Migration Guide 2.5.x to 2.6.x
An overview of the changes in Akka 2.6 is presented in the What’s new in Akka 2.6 video and the release announcement.
Akka 2.6.x is binary backwards compatible with 2.5.x with the ordinary exceptions listed in the Binary Compatibility Rules.
This means that updating an application from Akka 2.5.x to 2.6.x should be a smooth process, and that libraries built for Akka 2.5.x can also be used with Akka 2.6.x. For example Akka HTTP 10.1.10 and Akka Management 1.0.3 can be used with Akka 2.6.0 dependencies. You may have to add explicit dependencies to the new Akka version in your build.
That said, there are some changes to configuration and behavior that should be considered, so reading this migration guide and testing your application thoroughly is recommended.
Rolling updates are possible without shutting down all nodes of the Akka Cluster, but will require configuration adjustments as described in the Remoting section of this migration guide. Due to the changed serialization of the Cluster messages in Akka 2.6.2 a rolling update from 2.5.x must first be made to Akka 2.6.2 and then a second rolling update can change to Akka 2.6.3 or later.
Scala 2.11 no longer supported
If you are still using Scala 2.11 then you must upgrade to 2.12 or 2.13
Auto-downing removed
Auto-downing of unreachable Cluster members have been removed after warnings and recommendations against using it for many years. It was by default disabled, but could be enabled with configuration akka.cluster.auto-down-unreachable-after
.
For alternatives see the documentation about Downing.
Auto-downing was a naïve approach to remove unreachable nodes from the cluster membership. In a production environment it will eventually break down the cluster. When a network partition occurs, both sides of the partition will see the other side as unreachable and remove it from the cluster. This results in the formation of two separate, disconnected, clusters (known as Split Brain).
This behavior is not limited to network partitions. It can also occur if a node in the cluster is overloaded, or experiences a long GC pause.
When using Cluster Singleton or Cluster Sharding it can break the contract provided by those features. Both provide a guarantee that an actor will be unique in a cluster. With the auto-down feature enabled, it is possible for multiple independent clusters to form (*Split Brain*). When this happens the guaranteed uniqueness will no longer be true resulting in undesirable behavior in the system.
This is even more severe when Akka Persistence is used in conjunction with Cluster Sharding. In this case, the lack of unique actors can cause multiple actors to write to the same journal. Akka Persistence operates on a single writer principle. Having multiple writers will corrupt the journal and make it unusable.
Finally, even if you don’t use features such as Persistence, Sharding, or Singletons, auto-downing can lead the system to form multiple small clusters. These small clusters will be independent from each other. They will be unable to communicate and as a result you may experience performance degradation. Once this condition occurs, it will require manual intervention in order to reform the cluster.
Because of these issues, auto-downing should never be used in a production environment.
Removed features that were deprecated
After being deprecated since 2.5.0, the following have been removed in Akka 2.6.0.
- akka-camel module
- As an alternative we recommend Alpakka.
- This is of course not a drop-in replacement. If there is community interest we are open to setting up akka-camel as a separate community-maintained repository.
- akka-agent module
- If there is interest it may be moved to a separate, community-maintained repository.
- akka-contrib module
- To migrate, take the components you are using from Akka 2.5 and include them in your own project or library under your own package name.
- Actor DSL
- Actor DSL is a rarely used feature. Use plain
system.actorOf
instead of the DSL to create Actors if you have been using it.
- Actor DSL is a rarely used feature. Use plain
akka.stream.extra.Timing
operator- If you need it you can now find it in
akka.stream.contrib.Timed
from Akka Stream Contrib.
- If you need it you can now find it in
- Netty UDP (Classic remoting over UDP)
- To continue to use UDP configure Artery UDP or migrate to Artery TCP.
- A full cluster restart is required to change to Artery.
UntypedActor
- Use
AbstractActor
instead.
- Use
JavaTestKit
- Use
akka.testkit.javadsl.TestKit
instead.
- Use
UntypedPersistentActor
- Use
AbstractPersistentActor
instead.
- Use
UntypedPersistentActorWithAtLeastOnceDelivery
akka.stream.actor.ActorSubscriber
andakka.stream.actor.ActorPublisher
- Use
GraphStage
instead.
- Use
After being deprecated since 2.4.0, the following have been removed in Akka 2.6.0.
- Secure cookie in Classic Akka Remoting
After being deprecated since 2.2, the following have been removed in Akka 2.6.0.
actorFor
- Use
ActorSelection
instead.
- Use
Removed methods
Logging.getLogger(UntypedActor)
UntypedActor
has been removed, useAbstractActor
instead.LoggingReceive.create(Receive, ActorContext)
useAbstractActor.Receive
instead.ActorMaterialzierSettings.withAutoFusing
disabling fusing is no longer possible.AbstractActor.getChild
usefindChild
instead.Actor.getRef
useActor.getActorRef
instead.CircuitBreaker.onOpen
useCircuitBreaker.addOnOpenListener
CircuitBreaker.onHalfOpen
useCircuitBreaker.addOnHalfOpenListener
CircuitBreaker.onClose
useCircuitBreaker.addOnCloseListener
Source.actorSubscriber
, useSource.fromGraph
instead.Source.actorActorPublisher
, useSource.fromGraph
instead.
Deprecated features
PersistentFSM
Migration guide to Persistence Typed is in the PersistentFSM documentation.
TypedActor
akka.actor.TypedActor
has been deprecated as of 2.6.0 in favor of the akka.actor.typed
API which should be used instead.
There are several reasons for phasing out the old TypedActor
. The primary reason is they use transparent remoting which is not our recommended way of implementing and interacting with actors. Transparent remoting is when you try to make remote method invocations look like local calls. In contrast we believe in location transparency with explicit messaging between actors (same type of messaging for both local and remote actors). They also have limited functionality compared to ordinary actors, and worse performance.
To summarize the fallacy of transparent remoting:
- Was used in CORBA, RMI, and DCOM, and all of them failed. Those problems were noted by Waldo et al already in 1994
- Partial failure is a major problem. Remote calls introduce uncertainty whether the function was invoked or not. Typically handled by using timeouts but the client can’t always know the result of the call.
- Latency of calls over a network are several orders of magnitudes longer than latency of local calls, which can be more than surprising if encoded as an innocent looking local method call.
- Remote invocations have much lower throughput due to the need of serializing the data and you can’t just pass huge datasets in the same way.
Therefore explicit message passing is preferred. It looks different from local method calls (actorRef ! message
actorRef.tell(message)
) and there is no misconception that sending a message will result in it being processed instantaneously. The goal of location transparency is to unify message passing for both local and remote interactions, versus attempting to make remote interactions look like local method calls.
Warnings about TypedActor
have been mentioned in documentation for many years.
Cluster Client
Cluster client has been deprecated as of 2.6.0 in favor of Akka gRPC. It is not advised to build new applications with Cluster client, and existing users should migrate to Akka gRPC.
akka-protobuf
akka-protobuf
was never intended to be used by end users but perhaps this was not well-documented. Applications should use standard Protobuf dependency instead of akka-protobuf
. The artifact is still published, but the transitive dependency to akka-protobuf
has been removed.
Akka is now using Protobuf version 3.9.0 for serialization of messages defined by Akka.
ByteString.empty
It is now recommended to use ByteString
ByteString
.emptyByteString()
instead of ByteString
ByteString
.empty()
when using Java because ByteString
ByteString
.empty()
is no longer available as a static method in the artifacts built for Scala 2.13.
AkkaSslConfig
AkkaSslConfig
has been deprecated in favor of setting up TLS with javax.net.ssl.SSLEngine
directly.
This also means that methods Akka Streams TLS
and Tcp
that take SSLContext
or AkkaSslConfig
have been deprecated and replaced with corresponding methods that takes a factory function for creating the SSLEngine
.
See documentation of streaming IO with TLS.
JavaLogger
akka.event.jul.JavaLogger
for integration with java.util.logging
has been deprecated. Use SLF4J instead, which also has support for java.util.logging
.
akka.Main
akka.Main
is deprecated in favour of starting the ActorSystem
from a custom main class instead. akka.Main
was not adding much value and typically a custom main class is needed anyway.
Pluggable DNS
Plugging in your own DNS implementation is now deprecated and will be removed in 2.7.0
, it was originally added to support a third party DNS provided that supported SRV records. The built in async-dns
now supports SRV records.
The resolve
and cached
methods on the DNS
extension have also been deprecated in favour of ones that take in DnsProtocol.Resolve
. These methods return a new types that include SRV records.
Remoting
Default remoting is now Artery TCP
Artery TCP is now the default remoting implementation. Classic remoting has been deprecated and will be removed in 2.7.0
.
Migrating from classic remoting to Artery
Artery has the same functionality as classic remoting and you should normally only have to change the configuration to switch.
To switch a full cluster restart is required and any overrides for classic remoting need to be ported to Artery configuration. Artery has a completely different protocol, which means that a rolling update is not supported.
Artery defaults to TCP (see selected transport) which is a good start when migrating from classic remoting.
The protocol part in the Akka Address
, for example "akka.tcp://[email protected]:2552/user/actorName"
has changed from akka.tcp
to akka
. If you have configured or hardcoded any such addresses you have to change them to "akka://[email protected]:25520/user/actorName"
. akka
is used also when TLS is enabled. One typical place where such address is used is in the seed-nodes
configuration.
The default port is 25520 instead of 2552 to avoid connections between Artery and classic remoting due to misconfiguration. You can run Artery on 2552 if you prefer that (e.g. existing firewall rules) and then you have to configure the port with:
akka.remote.artery.canonical.port = 2552
The configuration for Artery is different, so you might have to revisit any custom configuration. See the full reference configuration for Artery and reference configuration for classic remoting.
Configuration that is likely required to be ported:
akka.remote.netty.tcp.hostname
=>akka.remote.artery.canonical.hostname
akka.remote.netty.tcp.port
=>akka.remote.artery.canonical.port
If using SSL then tcp-tls
needs to be enabled and setup. See Artery docs for SSL for how to do this.
The following events that are published to the eventStream
have changed:
- classic
akka.remote.QuarantinedEvent
isakka.remote.artery.QuarantinedEvent
in Artery - classic
akka.remote.GracefulShutdownQuarantinedEvent
isakka.remote.artery.GracefulShutdownQuarantinedEvent
in Artery - classic
akka.remote.ThisActorSystemQuarantinedEvent
isakka.remote.artery.ThisActorSystemQuarantinedEvent
in Artery
Migration from 2.5.x Artery to 2.6.x Artery
The following defaults have changed:
akka.remote.artery.transport
default has changed fromaeron-udp
totcp
The following properties have moved. If you don’t adjust these from their defaults no changes are required:
For Aeron-UDP:
akka.remote.artery.log-aeron-counters
toakka.remote.artery.advanced.aeron.log-aeron-counters
akka.remote.artery.advanced.embedded-media-driver
toakka.remote.artery.advanced.aeron.embedded-media-driver
akka.remote.artery.advanced.aeron-dir
toakka.remote.artery.advanced.aeron.aeron-dir
akka.remote.artery.advanced.delete-aeron-dir
toakka.remote.artery.advanced.aeron.aeron-delete-dir
akka.remote.artery.advanced.idle-cpu-level
toakka.remote.artery.advanced.aeron.idle-cpu-level
akka.remote.artery.advanced.give-up-message-after
toakka.remote.artery.advanced.aeron.give-up-message-after
akka.remote.artery.advanced.client-liveness-timeout
toakka.remote.artery.advanced.aeron.client-liveness-timeout
akka.remote.artery.advanced.image-liveless-timeout
toakka.remote.artery.advanced.aeron.image-liveness-timeout
akka.remote.artery.advanced.driver-timeout
toakka.remote.artery.advanced.aeron.driver-timeout
For TCP:
akka.remote.artery.advanced.connection-timeout
toakka.remote.artery.advanced.tcp.connection-timeout
Remaining with Classic remoting (not recommended)
Classic remoting is deprecated but can be used in 2.6.x Rolling update from Classic remoting to Artery is not supported so if you want to update from Akka 2.5.x with Classic remoting to Akka 2.6.x without a full shut down of the Cluster you have to enable Classic remoting. Later, you can plan for a full shutdown and migrate from classic remoting to Artery as a separate step.
Explicitly disable Artery by setting property akka.remote.artery.enabled
to false
. Further, any configuration under akka.remote
that is specific to classic remoting needs to be moved to akka.remote.classic
. To see which configuration options are specific to classic search for them in: akka-remote/reference.conf
.
If you have a Lightbend Subscription you can use our Config Checker enhancement to flag any settings that have not been properly migrated.
Persistent mode for Cluster Sharding
Cluster Sharding coordinator and Remembering Entities state could previously be stored in Distributed Data or via Akka Persistence. The Persistence mode has been deprecated in favour of using the Distributed Data mode for the coordinator state. A replacement for the state for Remembered Entities is tracked in issue 27763.
Java Serialization
Java serialization is known to be slow and prone to attacks of various kinds - it never was designed for high throughput messaging after all. One may think that network bandwidth and latency limit the performance of remote messaging, but serialization is a more typical bottleneck.
From Akka 2.6.0 the Akka serialization with Java serialization is disabled by default and Akka itself doesn’t use Java serialization for any of its internal messages.
You have to enable serialization to send messages between ActorSystems (nodes) in the Cluster. Serialization with Jackson is a good choice in many cases, and our recommendation if you don’t have other preferences or constraints.
For compatibility with older systems that rely on Java serialization it can be enabled with the following configuration:
akka.actor.allow-java-serialization = on
Akka will still log warning when Java serialization is used and to silent that you may add:
akka.actor.warn-about-java-serializer-usage = off
Rolling update
Please see the rolling update procedure from Java serialization to Jackson.
Java serialization in consistent hashing
When using a consistent hashing router keys that were not bytes or a String are serialized. You might have to add a serializer for you hash keys, unless one of the default serializer are not handling that type and it was previously “accidentally” serialized with Java serialization.
Configuration and behavior changes
The following documents configuration changes and behavior changes where no action is required. In some cases the old behavior can be restored via configuration.
Remoting dependencies have been made optional
Classic remoting depends on Netty and Artery UDP depends on Aeron. These are now both optional dependencies that need to be explicitly added. See classic remoting or artery remoting for instructions.
Remote watch and deployment have been disabled without Cluster use
By default, these remoting features are disabled when not using Akka Cluster:
- Remote Deployment: falls back to creating a local actor
- Remote Watch: ignores the watch and unwatch request, and
Terminated
will not be delivered when the remote actor is stopped or if a remote node crashes
Watching an actor on a node outside the cluster may have unexpected consequences, such as quarantining so it has been disabled by default in Akka 2.6.x This is the case if either cluster is not used at all (only plain remoting) or when watching an actor outside of the cluster.
On the other hand, failure detection between nodes of the same cluster do not have that shortcoming. Thus, when remote watching or deployment is used within the same cluster, they are working the same in 2.6.x as before, except that a remote watch attempt before a node has joined will log a warning and be ignored, it must be done after the node has joined.
To optionally enable a watch without Akka Cluster or across a Cluster boundary between Cluster and non Cluster, knowing the consequences, all watchers (cluster as well as remote) need to set:
akka.remote.use-unsafe-remote-features-outside-cluster = on`.
When enabled
- An initial warning is logged on startup of
RemoteActorRefProvider
-
A warning will be logged on remote watch attempts, which you can suppress by setting
akka.remote.warn-unsafe-watch-outside-cluster = off
Schedule periodically with fixed-delay vs. fixed-rate
The Scheduler.schedule
method has been deprecated in favor of selecting scheduleWithFixedDelay
or scheduleAtFixedRate
.
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
.
The deprecated schedule
method had the same semantics as scheduleAtFixedRate
, but since that can result in bursts of scheduled tasks or messages after long garbage collection pauses and in the worst case cause undesired load on the system scheduleWithFixedDelay
is often preferred.
For the same reason the following methods have also been deprecated:
TimerScheduler.startPeriodicTimer
, replaced bystartTimerWithFixedDelay
orstartTimerAtFixedRate
FSM.setTimer
, replaced bystartSingleTimer
,startTimerWithFixedDelay
orstartTimerAtFixedRate
PersistentFSM.setTimer
, replaced bystartSingleTimer
,startTimerWithFixedDelay
orstartTimerAtFixedRate
Internal dispatcher introduced
To protect the Akka internals against starvation when user code blocks the default dispatcher (for example by accidental use of blocking APIs from actors) a new internal dispatcher has been added. All of Akka’s internal, non-blocking actors now run on the internal dispatcher by default.
The dispatcher can be configured through akka.actor.internal-dispatcher
.
For maximum performance, you might want to use a single shared dispatcher for all non-blocking, asynchronous actors, user actors and Akka internal actors. In that case, you can configure the akka.actor.internal-dispatcher
with a string value of akka.actor.default-dispatcher
. This reinstantiates the behavior from previous Akka versions but also removes the isolation between user and Akka internals. So, use at your own risk!
Several use-dispatcher
configuration settings that previously accepted an empty value to fall back to the default dispatcher has now gotten an explicit value of akka.actor.internal-dispatcher
and no longer accept an empty string as value. If such an empty value is used in your application.conf
the same result is achieved by simply removing that entry completely and having the default apply.
For more details about configuring dispatchers, see the Dispatchers
Default dispatcher size
Previously the factor for the default dispatcher was set a bit high (3.0
) to give some extra threads in case of accidental blocking and protect a bit against starving the internal actors. Since the internal actors are now on a separate dispatcher the default dispatcher has been adjusted down to 1.0
which means the number of threads will be one per core, but at least 8
and at most 64
. This can be tuned using the individual settings in akka.actor.default-dispatcher.fork-join-executor
.
Mixed version
Startup will fail if mixed versions of a product family (such as Akka) are accidentally used. This was previously only logged as a warning. There is no guarantee mixed modules will work and it’s better to fail early than that the application is crashing at a later time than startup.
Cluster Sharding
waiting-for-state-timeout reduced to 2s
This has been reduced to speed up ShardCoordinator initialization in smaller clusters. The read from ddata is a ReadMajority. For small clusters (< majority-min-cap) every node needs to respond so it is more likely to timeout if there are nodes restarting, for example when there is a rolling re-deploy happening.
Passivate idle entity
The configuration akka.cluster.sharding.passivate-idle-entity-after
is now enabled by default. Sharding will passivate entities when they have not received any messages after this duration. To disable passivation you can use configuration:
akka.cluster.sharding.passivate-idle-entity-after = off
It is always disabled if Remembering Entities is enabled.
Cluster Sharding stats
A new field has been added to the response of a ShardRegion.GetClusterShardingStats
command for any shards per region that may have failed or not responded within the new configurable akka.cluster.sharding.shard-region-query-timeout
. This is described further in inspecting sharding state.
Distributed Data
Config for message payload size
Configuration properties for controlling sizes of Gossip
and DeltaPropagation
messages in Distributed Data have been reduced. Previous defaults sometimes resulted in messages exceeding max payload size for remote actor messages.
The new configuration properties are:
akka.cluster.distributed-data.max-delta-elements = 500
akka.cluster.distributed-data.delta-crdt.max-delta-size = 50
DataDeleted
DataDeleted
has been changed in its usage. While it is still a possible response to a Delete request, it is no longer the response when an Update
or Get
request couldn’t be performed because the entry has been deleted. In its place are two new possible responses to a request, UpdateDataDeleted
for an Update
and GetDataDeleted
for a Get
.
The reason for this change is that DataDeleted
didn’t extend the UpdateResponse
and GetResponse
types and could therefore cause problems when Update
and Get
were used with ask
. This was also a problem for Akka Typed.
CoordinatedShutdown is run from ActorSystem.terminate
No migration is needed but it is mentioned here because it is a change in behavior.
When ActorSystem.terminate()
is called, CoordinatedShutdown
will be run in Akka 2.6.x, which wasn’t the case in 2.5.x. For example, if using Akka Cluster this means that member will attempt to leave the cluster gracefully.
If this is not desired behavior, for example in tests, you can disable this feature with the following configuration and then it will behave as in Akka 2.5.x:
akka.coordinated-shutdown.run-by-actor-system-terminate = off
Scheduler not running tasks when shutdown
When the ActorSystem
was shutting down and the Scheduler
was closed all outstanding scheduled tasks were run, which was needed for some internals in Akka but a surprising behavior for end users. Therefore this behavior has changed in Akka 2.6.x and outstanding tasks are not run when the system is terminated.
Instead, system.registerOnTermination
or CoordinatedShutdown
can be used for running such tasks when shutting down.
IOSources & FileIO
FileIO.toPath
, StreamConverters.fromInputStream
, and StreamConverters.fromOutputStream
now always fail the materialized value in case of failure. It is no longer required to both check the materialized value and the Try[Done]
inside the IOResult
IOResult
. In case of an IO failure the exception will be IOOperationIncompleteException
IOOperationIncompleteException
instead of AbruptIOTerminationException
AbruptIOTerminationException
.
Additionally when downstream of the IO-sources cancels with a failure, the materialized value is failed with that failure rather than completed successfully.
Akka now uses Fork Join Pool from JDK
Previously, Akka contained a shaded copy of the ForkJoinPool. In benchmarks, we could not find significant benefits of keeping our own copy, so from Akka 2.6.0 on, the default FJP from the JDK will be used. The Akka FJP copy was removed.
Logging of dead letters
When the number of dead letters have reached configured akka.log-dead-letters
value it didn’t log more dead letters in Akka 2.5.x. In Akka 2.6.x the count is reset after configured akka.log-dead-letters-suspend-duration
.
akka.log-dead-letters-during-shutdown
default configuration changed from on
to off
.
Cluster failure detection
Default number of nodes that each node is observing for failure detection has increased from 5 to 9. The reason is to have better coverage and unreachability information for downing decisions.
Configuration property:
akka.cluster.monitored-by-nr-of-members = 9
TestKit
expectNoMessage()
without timeout parameter is now using a new configuration property akka.test.expect-no-message-default
(short timeout) instead of remainingOrDefault
(long timeout).
Config library resolution change
The Lightbend Config Library has been updated to load both reference.conf
and user config files such as application.conf
before substitution of variables used in the reference.conf
. This makes it possible to override such variables in reference.conf
with user configuration.
For example, the default config for Cluster Sharding, refers to the default config for Distributed Data, in reference.conf
like this:
akka.cluster.sharding.distributed-data = ${akka.cluster.distributed-data}
In Akka 2.5.x this meant that to override default gossip interval for both direct use of Distributed Data and Cluster Sharding in the same application you would have to change two settings:
akka.cluster.distributed-data.gossip-interval = 3s
akka.cluster.sharding.distributed-data = 3s
In Akka 2.6.0 and forward, changing the default in the akka.cluster.distributed-data
config block will be done before the variable in reference.conf
is resolved, so that the same change only needs to be done once:
akka.cluster.distributed-data.gossip-interval = 3s
The following default settings in Akka are using such substitution and may be affected if you are changing the right hand config path in your application.conf
:
akka.cluster.sharding.coordinator-singleton = ${akka.cluster.singleton}
akka.cluster.sharding.distributed-data = ${akka.cluster.distributed-data}
akka.cluster.singleton-proxy.singleton-name = ${akka.cluster.singleton.singleton-name}
akka.cluster.typed.receptionist.distributed-data = ${akka.cluster.distributed-data}
akka.remote.classic.netty.ssl = ${akka.remote.classic.netty.tcp}
akka.remote.artery.advanced.materializer = ${akka.stream.materializer}
Source incompatibilities
StreamRefs
The materialized value for StreamRefs.sinkRef
and StreamRefs.sourceRef
is no longer wrapped in Future
/CompletionStage
. It can be sent as reply to sender()
immediately without using the pipe
pattern.
StreamRefs
was marked as may change.
Akka Typed
Naming convention changed
In needing a way to distinguish the new APIs in code and docs from the original, Akka used the naming convention untyped
. All references of the original have now been changed to classic
. The reference of the new APIs as typed
is going away as it becomes the primary APIs.
Receptionist has moved
The receptionist had a name clash with the default Cluster Client Receptionist at /system/receptionist
and will now instead either run under /system/localReceptionist
or /system/clusterReceptionist
.
The path change means that the receptionist information will not be disseminated between 2.5.x and 2.6.x nodes during a rolling update from 2.5.x to 2.6.x if you use Akka Typed. See rolling updates with typed Receptionist
Cluster Receptionist using own Distributed Data
In 2.5.x the Cluster Receptionist was using the shared Distributed Data extension but that could result in undesired configuration changes if the application was also using that and changed for example the role
configuration.
In 2.6.x the Cluster Receptionist is using its own independent instance of Distributed Data.
This means that the receptionist information will not be disseminated between 2.5.x and 2.6.x nodes during a rolling update from 2.5.x to 2.6.x if you use Akka Typed. See rolling updates with typed Cluster Receptionist
Akka Typed API changes
Akka Typed APIs were still marked as may change in Akka 2.5.x and a few changes were made before finalizing the APIs. Compared to Akka 2.5.x the source incompatible changes are:
Behaviors.intercept
now takes a factory function for the interceptor.ActorSystem.scheduler
previously gave access to the classicakka.actor.Scheduler
but now returns a specificakka.actor.typed.Scheduler
. Additionallyschedule
method has been replaced byscheduleWithFixedDelay
andscheduleAtFixedRate
. Actors that need to schedule tasks should preferBehaviors.withTimers
.TimerScheduler.startPeriodicTimer
, replaced bystartTimerWithFixedDelay
orstartTimerAtFixedRate
Routers.pool
now takes a factory function rather than aBehavior
to protect against accidentally sharing same behavior instance and state across routees.- The
request
parameter in Distributed Data commands was removed, in favor of usingask
with the newReplicatorMessageAdapter
. - Removed
Behavior.same
,Behavior.unhandled
,Behavior.stopped
,Behavior.empty
, andBehavior.ignore
since they were redundant with corresponding scaladsl.Behaviors.xjavadsl.Behaviors.x. ActorContext
parameter removed injavadsl.ReceiveBuilder
for the functional style in Java. UseBehaviors.setup
to retrieveActorContext
, and use an enclosing class to hold initialization parameters andActorContext
.- Java
EntityRef
ask timeout now takes ajava.time.Duration
rather than aTimeout
Timeout
- Changed method signature for
EventAdapter.fromJournal
and support formanifest
inEventAdapter
. - Renamed
widen
Behaviors.widen
totransformMessages
Behaviors.transformMessages
BehaviorInterceptor
,Behaviors.monitor
,Behaviors.withMdc
andtransformMessages
Behaviors.transformMessages
takes aClassTag
parameter (probably source compatible)interceptMessageClass
parameter.interceptMessageType
method inBehaviorInterceptor
is replaced with thisClassTag
Class
parameter.Behavior.orElse
has been removed because it wasn’t safe together withnarrow
.StashBuffer
s are now created withBehaviors.withStash
rather than instantiating directly- To align with the Akka Typed style guide
SpawnProtocol
is now created throughSpawnProtocol()
SpawnProtocol.create()
, the specialSpawn
message factories has been removed and the top level of the actor protocol is nowSpawnProtocol.Command
Future
removed fromActorSystem.systemActorOf
.toUntyped
has been renamed totoClassic
.- Akka Typed is now using SLF4J as the logging API.
ActorContext.log
ActorContext.getLog
returns anorg.slf4j.Logger
. MDC has been changed to only supportString
values. setLoggerClass
inActorContext
has been renamed tosetLoggerName
.GetDataDeleted
andUpdateDataDeleted
introduced as described in DataDeleted.SubscribeResponse
introduced inSubscribe
because the responses can be bothChanged
andDeleted
.ReplicationDeleteFailure
renamed toDeleteFailure
.EventSourcedEntity
removed in favor using plainEventSourcedBehavior
because the alternative way was causing more confusion than adding value. Construction ofPersistentId
for theEventSourcedBehavior
is facilitated by factory methods inPersistenceId
.PersistenceId.apply(String)
renamed toPersistenceId.ofUniqueId(String)
akka.cluster.sharding.typed.scaladsl.Entity.apply
changed to use two parameter lists because the newEntityContext.entityTypeKey
required additional type parameter that is inferred better with a secondary parameter list.EventSourcedBehavior.withEnforcedReplies
signature changed. Command is not required to extendExpectingReply
anymore.ExpectingReply
has therefore been removed.ActorContext
is now a mandatory constructor parameter inAbstractBehavior
. Create viaBehaviors.setup
. The reason is to encourage right usage and detect mistakes like not creating a new instance (viasetup
) when the behavior is supervised and restarted.LoggingEventFilter
has been renamed toLoggingTestKit
and itsintercept
method renamed toassert
- Scala
ask
fromAskPattern
now implicitly converts an implicitActorSystem[_]
toScheduler
to eliminate some boilerplate.
Akka Typed Stream API changes
ActorSource.actorRef
relying onPartialFunction
has been replaced in the Java API with a variant more suitable to be called by Java.- Factories for creating a materializer from an
akka.actor.typed.ActorSystem
have been removed. A stream can be run with anakka.actor.typed.ActorSystem
in implicit scopeparameter and therefore the need for creating a materializer has been reduced. actorRefWithAck
has been renamed toactorRefWithBackpressure
Akka Stream changes
Materializer changes
A default materializer is now provided out of the box. For the Java API just pass system
when running streams, for Scala an implicit materializer is provided if there is an implicit ActorSystem
available. This avoids leaking materializers and simplifies most stream use cases somewhat.
The ActorMaterializer
factories has been deprecated and replaced with a few corresponding factories in akka.stream.Materializer
. New factories with per-materializer settings has not been provided but should instead be done globally through config or per stream, see below for more details.
Having a default materializer available means that most, if not all, usages of Java ActorMaterializer.create()
and Scala implicit val materializer = ActorMaterializer()
should be removed.
Details about the stream materializer can be found in Actor Materializer Lifecycle
When using streams from typed the same factories and methods for creating materializers and running streams as from classic can now be used with typed. The akka.stream.typed.scaladsl.ActorMaterializer
and akka.stream.typed.javadsl.ActorMaterializerFactory
that previously existed in the akka-stream-typed
module has been removed.
Materializer settings deprecated
The ActorMaterializerSettings
class has been deprecated.
All materializer settings are available as configuration to change the system default or through attributes that can be used for individual streams when they are materialized.
MaterializerSettings | Corresponding attribute | Config |
---|---|---|
initialInputBufferSize |
Attributes.inputBuffer(initial, max) |
akka.stream.materializer.initial-input-buffer-size |
maxInputBufferSize |
Attributes.inputBuffer(initial, max) |
akka.stream.materializer.max-input-buffer-size |
dispatcher |
ActorAttributes.dispatcher(name) |
akka.stream.materializer.dispatcher |
supervisionDecider |
ActorAttributes.supervisionStrategy |
na |
debugLogging |
ActorAttributes.debugLogging |
akka.stream.materializer.debug-logging |
outputBurstLimit |
ActorAttributes.outputBurstLimit |
akka.stream.materializer.output-burst-limit |
fuzzingMode |
ActorAttributes.fuzzingMode |
akka.stream.materializer.debug.fuzzing-mode |
autoFusing |
no longer used (since 2.5.0) | na |
maxFixedBufferSize |
ActorAttributes.maxFixedBufferSize |
akka.stream.materializer.max-fixed-buffer-size |
syncProcessingLimit |
ActorAttributes.syncProcessingLimit |
akka.stream.materializer.sync-processing-limit |
IOSettings.tcpWriteBufferSize |
Tcp.writeBufferSize |
akka.stream.materializer.io.tcp.write-buffer-size |
blockingIoDispatcher |
na | akka.stream.materializer.blocking-io-dispatcher |
StreamRefSettings | Corresponding StreamRefAttributes | Config |
---|---|---|
bufferCapacity |
bufferCapacity |
akka.stream.materializer.stream-ref.buffer-capacity |
demandRedeliveryInterval |
demandRedeliveryInterval |
akka.stream.materializer.stream-ref.demand-redelivery-interval |
subscriptionTimeout |
subscriptionTimeout |
akka.stream.materializer.stream-ref.subscription-timeout |
finalTerminationSignalDeadline |
finalTerminationSignalDeadline |
akka.stream.materializer.stream-ref.final-termination-signal-deadline |
SubscriptionTimeoutSettings | Corresponding ActorAttributes | Config |
---|---|---|
subscriptionTimeoutSettings.mode |
streamSubscriptionTimeoutMode |
akka.stream.materializer.subscription-timeout.mode |
subscriptionTimeoutSettings.timeout |
streamSubscriptionTimeout |
akka.stream.materializer.subscription-timeout.timeout |
Setting attributes on individual streams can be done like so:
- Scala
-
source
val stream: RunnableGraph[Future[Done]] = Source(1 to 10) .map(_.toString) .toMat(Sink.foreach(println))(Keep.right) .withAttributes(Attributes.inputBuffer(4, 4) and ActorAttributes.dispatcher("my-stream-dispatcher") and TcpAttributes.tcpWriteBufferSize(2048)) stream.run()
- Java
-
source
RunnableGraph<CompletionStage<Done>> stream = Source.range(1, 10) .map(Object::toString) .toMat(Sink.foreach(System.out::println), Keep.right()) .withAttributes( Attributes.inputBuffer(4, 4) .and(ActorAttributes.dispatcher("my-stream-dispatcher")) .and(TcpAttributes.tcpWriteBufferSize(2048))); stream.run(system);
Stream cancellation available upstream
Previously an Akka streams stage or operator failed it was impossible to discern this from the stage just cancelling. This has been improved so that when a stream stage fails the cause will be propagated upstream.
The following operators have a slight change in behavior because of this:
FileIO.fromPath
,FileIO.fromFile
andStreamConverters.fromInputStream
will fail the materialized future with anIOOperationIncompleteException
when downstream fails.watchTermination
will fail the materializedFuture
orCompletionStage
rather than completing it when downstream failsStreamRef
-SourceRef
will cancel with a failure when the receiving node is downed
This also means that custom GraphStage
implementations should be changed to pass on the cancellation cause when downstream cancels by implementing the OutHandler.onDownstreamFinish
signature taking a cause
parameter and calling cancelStage(cause)
to pass the cause upstream. The old zero-argument onDownstreamFinish
method has been deprecated.
Lazy and async stream operator changes
The operators that provide support for lazy and Future
CompletionStage
stream construction were revised to be more consistent.
The materialized value is now no longer wrapped in an Option
Optional
, instead the Future
CompletionStage
is failed with a akka.stream.NeverMaterializedException
in the cases that would previously lead to None
an empty Optional
A deferred creation of the stream based on the initial element like how the deprecated lazyInit
worked can be achieved by combining future(Flow|Sink)
completionStage(Flow|Sink)
with prefixAndTail
. See example in futureFlow completionStageFlow.
javadsl.Flow
old | new |
---|---|
lazyInit | lazyCompletionStageFlow in combination with prefixAndTail(1) |
lazyInitAsync | lazyCompletionStageFlow |
completionStageFlow | |
lazyFlow |
javadsl.Sink
old | new |
---|---|
lazyInit | lazyCompletionStageSink in combination with Flow.prefixAndTail(1) |
lazyInitAsync | lazyCompletionStageSink |
completionStageSink | |
lazySink |
javadsl.Source
old | new |
---|---|
fromFuture | future |
fromCompletionStage | completionStage |
fromFutureSource | futureSource |
fromSourceCompletionStage | completionStageSource |
lazily | lazySource |
lazilyAsync | lazyCompletionStage |
lazySingle | |
lazyCompletionStageSource |
scaladsl.Flow
old | new |
---|---|
lazyInit | lazyFutureFlow |
lazyInitAsync | lazyFutureFlow |
futureFlow | |
lazyFlow |
scaladsl.Sink
old | new |
---|---|
lazyInit | lazyFutureSink in combination with Flow.prefixAndTail(1) |
lazyInitAsync | lazyFutureSink |
futureSink | |
lazySink |
scaladsl.Source
old | new |
---|---|
fromFuture | future |
fromCompletionStage | completionStage |
fromFutureSource | futureSource |
fromSourceCompletionStage | |
lazily | lazySource |
lazilyAsync | lazyFuture |
lazySingle | |
lazyFutureSource |