Josep Prat
GitHub
parent
8b71fac817
commit
12513ec7df
13 changed files with 45 additions and 46 deletions
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@ -56,7 +56,7 @@ trait ReplicatedShardingExtension extends Extension {
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}
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/**
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* Represents the sharding instances for the replicas of one replicated event sourcing entity type
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* Represents the sharding instances for the replicas of one Replicated Event Sourcing entity type
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*
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* Not for user extension.
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*/
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@ -75,7 +75,7 @@ class ReplicatedShardingDirectReplicationSpec extends ScalaTestWithActorTestKit
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replicaAProbe.expectNoMessage()
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}
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"ignore messages not from replicated event sourcing" in {
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"ignore messages not from Replicated Event Sourcing" in {
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val replicaAProbe = createTestProbe[ShardingEnvelope[PublishedEvent]]()
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val replicationActor = spawn(
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@ -1191,7 +1191,7 @@ abstract class ShardCoordinator(
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/**
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* Singleton coordinator that decides where to allocate shards.
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*
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* Users can migrate to using DData to store state then either event sourcing or ddata to store
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* Users can migrate to using DData to store state then either Event Sourcing or ddata to store
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* the remembered entities.
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*
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* @see [[ClusterSharding$ ClusterSharding extension]]
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@ -31,7 +31,7 @@ Scala
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Java
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: @@snip [ClusterShardingTest.java](/akka-docs/src/test/java/jdocs/sharding/ClusterShardingTest.java) { #counter-actor }
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The above actor uses event sourcing and the support provided in @scala[`PersistentActor`] @java[`AbstractPersistentActor`] to store its state.
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The above actor uses Event Sourcing and the support provided in @scala[`PersistentActor`] @java[`AbstractPersistentActor`] to store its state.
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It does not have to be a persistent actor, but in case of failure or migration of entities between nodes it must be able to recover
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its state if it is valuable.
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@ -129,7 +129,6 @@ This means that:
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5. `A2` can see messages from `A1` interleaved with messages from `A3`
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6. Since there is no guaranteed delivery, any of the messages may be dropped, i.e. not arrive at `A2`
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@@@ note
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It is important to note that Akka’s guarantee applies to the order in which
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@ -288,7 +287,7 @@ idempotent on the level of the business logic.
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### Event Sourcing
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Event sourcing (and sharding) is what makes large websites scale to
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Event Sourcing (and sharding) is what makes large websites scale to
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billions of users, and the idea is quite simple: when a component (think actor)
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processes a command it will generate a list of events representing the effect
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of the command. These events are stored in addition to being applied to the
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@ -299,7 +298,7 @@ components may consume the event stream as a means to replicate the component’
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state on a different continent or to react to changes). If the component’s
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state is lost—due to a machine failure or by being pushed out of a cache—it can
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be reconstructed by replaying the event stream (usually employing
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snapshots to speed up the process). @ref:[Event sourcing](../typed/persistence.md#event-sourcing-concepts) is supported by
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snapshots to speed up the process). @ref:[Event Sourcing](../typed/persistence.md#event-sourcing-concepts) is supported by
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Akka Persistence.
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### Mailbox with Explicit Acknowledgement
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@ -197,7 +197,7 @@ Java
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## Performance and denormalization
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When building systems using @ref:[Event sourcing](typed/persistence.md#event-sourcing-concepts) and CQRS ([Command & Query Responsibility Segregation](https://docs.microsoft.com/en-us/previous-versions/msp-n-p/jj554200%28v=pandp.10%29)) techniques
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When building systems using @ref:[Event Sourcing](typed/persistence.md#event-sourcing-concepts) and CQRS ([Command & Query Responsibility Segregation](https://docs.microsoft.com/en-us/previous-versions/msp-n-p/jj554200%28v=pandp.10%29)) techniques
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it is tremendously important to realise that the write-side has completely different needs from the read-side,
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and separating those concerns into datastores that are optimised for either side makes it possible to offer the best
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experience for the write and read sides independently.
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@ -1,5 +1,5 @@
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---
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project.description: Akka Persistence Classic, event sourcing with Akka, At-Least-Once delivery, snapshots, recovery and replay with Akka actors.
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project.description: Akka Persistence Classic, Event Sourcing with Akka, At-Least-Once delivery, snapshots, recovery and replay with Akka actors.
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---
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# Classic Persistence
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@ -44,12 +44,12 @@ Replicated journals are available as [Community plugins](https://akka.io/communi
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* *Snapshot store*: A snapshot store persists snapshots of a persistent actor's state. Snapshots are
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used for optimizing recovery times. The storage backend of a snapshot store is pluggable.
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The persistence extension comes with a "local" snapshot storage plugin, which writes to the local filesystem. Replicated snapshot stores are available as [Community plugins](https://akka.io/community/)
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* *Event sourcing*. Based on the building blocks described above, Akka persistence provides abstractions for the
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development of event sourced applications (see section @ref:[Event sourcing](typed/persistence.md#event-sourcing-concepts)).
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* *Event Sourcing*. Based on the building blocks described above, Akka persistence provides abstractions for the
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development of event sourced applications (see section @ref:[Event Sourcing](typed/persistence.md#event-sourcing-concepts)).
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## Example
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Akka persistence supports event sourcing with the @scala[`PersistentActor` trait]@java[`AbstractPersistentActor` abstract class]. An actor that extends this @scala[trait]@java[class] uses the
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Akka persistence supports Event Sourcing with the @scala[`PersistentActor` trait]@java[`AbstractPersistentActor` abstract class]. An actor that extends this @scala[trait]@java[class] uses the
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`persist` method to persist and handle events. The behavior of @scala[a `PersistentActor`]@java[an `AbstractPersistentActor`]
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is defined by implementing @scala[`receiveRecover`]@java[`createReceiveRecover`] and @scala[`receiveCommand`]@java[`createReceive`]. This is demonstrated in the following example.
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@ -453,7 +453,7 @@ timer-based which keeps latencies at a minimum.
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It is possible to delete all messages (journaled by a single persistent actor) up to a specified sequence number;
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Persistent actors may call the `deleteMessages` method to this end.
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Deleting messages in event sourcing based applications is typically either not used at all, or used in conjunction with
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Deleting messages in Event Sourcing based applications is typically either not used at all, or used in conjunction with
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[snapshotting](#snapshots), i.e. after a snapshot has been successfully stored, a `deleteMessages(toSequenceNr)`
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up until the sequence number of the data held by that snapshot can be issued to safely delete the previous events
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while still having access to the accumulated state during replays - by loading the snapshot.
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@ -750,7 +750,7 @@ configuration key. The method can be overridden by implementation classes to ret
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## Event Adapters
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In long running projects using event sourcing sometimes the need arises to detach the data model from the domain model
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In long running projects using Event Sourcing sometimes the need arises to detach the data model from the domain model
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completely.
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Event Adapters help in situations where:
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@ -388,7 +388,7 @@ Links to reference documentation:
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The correspondence of the classic `PersistentActor` is @scala[`akka.persistence.typed.scaladsl.EventSourcedBehavior`]@java[`akka.persistence.typed.javadsl.EventSourcedBehavior`].
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The Typed API is much more guided to facilitate event sourcing best practises. It also has tighter integration with
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The Typed API is much more guided to facilitate Event Sourcing best practices. It also has tighter integration with
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Cluster Sharding.
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Links to reference documentation:
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@ -103,9 +103,9 @@ Java
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## Event deletion
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Deleting events in event sourcing based applications is typically either not used at all, or used in conjunction with snapshotting.
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Deleting events in Event Sourcing based applications is typically either not used at all, or used in conjunction with snapshotting.
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By deleting events you will lose the history of how the system changed before it reached current state, which is
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one of the main reasons for using event sourcing in the first place.
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one of the main reasons for using Event Sourcing in the first place.
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If snapshot-based retention is enabled, after a snapshot has been successfully stored, a delete of the events
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(journaled by a single event sourced actor) up until the sequence number of the data held by that snapshot can be issued.
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@ -47,7 +47,7 @@ provides tools to facilitate in building GDPR capable systems.
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@@@
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### Event sourcing concepts
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### Event Sourcing concepts
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See an [introduction to Event Sourcing](https://docs.microsoft.com/en-us/previous-versions/msp-n-p/jj591559%28v=pandp.10%29) at MSDN.
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@ -8,7 +8,7 @@ warning or deprecation period. It is also not recommended to use this module in
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@@@
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@ref[Event sourcing](./persistence.md) with `EventSourcedBehavior`s is based on the single writer principle, which means that there can only be one active instance of a `EventSourcedBehavior`
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@ref[Event Sourcing](./persistence.md) with `EventSourcedBehavior`s is based on the single writer principle, which means that there can only be one active instance of a `EventSourcedBehavior`
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with a given `persistenceId`. Otherwise, multiple instances would store interleaving events based on different states, and when these events would later be replayed it would not be possible to reconstruct the correct state.
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This restriction means that in the event of network partitions, and for a short time during rolling re-deploys, some
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@ -421,7 +421,7 @@ For a snapshot plugin to support replication it needs to store and read metadata
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To attach the metadata when reading the snapshot the `akka.persistence.SnapshotMetadata.apply` factory overload taking a `metadata` parameter is used.
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The @apidoc[SnapshotStoreSpec] in the Persistence TCK provides a capability flag `supportsMetadata` to toggle verification that metadata is handled correctly.
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The following plugins support replicated event sourcing:
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The following plugins support Replicated Event Sourcing:
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* [Akka Persistence Cassandra](https://doc.akka.io/docs/akka-persistence-cassandra/current/index.html) versions 1.0.3+
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* [Akka Persistence Spanner](https://doc.akka.io/docs/akka-persistence-spanner/current/overview.html) versions 1.0.0-RC4+
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@ -26,7 +26,7 @@ import akka.util.JavaDurationConverters._
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/**
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* [[DurableProducerQueue]] that can be used with [[akka.actor.typed.delivery.ProducerController]]
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* for reliable delivery of messages. It is implemented with event sourcing and stores one
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* for reliable delivery of messages. It is implemented with Event Sourcing and stores one
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* event before sending the message to the destination and one event for the confirmation
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* that the message has been delivered and processed.
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*
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@ -160,7 +160,7 @@ final class DiscardConfigurator extends StashOverflowStrategyConfigurator {
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}
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/**
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* Scala API: A persistent Actor - can be used to implement command or event sourcing.
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* Scala API: A persistent Actor - can be used to implement command or Event Sourcing.
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*/
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trait PersistentActor extends Eventsourced with PersistenceIdentity {
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def receive = receiveCommand
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@ -290,7 +290,7 @@ trait PersistentActor extends Eventsourced with PersistenceIdentity {
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}
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/**
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* Java API: an persistent actor - can be used to implement command or event sourcing.
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* Java API: an persistent actor - can be used to implement command or Event Sourcing.
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*/
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abstract class AbstractPersistentActor extends AbstractActor with AbstractPersistentActorLike {
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