Documentation

The documentation on this page is always for the latest version of Occurrent, currently 0.19.7.

Introduction

Occurrent is an event sourcing library, or if you wish, a set of event sourcing utilities for the JVM, created by Johan Haleby. There are many options for doing event sourcing in Java already so why build another one? There are a few reasons for this besides the intrinsic joy of doing something yourself:

• You should be able to design your domain model without any dependencies to Occurrent or any other library. Your domain model can be expressed with pure functions that returns events. Use Occurrent to store these events. This is a very important design decision! Many people talk about doing this, but I find it rare in practise, and some existing event sourcing frameworks makes this difficult or non-idiomatic.
• Simple: Pick only the libraries you need, no need for an all or nothing solution. If you don’t need subscriptions, then don’t use them! Use the infrastructure that you already have and hook these into Occurrent.
• Occurrent is not a database by itself. The goal is to be a thin wrapper around existing commodity databases that you may already be familiar with.
• Events are stored in a standard format (cloud events). You are responsible for serializing/deserializing the cloud events “body” (data) yourself. While this may seem like a limitation at first, why not just serialize your POJO directly to arbitrary JSON like you’re used to?, it really enables a lot of use cases and peace of mind. For example:
  • It should be possible to hook in various standard components into Occurrent that understands cloud events. For example a component could visualize a distributed tracing graph from the cloud events if using the distributed tracing cloud event extension.
  • Since the current idea is to be as close as possible to the specification even in the database,
    you can use the database to your advantage. For example, you can create custom indexes used for fast and fully consistent domain queries directly on an event stream (or even multiple streams).
• Composable: Function composition and pipes are encouraged. For example pipe the event stream to a rehydration function (any function that converts a stream of events to current state) before calling your domain model.
• Pragmatic: Need consistent projections? You can decide to write projections and events transactionally using tools you already know (such as Spring @Transactional)!
• Interoperable/Portable: Cloud events is a CNCF specification for describing event data in a common way. CloudEvents seeks to dramatically simplify event declaration and delivery across services, platforms, and beyond!
• Use the Occurrent components as lego bricks to compose your own pipelines. Components are designed to be small so that you should be able to re-write them tailored to your own needs if required. Missing a component? You should be able to write one yourself and hook into the rest of the eco-system. Write your own problem/domain specific layer on-top of Occurrent.

Concepts

Event Sourcing

Every system needs to store and update data somehow. Many times this is done by storing the current state of an entity in the database. For example, you might have an entity called Order stored in a order table in a relational database. Everytime something happens to the order, the table is updated with the new information and replacing the previous values. Event Sourcing is a technique that instead stores the changes, represented by events, that occurred for the entity. Events are facts, things that have happened, and they should never be updated. This means that not only can you derive the current state from the set of historic events, but you also know which steps that were involved to reach the current state.

CloudEvents

Cloud events is a CNCF specification for describing event data in a common way. CloudEvents seeks to dramatically simplify event declaration and delivery across services, platforms, and beyond. In Occurrent, you don’t persist your domain events directly to an event store, instead you convert them to a cloud event. You may regard a CloudEvent as a standardized envelope around the data in your domain event.

In practice, this means that instead of storing events in a proprietary or arbitrary format, Occurrent, stores events in accordance with the cloud event specification, even at the data-store level. I.e. you know the structure of your events, even in the database that the event store uses. It’s up to you as a user of the library to convert your domain events into cloud events when writing to the event store. This is extremely powerful, not only does it allow you to design your domains event in any way you find fit (for example without compromises enforced by a JSON serialization library) but it also allows for easier migration, data consistency and features such as (fully-consistent) queries to the event store for certain use cases. A cloud event is made-up by a set of pre-defined attributes described in the cloud event specification. In the context of event sourcing, we can leverage these attributes in the way suggested below:

Note that the table above is to be regarded as a rule of thumb, it’s ok to map things differently if it’s better suited for your application, but it’s a good idea to keep things consistent throughout your organization. To see an example of how this may look in code, refer to the application service documentation.

Occurrent CloudEvent Extensions

Occurrent automatically adds two extension attributes to each cloud event written to the event store:

These are required for Occurrent to operate. A long-term goal of Occurrent is to come up with a standardized set of cloud event extensions that are agreed upon and used by several different vendors.

In the meantime, it’s quite possible that Occurrent will provide a wider set of optional extensions in the future (such as correlation id and/or sequence number). But for now, it’s up to you as a user to add these if you need them (see CloudEvent Metadata), you would typically do this by creating or extending/wrapping an already existing application service.

CloudEvent Metadata

You can specify metadata to the cloud event by making use of extension attributes. This is the place to add things such as sequence number, correlation id, causation id etc. Actually there’s already a standard way of applying distributed tracing and sequence number generation extensions to cloud events that might be of interest.

EventStore

The event store is a place where you store events. Events are immutable pieces of data describing state changes for a particular stream. A stream is a collection of events that are related, typically but not limited to, a particular entity. For example a stream may include all events for a particular instance of a game or an order.

Occurrent provides an interface, EventStore, that allows to read and write events from the database. The EventStore interface is actually composed of various smaller interfaces since not all databases supports all aspects provided by the EventStore interface. Here’s an example that writes a cloud event to the event store and read it back:

CloudEvent event = CloudEventBuilder.v1()
                    .withId("eventId")
                    .withSource(URI.create("urn:mydomain"))
                    .withType("HelloWorld")
                    .withTime(LocalDateTime.now().atOffset(ZoneOffset.UTC))
                    .withSubject("subject")
                    .withDataContentType("application/json")
                    .withData("{ \"message\" : \"hello\" }".getBytes(StandardCharsets.UTF_8))
                    .build();

// Write                    
eventStore.write("streamId", Stream.of(event));

// Read
EventStream<CloudEvent> eventStream = eventStore.read("streamId");

val event = CloudEventBuilder.v1()
                    .withId("eventId")
                    .withSource(URI.create("urn:mydomain"))
                    .withType("HelloWorld")
                    .withTime(LocalDateTime.now().atOffset(ZoneOffset.UTC))
                    .withSubject("subject")
                    .withDataContentType("application/json")
                    .withData("{ \"message\" : \"hello\" }".toByteArray())
                    .build();

// Write                    
eventStore.write("streamId", Stream.of(event))

// Read
val eventStream : EventStream<CloudEvent> = eventStore.read("streamId")

Note that when reading the events, the EventStore won’t simply return a Stream of CloudEvent’s, instead it returns a wrapper called EventStream.

EventStream

The EventStream contains the CloudEvent’s for a stream and the version of the stream. The version can be used to guarantee that only one thread/process is allowed to write to the stream at the same time, i.e. optimistic locking. This can be achieved by including the version in a write condition.

Note that reading a stream that doesn’t exist (e.g. eventStore.read("non-existing-id") will return an instance of EventStream with an empty stream of events and 0 as version number. The reason for this is that you can use the same “application service” (a fancy word for a piece of code that loads events from the event store, applies them to the domain model and writes the new events returned to the event store) for both entity creation and subsequent use cases. For example consider this simple domain model:

public class WordGuessingGame {
	public static Stream<CloudEvent> startNewGame(String gameId, String wordToGuess) {	
		...
	}

	public static Stream<CloudEvent> guessWord(Stream<CloudEvent> eventStream, String word) {
		...
	}
}

// Note that the functions could might as well be placed directly in a package 
 object WordGuessingGame {
    fun startNewGame(gameId : String, wordToGuess : String) : Stream<CloudEvent> = ...	
 
    fun guessWord(eventStream : Stream<CloudEvent>, word : String) : Stream<CloudEvent> = ...
 }

Then we could write a generic application service that takes a higher-order function (Stream<CloudEvent>) -> Stream<CloudEvent>:

public class ApplicationService {

    private final EventStore eventStore;

    public ApplicationService(EventStore eventStore) {
        this.eventStore = eventStore;
    }

    public void execute(String streamId, Function<Stream<CloudEvent>, Stream<CloudEvent>> functionThatCallsDomainModel) {
        // Read all events from the event store for a particular stream
        EventStream<CloudEvent> eventStream = eventStore.read(streamId);

        // Invoke the domain model  
        Stream<CloudEvent> newEvents = functionThatCallsDomainModel.apply(eventStream.events());

        // Persist the new events  
        eventStore.write(streamId, eventStream.version(), newEvents);
    }
}

class ApplicationService constructor (val eventStore : EventStore) {

    fun execute(streamId : String, functionThatCallsDomainModel : (Stream<CloudEvent>) -> Stream<CloudEvent>) {
        // Read all events from the event store for a particular stream
        val  eventStream : EventStream<CloudEvent> = eventStore.read(streamId)
        
         // Invoke the domain model 
        val newEvents = functionThatCallsDomainModel(eventStream.events())

        // Persist the new events
        eventStore.write(streamId, eventStream.version(), newEvents)
    }
}

You could then call the application service like this regardless of you’re starting a new game or not:

// Here we image that we have received the data required to start a new game, e.g. from a REST endpoint. 
String gameId = ...
String wordToGuess = ...;

// Then we invoke the application service to start a game:
applicationService.execute(gameId, __ -> WordGuessingGame.startNewGame(gameId, wordToGuess));  

// Later a player guess a word:
String gameId = ...
String guess = ...;

// We thus invoke the application service again to guess the word:
applicationService.execute(gameId, events -> WordGuessingGame.guessWord(events, gameId, guess));

// Here we image that we have received the data required to start a new game, e.g. from a REST endpoint. 
val gameId : String = ...
val wordToGuess : String = ...;

// Then we invoke the application service to start a game:
applicationService.execute(gameId) { 
    WordGuessingGame.startNewGame(gameId, wordToGuess)
}  

// Later a player guess a word:
val gameId : String = ...
val guess : String = ...;

// We thus invoke the application service again to guess the word:
applicationService.execute(gameId, events -> WordGuessingGame.guessWord(events, gameId, guess));

Writing application services like this is both powerful and simple (once you get used to it). There’s less need for explicit commands and command handlers (the application service is a kind of command handler). You can also use other functional techniques such as partial application to make the code look, arguably, even nicer. It’s also easy to compose several calls to the domain model into one by using standard functional composition techniques. For example in this case you might consider both starting a game and let the player make her first guess from a single request to the REST API. No need to change the domain model to do this, just use function composition.

Write Condition

A “write condition” can be used to specify conditional writes to the event store. Typically, the purpose of this would be to achieve optimistic concurrency control (optimistic locking) of an event stream.

For example, image you have an Account to which you can deposit and withdraw money. A business rule says that it’s not allowed to have a negative balance on an account. Now imagine an account that is shared between two persons and contains 20 EUR. Person “A” wants to withdraw 15 EUR and person “B” wants to withdraw 10 EUR. If they try to do this, an error message should be presented to one of them since the account balance would be negative. But what happens if both persons try to withdraw the money at the same time? Let’s have a look:

// Person A at _time 1_
EventStream<CloudEvent> eventStream = eventStore.read("account1"); // A

// "withdraw" is a pure function in the Account domain model which takes a Stream
//  of all current events and the amount to withdraw, and returns new events. 
// In this case, a "MoneyWasWithdrawn" event is returned,  since 15 EUR is OK to withdraw.     
Stream<CloudEvent> events = Account.withdraw(eventStream.events(), Money.of(15, EUR));

// We write the new events to the event store  
eventStore.write("account1", events);

// Now in a different thread let's imagine Person B at _time 1_
EventStream<CloudEvent> eventStream = eventStore.read("account1"); // B

// Again we want to withdraw money, and the system will think this is OK, 
// since event streams for A and B has not yet recorded that the balance is negative.   
Stream<CloudEvent> events = Account.withdraw(eventStream.events(), Money.of(10, EUR));

// We write the new events to the event store without any problems! 😱 
// But this shouldn't work since it would violate the business rule!   
eventStore.write("account1", events);

// Person A at _time 1_
val eventStream = eventStore.read("account1") // A

// "withdraw" is a pure function in the Account domain model which takes a Stream
//  of all current events and the amount to withdraw. It returns a stream of 
// new events, in this case only a "MoneyWasWithdrawn" event,  since 15 EUR is OK to withdraw.     
val events = Account.withdraw(eventStream.events(), Money.of(15, EUR))

// We write the new events to the event store  
eventStore.write("account1", events)

// Now in a different thread let's imagine Person B at _time 1_
val eventStream = eventStore.read("account1") // B

// Again we want to withdraw money, and the system will think this is OK, 
// since the Account thinks that 10 EUR will have a balance of 10 EUR after 
// the withdrawal.   
val events = Account.withdraw(eventStream.events(), Money.of(10, EUR))

// We write the new events to the event store without any problems! 😱 
// But this shouldn't work since it would violate the business rule!   
eventStore.write("account1", events)

To avoid the problem above we want to make use of conditional writes. Let’s see how:

// Person A at _time 1_
EventStream<CloudEvent> eventStream = eventStore.read("account1"); // A
long currentVersion = eventStream.version(); 

// Withdraw money
Stream<CloudEvent> events = Account.withdraw(eventStream.events(), Money.of(15, EUR));

// We write the new events to the event store with a write condition that implies
// that the version of the event stream must be A.   
eventStore.write("account1", currentVersion, events);

// Now in a different thread let's imagine Person B at _time 1_
EventStream<CloudEvent> eventStream = eventStore.read("account1"); // A 
long currentVersion = eventStream.version();

// Again we want to withdraw money, and the system will think this is OK, 
// since event streams for A and B has not yet recorded that the balance is negative.   
Stream<CloudEvent> events = Account.withdraw(eventStream.events(), Money.of(10, EUR));

// We write the new events to the event store with a write condition that implies
// that the version of the event stream must be B. But now Occurrent will throw
// a "org.occurrent.eventstore.api.WriteConditionNotFulfilledException" since, in this
// case A was slightly faster, and the version of the event stream no longer match!
// The entire operation should be retried for person B and when "Account.withdraw(..)"
// is called again it could throw a "CannotWithdrawSinceBalanceWouldBeNegative" exception. 
eventStore.write("account1", currentVersion, events); 

// Person A at _time 1_
val eventStream = eventStore.read("account1") // A
val currentVersion = eventStream.version() 

// Withdraw money
val events = Account.withdraw(eventStream.events(), Money.of(15, EUR));

// We write the new events to the event store with a write condition that implies
// that the version of the event stream must be A.   
eventStore.write("account1", currentVersion, events)

// Now in a different thread let's imagine Person B at _time 1_
val eventStream = eventStore.read("account1"); // A 
val currentVersion = eventStream.version()

// Again we want to withdraw money, and the system will think this is OK, 
// since event streams for A and B has not yet recorded that the balance is negative.   
val events = Account.withdraw(eventStream.events(), Money.of(10, EUR))

// We write the new events to the event store with a write condition that implies
// that the version of the event stream must be B. But now Occurrent will throw
// a "org.occurrent.eventstore.api.WriteConditionNotFulfilledException" since, in this
// case A was slightly faster, and the version of the event stream no longer match!
// The entire operation should be retried for person B and when "Account.withdraw(..)"
// is called again it could throw a "CannotWithdrawSinceBalanceWouldBeNegative" exception. 
eventStore.write("account1", currentVersion, events) 

What you’ve seen above is a simple, but widely used, form of write condition. Actually, doing eventStore.write("streamId", version, events) is just a shortcut for:

eventStore.write("streamId", WriteCondition.streamVersionEq(version), events);

eventStore.write("streamId", WriteCondition.streamVersionEq(version), events)

But you can compose a more advanced write condition using a Condition:

eventStore.write("streamId", WriteCondition.streamVersion(and(lt(10), ne(5)), events);

eventStore.write("streamId", WriteCondition.streamVersion(and(lt(10), ne(5)), events)

where lt, ne and and is statically imported from org.occurrent.condition.Condition.

EventStore Queries

Since Occurrent builds on-top of existing databases it’s ok, given that you know what you’re doing*, to use the strengths of these databases. One such strength is that databases typically have good querying support. Occurrent exposes this with the EventStoreQueries interface that an EventStore implementation may implement to expose querying capabilities. For example:

OffsetDateTime lastTwoHours = OffsetDateTime.now().minusHours(2); 
// Query the database for all events the last two hours that have "subject" equal to "123" and sort these in descending order
Stream<CloudEvent> events = eventStore.query(subject("123").and(time(gte(lastTwoHours))), SortBy.time(DESCENDING));

val lastTwoHours = OffsetDateTime.now().minusHours(2);
// Query the database for all events the last two hours that have "subject" equal to "123" and sort these in descending order
val events : Stream<CloudEvent> = eventStore.query(subject("123").and(time(gte(lastTwoHours))), SortBy.time(DESCENDING))

The subject and time methods are statically imported from org.occurrent.filter.Filter and lte is statically imported from org.occurrent.condition.Condition.

EventStoreQueries is not bound to a particular stream, rather you can query any stream (or multiple streams at the same time). It also provides the ability to get an “all” stream:

// Return all events in an event store sorted by descending order
Stream<CloudEvent> events = eventStore.all(SortBy.time(DESCENDING));

// Return all events in an event store sorted by descending order
val events : Stream<CloudEvent> = eventStore.all(SortBy.time(DESCENDING))

The EventStoreQueries interface also supports skip and limit capabilities which allows for pagination:

// Skip 42, limit 1024
Stream<CloudEvent> events = eventStore.all(42, 1024);

// Skip 42, limit 1024
val events : Stream<CloudEvent> = eventStore.all(42, 1024)

To get started with an event store refer to Choosing An EventStore.

Subscriptions

A subscription is a way to get notified when new events are written to an event store. Typically, a subscription will be used to create views from events (such as projections, sagas, snapshots etc) or create integration events that can be forwarded to another piece of infrastructure such as a message bus. There are two different kinds of API’s, the first one is a blocking API represented by the org.occurrent.subscription.api.blocking.SubscriptionModel interface (in the org.occurrent:subscription-api-blocking module), and second one is a reactive API represented by the org.occurrent.subscription.api.reactor.SubscriptionModel interface (in the org.occurrent:subscription-api-reactor module).

The blocking API is callback based, which is fine if you’re working with individual events (you can of course use a simple function that aggregates events into batches yourself). If you want to work with streams of data, the reactor SubscriptionModel is probably a better option since it’s using the Flux publisher from project reactor.

Note that it’s fine to use reactive SubscriptionModel, even though the event store is implemented using the blocking api, and vice versa. If the datastore allows it, you can also run subscriptions in a different process than the processes reading and writing to the event store.

To get started with subscriptions refer to Using Subscriptions.

EventStore Operations

Occurrent event store implementations may optionally also implement the EventStoreOperations interface. It provides means to delete a specific event, or an entire event stream. For example:

// Delete an entire event stream
eventStoreOperations.deleteEventStream("streamId");
// Delete a specific event
eventStoreOperations.deleteEvent("cloudEventId", cloudEventSource);
// This will delete all events in stream "myStream" that has a version less than or equal to 19.
eventStoreOperations.delete(streamId("myStream").and(streamVersion(lte(19L)));

// Delete an entire event stream
eventStoreOperations.deleteEventStream("streamId")
// Delete a specific event
eventStoreOperations.deleteEvent("cloudEventId", cloudEventSource)
// This will delete all events in stream "myStream" that has a version less than or equal to 19.
eventStoreOperations.delete(streamId("myStream").and(streamVersion(lte(19L)))

These are probably operations that you want to use sparingly. Typically, you never want to remove any events, but there are some cases, such as GDPR or other regulations, that requires the deletion of an event or an entire event stream. You should be aware that there are other ways to solve this though. One way would be to encrypt personal data and throw away the key when the user no longer uses the service. Another would be to store personal data outside the event store.

Another reason for deleting events is if you’re implementing something like “closing the books” or certain types of snapshots, and don’t need the old events anymore.

Another feature provided by EventStoreOperations is the ability to update an event. Again, this is not something you normally want to do, but it can be useful for certain strategies of GDPR compliance. For example maybe you want to remove or update personal data in an event when a users unregisters from your service. Here’s an example:

eventStoreOperations.updateEvent("cloudEventId", cloudEventSource, cloudEvent -> {
    return CloudEventBuilder.v1(cloudEvent).withData(removePersonalDetailsFrom(cloudEvent)).build();
});

eventStoreOperations.updateEvent("cloudEventId", cloudEventSource) { cloudEvent -> 
    CloudEventBuilder.v1(cloudEvent).withData(removePersonalDetailsFrom(cloudEvent)).build()
})

Views

Occurrent doesn’t have any special components for creating views/projections. Instead, you simply create a subscription in which you can create and store the view as you find fit. But this doesn’t have to be difficult! Here’s a trivial example of a view that maintains the number of ended games. It does so by inceasing the “numberOfEndedGames” field in an (imaginary) database for each “GameEnded” event that is written to the event store:

// An imaginary database API
Database someDatabase = ...
// Subscribe to all "GameEnded" events by starting a subscription named "my-view" 
// and increase "numberOfEndedGames" for each ended game.   
subscriptionModel.subscribe("my-view", filter(type("GameEnded")), cloudEvent -> someDatabase.inc("numberOfEndedGames"));        

// An imaginary database API
val someDatabase : Database = ...
// Subscribe to all "GameEnded" events by starting a subscription named "my-view" 
// and increase "numberOfEndedGames" for each ended game. 
subscriptionModel.subscribe("my-view", filter(type("GameEnded"))) {  
    someDatabase.inc("numberOfEndedGames")
}

Where filter is imported from org.occurrent.subscription.OccurrentSubscriptionFilter and type is imported from org.occurrent.condition.Condition.

While this is a trivial example it shouldn’t be difficult to create a view that is backed by a JPA entity in a relational database based on a subscription.

Commands

A command is used to represent an intent in an event sourced system, i.e. something that you want to do. They’re different, in a very important way, from events in that commands can fail or be rejected, where-as events cannot. A typical example of a command would be a data structure whose name is defined as an imperative verb, for example PlaceOrder. The resulting event, if the command is processed successfully, could then be OrderPlaced. However, in Occurrent, as explained in more detail in the Command Philosophy section below, you may start off by not using explicit data structures for commands unless you want to. In Occurrent, you can instead use pure functions to represent commands and command handling. Combine this with function composition and you have a powerful way to invoke the domain model (refer to the application service for examples).

Command Philosophy

Occurrent doesn’t contain a built-in command bus. Instead, you’re encouraged to pick any infrastructure component you need to act as the command bus to send commands to another service. Personally, I typically make a call to a REST API or make an RPC invocation instead of using a distributed command bus that routes the commands to my aggregate. There are of course exceptions to this, such as the need for location transparency or if you’re using Decider’s. If you need location transparency, a command bus or an actor model can be of help. But I would argue that you may not always need the complexity by prematurely going down this route if your business requirements doesn’t point you in this direction. Decider’s are a nice alternative, that doesn’t require any additional infrastructure.

But what about internally? For example if a service exposes a REST API and upon receiving a request it publishes a command that’s somehow picked up and routed to a function in your domain model. This is where an application service becomes useful. However, let’s first explore the rationale behind the philosophy of Occurrent. In other frameworks, it’s not uncommon that you define your domain model like this:

public class WordGuessingGame extends AggregateRoot {

    @AggregateId
    private String gameId;
    private String wordToGuess;

    @HandleCommand
    public void handle(StartNewGameCommand startNewGameCommand) {
        // Insert some validation and logic
        ... 
        // Publish an event using the "publish" method from AggregateRoot
        publish(new WordGuessingGameWasStartedEvent(...));
    }
    
    @HandleCommand
    public void handle(GuessWordCommand guessWordCommand) {
        // Some validation and implementation ...
        ...	
        
        // Publish an event using the "publish" method from AggregateRoot
        publish(new WordGuessedEvent(...));
    }

    @HandleEvent
    public void handle(WordGuessingGameWasStartedEvent e) {
        this.gameId = e.getGameId();
        this.wordToGuess = e.getWordToGuess();    
    }        

    ... 
}

 class WordGuessingGame : AggregateRoot() {
 
     @AggregateId
     var gameId : String
     var wordToGuess : String
 
     @HandleCommand
     fun handle(startNewGameCommand : StartNewGameCommand) {
         // Insert some validation and logic
         ... 
         // Publish an event using the "publish" method from AggregateRoot
         publish(WordGuessingGameWasStartedEvent(...))
     }
     
     @HandleCommand
     fun handle(guessWordCommand : GuessWordCommand) {
         // Some validation and implementation ...
         ...	
         
         // Publish an event using the "publish" method from AggregateRoot
         publish(WordGuessedEvent(...))
     }
 
     @HandleEvent
     fun handle(e : WordGuessingGameWasStartedEvent) {
         gameId = e.getGameId()
         wordToGuess = e.getWordToGuess()    
     }        
 
     ... 
 }

Let’s look at a “command” and see what it typically looks like in these frameworks:

public class StartNewGameCommand {
    
    @AggregateId
    private String gameId;
    private String wordToGuess;
    
    public void setGameId(String gameId) {
        this.gameId = gameId;
    }
    
    public String getGameId() {
        return gameId;
    }

    public void setWordToGuess(String wordToGuess) {
        this.gameId = gameId;
    }
    
    public String getWordToGuess() {
        return wordToGuess;
    }
    
    // Equals/hashcode/tostring methods are excluded for breivty
}

data class StartNewGameCommand(@AggregateId var gameId: String, val wordToGuess : String)

Now that we have our WordGuessingGame implementation and a command we can dispatch it to a command bus:

commandbus.dispatch(new StartNewGameCommand("someGameId", "Secret word"));

commandbus.dispatch(StartNewGameCommand("someGameId", "Secret word"))

From a typical Java perspective one could argue that this is not too bad. But it does have a few things one could improve upon from a broader perspective:

1. The WordGuessingGame is complecting several things that may be modelled separately. Data, state, behavior, command- and event routing and event publishing are all defined in the same model (the WordGuessingGame class). It also uses framework specific annotations, classes and inheritance inside your domain model which is something you want to avoid. For small examples like this it arguably doesn’t matter, but if you have complex logic and a large system, it probably will in my experience. Keeping state and behavior separate allows for easier testing, referential transparency and function composition. It allows treating the state as a value which has many benefits.
2. Commands are defined as explicit data structures with framework-specific annotations when arguably they don’t have to. This is fine if you need to serialize the command (in order to send it to another location or to schedule it for the future) but one could argue that you don’t want to couple your commands to some infrastructure. This is of course a trade-off, in Occurrent you’re free to choose any approach you like (i.e. commands/functions can be completely free of framework/library/infrastructure concerns).

Commands in Occurrent

So how would one dispatch commands in Occurrent? As we’ve already mentioned there’s nothing stopping you from using a (distributed) command bus or to create explicit commands, and dispatch them the way we did in the example above. For example, if you’re using Decider’s, it could be nice to have commands explicitly defined. But if you recognize some of the points described above and are looking for a simpler approach, here’s another way to go about. First let’s refactor the domain model to pure functions, without any state or dependencies to Occurrent or any other library/framework.

public class WordGuessingGame {
	public static Stream<DomainEvent> startNewGame(String gameId, String wordToGuess) {	
		...
	}

	public static Stream<DomainEvent> guessWord(Stream<DomainEvent> eventStream, String word) {
		...
	}
}

// Note that the functions could might as well be placed directly in a package.
// You might also want to use a Kotlin Sequence or List instead of a Stream
 object WordGuessingGame {
    fun startNewGame(gameId : String, wordToGuess : String) : Stream<CloudEvent> = ...	
 
    fun guessWord(eventStream : Stream<DomainEvent>, word : String) : Stream<DomainEvent> = ...
 }

If you define your behavior like this it’ll be easy to test (and also to compose using normal function composition techniques). There are no side-effects (such as publishing events) which also allows for easier testing and local reasoning.

But where are our commands!? In this example we’ve decided to represent them as functions. I.e. the “command” is modeled as simple function, e.g. startNewGame! This means that the command handling logic is handled by function as well. You don’t need to switch/match over the command since you directly invoke the function itself. Again, you may prefer to actually define your commands explicitly, but in this example we’ll just be using normal functions.

But wait, how are these functions called? Create or copy a generic ApplicationService class like the one below (or use the generic application service provided by Occurrent):

public class ApplicationService {

    private final EventStore eventStore;
    private final Function<CloudEvent, DomainEvent> convertCloudEventToDomainEvent;
    private final Function<DomainEvent, CloudEvent> convertDomainEventToCloudEvent;

    public ApplicationService(EventStore eventStore, 
                              Function<CloudEvent, DomainEvent> convertCloudEventToDomainEvent, 
                              Function<DomainEvent, CloudEvent> convertDomainEventToCloudEvent) {
        this.eventStore = eventStore;
        this.convertCloudEventToDomainEvent = convertCloudEventToDomainEvent;
        this.convertDomainEventToCloudEvent = convertDomainEventToCloudEvent;
    }

    public void execute(String streamId, Function<Stream<DomainEvent>, Stream<DomainEvent>> functionThatCallsDomainModel) {
        // Read all events from the event store for a particular stream
        EventStream<CloudEvent> eventStream = eventStore.read(streamId);
        // Convert the cloud events into domain events
        Stream<DomainEvent> domainEventsInStream = eventStream.events().map(convertCloudEventToDomainEvent);

        // Call a pure function from the domain model which returns a Stream of domain events  
        Stream<DomainEvent> newDomainEvents = functionThatCallsDomainModel.apply(domainEventsInStream);

        // Convert domain events to cloud events and write them to the event store  
        eventStore.write(streamId, eventStream.version(), newDomainEvents.map(convertDomainEventToCloudEvent));
    }
}

class ApplicationService constructor (val eventStore : EventStore, 
                                      val convertCloudEventToDomainEvent : (CloudEvent) -> DomainEvent, 
                                      val convertDomainEventToCloudEvent : (DomainEvent) -> CloudEvent) {

    fun execute(streamId : String, functionThatCallsDomainModel : (Stream<DomainEvent>) -> Stream<DomainEvent>) {
        // Read all events from the event store for a particular stream
        val  eventStream : EventStream<CloudEvent> = eventStore.read(streamId)
        // Convert the cloud events into domain events
        val domainEventsInStream : Stream<DomainEvent> = eventStream.events().map(convertCloudEventToDomainEvent)

        // Call a pure function from the domain model which returns a Stream of domain events
        val newDomainEvents = functionThatCallsDomainModel(domainEventsInStream)

        // Convert domain events to cloud events and write them to the event store
        eventStore.write(streamId, eventStream.version(), newDomainEvents.map(convertDomainEventToCloudEvent))
    }
}

and then use the ApplicationService like this:

// A function that converts a CloudEvent to a "domain event"
Function<CloudEvent, DomainEvent> convertCloudEventToDomainEvent = ..
// A function that a "domain event" to a CloudEvent
Function<DomainEvent, CloudEvent> convertDomainEventToCloudEvent = ..
EventStore eventStore = ..
ApplicationService applicationService = new ApplicationService(eventStore, convertCloudEventToDomainEvent, convertDomainEventToCloudEvent);

// Now in your REST API use the application service:
String gameId = ... // From a form parameter
String wordToGuess = .. // From a form parameter
applicationService.execute(gameId, events -> WordGuessingGame.startNewGame(gameId, wordToGuess));

// A function that converts a CloudEvent to a "domain event"
val convertCloudEventToDomainEvent : (CloudEvent) -> DomainEvent = ..
// A function that a "domain event" to a CloudEvent
val convertDomainEventToCloudEvent = (DomainEvent) -> CloudEvent  = ..
val eventStore : EventStore = ..
val applicationService = ApplicationService(eventStore, convertCloudEventToDomainEvent, convertDomainEventToCloudEvent);

// Now in your REST API use the application service:
val gameId = ... // From a form parameter
val wordToGuess = .. // From a form parameter
applicationService.execute(gameId) { events -> 
    WordGuessingGame.startNewGame(gameId, wordToGuess)
}

We’re leveraging higher-order functions instead of using explicit commands.

Command Composition

Many times it’s useful to compose multiple commands into a single unit-of-work for the same stream/aggregate. What this means that you’ll “merge” several commands into one, and they will be executed in an atomic fashion. I.e. either all commands succeed, or all commands fail.

While you’re free to use any means and/or library to achieve this, Occurrent ships with a “command composition” library that you can leverage:

<dependency>
    <groupId>org.occurrent</groupId>
    <artifactId>command-composition</artifactId>
    <version>0.19.7</version>
</dependency>

compile 'org.occurrent:command-composition:0.19.7'

libraryDependencies += "org.occurrent" % "command-composition" % "0.19.7"

@Grab(group='org.occurrent', module='command-composition', version='0.19.7') 

[org.occurrent/command-composition "0.19.7"]

'org.occurrent:command-composition:jar:0.19.7'

<dependency org="org.occurrent" name="command-composition" rev="0.19.7" />

As an example consider this simple domain model:

public class WordGuessingGame {
    public Stream<DomainEvent> startNewGame(Stream<DomainEvents> events, String gameId, String wordToGuess) {
        // Implementation
    }
    
    public Stream<DomainEvent> guessWord(Stream<DomainEvents> events, String guess) {
        // Implementation
    }
}

object WordGuessingGame {
    fun startNewGame(events : Sequence<DomainEvent>), gameId : String, wordToGuess : String) : Sequence<DomainEvent> {
        // Implementation
    } 

    fun guessWord(events : Sequence<DomainEvent>, guess : String) : Sequence<DomainEvent> {
        // Implementation
    }    
}

Imagine that for a specific API you want to allow starting a new game and making a guess in the same request. Instead of changing your domain model, you can use function composition! If you import org.occurrent.application.composition.command.StreamCommandComposition.composeCommands you can do like this:

String gameId = ...
String wordToGuess = ...
String guess = ...
applicationService.execute(gameId, composeCommands(
    events -> WordGuessingGame.startNewGame(events, gameId, wordToGuess),
    events -> WordGuessingGame.makeGuess(events, guess) 
));

val gameId = ...
val wordToGuess = ...
val guess = ...
applicationService.execute(gameId, composeCommands(
    { events -> WordGuessingGame.startNewGame(events, gameId, wordToGuess) }
    { events -> WordGuessingGame.makeGuess(events, guess) } 
))

If you’re using Kotlin you can also make use of the andThen (infix) function for command composition (import org.occurrent.application.composition.command.andThen):

applicationService.execute(gameId,
    { events -> WordGuessingGame.startNewGame(events, gameId, wordToGuess) }
        andThen { events -> WordGuessingGame.makeGuess(events, guess) })

Events returned from WordGuessingGame.startNewGame(..) will be appended to the event stream when calling WordGuessingGame.makeGuess(..) and the new domain events returned by the two functions will be merged and written in an atomic fashion to the event store.

The command composition library also contains some utilities for partial function application that you can use to further enhance the example above (if you like). If you statically import partial method from org.occurrent.application.composition.command.partial.PartialFunctionApplication you can refactor the code above into this:

String gameId = ...
String wordToGuess = ...
String guess = ...
applicationService.execute(gameId, composeCommands(
    partial(WordGuessingGame::startNewGame, gameId, wordToGuess),
    partial(WordGuessingGame::makeGuess, guess)
));

val gameId = ...
val wordToGuess = ...
val guess = ...
applicationService.execute(gameId, composeCommands(
    WordGuessingGame::startNewGame.partial(gameId, wordToGuess)
    WordGuessingGame::makeGuess.partial(guess) 
))

With Kotlin, you can also use andThen (described above) to do:

applicationService.execute(gameId, 
    WordGuessingGame::startNewGame.partial(gameId, wordToGuess)
            andThen WordGuessingGame::makeGuess.partial(guess))

Command Conversion

If you have an application service that takes a higher-order function in the form of Function<Stream<DomainEvent>, Stream<DomainEvent>> but your domain model is defined with list’s (Function<List<DomainEvent, List<DomainEvent>) then Occurrent provides means to easily convert between them. First you need to depend on the Command Composition library:

<dependency>
    <groupId>org.occurrent</groupId>
    <artifactId>command-composition</artifactId>
    <version>0.19.7</version>
</dependency>

compile 'org.occurrent:command-composition:0.19.7'

libraryDependencies += "org.occurrent" % "command-composition" % "0.19.7"

@Grab(group='org.occurrent', module='command-composition', version='0.19.7') 

[org.occurrent/command-composition "0.19.7"]

'org.occurrent:command-composition:jar:0.19.7'

<dependency org="org.occurrent" name="command-composition" rev="0.19.7" />

Let’s say you have a domain model defined like this:

public class WordGuessingGame {
    public List<DomainEvent> guessWord(List<DomainEvents> events, String guess) {
        // Implementation
    }
}

object WordGuessingGame {
    fun guessWord(events : List<DomainEvent>, guess : String) : List<DomainEvent> {
        // Implementation
    }    
}

But you application service takes a Function<Stream<DomainEvent>, Stream<DomainEvent>>:

public class ApplicationService {
    public void execute(String streamId, Function<Stream<DomainEvent>, Stream<DomainEvent>> functionThatCallsDomainModel) {
        // Implementation
    }
}

Then you can make use of the toStreamCommand in org.occurrent.application.composition.command.CommandConversion to call the domain function:

String guess = ...
applicationService.execute(gameId, toStreamCommand( events -> WordGuessingGame.makeGuess(events, guess)));

val guess = ...
applicationService.execute(gameId, toStreamCommand { events -> WordGuessingGame.makeGuess(events, guess) } )

CloudEvent Conversion

To convert between domain events and cloud events you can use the cloud event converter API that’s shipped with Occurrent. This is optional, but components such as the application service and subscription dsl uses a cloud event converter to function. If you’re only using an event store and subscriptions then you don’t need a cloud event converter (or you can roll your own). All cloud event converters implements the org.occurrent.application.converter.CloudEventConverter interface from the org.occurrent:cloudevent-converter module (see custom cloudevent converter).

Generic CloudEvent Converter

This is a really simple cloud event converter to which you can pass two higher-order functions that converts to and from domain events respectively. To use it depend on:

<dependency>
    <groupId>org.occurrent</groupId>
    <artifactId>cloudevent-converter-generic</artifactId>
    <version>0.19.7</version>
</dependency>

compile 'org.occurrent:cloudevent-converter-generic:0.19.7'

libraryDependencies += "org.occurrent" % "cloudevent-converter-generic" % "0.19.7"

@Grab(group='org.occurrent', module='cloudevent-converter-generic', version='0.19.7') 

[org.occurrent/cloudevent-converter-generic "0.19.7"]

'org.occurrent:cloudevent-converter-generic:jar:0.19.7'

<dependency org="org.occurrent" name="cloudevent-converter-generic" rev="0.19.7" />

For example:

Function<CloudEvent, DomainEvent> convertCloudEventToDomainEventFunction = .. // You implement this function
Function<DomainEvent, CloudEvent> convertDomainEventToCloudEventFunction = .. // You implement this function
CloudEventConverter<CloudEvent> cloudEventConverter = new GenericCloudEventConverter<>(convertCloudEventToDomainEventFunction, convertDomainEventToCloudEventFunction);

If your domain model is already using a CloudEvent (and not a custom domain event) then you can just pass a Function.identity() to the GenericCloudEventConverter:

CloudEventConverter<CloudEvent> cloudEventConverter = new GenericCloudEventConverter<>(Function.identity(), Function.identity());

XStream CloudEvent Converter

This cloud event converter uses XStream to convert domain events to cloud events to XML and back. To use it, first depend on this module:

<dependency>
    <groupId>org.occurrent</groupId>
    <artifactId>cloudevent-converter-xstream</artifactId>
    <version>0.19.7</version>
</dependency>

compile 'org.occurrent:cloudevent-converter-xstream:0.19.7'

libraryDependencies += "org.occurrent" % "cloudevent-converter-xstream" % "0.19.7"

@Grab(group='org.occurrent', module='cloudevent-converter-xstream', version='0.19.7') 

[org.occurrent/cloudevent-converter-xstream "0.19.7"]

'org.occurrent:cloudevent-converter-xstream:jar:0.19.7'

<dependency org="org.occurrent" name="cloudevent-converter-xstream" rev="0.19.7" />

Next you can instantiate it like this:

XStream xStream = new XStream();
xStream.allowTypeHierarchy(MyDomainEvent.class);
URI cloudEventSource = URI.create("urn:company:domain") 
XStreamCloudEventConverter<MyDomainEvent> cloudEventConverter = new XStreamCloudEventConverter<>(xStream, cloudEventSource);

val xStream = XStream().apply { allowTypeHierarchy(MyDomainEvent::class.java) }
val cloudEventSource = URI.create("urn:company:domain")
val cloudEventConverter = new XStreamCloudEventConverter<>(xStream, cloudEventSource)

You can also configure how different attributes of the domain event should be represented in the cloud event by using the builder, new XStreamCloudEventConverter.Builder<MyDomainEvent>().. build().

Jackson CloudEvent Converter

This cloud event converter uses Jackson to convert domain events to cloud events to JSON and back. To use it, first depend on this module:

<dependency>
    <groupId>org.occurrent</groupId>
    <artifactId>cloudevent-converter-jackson</artifactId>
    <version>0.19.7</version>
</dependency>

compile 'org.occurrent:cloudevent-converter-jackson:0.19.7'

libraryDependencies += "org.occurrent" % "cloudevent-converter-jackson" % "0.19.7"

@Grab(group='org.occurrent', module='cloudevent-converter-jackson', version='0.19.7') 

[org.occurrent/cloudevent-converter-jackson "0.19.7"]

'org.occurrent:cloudevent-converter-jackson:jar:0.19.7'

<dependency org="org.occurrent" name="cloudevent-converter-jackson" rev="0.19.7" />

Next you can instantiate it like this:

ObjectMapper objectMapper = new ObjectMapper();
URI cloudEventSource = URI.create("urn:company:domain")
JacksonCloudEventConverter<MyDomainEvent> cloudEventConverter = new JacksonCloudEventConverter<>(objectMapper, cloudEventSource);

val objectMapper = jacksonObjectMapper()
val cloudEventSource = URI.create("urn:company:domain")
val cloudEventConverter = new JacksonCloudEventConverter<>(objectMapper, cloudEventSource)

You can also configure how different attributes of the domain event should be represented in the cloud event by using the builder, new JacksonCloudEventConverter.Builder<MyDomainEvent>().. build(). In production, you almost certainly want to change the way the JacksonCloudEventConverter generates the cloud event type from the domain event. By default, the cloud event type will be generated from the fully-qualified class name of the domain event class type. I.e. if you do:

CloudEventConverter<MyDomainEvent> cloudEventConverter = new JacksonCloudEventConverter<>(objectMapper, cloudEventSource);
CloudEvent cloudEvent = cloudEventConverter.toCloudEvent(new SomeDomainEvent());

Then cloudEvent.getType() will return com.mycompany.SomeDomainEvent. Typically, you want to decouple the cloud event type from the fully-qualified name of the class. A better, but arguably still not optimal way, would be to make cloudEvent.getType() return SomeDomainEvent instead. The JacksonCloudEventConverter allows us to do this by using the builder:

CloudEventConverter<MyDomainEvent> cloudEventConverter = new JacksonCloudEventConverter.Builder<MyDomainEvent>()
        .typeMapper(..) // Specify a custom way to map the domain event to a cloud event and vice versa
        .build();

But when using Jackson, we can’t just configure the type mapper to return the “simple name” of the domain event class instead of the fully-qualified name. This is because there’s no generic way to derive the fully-qualified name from just the simple name. The fully-qualified name is needed in order for Jackson to map the cloud event back into a domain event. In order to work-around this you could implement your own type mapper (that you pass to the builder above) or create an instance of ReflectionCloudEventTypeMapper that knows how to convert the “simple name” cloud event type back into the domain event class. There are a couple of ways, the most simple one is probably this:

CloudEventTypeMapper<MyDomainEvent> typeMapper = ReflectionCloudEventTypeMapper.simple(MyDomainEvent.class);

This will create an instance of ReflectionCloudEventTypeMapper that uses the simple name of the domain event as cloud event type. But the crucial thing is that when deriving the domain event type from the cloud event, the ReflectionCloudEventTypeMapper will prepend the package name of supplied domain event type (MyDomainEvent) to the cloud event type, thus reconstructing the fully-qualified name of the class. For this to work, all domain events must reside in exactly the same package as MyDomainEvent.

Another approach would be to supply a higher-order function that knows how to map the cloud event type back into a domain event class.

CloudEventTypeMapper<MyDomainEvent> typeMapper = ReflectionCloudEventTypeMapper.simple(cloudEventType -> ...);

Again, this will create an instance of ReflectionCloudEventTypeMapper that uses the simple name of the domain event as cloud event type, but you are responsible to, somehow, map the cloud event type (cloudEventType) back into a domain event class.

If you don’t want to use reflection or don’t want to couple the class name to the event name (which is recommended) you can roll your own custom CloudEventTypeMapper by implementing the org.occurrent.application.converter.typemapper.CloudEventTypeMapper interface.

Custom CloudEvent Converter

To create a custom cloud event converter first depend on:

<dependency>
    <groupId>org.occurrent</groupId>
    <artifactId>cloudevent-converter-api</artifactId>
    <version>0.19.7</version>
</dependency>

compile 'org.occurrent:cloudevent-converter-api:0.19.7'

libraryDependencies += "org.occurrent" % "cloudevent-converter-api" % "0.19.7"

@Grab(group='org.occurrent', module='cloudevent-converter-api', version='0.19.7') 

[org.occurrent/cloudevent-converter-api "0.19.7"]

'org.occurrent:cloudevent-converter-api:jar:0.19.7'

<dependency org="org.occurrent" name="cloudevent-converter-api" rev="0.19.7" />

Let’s have a look at a naive example of how we can create a custom converter that converts domain events to cloud events (and vice versa). This cloud event converter can then be used with the generic application service (the application service implementation provided by Occurrent) and other Occurrent components that requires a CloudEventConverter. Note that instead of using the code below you might as well use the Jackson CloudEvent Converter, this is just an example showing how you could roll your own.

import com.fasterxml.jackson.databind.ObjectMapper;
import io.cloudevents.CloudEvent;
import io.cloudevents.core.builder.CloudEventBuilder;
import org.occurrent.application.converter.CloudEventConverter;

import java.io.IOException;
import java.net.URI;

import static java.time.ZoneOffset.UTC;
import static org.occurrent.functional.CheckedFunction.unchecked;
import static org.occurrent.time.TimeConversion.toLocalDateTime;

public class MyCloudEventConverter implements CloudEventConverter<DomainEvent> {

    private final ObjectMapper objectMapper;

    public MyCloudEventConverter(ObjectMapper objectMapper) {
        this.objectMapper = objectMapper;
    }

    @Override
    public CloudEvent toCloudEvent(DomainEvent e) {
        try {
            return CloudEventBuilder.v1()
                    .withId(e.getEventId())
                    .withSource(URI.create("urn:myapplication:streamtype"))
                    .withType(getCloudEventType(e))
                    .withTime(LocalDateTime.ofInstant(e.getDate().toInstant(), UTC).atOffset(UTC)
                                           .truncatedTo(ChronoUnit.MILLIS))
                    .withSubject(e.getName())
                    .withDataContentType("application/json")
                    .withData(objectMapper.writeValueAsBytes(e))
                    .build();
        } catch (JsonProcessingException jsonProcessingException) {
            throw new RuntimeException(jsonProcessingException);
        }
    }

    @Override
    public DomainEvent toDomainEvent(CloudEvent cloudEvent) {
        try {
            return (DomainEvent) objectMapper.readValue(cloudEvent.getData().toBytes(), Class.forName(cloudEvent.getType()));
        } catch (IOException | ClassNotFoundException e) {
            throw new RuntimeException(e);
        }
    }
    
    @Override
    public String getCloudEventType(Class<? extends T> type) {
        return type.getName();
    }
}        

To see what the attributes mean in the context of event sourcing refer to the CloudEvents documentation. You can also have a look at GenericApplicationServiceTest.java for an actual code example.

Note that if the data content type in the CloudEvent is specified as “application/json” (or a json compatible content-type) then Occurrent will automatically store it as Bson in a MongoDB event store. The reason for this so that you’re able to query the data, either by the EventStoreQueries API, or manually using MongoDB queries. In order to do this, the byte[] passed to withData, will be converted into a org.bson.Document that is later written to the database. This is not optimal from a performance perspective. A more performant option would be to make use of the io.cloudevents.core.data.PojoCloudEventData class. This class implements the io.cloudevents.CloudEventData interface and allows passing a pre-baked Map or org.bson.Document instance to it. Then no additional conversion will need to take place! Here’s an example:

import com.fasterxml.jackson.databind.ObjectMapper;
import io.cloudevents.CloudEvent;
import io.cloudevents.core.builder.CloudEventBuilder;
import io.cloudevents.core.data.PojoCloudEventData;
import org.bson.Document;

import java.io.IOException;
import java.net.URI;

import static java.time.ZoneOffset.UTC;
import static org.occurrent.functional.CheckedFunction.unchecked;
import static org.occurrent.time.TimeConversion.toLocalDateTime;
import static java.time.temporal.ChronoUnit.MILLIS;

public class MyCloudEventConverter implements CloudEventConverter<DomainEvent> {
    
    private final ObjectMapper objectMapper;
    
    public MyCloudEventConverter(ObjectMapper objectMapper) {
        this.objectMapper = objectMapper;
    } 

    @Override
    public CloudEvent toCloudEvent(DomainEvent e) {  
            // Convert the data in the domain event into a Document 
            Map<String, Object> eventData = convertDataInDomainEventToMap(e);
            return CloudEventBuilder.v1()
                    .withId(e.getEventId())
                    .withSource(URI.create("http://name"))
                    .withType(getCloudEventType(e))
                    .withTime(LocalDateTime.ofInstant(e.getDate().toInstant(), UTC).atOffset(UTC)
                                           .truncatedTo(MILLIS))
                    .withSubject(e.getName())
                    .withDataContentType("application/json")  
                    // Use the "eventData" map to create an instance of PojoCloudEventData.
                    // If an event store implementation doesn't know how to handle "Map" data,
                    // it'll call the higher-order function that converts the map into byte[] 
                    // (objectMapper::writeValueAsBytes), that it _has_ to understand.
                    // But since all Occurrent event stores currently knows how to handle maps, 
                    // the objectMapper::writeValueAsBytes method will never be called.
                    .withData(PojoCloudEventData.wrap(eventData, objectMapper::writeValueAsBytes))
                    .build();
    }
    
    @Override
    public DomainEvent toDomainEvent(CloudEvent cloudEvent) {
        CloudEventData cloudEventData = cloudEvent.getData();
        if (cloudEventData instanceof PojoCloudEventData && cloudEventData.getValue() instanceof Map) {
            Map<String, Object> eventData = ((PojoCloudEventData<Map<String, Object>>) cloudEventData).getValue();
            return convertToDomainEvent(cloudEvent, eventData);
        } else {
            return objectMapper.readValue(cloudEventData.toBytes(), DomainEvent.class); // try-catch omitted
        }
    }
    
    @Override
    public String getCloudEventType(Class<? extends T> type) {
        return type.getSimpleName();
    }
    
    private static Map<String, Object> convertDataInDomainEventToDocument(DomainEvent e) {
        // Convert the domain event into a Map                
        Map<String, Object> data = new HashMap<String, Object>();
        if (e instanceof GameStarted) {
           data.put("type", "GameStarted"); 
           // Put the rest of the values
        } else if (...) {
            // More events
        }
        return map;
    }

    private static DomainEvent convertToDomainEvent(CloudEvent cloudEvent, Map<String, Object> data) {
        // Re-construct the domain event instance from the cloud event and data
        switch ((String) data.get("type")) {
            case "GameStarted" -> // Convert map to GameStartedEvent 
                break;
            ...
        }
    }
}        

Application Service

Occurrent provides a generic application service that is a good starting point for most use cases. First add the module as a dependency to your project:

<dependency>
    <groupId>org.occurrent</groupId>
    <artifactId>application-service-blocking</artifactId>
    <version>0.19.7</version>
</dependency>

compile 'org.occurrent:application-service-blocking:0.19.7'

libraryDependencies += "org.occurrent" % "application-service-blocking" % "0.19.7"

@Grab(group='org.occurrent', module='application-service-blocking', version='0.19.7') 

[org.occurrent/application-service-blocking "0.19.7"]

'org.occurrent:application-service-blocking:jar:0.19.7'

<dependency org="org.occurrent" name="application-service-blocking" rev="0.19.7" />

This module provides an interface, org.occurrent.application.service.blocking.ApplicationService, and a default implementation, org.occurrent.application.service.blocking.implementation.GenericApplicationService. The GenericApplicationService takes an EventStore and a org.occurrent.application.converter.CloudEventConverter implementation as parameters. The latter is used to convert domain events to and from cloud events when loaded/written to the event store. There’s a default implementation that you may decide to use called, org.occurrent.application.converter.implementation.GenericCloudEventConverter available in the org.occurrent:cloudevent-converter-generic module. You can see an example in the next section.

As of version 0.11.0, the GenericApplicationService also takes a RetryStrategy as an optional third parameter.
By default, the retry strategy uses exponential backoff starting with 100 ms and progressively go up to max 2 seconds wait time between each retry, if a WriteConditionNotFulfilledException is caught (see write condition docs). It will, again by default, only retry 5 times before giving up, rethrowing the original exception. You can override the default strategy by calling new GenericApplicationService(eventStore, cloudEventConverter, retryStrategy). Use new GenericApplicationService(eventStore, cloudEventConverter, RetryStrategy.none()) to disable retry. This is also useful if you want to use another retry library.

Using the Application Service

Now you can instantiate the (blocking) GenericApplicationService:

EventStore eventStore = ..
CloudEventConverter<DomainEvent> cloudEventConverter = ..
ApplicationService<DomainEvent> applicationService = new GenericApplicationService<>(eventStore, cloudEventConverter);

val eventStore : EventStore = ..
val cloudEventConverter : CloudEventConverter<DomainEvent> = ..
val applicationService : ApplicationService<DomainEvent> = GenericApplicationService(eventStore, cloudEventConverter)

You’re now ready to use the generic application service in your application.

As an example let’s say you have a domain model with a method defined like this:

public class WordGuessingGame {
    public static Stream<DomainEvent> guessWord(Stream<DomainEvent> events, String guess) {
        // Implementation
    }    
}

You can call it using the application service:

applicationService.execute(gameId, events -> WordGuessingGame.guessWord(events, guess));

applicationService.execute(gameId) { events -> 
    WordGuessingGame.guessWord(events, guess)
}

Application Service Side-Effects

The GenericApplicationService supports executing side-effects after the events returned from the domain model have been written to the event store. This is useful if you need to, for example, update a view synchronously after events have been written to the event store. Note that to perform side-effects (or policies) asynchronously you should use a subscription. As an example, consider that you want to synchronously register a game as ongoing when it is started. It may be defined like this:

public class RegisterOngoingGame {
    private final DatabaseApi someDatabaseApi;
    
    pubic RegisterOngoingGame(DatabaseApi someDatabaseApi) {
        this.someDatabaseApi = someDatabaseApi;
    }

    public void registerGameAsOngoingWhenGameWasStarted(GameWasStarted event) {
        // Add the id of the game started event to a set to handle duplicates and idempotency.
        someDatabaseApi.addToSet("ongoingGames", Map.of("gameId", e.gameId(), "date", e.getDate()));                
    }
}

class RegisterOngoingGame(private val someDatabaseApi : DatabaseApi) {
    fun registerGameAsOngoingWhenGameWasStarted(event : GameWasStarted) {
        // Add the id of the game started event to a set to handle duplicates and idempotency.
        someDatabaseApi.addToSet("ongoingGames", Map.of("gameId", e.gameId(), "date", e.getDate()));                
    }
}

The reason for doing this synchronously is, for example, if you have a REST API and the player expects the ongoing games view to be updated once the “start game” command has executed. This can be achieved by other means (RSocket, Websockets, server-sent events, polling) but synchronous updates is simple and works quite well in many cases.

Now that we have the code that registers ongoing games, we can call it from our from the application service:

RegisterOngoingGame registerOngoingGame = ..
applicationService.execute(gameId, events -> WordGuessingGame.guessWord(events, guess), events -> {
    events.filter(event -> event instanceof GameWasStarted)
         .findFirst()
         .map(GameWasStarted.class::cast)
         .ifPresent(registerOngoingGame::registerGameAsOngoingWhenGameWasStarted)
});

val registerOngoingGame : RegisterOngoingGame = ..
applicationService.execute(gameId, { events -> WordGuessingGame.guessWord(events, guess) }) { events -> 
    val gameWasStarted = events.find { event is GameWasStarted }
    if(gameWasStarted != null) {
        registerOngoingGame.registerGameAsOngoingWhenGameWasStarted(gameWasStarted) 
    }
}

Voila! Now registerGameAsOngoingWhenGameWasStarted will be called after the events returned from WordGuessingGame.guessWord(..) is written to the event store. You can however improve on the code above and make use of the executePolicy method shipped with the application service in the org.occurrent.application.service.blocking.PolicySideEffect. The code can then be refactored to this:

applicationService.execute(gameId, events -> WordGuessingGame.guessWord(events, guess), executePolicy(GameWasStarted.class, registerOngoingGame::registerGameAsOngoingWhenGameWasStarted)); 

If using the Kotlin extension functions (org.occurrent.application.service.blocking.executePolicy) you can write the code like this:

applicationService.execute(gameId, { events -> WordGuessingGame.guessWord(events, guess) }, executePolicy<GameWasStarted>(registerOngoingGame::registerGameAsOngoingWhenGameWasStarted))

Policies can also be composed:

RegisterOngoingGame registerOngoingGame  = ..
RemoveFromOngoingGamesWhenGameEnded removeFromOngoingGamesWhenGameEnded = ..

applicationService.execute(gameId, events -> WordGuessingGame.guessWord(events, guess), 
                           executePolicy(GameWasStarted.class, registerOngoingGame::registerGameAsOngoingWhenGameWasStarted)
                            .andThenExecuteAnotherPolicy(removeFromOngoingGamesWhenGameEnded::removeFromOngoingGamesWhenGameEnded));

val registerOngoingGame : RegisterOngoingGame = ..
val removeFromOngoingGamesWhenGameEnded : RemoveFromOngoingGamesWhenGameEnded = ..

applicationService.execute(gameId, { events -> WordGuessingGame.guessWord(events, guess) }, 
                            executePolicies(registerOngoingGame::registerGameAsOngoingWhenGameWasStarted, 
                                            removeFromOngoingGamesWhenGameEnded::removeFromOngoingGamesWhenGameEnded))

Application Service Transactional Side-Effects

In the example above, writing the events to the event store and executing policies is not an atomic operation. If your app crashes after the call to registerOngoingGame::registerGameAsOngoingWhenGameWasStarted but before removeFromOngoingGamesWhenGameEnded::removeFromOngoingGamesWhenGameEnded, you will need to handle idempotency. But if your policies/side-effects are writing data to the same database as the event store you can make use of transactions to write everything atomically! This is very easy if you’re using a Spring EventStore. What you need to do is to wrap the ApplicationService provided by Occurrent in your own application service, something like this:

@Service
public class CustomApplicationServiceImpl implements ApplicationService<DomainEvent> {
	private final GenericApplicationService<DomainEvent> occurrentApplicationService;

	public CustomApplicationService(GenericApplicationService<DomainEvent> occurrentApplicationService) {
		this.occurrentApplicationService = occurrentApplicationService;
	}

	@Transactional
	@Override
    public void execute(String gameId, Function<Stream<DomainEvent>, Stream<DomainEvent>> functionThatCallsDomainModel, Consumer<Stream<DomainEvent>> sideEffect) {
		occurrentApplicationService.execute(gameId, functionThatCallsDomainModel, sideEffect);
    }
}

@Service
class CustomApplicationServiceImpl(val occurrentApplicationService:  GenericApplicationService<DomainEvent>) : ApplicationService<DomainEvent> {

	@Transactional
    override fun execute(gameId : String, functionThatCallsDomainModel: Function<Stream<DomainEvent>, Stream<DomainEvent>> , sideEffect : Consumer<Stream<DomainEvent>>) {
		occurrentApplicationService.execute(gameId, functionThatCallsDomainModel, sideEffect)
    }
}

Given that you’ve defined a MongoTransactionManager in your Spring Boot configuration (and using this when creating your event store instance) the side-effects and events are written atomically in the same transaction!

Application Service Kotlin Extensions

If you’re using Kotlin chances are that your domain model is using a Sequence instead of a java Stream:

object WordGuessingGame {
    fun guessWord(events : Sequence<DomainEvent>, guess : String) : Sequence<DomainEvent> {
        // Implementation
    }    
}

Occurrent provides a set of extension functions for Kotlin in the application service module:

<dependency>
    <groupId>org.occurrent</groupId>
    <artifactId>application-service-blocking</artifactId>
    <version>0.19.7</version>
</dependency>

compile 'org.occurrent:application-service-blocking:0.19.7'

libraryDependencies += "org.occurrent" % "application-service-blocking" % "0.19.7"

@Grab(group='org.occurrent', module='application-service-blocking', version='0.19.7') 

[org.occurrent/application-service-blocking "0.19.7"]

'org.occurrent:application-service-blocking:jar:0.19.7'

<dependency org="org.occurrent" name="application-service-blocking" rev="0.19.7" />

You can then use one of the org.occurrent.application.service.blocking.execute extension functions to do:

applicationService.execute(gameId) { events : Sequence<DomainEvent> -> 
    WordGuessingGame.guessWord(events, guess)
}

Sagas

A “saga” can be used to represent and coordinate a long-lived business transaction/process (where “long-lived” is kind of arbitrary). This is an advanced subject and you should try to avoid sagas if there are other means available to solve the problem (for example use policies if they are sufficient). Occurrent doesn’t provide or enforce any specific Saga implementation. But since Occurrent is a library you can hook in already existing solutions, for example:

• Temporal - Open source microservices orchestration platform for running mission critical code at any scale.
• zio-saga - If you’re using Scala and zio (there’s also a cats implementation).
• Apache Camel Saga - If you’re using Java and don’t mind bringing in Apache Camel as a dependency.
• nflow - Battle-proven solution for orchestrating business processes in Java.
• saga-coordinator-java - Saga Coordinator as a Finite State Machine (FSM) in Java.
• Baker - Baker is a library that reduces the effort to orchestrate (micro)service-based process flows.
• Use the routing-slip pattern from the Enterprise Integration Patterns book.
• Represent sagas as todo lists. This is described in the event modeling documentation in the automation section.

The way to integrate Occurrent with any of these libraries/frameworks/patterns is to create a subscription that forwards the events written to the event store to the preferred library/framework/view.

Policy

A policy (aka reaction/trigger) can be used to deal with workflows such as “whenever this happens, do that”. For example, whenever a game is won, send an email to the winner. For simple workflows like this there’s typically no need for a full-fledged saga.

Asynchronous Policy

In Occurrent, you can create asynchronous policies by creating a subscription. Let’s consider the example above:

public class WhenGameWonThenSendEmailToWinnerPolicy {

    private final SubscriptionModel subscriptionModel;
    private final EmailClient emailClient;
    private final Players players;
    
    public WhenGameWonThenSendEmailToWinnerPolicy(SubscriptionModel subscriptionModel, EmailClient emailClient, Players players) {
        this.subscriptionModel = subscriptionModel;
        this.emailClient = emailClient;
        this.players = players;
    }
    
    @PostConstruct
    public void whenGameWonThenSendEmailToWinner() {
        subscriptionModel.subscribe("whenGameWonThenSendEmailToWinnerPolicy", filter(type("GameWon")), cloudEvent -> {
            String playerEmailAddress =  players.whatIsTheEmailAddressOfPlayer(playerIdIn(cloudEvent.getData()));
            emailClient.sendEmail(playerEmailAddress, "You won, yaay!");
        }          
    }
}

class WhenGameWonThenSendEmailToWinnerPolicy(val subscriptionModel : SubscriptionModel, 
                                             val emailClient : EmailClient, val players : Players) {

    @PostConstruct
    fun whenGameWonThenSendEmailToWinner() = 
        subscriptionModel.subscribe("whenGameWonThenSendEmailToWinnerPolicy", filter(type("GameWon")) { cloudEvent -> 
            val playerEmailAddress =  players.whatIsTheEmailAddressOfPlayer(playerIdIn(cloudEvent.getData()))
            emailClient.sendEmail(playerEmailAddress, "You won, yaay!")
        }          
}

You could also create a generic policy that simply forwards all events to another piece of infrastructure. For example, you may wish to forward all events to rabbitmq (by publishing them) or Spring’s event infrastructure, and then create policies that subscribes to events from these systems instead. There’s an example in the github repository that shows an example of how one can achieve this.

You may also want to look into the “todo-list” pattern described in the automation section on the in the event modeling website.

Synchronous Policy

In some cases, for example if you have a simple website and you want views to be updated when a command is dispatched by a REST API, it can be useful to update a policy in a synchronous fashion. The application service provided by Occurrent allows for this, please see the application service documentation for an example.

Snapshots

Snapshotting is an optimization technique that can be applied if it takes too long to derive the current state from an event stream for each command. There are several ways to do this and Occurrent doesn’t enforce any particular strategy. One strategy is to use so-called “snapshot events” (special events that contains a pre-calculated view of the state of an event stream at a particular time) and another technique is to write snapshots to another datastore than the event store.

The application service need to be modified to first load the up the snapshot and then load events that have not yet been materialized in the snapshot (if any).

Synchronous Snapshots

With Occurrent, you can trade-off write speed for understandability. For example, let’s say that you want to update the snapshot on every write and it should be consistent with the writes to the event store. One way to do this is to use Spring’s transactional support:

public class ApplicationService {

    private final EventStore eventStore;
    private final SnapshotRepository snapshotRepository;
    
    public ApplicationService(EventStore eventStore,  SnapshotRepository snapshotRepository) {
        this.eventStore = eventStore;
        this.snapshotRepository = snapshotRepository;
    }
    
    @Transactional
    public void execute(String streamId, BiFunction<Snapshot, Stream<CloudEvent>, Stream<CloudEvent>> functionThatCallsDomainModel) {
        // Read snapshot from a the snapshot repsitory 
        Snapshot snapshot = snapshotRepsitory.findByStreamId(streamId);
        long snapshotVersion = snapshot.version();        
    
        // Read all events for "streamId" from snapshotVersion  
        EventStream<CloudEvent> eventStream = eventStore.read(streamId, snapshotVersion, Long.MAX_VALUE);

        // Call a pure function from the domain model which returns a Stream of new events  
        List<CloudEvent> newEvents = functionThatCallsDomainModel.apply(snapshot.state(), eventStream).collect(Collectors.toList());

        // Convert domain events to cloud events and write them to the event store  
        eventStore.write(streamId, eventStream.version(), newEvents.stream());
        
        // Update the snapshot
        Snapshot updatedSnapshot = snapshot.updateFrom(newEvents.stream(), eventStream.version());
        snapshotRepsitory.save(updatedSnapshot);
    }
}

class ApplicationService(val eventStore : EventStore, val snapshotRepository : SnapshotRepository) {
    
    @Transactional
    fun execute(String streamId, functionThatCallsDomainModel : (Snapshot, Stream<CloudEvent>) -> Stream<CloudEvent>) {
        // Read snapshot from a the snapshot repsitory 
        val snapshot : Snapshot = snapshotRepsitory.findByStreamId(streamId)
        long snapshotVersion = snapshot.streamVersion()        
    
        // Read all events for "streamId" from snapshotVersion  
        val eventStream = eventStore.read(streamId, snapshotVersion, Long.MAX_VALUE)

        // Call a pure function from the domain model which returns a Stream of new events  
        val newEvents = functionThatCallsDomainModel(snapshot.state(), eventStream).collect(Collectors.toList())

        // Convert domain events to cloud events and write them to the event store  
        eventStore.write(streamId, eventStream.version(), newEvents.stream())
        
        // Update the snapshot
        val updatedSnapshot = snapshot.updateFrom(newEvents.stream(), eventStream.version())
        snapshotRepsitory.save(updatedSnapshot)
    }
}

It’s quite likely that you don’t need to update the snapshot in every write (like it’s done in the example above). If you only wish to update the snapshot for every third event then you could do:

if (eventStream.version() - snapshot.version() >= 3) {
    Snapshot updatedSnapshot = snapshot.updateFrom(newEvents.stream(), eventStream.version());
    snapshotRepsitory.save(updatedSnapshot);
}

Asynchronous Snapshots

As an alternative to synchronous and fully-consistent snapshots, you can update snapshots asynchronously. You do this by creating a subscription that updates the snapshot. For example:

public class UpdateSnapshotWhenNewEventsAreWrittenToEventStore {

    private final SubscriptionModel subscriptionModel;
    private final SnapshotRepository snapshotRepository;
    
    public UpdateSnapshotWhenNewEventsAreWrittenToEventStore(SubscriptionModel subscriptionModel, SnapshotRepository snapshotRepository) {
        this.subscription = subscription;
        this.snapshotRepository = snapshotRepository;
    }
    
    @PostConstruct
    public void updateSnapshotWhenNewEventsAreWrittenToEventStore() {
        subscription.subscribe("updateSnapshots", cloudEvent -> {
            String streamId = OccurrentExtensionGetter.getStreamId(cloudEvent);
            long streamVersion = OccurrentExtensionGetter.getStreamVersion(cloudEvent);
            
            Snapshot snapshot = snapshotRepository.findByStreamId(streamId);        
            snapshot.updateFrom(cloudEvent, streamVersion);
            snapshotRepository.save(snapshot);
        }          
    }
}

class UpdateSnapshotWhenNewEventsAreWrittenToEventStore(val subscription : BlockingSubscription, 
                                                        val snapshotRepository : SnapshotRepository) {

    @PostConstruct
    fun updateSnapshotWhenNewEventsAreWrittenToEventStore() {
        subscription.subscribe("updateSnapshots", { cloudEvent -> 
            String streamId = OccurrentExtensionGetter.getStreamId(cloudEvent)
            long streamVersion = OccurrentExtensionGetter.getStreamVersion(cloudEvent)
            
            Snapshot snapshot = snapshotRepository.findByStreamId(streamId)        
            snapshot.updateFrom(cloudEvent, streamVersion)
            snapshotRepository.save(snapshot)
        }          
    }
}

It’s quite likely that you don’t need to update the snapshot in every write (like it’s done in the example above). If you only wish to update the snapshot for every third event then you could do:

if (streamVersion - snapshot.version() >= 3) {
    Snapshot updatedSnapshot = snapshot.updateFrom(newEvents.stream(), eventStream.version());
    snapshotRepsitory.save(updatedSnapshot);
}

Closing the Books

This is a pattern that can be applied instead of updating snapshots for every n event. The idea is to try to keep event streams short and instead create snapshots periodically. For example, once every month we run a job that creates snapshots for certain event streams. This is especially well suited for problem domains where “closing the books” is a concept in the domain (such as accounting).

Deadlines

Deadlines (aka scheduling, alarm clock) is a very handy technique to schedule to something to be executed in the future. Imagine, for example, a multiplayer game (like word guessing game shown in previous examples), where we want to game to end automatically after 10 hours of inactivity. This means that as soon as a player has made a guess, we’d like to schedule a “timeout game command” to be executed after 10 hours.

The way it works in Occurrent is that you schedule a Deadline (org.occurrent.deadline.api.blocking.Deadline) using a DeadlineScheduler (org.occurrent.deadline.api.blocking.DeadlineScheduler) implementation. The Deadline is a date/time in the future when the deadline is up. To handle the deadline, you also register a DeadlineConsumer (org.occurrent.deadline.api.blocking.DeadlineConsumer) to a DeadlineConsumerRegistry (org.occurrent.deadline.api.blocking.DeadlineConsumerRegistry) implementation, and it’ll be invoked when a deadline is up. For example:

// In some method we schedule a deadline two hours from now with data "hello world" 
var deadlineId = UUID.randomUUID(); 
var deadlineCategory = "hello-world"; 
var deadline = Deadline.afterHours(2);
deadlineScheduler.schedule(deadlineId, deadlineCategory, deadline, "hello world");

// In some other method, during application startup, we register a deadline consumer to the registry for the "hello-world" deadline category
deadlineConsumerRegistry.register("hello-world", (deadlineId, deadlineCategory, deadline, data) -> System.out.println(data));

In the example above, the deadline consumer will print “hello world” after 2 hours.

There are two implementations of DeadlineScheduler and DeadlineConsumerRegistry, JobRunr and InMemory.

JobRunr Deadline Scheduler

This is a persistent (meaning that your application can be restarted and deadlines are still around) DeadlineScheduler based on JobRunr. To get started, depend on:

<dependency>
    <groupId>org.occurrent</groupId>
    <artifactId>deadline-jobrunr</artifactId>
    <version>0.19.7</version>
</dependency>

compile 'org.occurrent:deadline-jobrunr:0.19.7'

libraryDependencies += "org.occurrent" % "deadline-jobrunr" % "0.19.7"

@Grab(group='org.occurrent', module='deadline-jobrunr', version='0.19.7') 

[org.occurrent/deadline-jobrunr "0.19.7"]

'org.occurrent:deadline-jobrunr:jar:0.19.7'

<dependency org="org.occurrent" name="deadline-jobrunr" rev="0.19.7" />

You then need to create an instance of org.jobrunr.scheduling.JobRequestScheduler (see JobRunr documentation for different ways of doing this). Once you have a JobRequestScheduler you need to create an instance of org.occurrent.deadline.jobrunr.JobRunrDeadlineScheduler:

JobRequestScheduler jobRequestScheduler = ..
DeadlineScheduler deadlineScheduler = new JobRunrDeadlineScheduler(jobRequestScheduler); 

You also need to create an instance of org.occurrent.deadline.jobrunr.JobRunrDeadlineConsumerRegistry:

DeadlineConsumerRegistry deadlineConsumerRegistry = new JobRunrDeadlineConsumerRegistry();  

You register so-called “deadline consumers” to the DeadlineConsumerRegistry for a certain “category” (see example above). A deadline consumer will be invoked once a deadline is up. Note that you can only have one deadline consumer instance per category. You want to register your deadline consumer everytime your application starts up. If you’re using Spring, you can, for example, do this using a @PostConstructor method:

@PostConstruct
void registerDeadlineConsumersOnApplicationStart() {
    deadlineConsumerRegistry.register("CancelPayment", (id, category, deadline, data) -> {
        CancelPayment cancelPayment = (CancelPayment) data; 
        paymentApi.cancel(cancelPayment.getPaymentId());    
    }):
}

The example above will register a deadline consumer for the “CancelPayment” category and call an imaginary api (paymentApi) to cancel the payment. The deadline consumer will be called by Occurrent when the scheduled deadline is up. Here’s an example of you can schedule this deadline using the JobRunrDeadlineConsumerRegistry, but first lets see what CancelPayment looks like:

public class CancelPayment {
    private String paymentId;

    CancelPayment() {
    }

    public CancelPayment(String paymentId) {
        this.paymentId = paymentId;
    }
    
    public void setPaymentId(String paymentId) {
        this.paymentId = paymentId;
    }

    public String getPaymentId() {
        return paymentId;
    }
}

As you can see it’s a regular Java POJO. This is very important since JobRunr needs to serialize/de-serialize this class to the database. Typically, this is done using Jackson (so it’s fine to use Jackson annotations etc), but JobRunr has support for other mappers as well.

Now lets see how we can schedule a “CancelPayment”:

String paymentId = ...
deadlineScheduler.schedule(UUID.randomUUID(), "CancelPayment", Deadline.afterWeeks(2), new CancelPayment(paymentId));

This will schedule a deadline after 2 weeks, that’ll be picked-up by the deadline consumer registered in the registerDeadlineConsumersOnApplicationStart method. Note that in this case, the class (CancelPayment) has the same name as the category, but this is not required.

Here’s an example of you can setup Occurrent Deadline Scheduling in Spring Boot:

@Configuration
public class DeadlineSpringConfig {

    @Bean
    JobRunrConfigurationResult initJobRunr(ApplicationContext applicationContext, MongoClient mongoClient,
                                           @Value("${spring.data.mongodb.uri}") String mongoUri) {
        var connectionString = new ConnectionString(mongoUri);
        var database = connectionString.getDatabase();

        return JobRunr.configure()
                .useJobActivator(applicationContext::getBean)
                .useStorageProvider(new MongoDBStorageProvider(mongoClient, database, "jobrunr-"))
                .useBackgroundJobServer()
                .useDashboard(
                        JobRunrDashboardWebServerConfiguration
                                .usingStandardDashboardConfiguration()
                                .andPort(8082)
                                .andAllowAnonymousDataUsage(false)
                )
                .initialize();
    }

    @PostConstruct
    void destroyJobRunnerOnShutdown() {
        JobRunr.destroy();
    }

    @Bean
    DeadlineScheduler deadlineScheduler(JobRunrConfigurationResult jobRunrConfigurationResult) {
        return new JobRunrDeadlineScheduler(jobRunrConfigurationResult.getJobRequestScheduler());
    }

    @Bean
    DeadlineConsumerRegistry deadlineConsumerRegistry() {
        return new JobRunrDeadlineConsumerRegistry();
    }
}

Have a look at JobRunr for more configuration options.

In-Memory Deadline Scheduler

This is an in-memory, non-persistent (meaning that scheduled deadlines will be lost on application restart), DeadlineScheduler. To get started, depend on:

<dependency>
    <groupId>org.occurrent</groupId>
    <artifactId>deadline-inmemory</artifactId>
    <version>0.19.7</version>
</dependency>

compile 'org.occurrent:deadline-inmemory:0.19.7'

libraryDependencies += "org.occurrent" % "deadline-inmemory" % "0.19.7"

@Grab(group='org.occurrent', module='deadline-inmemory', version='0.19.7') 

[org.occurrent/deadline-inmemory "0.19.7"]

'org.occurrent:deadline-inmemory:jar:0.19.7'

<dependency org="org.occurrent" name="deadline-inmemory" rev="0.19.7" />

Next, you need to create in instance of org.occurrent.deadline.inmemory.InMemoryDeadlineScheduler and org.occurrent.deadline.inmemory.InMemoryDeadlineConsumerRegistry. In order for these two components to communicate with each other, you also need to provide an instance of a e java.util.concurrent.BlockingDeque to the constructor. Here’s an example:

BlockingDeque<Object> queue = new LinkedBlockingDeque<>();
DeadlineConsumerRegistry deadlineConsumerRegistry = new InMemoryDeadlineConsumerRegistry(queue);
DeadlineConsumerRegistry deadlineScheduler = new InMemoryDeadlineScheduler(queue);

You can configure things, such as poll interval and retry strategy, for InMemoryDeadlineConsumerRegistry by supplying an instance of org.occurrent.deadline.inmemory.InMemoryDeadlineConsumerRegistry$Config as the second constructor argument:

new InMemoryDeadlineConsumerRegistry(queue, new Config().pollIntervalMillis(300).retryStrategy(RetryStrategy.fixed(Duration.of(2, SECONDS))));

Note that it’s very important to call shutdown on both InMemoryDeadlineConsumerRegistry and InMemoryDeadlineScheduler on application/test end.

For usage examples, see Deadlines and JobRunr Scheduler.

Other Ways of Expressing Deadlines

If you don’t want to use any of the Occurrent libraries for deadline scheduling, or if you’re looking for more features that are not (yet) available, you can use other libraries from the Java ecosystem, such as:

• JobRunr - An easy way to perform background processing in Java. Distributed and backed by persistent storage.
• Quartz - Can be used to create simple or complex schedules for executing tens, hundreds, or even tens-of-thousands of jobs.
• db-scheduler - Task-scheduler for Java that was inspired by the need for a clustered java.util.concurrent.ScheduledExecutorService simpler than Quartz.
• Spring Scheduling - Worth looking into if you’re already using Spring.

Getting started

Getting started with Occurrent involves these steps:

1. Choose an underlying datastore for an event store. Luckily there are only two choices at the moment, MongoDB and an in-memory implementation. Hopefully this will be a more difficult decision in the future :)
2. Once a datastore has been decided, it’s time to choose an EventStore implementation for this datastore since there may be more than one.
3. If you need subscriptions (i.e. the ability to subscribe to changes from an EventStore) then you need to pick a library that implements this for the datastore that you’ve chosen. Again, there may be several implementations to choose from.
4. If a subscriber needs to be able to continue from where it left off on application restart, it’s worth looking into a so called position storage library. These libraries provide means to automatically (or selectively) store the position for a subscriber to a datastore. Note that the datastore that stores this position can be a different datastore than the one used as EventStore. For example, you can use MongoDB as EventStore but store subscription positions in Redis.
5. You’re now good to go, but you may also want to look into more higher-level components if you don’t have the need to role your own. We recommend looking into:
   • Application Service
   • Subscription DSL
   • Query DSL
   • Retry Component
   • Decider’s

Choosing An EventStore

There are currently two different datastores to choose from, MongoDB and In-Memory.

MongoDB

Uses MongoDB, version 4.2 or above, as the underlying datastore for the CloudEvents. All implementations use transactions to guarantee consistent writes (see WriteCondition). Each EventStore will automatically create a few indexes on startup to allow for fast consistent writes, optimistic concurrency control and to avoid duplicated events. These indexes can also be used in queries against the EventStore (see EventStoreQueries).

There are three different MongoDB EventStore implementations to choose from:

• Native Driver
• Spring (Blocking)
• Spring (Reactive)

MongoDB Schema

All MongoDB EventStore implementations tries to stay as close as possible to the CloudEvent’s specification even in the persitence layer. Occurrent, by default, automatically adds a custom “Occurrent extension” to each cloud event that is written to an EventStore. The Occurrent CloudEvent Extension consists of these attributes:

A json schema describing a complete Occurrent CloudEvent, as it will be persisted to a MongoDB collection, can be found here (a “raw” cloud event json schema can be found here for comparison).

Note that MongoDB will automatically add an _id field (which is not used by Occurrent). The reason why the CloudEvent id attribute is not stored as _id in MongoDB is that the id of a CloudEvent is not globally unique! The combination of id and source is a globally unique CloudEvent. Note also that _id will not be included when the CloudEvent is read from an EventStore.