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 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
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:
- the supertype of all state names, usually a sealed trait with case objects extending it,
- 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 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, 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
Contents