The most basic implementation of the repository is AbstractRepository. It takes care of the event publishing when an aggregate is saved. The actual persistence mechanism must still be implemented. This implementation doesn't provide any locking mechanism and expects the underlying data storage mechanism to provide it.

If the underlying data store does not provide any locking mechanism to prevent concurrent modifications of aggregates, consider using the abstract LockingRepository implementation. Besides providing event dispatching logic, it will also ensure that aggregates are not concurrently modified.

You can configure the LockingRepository to use an optimistic locking strategy, or a pessimistic one. When the optimistic lock detects concurrent access, the second thread saving an aggregate will receive a ConcurrencyException. The pessimistic lock will prevent concurrent access to the aggregate alltogether. The pessimistic locking strategy is the default strategy.

Event ordering and optimistic locking strategy

Note that the optimistic lock doesn't lock any threads at all. While this reduces contention, it also means that the thread scheduler of your underlying architecture (OS, CPU, etc) is free to schedule threads as it sees fit. In high-concurrent environments (many threads accessing the same aggregate simultaneously), this could lead to events not being dispatched in exactly the same order as they are generated. If this guarantee is important, use pessimistic locking instead.

ConcurrencyException vs ConflictingModificationException

Note that there is a clear distinction between a ConcurrencyException and a ConflictingModificationException. The first is used to indicate a repository cannot save an aggregate, because the changes it contains were not applied to the latest available version. The latter indicates that the loaded aggregate contains changes that might not have been seen by the end-user. See Section 5.5, “Advanced conflict detection and resolution” for more information.

This is a repository implementation that can store JPA compatible Aggregates, such as AbstractJpaAggregateRoot subclasses. It is configured with an EntityManager to manage the actual persistence, and a class specifiying the actual type of Aggregate stored in the Repository.

The EventSourcingRepository implementation provides the basic functionality needed by any event sourcing repository in the AxonFramework. It depends on an EventStore (seeSection 5.3, “Event store implementations”), which abstracts the actual storage mechanism for the events and anAggregateFactory, which is reponsible for creating uninitialized aggregate instances.

The AggregateFactory specifies which aggregate needs to be created and how. Once an aggregate has been created, the EventSourcingRepository can initialize is using the Events it loaded from the Event Store. Axon Framework comes with a number of AggregateFactory implementations that you may use. If they do not suffice, it is very easy to create your own implementation.

Initializing aggregates based on the events can be a time-consuming effort, compared to the direct aggregate loading of the simple repository implementations. The CachingEventSourcingRepository provides a cache from which aggregates can be loaded if available. You can configure any jcache implementation with this repository. Note that this implementation can only use caching in combination with a pessimistic locking strategy.

	Note
	Using a cache with optimistic locking would create undesired side-effects. Optimistic locking allows concurrent access to objects and will only fail when two threads have concurrently made any modifications to that object. When using a cache, both threads will receive the same instance of the object. They will both apply their changes to that same instance, potentially interfering with eachother.

The GenericAggregateFactory is a special AggregateFactory implementation that can be used for any type of Event Sourced Aggregate Root. There is however, a convention that these EventSourcedAggregateRoot classes must adhere to: the type must declare an accessible constructor accepting an AggregateIdentifier as single parameter. This constructor may not perform any initialization on the aggregate, other than setting the identifier.

The GenericAggregateFactory is suitable for most scenarios where aggregates do not need special injection of non-serializable resources.

Depending on your architectural choices, it might be useful to inject dependencies into your aggregates using Spring. You could, for example, inject query repositories into your aggregate to ensure the existance (or inexistance) of certain values.

To inject dependencies into your aggregates, you need to configure a prototype bean of your aggregate root in the Spring context that also defines the SpringPrototypeAggregateFactory. Instead of creating regular instances of using a constructor, it uses the Spring Application Context to instantiate your aggregates. This will also inject any dependencies in your aggregate.

In some cases, the GenericAggregateFactory just doesn't deliver what you need. For example, you could have an abstract aggregate type with multiple implementations for different scenarios (e.g. PublicUserAccount and BackOfficeAccount both extending anAccount). Instead of creating different repositories for each of the aggregates, you could use a single repository, and configure an AggregateFactory that is aware of the different implementations.

The AggregateFactory must specify the aggregate type identifier. This is a String that the Event Store needs to figure out which events belong to which type of aggregate. Typically, this name is deducted from the abstract super-aggregate. In the given example that could be: Account.

The bulk of the work the Aggregate Factory does is creating uninitialized Aggregate instances. It must do so using a given aggregate identifier and the first Event from the stream. Usually, this Event is a creation event which contains hints about the expected type of aggregate. You can use this information to choose an implementation and invoke its constructor. Make sure no Events are applied by that constructor; the aggregate must be uninitialized.

The HybridJpaRepository is a combination of the GenericJpaRepository and an Event Sourcing repository. It can only deal with event sourced aggregates, and stores them in a relational model as well as in an event store. When the repository reads an aggregate back in, it uses the relational model exclusively.

This repository removes the need for Event Upcasters, making data migrations potentially easier. Since the aggregates are event sourced, you keep the ability to use the given-when-then test fixtures (seeChapter 8, Testing). On the other hand, since it doesn't use the event store for reading, it doesn't allow for automated conflict resolution.

The FileSystemEventStore stores the events in a file on the file system. It provides good performance and easy configuration. The downside of this event store is that is does not provide transaction support and doesn't cluster very well. The only configuration needed is the location where the event store may store its files and the serializer to use to actually serialize and deserialize the events. Note that the provided url must end on a slash. This is due to the way Spring's Resource implementations work.

The JpaEventStore stores events in a JPA-compatible data source. Unlike the file system version, the JPAEventStore supports transactions. The JPA Event Store stores events in so called entries. These entries contain the serialized form of an event, as well as some fields where meta-data is stored for fast lookup of these entries. To use the JpaEventStore, you must have the javax.persistence annotations on your classpath.

By default, the event store needs you to configure your persistence context (defined in META-INF/persistence.xml file) to contain the classes DomainEventEntry and SnapshotEventEntry (both in the org.axonframework.eventstore.jpa package).

Below is an example configuration of a persistence context configuration:

<persistence xmlns="http://java.sun.com/xml/ns/persistence" version="1.0">
    <persistence-unit name="eventStore" transaction-type="RESOURCE_LOCAL">
        <class>org...eventstore.jpa.DomainEventEntry</class> 
        <class>org...eventstore.jpa.SnapshotEventEntry</class>
    </persistence-unit>
</persistence>

Detecting duplicate key violations in the database

Axon uses Locking to prevent two threads from accessing the same Aggregate. However, if you have multiple JVMs on the same database, this won't help you. In that case, you'd have to rely on the database to detect conflicts. Concurrent access to the event store will result in a Key Constraint Violation, as the table only allows a single Event for an aggregate with any sequence number. Inserting a second event for an existing aggregate with an existing sequence number will result in an error. The JPA EventStore can detect this error and translate it to a ConcurrencyException. However, each database system reports this violation differently. If you register your DataSource with the JpaEventStore, it will try to detect the type of database and figure out which error codes represent a Key Constraint Violation. Alternatively, you may provide a PersistenceExceptionTranslator instance, which can tell if a given exception represents a Key Constraint Violation. If no DataSource or PersistenceExceptionTranslator is provided, exceptions from the Database driver are thrown as-is.

By default, the JPA Event Store stores entries in DomainEventEntry and SnapshotEventEntry entities. While still will suffice in many cases, you might encounter a situation where the meta-data provided by these entities is not enough. Or you might want to store events of different aggregate types in different tables.

If that is the case, you may provide your own implementation of EventEntryStore in the JPA Event Store's constructor. You will need to provide implementations of methods that load and store serialized events. Check the API Documentation of the EventEntryStore class for implementation requirements.

Memory consumption warning

Note that persistence providers, such as Hibernate, use a first-level cache on their EntityManager implementation. Typically, this means that all entities used or returned in queries are attached to the EntityManager. They are only cleared when the surrounding transaction is committed or an explicit "clear" in performed inside the transaction. To work around this issue, make sure to exclusively query the serialized form (the byte[]) of events. Do not fetch the entire entity object. Alternatively, call EntityManager.flush() and EntityManager.clear() after fetching a batch of events. Failure to do so might result in OutOfMemoryExceptions when loading large streams of events.

If you have specific requirements for an event store, it is quite easy to implement one using different underlying data sources. Reading and appending events is done using a DomainEventStream, which is quite similar to iterator implementations.

	Tip
	The SimpleDomainEventStream class will make the contents of a sequence ( List or array) of DomainEvent instances accessible as event stream.

Event Stores need a way to serialize the Domain Event to prepare it for storage. By default, Axon uses the XStreamEventSerializer, which uses XStream (see xstream.codehaus.org) to serialize Domain Events into XML and vice versa. XStream is reasonably fast and is more flexible than Java Serialization. Furthermore, the result of XStream serialization is human readable. Quite useful for logging and debugging purposes.

The XStreamEventSerializer can be configured. You can define aliases it should use for certain packages, classes or even fields. Besides being a nice way to shorten potentially long names, aliases can also be used when class definitions of event change. For more information about aliases, visit the XStream website: xstream.codehaus.org.

You may also implement your own Event Serializer, simply by creating a class that implements Serializer, and configuring the Event Store to use that implementation instead of the default.

It is not unlikely that a definition of an Event remains unchanged during the entire lifespan of an application. New insights, changes in requirements and many other factors can lead to modifications in Events. Since the Event Store is considered a read and append-only data source, your application must be able to read all events, regardless of when they have been added.

In Axon, Events have a revision, a numeric value that defaults to 0. If an Event definition changes, you should update the revision number too. The deserialization process can then be adapted when your application needs to cope with old revisions of events. A class file for an Event only needs to support the latest revision. When old revisions are deserialized, they can be "upcasted" to the newer revision. The revision number of an Event is provided to the constructor on the abstract event classes. The revision of an event is passed as a parameter in the constructor of DomainEvent.

The EventUpcaster is responsible for transforming old events into the last revision. Upcasters typically work on an intermediate representation of the Event. In the case of the XStreamEventSerializater, this intermediate representation is dom4j (see http://dom4j.sourceforge.net/), an easy to use java XML library that integrates nicely with XStream. The EventUpcaster can modify the XML structure of the event so that it matches the new definition.