: immutable.Seq[Any])
- Java
-
source
static final class SetTarget { private final ActorRef ref; public SetTarget(ActorRef ref) { this.ref = ref; } public ActorRef getRef() { return ref; } @Override public String toString() { return "SetTarget{" + "ref=" + ref + '}'; } } static final class Queue { private final Object obj; public Queue(Object obj) { this.obj = obj; } public Object getObj() { return obj; } @Override public String toString() { return "Queue{" + "obj=" + obj + '}'; } } static final class Batch { private final List<Object> list; public Batch(List<Object> list) { this.list = list; } public List<Object> getList() { return list; } @Override public boolean equals(Object o) { if (this == o) return true; if (o == null || getClass() != o.getClass()) return false; Batch batch = (Batch) o; return list.equals(batch.list); } @Override public int hashCode() { return list.hashCode(); } @Override public String toString() { final StringBuilder builder = new StringBuilder(); builder.append("Batch{list="); list.stream() .forEachOrdered( e -> { builder.append(e); builder.append(","); }); int len = builder.length(); builder.replace(len, len, "}"); return builder.toString(); } } static enum Flush { Flush }
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.
- Scala
-
source
// states sealed trait State case object Idle extends State case object Active extends State sealed trait Data case object Uninitialized extends Data final case class Todo(target: ActorRef, queue: immutable.Seq[Any]) extends Data
- Java
-
source
// states enum State { Idle, Active } // state data interface Data {} enum Uninitialized implements Data { Uninitialized } final class Todo implements Data { private final ActorRef target; private final List<Object> queue; public Todo(ActorRef target, List<Object> queue) { this.target = target; this.queue = queue; } public ActorRef getTarget() { return target; } public List<Object> getQueue() { return queue; } @Override public String toString() { return "Todo{" + "target=" + target + ", queue=" + queue + '}'; } public Todo addElement(Object element) { List<Object> nQueue = new LinkedList<>(queue); nQueue.add(element); return new Todo(this.target, nQueue); } public Todo copy(List<Object> queue) { return new Todo(this.target, queue); } public Todo copy(ActorRef target) { return new Todo(target, this.queue); } }
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:
- Scala
-
source
class Buncher extends FSM[State, Data] { startWith(Idle, Uninitialized) when(Idle) { case Event(SetTarget(ref), Uninitialized) => stay().using(Todo(ref, Vector.empty)) } onTransition { case Active -> Idle => stateData match { case Todo(ref, queue) => ref ! Batch(queue) case _ => // nothing to do } } when(Active, stateTimeout = 1 second) { case Event(Flush | StateTimeout, t: Todo) => goto(Idle).using(t.copy(queue = Vector.empty)) } 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() } initialize() }
- Java
-
source
public class Buncher extends AbstractFSM<State, Data> { { startWith(Idle, Uninitialized); when( Idle, matchEvent( SetTarget.class, Uninitialized.class, (setTarget, uninitialized) -> stay().using(new Todo(setTarget.getRef(), new LinkedList<>())))); onTransition( matchState( Active, Idle, () -> { // reuse this matcher final UnitMatch<Data> m = UnitMatch.create( matchData( Todo.class, todo -> todo.getTarget().tell(new Batch(todo.getQueue()), getSelf()))); m.match(stateData()); }) .state( Idle, Active, () -> { /* Do something here */ })); when( Active, Duration.ofSeconds(1L), matchEvent( Arrays.asList(Flush.class, StateTimeout()), Todo.class, (event, todo) -> goTo(Idle).using(todo.copy(new LinkedList<>())))); whenUnhandled( matchEvent( Queue.class, Todo.class, (queue, todo) -> goTo(Active).using(todo.addElement(queue.getObj()))) .anyEvent( (event, state) -> { log() .warning( "received unhandled request {} in state {}/{}", event, stateName(), state); return stay(); })); initialize(); } }
The basic strategy is to declare the actor, mixing in the FSM
traitby inheriting the AbstractFSM
class 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 passedPartialFunction
will be concatenated usingorElse
) - 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
state with Uninitialized
data, 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:
- Scala
-
source
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() }
- Java
-
source
whenUnhandled( matchEvent( Queue.class, Todo.class, (queue, todo) -> goTo(Active).using(todo.addElement(queue.getObj()))) .anyEvent( (event, state) -> { log() .warning( "received unhandled request {} in state {}/{}", event, stateName(), state); return 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).
- Scala
-
source
onTransition { case Active -> Idle => stateData match { case Todo(ref, queue) => ref ! Batch(queue) case _ => // nothing to do } }
- Java
-
source
onTransition( matchState( Active, Idle, () -> { // reuse this matcher final UnitMatch<Data> m = UnitMatch.create( matchData( Todo.class, todo -> todo.getTarget().tell(new Batch(todo.getQueue()), getSelf()))); m.match(stateData()); }) .state( Idle, Active, () -> { /* Do something here */ }));
The transition callback is a partial functionbuilder constructed by matchState
, followed by zero or multiple state
, 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
stateData()
as shown, and the new state data would be available as nextStateData
nextStateData()
.
Same-state transitions can be implemented (when currently in state S
) using goto(S)
or stay()
. The difference between those being that goto(S)
will emit an event S->S
event that can be handled by onTransition
, whereas stay()
will not.
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
TestKit, here using JUnit as an example:
- Scala
-
source
import akka.actor.Props import scala.collection.immutable object FSMDocSpec { // messages and data types } class FSMDocSpec extends MyFavoriteTestFrameWorkPlusAkkaTestKit { import FSMDocSpec._ import akka.actor.{ ActorRef, FSM } import scala.concurrent.duration._ class Buncher extends FSM[State, Data] { startWith(Idle, Uninitialized) when(Idle) { case Event(SetTarget(ref), Uninitialized) => stay().using(Todo(ref, Vector.empty)) } onTransition { case Active -> Idle => stateData match { case Todo(ref, queue) => ref ! Batch(queue) case _ => // nothing to do } } when(Active, stateTimeout = 1 second) { case Event(Flush | StateTimeout, t: Todo) => goto(Idle).using(t.copy(queue = Vector.empty)) } 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() } initialize() } object DemoCode { trait StateType case object SomeState extends StateType case object Processing extends StateType case object Error extends StateType case object Idle extends StateType case object Active extends StateType class Dummy extends FSM[StateType, Int] { class X val newData = 42 object WillDo object Tick when(SomeState) { case Event(msg, _) => goto(Processing).using(newData).forMax(5 seconds).replying(WillDo) } onTransition { case Idle -> Active => startTimerWithFixedDelay("timeout", Tick, 1 second) case Active -> _ => cancelTimer("timeout") case x -> Idle => log.info("entering Idle from " + x) } onTransition(handler _) def handler(from: StateType, to: StateType): Unit = { // handle it here ... } when(Error) { case Event("stop", _) => // do cleanup ... stop() } 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) }) 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)) onTermination { case StopEvent(FSM.Normal, state, data) => // ... case StopEvent(FSM.Shutdown, state, data) => // ... case StopEvent(FSM.Failure(cause), state, data) => // ... } whenUnhandled { case Event(x: X, data) => log.info("Received unhandled event: " + x) stay() case Event(msg, _) => log.warning("Received unknown event: " + msg) goto(Error) } } 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) } // ... } } "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) expectNoMessage() } } }
- Java
-
source
public class BuncherTest extends AbstractJavaTest { static ActorSystem system; @BeforeClass public static void setup() { system = ActorSystem.create("BuncherTest"); } @AfterClass public static void tearDown() { TestKit.shutdownActorSystem(system); system = null; } @Test public void testBuncherActorBatchesCorrectly() { new TestKit(system) { { final ActorRef buncher = system.actorOf(Props.create(Buncher.class)); final ActorRef probe = getRef(); buncher.tell(new SetTarget(probe), probe); buncher.tell(new Queue(42), probe); buncher.tell(new Queue(43), probe); LinkedList<Object> list1 = new LinkedList<>(); list1.add(42); list1.add(43); expectMsgEquals(new Batch(list1)); buncher.tell(new Queue(44), probe); buncher.tell(Flush, probe); buncher.tell(new Queue(45), probe); LinkedList<Object> list2 = new LinkedList<>(); list2.add(44); expectMsgEquals(new Batch(list2)); LinkedList<Object> list3 = new LinkedList<>(); list3.add(45); expectMsgEquals(new Batch(list3)); system.stop(buncher); } }; } @Test public void testBuncherActorDoesntBatchUninitialized() { new TestKit(system) { { final ActorRef buncher = system.actorOf(Props.create(Buncher.class)); final ActorRef probe = getRef(); buncher.tell(new Queue(42), probe); expectNoMessage(); system.stop(buncher); } }; } }
Reference
The FSM Trait and ObjectAbstractFSM Class
The FSM
trait inherits directly from Actor
, when you extend FSM
you must be aware that an actor is actually created: The AbstractFSM
abstract class is the base class used to implement an FSM. It implements Actor since an Actor is created to drive the FSM.
- Scala
-
source
class Buncher extends FSM[State, Data] { startWith(Idle, Uninitialized) when(Idle) { case Event(SetTarget(ref), Uninitialized) => stay().using(Todo(ref, Vector.empty)) } onTransition { case Active -> Idle => stateData match { case Todo(ref, queue) => ref ! Batch(queue) case _ => // nothing to do } } when(Active, stateTimeout = 1 second) { case Event(Flush | StateTimeout, t: Todo) => goto(Idle).using(t.copy(queue = Vector.empty)) } 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() } initialize() }
- Java
-
source
public class Buncher extends AbstractFSM<State, Data> { { startWith(Idle, Uninitialized); when( Idle, matchEvent( SetTarget.class, Uninitialized.class, (setTarget, uninitialized) -> stay().using(new Todo(setTarget.getRef(), new LinkedList<>())))); onTransition( matchState( Active, Idle, () -> { // reuse this matcher final UnitMatch<Data> m = UnitMatch.create( matchData( Todo.class, todo -> todo.getTarget().tell(new Batch(todo.getQueue()), getSelf()))); m.match(stateData()); }) .state( Idle, Active, () -> { /* Do something here */ })); when( Active, Duration.ofSeconds(1L), matchEvent( Arrays.asList(Flush.class, StateTimeout()), Todo.class, (event, todo) -> goTo(Idle).using(todo.copy(new LinkedList<>())))); whenUnhandled( matchEvent( Queue.class, Todo.class, (queue, todo) -> goTo(Active).using(todo.addElement(queue.getObj()))) .anyEvent( (event, state) -> { log() .warning( "received unhandled request {} in state {}/{}", event, stateName(), state); return stay(); })); initialize(); } }
The FSM
traitAbstractFSM
class 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
traitAbstractFSM
class takes two type parameters:
- the supertype of all state names, usually a sealed trait with case objects extending itan enum
- the type of the state data which are tracked by the
FSM
AbstractFSM
module itself.
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
traitAbstractFSM
class. 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 literalstate function builder syntax as demonstrated below:
- Scala
-
source
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)) }
- Java
-
source
when( Idle, matchEvent( SetTarget.class, Uninitialized.class, (setTarget, uninitialized) -> stay().using(new Todo(setTarget.getRef(), new LinkedList<>()))));
The Event(msg: Any, data: D)
case class is parameterized with the data type held by the FSM for convenient pattern matching.
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 traitan enum 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:
- Scala
-
source
when(SomeState)(FSM.NullFunction)
- Java
-
source
when(SomeState, AbstractFSM.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 None
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)
:
- Scala
-
source
whenUnhandled { case Event(x: X, data) => log.info("Received unhandled event: " + x) stay() case Event(msg, _) => log.warning("Received unknown event: " + msg) goto(Error) }
- Java
-
source
whenUnhandled( matchEvent( X.class, (x, data) -> { log().info("Received unhandled event: " + x); return stay(); }) .anyEvent( (event, data) -> { log().warning("Received unknown event: " + event); return 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 aStateTimeout
message to the FSM. This timer is canceled upon reception of any other message in the meantime; you can rely on the fact that theStateTimeout
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, useDuration.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:
- Scala
-
source
when(SomeState) { case Event(msg, _) => goto(Processing).using(newData).forMax(5 seconds).replying(WillDo) }
- Java
-
source
when( SomeState, matchAnyEvent( (msg, data) -> { return goTo(Processing) .using(newData) .forMax(Duration.ofSeconds(5)) .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.
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.
- Scala
-
source
onTransition { case Idle -> Active => startTimerWithFixedDelay("timeout", Tick, 1 second) case Active -> _ => cancelTimer("timeout") case x -> Idle => log.info("entering Idle from " + x) }
- Java
-
source
onTransition( matchState( Idle, Active, () -> startTimerWithFixedDelay("timeout", Tick, Duration.ofSeconds(1L))) .state(Active, null, () -> cancelTimer("timeout")) .state(null, Idle, (f, t) -> log().info("entering Idle from " + f)));
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:
- Scala
-
source
onTransition(handler _) def handler(from: StateType, to: StateType): Unit = { // handle it here ... }
- Java
-
source
public void handler(StateType from, StateType to) { // handle transition here } onTransition(this::handler);
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.
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 state change is triggered.
Please note that a state change includes the action of performing an goto(S)
, while already being state S
. In that case the monitoring actor will be notified with an Transition(ref,S,S)
message. This may be useful if your FSM
should react on all (also same-state) transitions. In case you’d rather not emit events for same-state transitions use stay()
instead of goto(S)
.
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:
sourcewhen(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:
sourceval 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
startSingleTimer(name, msg, interval)
startTimerWithFixedDelay(name, msg, interval)
where msg
is the message object which will be sent after the duration interval
has elapsed.
Any existing timer with the same name will automatically be canceled before adding the new timer.
The Scheduler documentation describes the difference between fixed-delay
and fixed-rate
scheduling. If you are uncertain of which one to use you should pick startTimerWithFixedDelay
.
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.
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).
- Scala
-
source
when(Error) { case Event("stop", _) => // do cleanup ... stop() }
- Java
-
source
when( Error, matchEventEquals( "stop", (event, data) -> { // do cleanup ... return 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:
- Scala
-
source
onTermination { case StopEvent(FSM.Normal, state, data) => // ... case StopEvent(FSM.Shutdown, state, data) => // ... case StopEvent(FSM.Failure(cause), state, data) => // ... }
- Java
-
source
onTermination( matchStop( Normal(), (state, data) -> { /* Do something here */ }) .stop( Shutdown(), (state, data) -> { /* Do something here */ }) .stop( Failure.class, (reason, state, data) -> { /* Do something here */ }));
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
traitAbstractFSM
class is to execute the onTermination
handler if that is prepared to handle a StopEvent(Shutdown, ...)
.
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 TestFSMRef and in the following.
Event Tracing
The setting akka.actor.debug.fsm
in configuration enables logging of an event trace by LoggingFSM
instances:
- Scala
-
source
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) } // ... }
- Java
-
source
static class MyFSM extends AbstractLoggingFSM<StateType, Data> { @Override public int logDepth() { return 12; } { onTermination( matchStop( Failure.class, (reason, state, data) -> { String lastEvents = getLog().mkString("\n\t"); log() .warning( "Failure in state " + state + " with data " + data + "\n" + "Events leading up to this point:\n\t" + lastEvents); })); // ... } }
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
traitAbstractLoggingFSM
class 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:
- Scala
-
source
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) } // ... }
- Java
-
source
static class MyFSM extends AbstractLoggingFSM<StateType, Data> { @Override public int logDepth() { return 12; } { onTermination( matchStop( Failure.class, (reason, state, data) -> { String 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.
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.