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Normalize Event Sourcing wording #29577 (#29856)

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Josep Prat 2020-12-07 08:41:43 +01:00 • committed by GitHub
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2
akka-cluster-sharding-typed/src/main/scala/akka/cluster/sharding/typed/ReplicatedShardingExtension.scala
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@ -56,7 +56,7 @@ trait ReplicatedShardingExtension extends Extension {
} }
/** /**
* Represents the sharding instances for the replicas of one replicated event sourcing entity type * Represents the sharding instances for the replicas of one Replicated Event Sourcing entity type
* *
* Not for user extension. * Not for user extension.
*/ */

2
akka-cluster-sharding-typed/src/test/scala/akka/cluster/sharding/typed/ReplicatedShardingDirectReplicationSpec.scala
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@ -75,7 +75,7 @@ class ReplicatedShardingDirectReplicationSpec extends ScalaTestWithActorTestKit
replicaAProbe.expectNoMessage() replicaAProbe.expectNoMessage()
} }
"ignore messages not from replicated event sourcing" in { "ignore messages not from Replicated Event Sourcing" in {
val replicaAProbe = createTestProbe[ShardingEnvelope[PublishedEvent]]() val replicaAProbe = createTestProbe[ShardingEnvelope[PublishedEvent]]()
val replicationActor = spawn( val replicationActor = spawn(

2
akka-cluster-sharding/src/main/scala/akka/cluster/sharding/ShardCoordinator.scala
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@ -1191,7 +1191,7 @@ abstract class ShardCoordinator(
/** /**
* Singleton coordinator that decides where to allocate shards. * Singleton coordinator that decides where to allocate shards.
* *
* Users can migrate to using DData to store state then either event sourcing or ddata to store * Users can migrate to using DData to store state then either Event Sourcing or ddata to store
* the remembered entities. * the remembered entities.
* *
* @see [[ClusterSharding$ ClusterSharding extension]] * @see [[ClusterSharding$ ClusterSharding extension]]

2
akka-docs/src/main/paradox/cluster-sharding.md
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@ -31,7 +31,7 @@ Scala
Java Java
: @@snip [ClusterShardingTest.java](/akka-docs/src/test/java/jdocs/sharding/ClusterShardingTest.java) { #counter-actor } : @@snip [ClusterShardingTest.java](/akka-docs/src/test/java/jdocs/sharding/ClusterShardingTest.java) { #counter-actor }
The above actor uses event sourcing and the support provided in @scala[`PersistentActor`] @java[`AbstractPersistentActor`] to store its state. The above actor uses Event Sourcing and the support provided in @scala[`PersistentActor`] @java[`AbstractPersistentActor`] to store its state.
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 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
its state if it is valuable. its state if it is valuable.

5
akka-docs/src/main/paradox/general/message-delivery-reliability.md
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@ -129,7 +129,6 @@ This means that:
5. `A2` can see messages from `A1` interleaved with messages from `A3` 5. `A2` can see messages from `A1` interleaved with messages from `A3`
6. Since there is no guaranteed delivery, any of the messages may be dropped, i.e. not arrive at `A2` 6. Since there is no guaranteed delivery, any of the messages may be dropped, i.e. not arrive at `A2`
@@@ note @@@ note
It is important to note that Akka’s guarantee applies to the order in which It is important to note that Akka’s guarantee applies to the order in which
@ -288,7 +287,7 @@ idempotent on the level of the business logic.
### Event Sourcing ### Event Sourcing
Event sourcing (and sharding) is what makes large websites scale to Event Sourcing (and sharding) is what makes large websites scale to
billions of users, and the idea is quite simple: when a component (think actor) billions of users, and the idea is quite simple: when a component (think actor)
processes a command it will generate a list of events representing the effect processes a command it will generate a list of events representing the effect
of the command. These events are stored in addition to being applied to the of the command. These events are stored in addition to being applied to the
@ -299,7 +298,7 @@ components may consume the event stream as a means to replicate the component’
state on a different continent or to react to changes). If the component’s state on a different continent or to react to changes). If the component’s
state is lost—due to a machine failure or by being pushed out of a cache—it can state is lost—due to a machine failure or by being pushed out of a cache—it can
be reconstructed by replaying the event stream (usually employing be reconstructed by replaying the event stream (usually employing
snapshots to speed up the process). @ref:[Event sourcing](../typed/persistence.md#event-sourcing-concepts) is supported by snapshots to speed up the process). @ref:[Event Sourcing](../typed/persistence.md#event-sourcing-concepts) is supported by
Akka Persistence. Akka Persistence.
### Mailbox with Explicit Acknowledgement ### Mailbox with Explicit Acknowledgement

2
akka-docs/src/main/paradox/persistence-query.md
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@ -197,7 +197,7 @@ Java
## Performance and denormalization ## Performance and denormalization
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 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
it is tremendously important to realise that the write-side has completely different needs from the read-side, it is tremendously important to realise that the write-side has completely different needs from the read-side,
and separating those concerns into datastores that are optimised for either side makes it possible to offer the best and separating those concerns into datastores that are optimised for either side makes it possible to offer the best
experience for the write and read sides independently. experience for the write and read sides independently.

12
akka-docs/src/main/paradox/persistence.md
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@ -1,5 +1,5 @@
--- ---
project.description: Akka Persistence Classic, event sourcing with Akka, At-Least-Once delivery, snapshots, recovery and replay with Akka actors. project.description: Akka Persistence Classic, Event Sourcing with Akka, At-Least-Once delivery, snapshots, recovery and replay with Akka actors.
--- ---
# Classic Persistence # Classic Persistence
@ -44,12 +44,12 @@ Replicated journals are available as [Community plugins](https://akka.io/communi
* *Snapshot store*: A snapshot store persists snapshots of a persistent actor's state. Snapshots are * *Snapshot store*: A snapshot store persists snapshots of a persistent actor's state. Snapshots are
used for optimizing recovery times. The storage backend of a snapshot store is pluggable. 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](https://akka.io/community/) 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/)
* *Event sourcing*. Based on the building blocks described above, Akka persistence provides abstractions for the * *Event Sourcing*. Based on the building blocks described above, Akka persistence provides abstractions for the
development of event sourced applications (see section @ref:[Event sourcing](typed/persistence.md#event-sourcing-concepts)). development of event sourced applications (see section @ref:[Event Sourcing](typed/persistence.md#event-sourcing-concepts)).
## Example ## Example
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 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
`persist` method to persist and handle events. The behavior of @scala[a `PersistentActor`]@java[an `AbstractPersistentActor`] `persist` method to persist and handle events. The behavior of @scala[a `PersistentActor`]@java[an `AbstractPersistentActor`]
is defined by implementing @scala[`receiveRecover`]@java[`createReceiveRecover`] and @scala[`receiveCommand`]@java[`createReceive`]. This is demonstrated in the following example. is defined by implementing @scala[`receiveRecover`]@java[`createReceiveRecover`] and @scala[`receiveCommand`]@java[`createReceive`]. This is demonstrated in the following example.
@ -453,7 +453,7 @@ timer-based which keeps latencies at a minimum.
It is possible to delete all messages (journaled by a single persistent actor) up to a specified sequence number; 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. 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 Deleting messages in Event Sourcing based applications is typically either not used at all, or used in conjunction with
[snapshotting](#snapshots), i.e. after a snapshot has been successfully stored, a `deleteMessages(toSequenceNr)` [snapshotting](#snapshots), 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 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. while still having access to the accumulated state during replays - by loading the snapshot.
@ -750,7 +750,7 @@ configuration key. The method can be overridden by implementation classes to ret
## Event Adapters ## Event Adapters
In long running projects using event sourcing sometimes the need arises to detach the data model from the domain model In long running projects using Event Sourcing sometimes the need arises to detach the data model from the domain model
completely. completely.
Event Adapters help in situations where: Event Adapters help in situations where:

2
akka-docs/src/main/paradox/typed/from-classic.md
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@ -388,7 +388,7 @@ Links to reference documentation:
The correspondence of the classic `PersistentActor` is @scala[`akka.persistence.typed.scaladsl.EventSourcedBehavior`]@java[`akka.persistence.typed.javadsl.EventSourcedBehavior`]. The correspondence of the classic `PersistentActor` is @scala[`akka.persistence.typed.scaladsl.EventSourcedBehavior`]@java[`akka.persistence.typed.javadsl.EventSourcedBehavior`].
The Typed API is much more guided to facilitate event sourcing best practises. It also has tighter integration with The Typed API is much more guided to facilitate Event Sourcing best practices. It also has tighter integration with
Cluster Sharding. Cluster Sharding.
Links to reference documentation: Links to reference documentation:

4
akka-docs/src/main/paradox/typed/persistence-snapshot.md
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@ -103,9 +103,9 @@ Java
## Event deletion ## Event deletion
Deleting events in event sourcing based applications is typically either not used at all, or used in conjunction with snapshotting. Deleting events in Event Sourcing based applications is typically either not used at all, or used in conjunction with snapshotting.
By deleting events you will lose the history of how the system changed before it reached current state, which is By deleting events you will lose the history of how the system changed before it reached current state, which is
one of the main reasons for using event sourcing in the first place. one of the main reasons for using Event Sourcing in the first place.
If snapshot-based retention is enabled, after a snapshot has been successfully stored, a delete of the events If snapshot-based retention is enabled, after a snapshot has been successfully stored, a delete of the events
(journaled by a single event sourced actor) up until the sequence number of the data held by that snapshot can be issued. (journaled by a single event sourced actor) up until the sequence number of the data held by that snapshot can be issued.

2
akka-docs/src/main/paradox/typed/persistence.md
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@ -47,7 +47,7 @@ provides tools to facilitate in building GDPR capable systems.
@@@ @@@
### Event sourcing concepts ### Event Sourcing concepts
See an [introduction to Event Sourcing](https://docs.microsoft.com/en-us/previous-versions/msp-n-p/jj591559%28v=pandp.10%29) at MSDN. See an [introduction to Event Sourcing](https://docs.microsoft.com/en-us/previous-versions/msp-n-p/jj591559%28v=pandp.10%29) at MSDN.

4
akka-docs/src/main/paradox/typed/replicated-eventsourcing.md
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@ -8,7 +8,7 @@ warning or deprecation period. It is also not recommended to use this module in
@@@ @@@
@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` @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`
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. 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.
This restriction means that in the event of network partitions, and for a short time during rolling re-deploys, some This restriction means that in the event of network partitions, and for a short time during rolling re-deploys, some
@ -421,7 +421,7 @@ For a snapshot plugin to support replication it needs to store and read metadata
To attach the metadata when reading the snapshot the `akka.persistence.SnapshotMetadata.apply` factory overload taking a `metadata` parameter is used. To attach the metadata when reading the snapshot the `akka.persistence.SnapshotMetadata.apply` factory overload taking a `metadata` parameter is used.
The @apidoc[SnapshotStoreSpec] in the Persistence TCK provides a capability flag `supportsMetadata` to toggle verification that metadata is handled correctly. The @apidoc[SnapshotStoreSpec] in the Persistence TCK provides a capability flag `supportsMetadata` to toggle verification that metadata is handled correctly.
The following plugins support replicated event sourcing: The following plugins support Replicated Event Sourcing:
* [Akka Persistence Cassandra](https://doc.akka.io/docs/akka-persistence-cassandra/current/index.html) versions 1.0.3+ * [Akka Persistence Cassandra](https://doc.akka.io/docs/akka-persistence-cassandra/current/index.html) versions 1.0.3+
* [Akka Persistence Spanner](https://doc.akka.io/docs/akka-persistence-spanner/current/overview.html) versions 1.0.0-RC4+ * [Akka Persistence Spanner](https://doc.akka.io/docs/akka-persistence-spanner/current/overview.html) versions 1.0.0-RC4+

2
akka-persistence-typed/src/main/scala/akka/persistence/typed/delivery/EventSourcedProducerQueue.scala
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@ -26,7 +26,7 @@ import akka.util.JavaDurationConverters._
/** /**
* [[DurableProducerQueue]] that can be used with [[akka.actor.typed.delivery.ProducerController]] * [[DurableProducerQueue]] that can be used with [[akka.actor.typed.delivery.ProducerController]]
* for reliable delivery of messages. It is implemented with event sourcing and stores one * for reliable delivery of messages. It is implemented with Event Sourcing and stores one
* event before sending the message to the destination and one event for the confirmation * event before sending the message to the destination and one event for the confirmation
* that the message has been delivered and processed. * that the message has been delivered and processed.
* *

4
akka-persistence/src/main/scala/akka/persistence/PersistentActor.scala
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@ -160,7 +160,7 @@ final class DiscardConfigurator extends StashOverflowStrategyConfigurator {
} }
/** /**
* Scala API: A persistent Actor - can be used to implement command or event sourcing. * Scala API: A persistent Actor - can be used to implement command or Event Sourcing.
*/ */
trait PersistentActor extends Eventsourced with PersistenceIdentity { trait PersistentActor extends Eventsourced with PersistenceIdentity {
def receive = receiveCommand def receive = receiveCommand
@ -290,7 +290,7 @@ trait PersistentActor extends Eventsourced with PersistenceIdentity {
} }
/** /**
* Java API: an persistent actor - can be used to implement command or event sourcing. * Java API: an persistent actor - can be used to implement command or Event Sourcing.
*/ */
abstract class AbstractPersistentActor extends AbstractActor with AbstractPersistentActorLike { abstract class AbstractPersistentActor extends AbstractActor with AbstractPersistentActorLike {