永続化
Akka persistence enables stateful actors to persist their internal state so that it can be recovered when an actor is started, restarted after a JVM crash or by a supervisor, or migrated in a cluster. The key concept behind Akka persistence is that only changes to an actor's internal state are persisted but never its current state directly (except for optional snapshots). These changes are only ever appended to storage, nothing is ever mutated, which allows for very high transaction rates and efficient replication. Stateful actors are recovered by replaying stored changes to these actors from which they can rebuild internal state. This can be either the full history of changes or starting from a snapshot which can dramatically reduce recovery times. Akka persistence also provides point-to-point communication with at-least-once message delivery semantics.
Akka persistence is inspired by and the official replacement of the eventsourced library. It follows the same concepts and architecture of eventsourced but significantly differs on API and implementation level. See also Migration Guide Eventsourced to Akka Persistence 2.3.x
Dependencies
Akka persistence is a separate jar file. Make sure that you have the following dependency in your project:
"com.typesafe.akka" %% "akka-persistence" % "@version@" @crossString@
The Akka persistence extension comes with few built-in persistence plugins, including in-memory heap based journal, local file-system based snapshot-store and LevelDB based journal.
LevelDB based plugins will require the following additional dependency declaration:
"org.iq80.leveldb" % "leveldb" % "0.7"
"org.fusesource.leveldbjni" % "leveldbjni-all" % "1.8"
Architecture
- PersistentActor: Is a persistent, stateful actor. It is able to persist events to a journal and can react to them in a thread-safe manner. It can be used to implement both command as well as event sourced actors. When a persistent actor is started or restarted, journaled messages are replayed to that actor so that it can recover internal state from these messages.
- PersistentView: A view is a persistent, stateful actor that receives journaled messages that have been written by another persistent actor. A view itself does not journal new messages, instead, it updates internal state only from a persistent actor's replicated message stream.
- AtLeastOnceDelivery: To send messages with at-least-once delivery semantics to destinations, also in case of sender and receiver JVM crashes.
- AsyncWriteJournal: A journal stores the sequence of messages sent to a persistent actor. An application can control which messages are journaled and which are received by the persistent actor without being journaled. Journal maintains highestSequenceNr that is increased on each message. The storage backend of a journal is pluggable. The persistence extension comes with a "leveldb" journal plugin, which writes to the local filesystem. Replicated journals are available as Community plugins.
- Snapshot store: A snapshot store persists snapshots of a persistent actor's or a view's internal state. Snapshots are used for optimizing recovery times. The storage backend of a snapshot store is pluggable. The persistence extension comes with a "local" snapshot storage plugin, which writes to the local filesystem. Replicated snapshot stores are available as Community plugins.
Event sourcing
The basic idea behind Event Sourcing is quite simple. A persistent actor receives a (non-persistent) command which is first validated if it can be applied to the current state. Here validation can mean anything, from simple inspection of a command message's fields up to a conversation with several external services, for example. If validation succeeds, events are generated from the command, representing the effect of the command. These events are then persisted and, after successful persistence, used to change the actor's state. When the persistent actor needs to be recovered, only the persisted events are replayed of which we know that they can be successfully applied. In other words, events cannot fail when being replayed to a persistent actor, in contrast to commands. Event sourced actors may of course also process commands that do not change application state such as query commands for example.
Akka persistence supports event sourcing with the PersistentActor
trait. An actor that extends this trait uses the
persist
method to persist and handle events. The behavior of a PersistentActor
is defined by implementing receiveRecover
and receiveCommand
. This is demonstrated in the following example.
The example defines two data types, Cmd
and Evt
to represent commands and events, respectively. The
state
of the ExamplePersistentActor
is a list of persisted event data contained in ExampleState
.
The persistent actor's receiveRecover
method defines how state
is updated during recovery by handling Evt
and SnapshotOffer
messages. The persistent actor's receiveCommand
method is a command handler. In this example,
a command is handled by generating two events which are then persisted and handled. Events are persisted by calling
persist
with an event (or a sequence of events) as first argument and an event handler as second argument.
The persist
method persists events asynchronously and the event handler is executed for successfully persisted
events. Successfully persisted events are internally sent back to the persistent actor as individual messages that trigger
event handler executions. An event handler may close over persistent actor state and mutate it. The sender of a persisted
event is the sender of the corresponding command. This allows event handlers to reply to the sender of a command
(not shown).
The main responsibility of an event handler is changing persistent actor state using event data and notifying others about successful state changes by publishing events.
When persisting events with persist
it is guaranteed that the persistent actor will not receive further commands between
the persist
call and the execution(s) of the associated event handler. This also holds for multiple persist
calls in context of a single command. Incoming messages are stashed until the persist
is completed.
If persistence of an event fails, onPersistFailure
will be invoked (logging the error by default),
and the actor will unconditionally be stopped. If persistence of an event is rejected before it is
stored, e.g. due to serialization error, onPersistRejected
will be invoked (logging a warning
by default) and the actor continues with the next message.
The easiest way to run this example yourself is to download Lightbend Activator
and open the tutorial named Akka Persistence Samples with Scala.
It contains instructions on how to run the PersistentActorExample
.
注釈
It's also possible to switch between different command handlers during normal processing and recovery
with context.become()
and context.unbecome()
. To get the actor into the same state after
recovery you need to take special care to perform the same state transitions with become
and
unbecome
in the receiveRecover
method as you would have done in the command handler.
Note that when using become
from receiveRecover
it will still only use the receiveRecover
behavior when replaying the events. When replay is completed it will use the new behavior.
Identifiers
A persistent actor must have an identifier that doesn't change across different actor incarnations.
The identifier must be defined with the persistenceId
method.
override def persistenceId = "my-stable-persistence-id"
注釈
persistenceId
must be unique to a given entity in the journal (database table/keyspace).
When replaying messages persisted to the journal, you query messages with a persistenceId
.
So, if two different entities share the same persistenceId
, message-replaying
behavior is corrupted.
Recovery
By default, a persistent actor is automatically recovered on start and on restart by replaying journaled messages. New messages sent to a persistent actor during recovery do not interfere with replayed messages. They are cached and received by a persistent actor after recovery phase completes.
注釈
Accessing the sender()
for replayed messages will always result in a deadLetters
reference,
as the original sender is presumed to be long gone. If you indeed have to notify an actor during
recovery in the future, store its ActorPath
explicitly in your persisted events.
Recovery customization
Applications may also customise how recovery is performed by returning a customised Recovery
object
in the recovery
method of a PersistentActor
, for example setting an upper bound to the replay
which allows the actor to be replayed to a certain point "in the past" instead to its most up to date state:
override def recovery = Recovery(toSequenceNr = 457L)
Recovery can be disabled by returning Recovery.none()
in the recovery
method of a PersistentActor
:
override def recovery = Recovery.none
Recovery status
A persistent actor can query its own recovery status via the methods
def recoveryRunning: Boolean
def recoveryFinished: Boolean
Sometimes there is a need for performing additional initialization when the
recovery has completed before processing any other message sent to the persistent actor.
The persistent actor will receive a special RecoveryCompleted
message right after recovery
and before any other received messages.
override def receiveRecover: Receive = {
case RecoveryCompleted =>
// perform init after recovery, before any other messages
//...
case evt => //...
}
override def receiveCommand: Receive = {
case msg => //...
}
If there is a problem with recovering the state of the actor from the journal, onRecoveryFailure
is called (logging the error by default) and the actor will be stopped.
Internal stash
The persistent actor has a private stash for internally caching incoming messages during
recovery or the persist\persistAll
method persisting events. You can still use/inherit from the
Stash
interface. The internal stash cooperates with the normal stash by hooking into unstashAll
method and
making sure messages are unstashed properly to the internal stash to maintain ordering guarantees.
You should be careful to not send more messages to a persistent actor than it can keep up with, otherwise the number
of stashed messages will grow without bounds. It can be wise to protect against OutOfMemoryError
by defining a
maximum stash capacity in the mailbox configuration:
akka.actor.default-mailbox.stash-capacity=10000
Note that the stash capacity is per actor. If you have many persistent actors, e.g. when using cluster sharding,
you may need to define a small stash capacity to ensure that the total number of stashed messages in the system
don't consume too much memory. Additionally, The persistent actor defines three strategies to handle failure when the
internal stash capacity is exceeded. The default overflow strategy is the ThrowOverflowExceptionStrategy
, which
discards the current received message and throws a StashOverflowException
, causing actor restart if default
supervision strategy is used. you can override the internalStashOverflowStrategy
method to return
DiscardToDeadLetterStrategy
or ReplyToStrategy
for any "individual" persistent actor, or define the "default"
for all persistent actors by providing FQCN, which must be a subclass of StashOverflowStrategyConfigurator
, in the
persistence configuration:
akka.persistence.internal-stash-overflow-strategy=
"akka.persistence.ThrowExceptionConfigurator"
The DiscardToDeadLetterStrategy
strategy also has a pre-packaged companion configurator
akka.persistence.DiscardConfigurator
.
You can also query default strategy via the Akka persistence extension singleton:
Persistence(context.system).defaultInternalStashOverflowStrategy
注釈
The bounded mailbox should be avoided in the persistent actor, by which the messages come from storage backends may be discarded. You can use bounded stash instead of it.
Relaxed local consistency requirements and high throughput use-cases
If faced with relaxed local consistency requirements and high throughput demands sometimes PersistentActor
and its
persist
may not be enough in terms of consuming incoming Commands at a high rate, because it has to wait until all
Events related to a given Command are processed in order to start processing the next Command. While this abstraction is
very useful for most cases, sometimes you may be faced with relaxed requirements about consistency – for example you may
want to process commands as fast as you can, assuming that the Event will eventually be persisted and handled properly in
the background, retroactively reacting to persistence failures if needed.
The persistAsync
method provides a tool for implementing high-throughput persistent actors. It will not
stash incoming Commands while the Journal is still working on persisting and/or user code is executing event callbacks.
In the below example, the event callbacks may be called "at any time", even after the next Command has been processed. The ordering between events is still guaranteed ("evt-b-1" will be sent after "evt-a-2", which will be sent after "evt-a-1" etc.).
class MyPersistentActor extends PersistentActor {
override def persistenceId = "my-stable-persistence-id"
override def receiveRecover: Receive = {
case _ => // handle recovery here
}
override def receiveCommand: Receive = {
case c: String => {
sender() ! c
persistAsync(s"evt-$c-1") { e => sender() ! e }
persistAsync(s"evt-$c-2") { e => sender() ! e }
}
}
}
// usage
persistentActor ! "a"
persistentActor ! "b"
// possible order of received messages:
// a
// b
// evt-a-1
// evt-a-2
// evt-b-1
// evt-b-2
注釈
In order to implement the pattern known as "command sourcing" simply call persistAsync(cmd)(...)
right away on all incoming
messages and handle them in the callback.
警告
The callback will not be invoked if the actor is restarted (or stopped) in between the call to
persistAsync
and the journal has confirmed the write.
Deferring actions until preceding persist handlers have executed
Sometimes when working with persistAsync
you may find that it would be nice to define some actions in terms of
''happens-after the previous persistAsync
handlers have been invoked''. PersistentActor
provides an utility method
called deferAsync
, which works similarly to persistAsync
yet does not persist the passed in event. It is recommended to
use it for read operations, and actions which do not have corresponding events in your domain model.
Using this method is very similar to the persist family of methods, yet it does not persist the passed in event. It will be kept in memory and used when invoking the handler.
class MyPersistentActor extends PersistentActor {
override def persistenceId = "my-stable-persistence-id"
override def receiveRecover: Receive = {
case _ => // handle recovery here
}
override def receiveCommand: Receive = {
case c: String => {
sender() ! c
persistAsync(s"evt-$c-1") { e => sender() ! e }
persistAsync(s"evt-$c-2") { e => sender() ! e }
deferAsync(s"evt-$c-3") { e => sender() ! e }
}
}
}
Notice that the sender()
is safe to access in the handler callback, and will be pointing to the original sender
of the command for which this deferAsync
handler was called.
The calling side will get the responses in this (guaranteed) order:
persistentActor ! "a"
persistentActor ! "b"
// order of received messages:
// a
// b
// evt-a-1
// evt-a-2
// evt-a-3
// evt-b-1
// evt-b-2
// evt-b-3
警告
The callback will not be invoked if the actor is restarted (or stopped) in between the call to
deferAsync
and the journal has processed and confirmed all preceding writes.
Nested persist calls
It is possible to call persist
and persistAsync
inside their respective callback blocks and they will properly
retain both the thread safety (including the right value of sender()
) as well as stashing guarantees.
In general it is encouraged to create command handlers which do not need to resort to nested event persisting,
however there are situations where it may be useful. It is important to understand the ordering of callback execution in
those situations, as well as their implication on the stashing behaviour (that persist()
enforces). In the following
example two persist calls are issued, and each of them issues another persist inside its callback:
override def receiveCommand: Receive = {
case c: String =>
sender() ! c
persist(s"$c-1-outer") { outer1 =>
sender() ! outer1
persist(s"$c-1-inner") { inner1 =>
sender() ! inner1
}
}
persist(s"$c-2-outer") { outer2 =>
sender() ! outer2
persist(s"$c-2-inner") { inner2 =>
sender() ! inner2
}
}
}
When sending two commands to this PersistentActor
, the persist handlers will be executed in the following order:
persistentActor ! "a"
persistentActor ! "b"
// order of received messages:
// a
// a-outer-1
// a-outer-2
// a-inner-1
// a-inner-2
// and only then process "b"
// b
// b-outer-1
// b-outer-2
// b-inner-1
// b-inner-2
First the "outer layer" of persist calls is issued and their callbacks are applied. After these have successfully completed,
the inner callbacks will be invoked (once the events they are persisting have been confirmed to be persisted by the journal).
Only after all these handlers have been successfully invoked will the next command be delivered to the persistent Actor.
In other words, the stashing of incoming commands that is guaranteed by initially calling persist()
on the outer layer
is extended until all nested persist
callbacks have been handled.
It is also possible to nest persistAsync
calls, using the same pattern:
override def receiveCommand: Receive = {
case c: String =>
sender() ! c
persistAsync(c + "-outer-1") { outer =>
sender() ! outer
persistAsync(c + "-inner-1") { inner => sender() ! inner }
}
persistAsync(c + "-outer-2") { outer =>
sender() ! outer
persistAsync(c + "-inner-2") { inner => sender() ! inner }
}
}
In this case no stashing is happening, yet events are still persisted and callbacks are executed in the expected order:
persistentActor ! "a"
persistentActor ! "b"
// order of received messages:
// a
// b
// a-outer-1
// a-outer-2
// b-outer-1
// b-outer-2
// a-inner-1
// a-inner-2
// b-inner-1
// b-inner-2
// which can be seen as the following causal relationship:
// a -> a-outer-1 -> a-outer-2 -> a-inner-1 -> a-inner-2
// b -> b-outer-1 -> b-outer-2 -> b-inner-1 -> b-inner-2
While it is possible to nest mixed persist
and persistAsync
with keeping their respective semantics
it is not a recommended practice, as it may lead to overly complex nesting.
Failures
If persistence of an event fails, onPersistFailure
will be invoked (logging the error by default),
and the actor will unconditionally be stopped.
The reason that it cannot resume when persist fails is that it is unknown if the event was actually
persisted or not, and therefore it is in an inconsistent state. Restarting on persistent failures
will most likely fail anyway since the journal is probably unavailable. It is better to stop the
actor and after a back-off timeout start it again. The akka.pattern.BackoffSupervisor
actor
is provided to support such restarts.
val childProps = Props[MyPersistentActor]
val props = BackoffSupervisor.props(
Backoff.onStop(
childProps,
childName = "myActor",
minBackoff = 3.seconds,
maxBackoff = 30.seconds,
randomFactor = 0.2))
context.actorOf(props, name = "mySupervisor")
If persistence of an event is rejected before it is stored, e.g. due to serialization error,
onPersistRejected
will be invoked (logging a warning by default), and the actor continues with
next message.
If there is a problem with recovering the state of the actor from the journal when the actor is
started, onRecoveryFailure
is called (logging the error by default), and the actor will be stopped.
Atomic writes
Each event is of course stored atomically, but it is also possible to store several events atomically by
using the persistAll
or persistAllAsync
method. That means that all events passed to that method
are stored or none of them are stored if there is an error.
The recovery of a persistent actor will therefore never be done partially with only a subset of events persisted by persistAll.
Some journals may not support atomic writes of several events and they will then reject the persistAll
command, i.e. onPersistRejected
is called with an exception (typically UnsupportedOperationException
).
Batch writes
In order to optimize throughput when using persistAsync
, a persistent actor
internally batches events to be stored under high load before writing them to
the journal (as a single batch). The batch size is dynamically determined by
how many events are emitted during the time of a journal round-trip: after
sending a batch to the journal no further batch can be sent before confirmation
has been received that the previous batch has been written. Batch writes are never
timer-based which keeps latencies at a minimum.
Message deletion
It is possible to delete all messages (journaled by a single persistent actor) up to a specified sequence number;
Persistent actors may call the deleteMessages
method to this end.
Deleting messages in event sourcing based applications is typically either not used at all, or used in conjunction with
snapshotting, i.e. after a snapshot has been successfully stored, a deleteMessages(toSequenceNr)
up until the sequence number of the data held by that snapshot can be issued to safely delete the previous events
while still having access to the accumulated state during replays - by loading the snapshot.
The result of the deleteMessages
request is signaled to the persistent actor with a DeleteMessagesSuccess
message if the delete was successful or a DeleteMessagesFailure
message if it failed.
Message deletion doesn't affect the highest sequence number of the journal, even if all messages were deleted from it after deleteMessages
invocation.
Persistence status handling
Persisting, deleting, and replaying messages can either succeed or fail.
Method | Success | Failure / Rejection | After failure handler invoked |
persist / persistAsync |
persist handler invoked | onPersistFailure |
Actor is stopped. |
onPersistRejected |
No automatic actions. | ||
recovery |
RecoveryCompleted |
onRecoveryFailure |
Actor is stopped. |
deleteMessages |
DeleteMessagesSuccess |
DeleteMessagesFailure |
No automatic actions. |
The most important operations (persist
and recovery
) have failure handlers modelled as explicit callbacks which
the user can override in the PersistentActor
. The default implementations of these handlers emit a log message
(error
for persist/recovery failures, and warning
for others), logging the failure cause and information about
which message caused the failure.
For critical failures, such as recovery or persisting events failing, the persistent actor will be stopped after the failure
handler is invoked. This is because if the underlying journal implementation is signalling persistence failures it is most
likely either failing completely or overloaded and restarting right-away and trying to persist the event again will most
likely not help the journal recover – as it would likely cause a Thundering herd problem, as many persistent actors
would restart and try to persist their events again. Instead, using a BackoffSupervisor
(as described in Failures) which
implements an exponential-backoff strategy which allows for more breathing room for the journal to recover between
restarts of the persistent actor.
注釈
Journal implementations may choose to implement a retry mechanism, e.g. such that only after a write fails N number of times a persistence failure is signalled back to the user. In other words, once a journal returns a failure, it is considered fatal by Akka Persistence, and the persistent actor which caused the failure will be stopped.
Check the documentation of the journal implementation you are using for details if/how it is using this technique.
Safely shutting down persistent actors
Special care should be given when shutting down persistent actors from the outside. With normal Actors it is often acceptable to use the special PoisonPill message to signal to an Actor that it should stop itself once it receives this message – in fact this message is handled automatically by Akka, leaving the target actor no way to refuse stopping itself when given a poison pill.
This can be dangerous when used with PersistentActor
due to the fact that incoming commands are stashed while
the persistent actor is awaiting confirmation from the Journal that events have been written when persist()
was used.
Since the incoming commands will be drained from the Actor's mailbox and put into its internal stash while awaiting the
confirmation (thus, before calling the persist handlers) the Actor may receive and (auto)handle the PoisonPill
before it processes the other messages which have been put into its stash, causing a pre-mature shutdown of the Actor.
警告
Consider using explicit shut-down messages instead of PoisonPill
when working with persistent actors.
The example below highlights how messages arrive in the Actor's mailbox and how they interact with its internal stashing
mechanism when persist()
is used. Notice the early stop behaviour that occurs when PoisonPill
is used:
/** Explicit shutdown message */
case object Shutdown
class SafePersistentActor extends PersistentActor {
override def persistenceId = "safe-actor"
override def receiveCommand: Receive = {
case c: String =>
println(c)
persist(s"handle-$c") { println(_) }
case Shutdown =>
context.stop(self)
}
override def receiveRecover: Receive = {
case _ => // handle recovery here
}
}
// UN-SAFE, due to PersistentActor's command stashing:
persistentActor ! "a"
persistentActor ! "b"
persistentActor ! PoisonPill
// order of received messages:
// a
// # b arrives at mailbox, stashing; internal-stash = [b]
// PoisonPill is an AutoReceivedMessage, is handled automatically
// !! stop !!
// Actor is stopped without handling `b` nor the `a` handler!
// SAFE:
persistentActor ! "a"
persistentActor ! "b"
persistentActor ! Shutdown
// order of received messages:
// a
// # b arrives at mailbox, stashing; internal-stash = [b]
// # Shutdown arrives at mailbox, stashing; internal-stash = [b, Shutdown]
// handle-a
// # unstashing; internal-stash = [Shutdown]
// b
// handle-b
// # unstashing; internal-stash = []
// Shutdown
// -- stop --
Replay Filter
There could be cases where event streams are corrupted and multiple writers (i.e. multiple persistent actor instances) journaled different messages with the same sequence number. In such a case, you can configure how you filter replayed messages from multiple writers, upon recovery.
In your configuration, under the akka.persistence.journal.xxx.replay-filter
section (where xxx
is your journal plugin id),
you can select the replay filter mode
from one of the following values:
- repair-by-discard-old
- fail
- warn
- off
For example, if you configure the replay filter for leveldb plugin, it looks like this:
# The replay filter can detect a corrupt event stream by inspecting
# sequence numbers and writerUuid when replaying events.
akka.persistence.journal.leveldb.replay-filter {
# What the filter should do when detecting invalid events.
# Supported values:
# `repair-by-discard-old` : discard events from old writers,
# warning is logged
# `fail` : fail the replay, error is logged
# `warn` : log warning but emit events untouched
# `off` : disable this feature completely
mode = repair-by-discard-old
}
Persistent Views
警告
PersistentView
is deprecated. Use Persistence Query instead. The corresponding
query type is EventsByPersistenceId
. There are several alternatives for connecting the Source
to an actor corresponding to a previous PersistentView
actor:
- Sink.actorRef is simple, but has the disadvantage that there is no back-pressure signal from the destination actor, i.e. if the actor is not consuming the messages fast enough the mailbox of the actor will grow
- mapAsync combined with Ask: Send-And-Receive-Future is almost as simple with the advantage of back-pressure being propagated all the way
- ActorSubscriber in case you need more fine grained control
The consuming actor may be a plain Actor
or a PersistentActor
if it needs to store its
own state (e.g. fromSequenceNr offset).
Persistent views can be implemented by extending the PersistentView
trait and implementing the receive
and the persistenceId
methods.
class MyView extends PersistentView {
override def persistenceId: String = "some-persistence-id"
override def viewId: String = "some-persistence-id-view"
def receive: Receive = {
case payload if isPersistent =>
// handle message from journal...
case payload =>
// handle message from user-land...
}
}
The persistenceId
identifies the persistent actor from which the view receives journaled messages. It is not necessary that
the referenced persistent actor is actually running. Views read messages from a persistent actor's journal directly. When a
persistent actor is started later and begins to write new messages, by default the corresponding view is updated automatically.
It is possible to determine if a message was sent from the Journal or from another actor in user-land by calling the isPersistent
method. Having that said, very often you don't need this information at all and can simply apply the same logic to both cases
(skip the if isPersistent
check).
Updates
The default update interval of all views of an actor system is configurable:
akka.persistence.view.auto-update-interval = 5s
PersistentView
implementation classes may also override the autoUpdateInterval
method to return a custom update
interval for a specific view class or view instance. Applications may also trigger additional updates at
any time by sending a view an Update
message.
val view = system.actorOf(Props[MyView])
view ! Update(await = true)
If the await
parameter is set to true
, messages that follow the Update
request are processed when the
incremental message replay, triggered by that update request, completed. If set to false
(default), messages
following the update request may interleave with the replayed message stream. Automated updates always run with
await = false
.
Automated updates of all persistent views of an actor system can be turned off by configuration:
akka.persistence.view.auto-update = off
Implementation classes may override the configured default value by overriding the autoUpdate
method. To
limit the number of replayed messages per update request, applications can configure a custom
akka.persistence.view.auto-update-replay-max
value or override the autoUpdateReplayMax
method. The number
of replayed messages for manual updates can be limited with the replayMax
parameter of the Update
message.
Recovery
Initial recovery of persistent views works the very same way as for persistent actors (i.e. by sending a Recover
message
to self). The maximum number of replayed messages during initial recovery is determined by autoUpdateReplayMax
.
Further possibilities to customize initial recovery are explained in section Recovery.
Identifiers
A persistent view must have an identifier that doesn't change across different actor incarnations.
The identifier must be defined with the viewId
method.
The viewId
must differ from the referenced persistenceId
, unless Snapshots of a view and its
persistent actor should be shared (which is what applications usually do not want).
Snapshots
Snapshots can dramatically reduce recovery times of persistent actors and views. The following discusses snapshots in context of persistent actors but this is also applicable to persistent views.
Persistent actors can save snapshots of internal state by calling the saveSnapshot
method. If saving of a snapshot
succeeds, the persistent actor receives a SaveSnapshotSuccess
message, otherwise a SaveSnapshotFailure
message
var state: Any = _
override def receiveCommand: Receive = {
case "snap" => saveSnapshot(state)
case SaveSnapshotSuccess(metadata) => // ...
case SaveSnapshotFailure(metadata, reason) => // ...
}
where metadata
is of type SnapshotMetadata
:
During recovery, the persistent actor is offered a previously saved snapshot via a SnapshotOffer
message from
which it can initialize internal state.
var state: Any = _
override def receiveRecover: Receive = {
case SnapshotOffer(metadata, offeredSnapshot) => state = offeredSnapshot
case RecoveryCompleted =>
case event => // ...
}
The replayed messages that follow the SnapshotOffer
message, if any, are younger than the offered snapshot.
They finally recover the persistent actor to its current (i.e. latest) state.
In general, a persistent actor is only offered a snapshot if that persistent actor has previously saved one or more snapshots
and at least one of these snapshots matches the SnapshotSelectionCriteria
that can be specified for recovery.
override def recovery = Recovery(fromSnapshot = SnapshotSelectionCriteria(
maxSequenceNr = 457L,
maxTimestamp = System.currentTimeMillis))
If not specified, they default to SnapshotSelectionCriteria.Latest
which selects the latest (= youngest) snapshot.
To disable snapshot-based recovery, applications should use SnapshotSelectionCriteria.None
. A recovery where no
saved snapshot matches the specified SnapshotSelectionCriteria
will replay all journaled messages.
注釈
In order to use snapshots, a default snapshot-store (akka.persistence.snapshot-store.plugin
) must be configured,
or the PersistentActor
can pick a snapshot store explicitly by overriding def snapshotPluginId: String
.
Since it is acceptable for some applications to not use any snapshotting, it is legal to not configure a snapshot store.
However, Akka will log a warning message when this situation is detected and then continue to operate until
an actor tries to store a snapshot, at which point the operation will fail (by replying with an SaveSnapshotFailure
for example).
Note that クラスターシャーディング is using snapshots, so if you use Cluster Sharding you need to define a snapshot store plugin.
Snapshot deletion
A persistent actor can delete individual snapshots by calling the deleteSnapshot
method with the sequence number of
when the snapshot was taken.
To bulk-delete a range of snapshots matching SnapshotSelectionCriteria
,
persistent actors should use the deleteSnapshots
method.
Snapshot status handling
Saving or deleting snapshots can either succeed or fail – this information is reported back to the persistent actor via status messages as illustrated in the following table.
Method | Success | Failure message |
---|---|---|
saveSnapshot(Any) |
SaveSnapshotSuccess |
SaveSnapshotFailure |
deleteSnapshot(Long) |
DeleteSnapshotSuccess |
DeleteSnapshotFailure |
deleteSnapshots(SnapshotSelectionCriteria) |
DeleteSnapshotsSuccess |
DeleteSnapshotsFailure |
If failure messages are left unhandled by the actor, a default warning log message will be logged for each incoming failure message. No default action is performed on the success messages, however you're free to handle them e.g. in order to delete an in memory representation of the snapshot, or in the case of failure to attempt save the snapshot again.
At-Least-Once Delivery
To send messages with at-least-once delivery semantics to destinations you can mix-in AtLeastOnceDelivery
trait to your PersistentActor
on the sending side. It takes care of re-sending messages when they
have not been confirmed within a configurable timeout.
The state of the sending actor, including which messages have been sent that have not been
confirmed by the recipient must be persistent so that it can survive a crash of the sending actor
or JVM. The AtLeastOnceDelivery
trait does not persist anything by itself. It is your
responsibility to persist the intent that a message is sent and that a confirmation has been
received.
注釈
At-least-once delivery implies that original message sending order is not always preserved,
and the destination may receive duplicate messages.
Semantics do not match those of a normal ActorRef
send operation:
- it is not at-most-once delivery
- message order for the same sender–receiver pair is not preserved due to possible resends
- after a crash and restart of the destination messages are still delivered to the new actor incarnation
These semantics are similar to what an ActorPath
represents (see
アクターのライフサクル), therefore you need to supply a path and not a
reference when delivering messages. The messages are sent to the path with
an actor selection.
Use the deliver
method to send a message to a destination. Call the confirmDelivery
method
when the destination has replied with a confirmation message.
Relationship between deliver and confirmDelivery
To send messages to the destination path, use the deliver
method after you have persisted the intent
to send the message.
The destination actor must send back a confirmation message. When the sending actor receives this
confirmation message you should persist the fact that the message was delivered successfully and then call
the confirmDelivery
method.
If the persistent actor is not currently recovering, the deliver
method will send the message to
the destination actor. When recovering, messages will be buffered until they have been confirmed using confirmDelivery
.
Once recovery has completed, if there are outstanding messages that have not been confirmed (during the message replay),
the persistent actor will resend these before sending any other messages.
Deliver requires a deliveryIdToMessage
function to pass the provided deliveryId
into the message so that the correlation
between deliver
and confirmDelivery
is possible. The deliveryId
must do the round trip. Upon receipt
of the message, the destination actor will send the same``deliveryId`` wrapped in a confirmation message back to the sender.
The sender will then use it to call confirmDelivery
method to complete the delivery routine.
import akka.actor.{ Actor, ActorSelection }
import akka.persistence.AtLeastOnceDelivery
case class Msg(deliveryId: Long, s: String)
case class Confirm(deliveryId: Long)
sealed trait Evt
case class MsgSent(s: String) extends Evt
case class MsgConfirmed(deliveryId: Long) extends Evt
class MyPersistentActor(destination: ActorSelection)
extends PersistentActor with AtLeastOnceDelivery {
override def persistenceId: String = "persistence-id"
override def receiveCommand: Receive = {
case s: String => persist(MsgSent(s))(updateState)
case Confirm(deliveryId) => persist(MsgConfirmed(deliveryId))(updateState)
}
override def receiveRecover: Receive = {
case evt: Evt => updateState(evt)
}
def updateState(evt: Evt): Unit = evt match {
case MsgSent(s) =>
deliver(destination)(deliveryId => Msg(deliveryId, s))
case MsgConfirmed(deliveryId) => confirmDelivery(deliveryId)
}
}
class MyDestination extends Actor {
def receive = {
case Msg(deliveryId, s) =>
// ...
sender() ! Confirm(deliveryId)
}
}
The deliveryId
generated by the persistence module is a strictly monotonically increasing sequence number
without gaps. The same sequence is used for all destinations of the actor, i.e. when sending to multiple
destinations the destinations will see gaps in the sequence. It is not possible to use custom deliveryId
.
However, you can send a custom correlation identifier in the message to the destination. You must then retain
a mapping between the internal deliveryId
(passed into the deliveryIdToMessage
function) and your custom
correlation id (passed into the message). You can do this by storing such mapping in a Map(correlationId -> deliveryId)
from which you can retrieve the deliveryId
to be passed into the confirmDelivery
method once the receiver
of your message has replied with your custom correlation id.
The AtLeastOnceDelivery
trait has a state consisting of unconfirmed messages and a
sequence number. It does not store this state itself. You must persist events corresponding to the
deliver
and confirmDelivery
invocations from your PersistentActor
so that the state can
be restored by calling the same methods during the recovery phase of the PersistentActor
. Sometimes
these events can be derived from other business level events, and sometimes you must create separate events.
During recovery, calls to deliver
will not send out messages, those will be sent later
if no matching confirmDelivery
will have been performed.
Support for snapshots is provided by getDeliverySnapshot
and setDeliverySnapshot
.
The AtLeastOnceDeliverySnapshot
contains the full delivery state, including unconfirmed messages.
If you need a custom snapshot for other parts of the actor state you must also include the
AtLeastOnceDeliverySnapshot
. It is serialized using protobuf with the ordinary Akka
serialization mechanism. It is easiest to include the bytes of the AtLeastOnceDeliverySnapshot
as a blob in your custom snapshot.
The interval between redelivery attempts is defined by the redeliverInterval
method.
The default value can be configured with the akka.persistence.at-least-once-delivery.redeliver-interval
configuration key. The method can be overridden by implementation classes to return non-default values.
The maximum number of messages that will be sent at each redelivery burst is defined by the
redeliveryBurstLimit
method (burst frequency is half of the redelivery interval). If there's a lot of
unconfirmed messages (e.g. if the destination is not available for a long time), this helps to prevent an overwhelming
amount of messages to be sent at once. The default value can be configured with the
akka.persistence.at-least-once-delivery.redelivery-burst-limit
configuration key. The method can be overridden
by implementation classes to return non-default values.
After a number of delivery attempts a AtLeastOnceDelivery.UnconfirmedWarning
message
will be sent to self
. The re-sending will still continue, but you can choose to call
confirmDelivery
to cancel the re-sending. The number of delivery attempts before emitting the
warning is defined by the warnAfterNumberOfUnconfirmedAttempts
method. The default value can be
configured with the akka.persistence.at-least-once-delivery.warn-after-number-of-unconfirmed-attempts
configuration key. The method can be overridden by implementation classes to return non-default values.
The AtLeastOnceDelivery
trait holds messages in memory until their successful delivery has been confirmed.
The maximum number of unconfirmed messages that the actor is allowed to hold in memory
is defined by the maxUnconfirmedMessages
method. If this limit is exceed the deliver
method will
not accept more messages and it will throw AtLeastOnceDelivery.MaxUnconfirmedMessagesExceededException
.
The default value can be configured with the akka.persistence.at-least-once-delivery.max-unconfirmed-messages
configuration key. The method can be overridden by implementation classes to return non-default values.
Event Adapters
In long running projects using event sourcing sometimes the need arises to detach the data model from the domain model completely.
Event Adapters help in situations where:
- Version Migrations – existing events stored in Version 1 should be "upcasted" to a new Version 2 representation,
and the process of doing so involves actual code, not just changes on the serialization layer. For these scenarios
the
toJournal
function is usually an identity function, however thefromJournal
is implemented asv1.Event=>v2.Event
, performing the neccessary mapping inside the fromJournal method. This technique is sometimes refered to as "upcasting" in other CQRS libraries. - Separating Domain and Data models – thanks to EventAdapters it is possible to completely separate the domain model
from the model used to persist data in the Journals. For example one may want to use case classes in the
domain model, however persist their protocol-buffer (or any other binary serialization format) counter-parts to the Journal.
A simple
toJournal:MyModel=>MyDataModel
andfromJournal:MyDataModel=>MyModel
adapter can be used to implement this feature. - Journal Specialized Data Types – exposing data types understood by the underlying Journal, for example for data stores which
understand JSON it is possible to write an EventAdapter
toJournal:Any=>JSON
such that the Journal can directly store the json instead of serializing the object to its binary representation.
Implementing an EventAdapter is rather stright forward:
class MyEventAdapter(system: ExtendedActorSystem) extends EventAdapter {
override def manifest(event: Any): String =
"" // when no manifest needed, return ""
override def toJournal(event: Any): Any =
event // identity
override def fromJournal(event: Any, manifest: String): EventSeq =
EventSeq.single(event) // identity
}
Then in order for it to be used on events coming to and from the journal you must bind it using the below configuration syntax:
akka.persistence.journal {
inmem {
event-adapters {
tagging = "docs.persistence.MyTaggingEventAdapter"
user-upcasting = "docs.persistence.UserUpcastingEventAdapter"
item-upcasting = "docs.persistence.ItemUpcastingEventAdapter"
}
event-adapter-bindings {
"docs.persistence.Item" = tagging
"docs.persistence.TaggedEvent" = tagging
"docs.persistence.v1.Event" = [user-upcasting, item-upcasting]
}
}
}
It is possible to bind multiple adapters to one class for recovery, in which case the fromJournal
methods of all
bound adapters will be applied to a given matching event (in order of definition in the configuration). Since each adapter may
return from 0
to n
adapted events (called as EventSeq
), each adapter can investigate the event and if it should
indeed adapt it return the adapted event(s) for it. Other adapters which do not have anything to contribute during this
adaptation simply return EventSeq.empty
. The adapted events are then delivered in-order to the PersistentActor
during replay.
注釈
For more advanced schema evolution techniques refer to the Persistence - Schema Evolution documentation.
Persistent FSM
PersistentFSM
handles the incoming messages in an FSM like fashion.
Its internal state is persisted as a sequence of changes, later referred to as domain events.
Relationship between incoming messages, FSM's states and transitions, persistence of domain events is defined by a DSL.
警告
PersistentFSM
is marked as “experimental” as of its introduction in Akka 2.4.0. We will continue to
improve this API based on our users’ feedback, which implies that while we try to keep incompatible
changes to a minimum the binary compatibility guarantee for maintenance releases does not apply to the
contents of the classes related to ``PersistentFSM`.
A Simple Example
To demonstrate the features of the PersistentFSM
trait, consider an actor which represents a Web store customer.
The contract of our "WebStoreCustomerFSMActor" is that it accepts the following commands:
AddItem
sent when the customer adds an item to a shopping cart
Buy
- when the customer finishes the purchase
Leave
- when the customer leaves the store without purchasing anything
GetCurrentCart
allows to query the current state of customer's shopping cart
The customer can be in one of the following states:
LookingAround
customer is browsing the site, but hasn't added anything to the shopping cart
Shopping
customer has recently added items to the shopping cart
Inactive
customer has items in the shopping cart, but hasn't added anything recently
Paid
customer has purchased the items
注釈
PersistentFSM
states must inherit from trait PersistentFSM.FSMState
and implement the
def identifier: String
method. This is required in order to simplify the serialization of FSM states.
String identifiers should be unique!
Customer's actions are "recorded" as a sequence of "domain events" which are persisted. Those events are replayed on an actor's start in order to restore the latest customer's state:
Customer state data represents the items in a customer's shopping cart:
Here is how everything is wired together:
注釈
State data can only be modified directly on initialization. Later it's modified only as a result of applying domain events.
Override the applyEvent
method to define how state data is affected by domain events, see the example below
andThen
can be used to define actions which will be executed following event's persistence - convenient for "side effects" like sending a message or logging.
Notice that actions defined in andThen
block are not executed on recovery:
A snapshot of state data can be persisted by calling the saveStateSnapshot()
method:
On recovery state data is initialized according to the latest available snapshot, then the remaining domain events are replayed, triggering the
applyEvent
method.
Storage plugins
Storage backends for journals and snapshot stores are pluggable in the Akka persistence extension.
A directory of persistence journal and snapshot store plugins is available at the Akka Community Projects page, see Community plugins
Plugins can be selected either by "default" for all persistent actors and views, or "individually", when a persistent actor or view defines its own set of plugins.
When a persistent actor or view does NOT override the journalPluginId
and snapshotPluginId
methods,
the persistence extension will use the "default" journal and snapshot-store plugins configured in reference.conf
:
akka.persistence.journal.plugin = ""
akka.persistence.snapshot-store.plugin = ""
However, these entries are provided as empty "", and require explicit user configuration via override in the user application.conf
.
For an example of a journal plugin which writes messages to LevelDB see Local LevelDB journal.
For an example of a snapshot store plugin which writes snapshots as individual files to the local filesystem see Local snapshot store.
Applications can provide their own plugins by implementing a plugin API and activating them by configuration. Plugin development requires the following imports:
import akka.persistence._
import akka.persistence.journal._
import akka.persistence.snapshot._
Eager initialization of persistence plugin
By default, persistence plugins are started on-demand, as they are used. In some case, however, it might be beneficial
to start a certain plugin eagerly. In order to do that, you should first add the akka.persistence.Persistence
under the akka.extensions
key. Then, specify the IDs of plugins you wish to start automatically under
akka.persistence.journal.auto-start-journals
and akka.persistence.snapshot-store.auto-start-snapshot-stores
.
Journal plugin API
A journal plugin extends AsyncWriteJournal
.
AsyncWriteJournal
is an actor and the methods to be implemented are:
If the storage backend API only supports synchronous, blocking writes, the methods should be implemented as:
def asyncWriteMessages(messages: immutable.Seq[AtomicWrite]): Future[immutable.Seq[Try[Unit]]] =
Future.fromTry(Try {
// blocking call here
???
})
A journal plugin must also implement the methods defined in AsyncRecovery
for replays and sequence number recovery:
A journal plugin can be activated with the following minimal configuration:
# Path to the journal plugin to be used
akka.persistence.journal.plugin = "my-journal"
# My custom journal plugin
my-journal {
# Class name of the plugin.
class = "docs.persistence.MyJournal"
# Dispatcher for the plugin actor.
plugin-dispatcher = "akka.actor.default-dispatcher"
}
The specified plugin class
must have a no-arg constructor. The plugin-dispatcher
is the dispatcher
used for the plugin actor. If not specified, it defaults to akka.persistence.dispatchers.default-plugin-dispatcher
.
The journal plugin instance is an actor so the methods corresponding to requests from persistent actors are executed sequentially. It may delegate to asynchronous libraries, spawn futures, or delegate to other actors to achive parallelism.
The journal plugin class must have a constructor without parameters or a constructor with one com.typesafe.config.Config
parameter. The plugin section of the actor system's config will be passed in the config constructor parameter.
Don't run journal tasks/futures on the system default dispatcher, since that might starve other tasks.
Snapshot store plugin API
A snapshot store plugin must extend the SnapshotStore
actor and implement the following methods:
A snapshot store plugin can be activated with the following minimal configuration:
# Path to the snapshot store plugin to be used
akka.persistence.snapshot-store.plugin = "my-snapshot-store"
# My custom snapshot store plugin
my-snapshot-store {
# Class name of the plugin.
class = "docs.persistence.MySnapshotStore"
# Dispatcher for the plugin actor.
plugin-dispatcher = "akka.persistence.dispatchers.default-plugin-dispatcher"
}
The specified plugin class
must have a no-arg constructor. The plugin-dispatcher
is the dispatcher
used for the plugin actor. If not specified, it defaults to akka.persistence.dispatchers.default-plugin-dispatcher
.
The snapshot store instance is an actor so the methods corresponding to requests from persistent actors are executed sequentially. It may delegate to asynchronous libraries, spawn futures, or delegate to other actors to achive parallelism.
The snapshot store plugin class must have a constructor without parameters or a constructor with one com.typesafe.config.Config
parameter. The plugin section of the actor system's config will be passed in the config constructor parameter.
Don't run snapshot store tasks/futures on the system default dispatcher, since that might starve other tasks.
Plugin TCK
In order to help developers build correct and high quality storage plugins, we provide a Technology Compatibility Kit (TCK for short).
The TCK is usable from Java as well as Scala projects. For Scala you need to include the akka-persistence-tck dependency:
"com.typesafe.akka" %% "akka-persistence-tck" % "@version@" % "test"
To include the Journal TCK tests in your test suite simply extend the provided JournalSpec
:
class MyJournalSpec extends JournalSpec(
config = ConfigFactory.parseString(
"""akka.persistence.journal.plugin = "my.journal.plugin"""")) {
override def supportsRejectingNonSerializableObjects: CapabilityFlag =
false // or CapabilityFlag.off
}
Please note that some of the tests are optional, and by overriding the supports...
methods you give the
TCK the needed information about which tests to run. You can implement these methods using boolean falues or the
provided CapabilityFlag.on
/ CapabilityFlag.off
values.
We also provide a simple benchmarking class JournalPerfSpec
which includes all the tests that JournalSpec
has, and also performs some longer operations on the Journal while printing its performance stats. While it is NOT aimed
to provide a proper benchmarking environment it can be used to get a rough feel about your journal's performance in the most
typical scenarios.
In order to include the SnapshotStore
TCK tests in your test suite simply extend the SnapshotStoreSpec
:
class MySnapshotStoreSpec extends SnapshotStoreSpec(
config = ConfigFactory.parseString(
"""
akka.persistence.snapshot-store.plugin = "my.snapshot-store.plugin"
"""))
In case your plugin requires some setting up (starting a mock database, removing temporary files etc.) you can override the
beforeAll
and afterAll
methods to hook into the tests lifecycle:
class MyJournalSpec extends JournalSpec(
config = ConfigFactory.parseString(
"""
akka.persistence.journal.plugin = "my.journal.plugin"
""")) {
override def supportsRejectingNonSerializableObjects: CapabilityFlag =
true // or CapabilityFlag.on
val storageLocations = List(
new File(system.settings.config.getString("akka.persistence.journal.leveldb.dir")),
new File(config.getString("akka.persistence.snapshot-store.local.dir")))
override def beforeAll() {
super.beforeAll()
storageLocations foreach FileUtils.deleteRecursively
}
override def afterAll() {
storageLocations foreach FileUtils.deleteRecursively
super.afterAll()
}
}
We highly recommend including these specifications in your test suite, as they cover a broad range of cases you might have otherwise forgotten to test for when writing a plugin from scratch.
Pre-packaged plugins
Local LevelDB journal
The LevelDB journal plugin config entry is akka.persistence.journal.leveldb
. It writes messages to a local LevelDB
instance. Enable this plugin by defining config property:
# Path to the journal plugin to be used
akka.persistence.journal.plugin = "akka.persistence.journal.leveldb"
LevelDB based plugins will also require the following additional dependency declaration:
"org.iq80.leveldb" % "leveldb" % "0.7"
"org.fusesource.leveldbjni" % "leveldbjni-all" % "1.8"
The default location of LevelDB files is a directory named journal
in the current working
directory. This location can be changed by configuration where the specified path can be relative or absolute:
akka.persistence.journal.leveldb.dir = "target/journal"
With this plugin, each actor system runs its own private LevelDB instance.
Local snapshot store
The local snapshot store plugin config entry is akka.persistence.snapshot-store.local
. It writes snapshot files to
the local filesystem. Enable this plugin by defining config property:
# Path to the snapshot store plugin to be used
akka.persistence.snapshot-store.plugin = "akka.persistence.snapshot-store.local"
The default storage location is a directory named snapshots
in the current working
directory. This can be changed by configuration where the specified path can be relative or absolute:
akka.persistence.snapshot-store.local.dir = "target/snapshots"
Note that it is not mandatory to specify a snapshot store plugin. If you don't use snapshots you don't have to configure it.
Persistence Plugin Proxy
A persistence plugin proxy allows sharing of journals and snapshot stores across multiple actor systems (on the same or on different nodes). This, for example, allows persistent actors to failover to a backup node and continue using the shared journal instance from the backup node. The proxy works by forwarding all the journal/snapshot store messages to a single, shared, persistence plugin instance, and therefor supports any use case supported by the proxied plugin.
警告
A shared journal/snapshot store is a single point of failure and should therefore only be used for testing purposes. Highly-available, replicated persistence plugins are available as Community plugins.
The journal and snapshot store proxies are controlled via the akka.persistence.journal.proxy
and
akka.persistence.snapshot-store.proxy
configuration entries, respectively. Set the target-journal-plugin
or
target-snapshot-store-plugin
keys to the underlying plugin you wish to use (for example:
akka.persistence.journal.leveldb
). The start-target-journal
and start-target-snapshot-store
keys should be
set to on
in exactly one actor system - this is the system that will instantiate the shared persistence plugin.
Next, the proxy needs to be told how to find the shared plugin. This can be done by setting the target-journal-address
and target-snapshot-store-address
configuration keys, or programmatically by calling the
PersistencePluginProxy.setTargetLocation
method.
注釈
Akka starts extensions lazily when they are required, and this includes the proxy. This means that in order for the
proxy to work, the persistence plugin on the target node must be instantiated. This can be done by instantiating the
PersistencePluginProxyExtension
extension, or by calling the PersistencePluginProxy.start
method.
注釈
The proxied persistence plugin can (and should) be configured using its original configuration keys.
Custom serialization
Serialization of snapshots and payloads of Persistent
messages is configurable with Akka's
Serialization infrastructure. For example, if an application wants to serialize
- payloads of type
MyPayload
with a customMyPayloadSerializer
and - snapshots of type
MySnapshot
with a customMySnapshotSerializer
it must add
akka.actor {
serializers {
my-payload = "docs.persistence.MyPayloadSerializer"
my-snapshot = "docs.persistence.MySnapshotSerializer"
}
serialization-bindings {
"docs.persistence.MyPayload" = my-payload
"docs.persistence.MySnapshot" = my-snapshot
}
}
to the application configuration. If not specified, a default serializer is used.
For more advanced schema evolution techniques refer to the Persistence - Schema Evolution documentation.
Testing
When running tests with LevelDB default settings in sbt
, make sure to set fork := true
in your sbt project. Otherwise, you'll see an UnsatisfiedLinkError
. Alternatively, you can switch to a LevelDB Java port by setting
akka.persistence.journal.leveldb.native = off
or
akka.persistence.journal.leveldb-shared.store.native = off
in your Akka configuration. The LevelDB Java port is for testing purposes only.
警告
It is not possible to test persistence provided classes (i.e. PersistentActor
and AtLeastOnceDelivery) using TestActorRef
due to its synchronous nature.
These traits need to be able to perform asynchronous tasks in the background in order to handle internal persistence
related events.
When testing Persistence based projects always rely on asynchronous messaging using the TestKit.
Configuration
There are several configuration properties for the persistence module, please refer to the reference configuration.
Multiple persistence plugin configurations
By default, a persistent actor or view will use the "default" journal and snapshot store plugins
configured in the following sections of the reference.conf
configuration resource:
# Absolute path to the default journal plugin configuration entry.
akka.persistence.journal.plugin = "akka.persistence.journal.inmem"
# Absolute path to the default snapshot store plugin configuration entry.
akka.persistence.snapshot-store.plugin = "akka.persistence.snapshot-store.local"
Note that in this case the actor or view overrides only the persistenceId
method:
trait ActorWithDefaultPlugins extends PersistentActor {
override def persistenceId = "123"
}
When the persistent actor or view overrides the journalPluginId
and snapshotPluginId
methods,
the actor or view will be serviced by these specific persistence plugins instead of the defaults:
trait ActorWithOverridePlugins extends PersistentActor {
override def persistenceId = "123"
// Absolute path to the journal plugin configuration entry in the `reference.conf`.
override def journalPluginId = "akka.persistence.chronicle.journal"
// Absolute path to the snapshot store plugin configuration entry in the `reference.conf`.
override def snapshotPluginId = "akka.persistence.chronicle.snapshot-store"
}
Note that journalPluginId
and snapshotPluginId
must refer to properly configured reference.conf
plugin entries with a standard class
property as well as settings which are specific for those plugins, i.e.:
# Configuration entry for the custom journal plugin, see `journalPluginId`.
akka.persistence.chronicle.journal {
# Standard persistence extension property: provider FQCN.
class = "akka.persistence.chronicle.ChronicleSyncJournal"
# Custom setting specific for the journal `ChronicleSyncJournal`.
folder = $${user.dir}/store/journal
}
# Configuration entry for the custom snapshot store plugin, see `snapshotPluginId`.
akka.persistence.chronicle.snapshot-store {
# Standard persistence extension property: provider FQCN.
class = "akka.persistence.chronicle.ChronicleSnapshotStore"
# Custom setting specific for the snapshot store `ChronicleSnapshotStore`.
folder = $${user.dir}/store/snapshot
}
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