Implementing event sourcing with Java Streams API

15 Sep 2023

eventSourcing

Event sourcing is a powerful architectural pattern that captures and persists every mutation made to an application’s state as a series of events. It provides a reliable and flexible approach to restoring and replaying events, enabling a system to be rebuilt from scratch at any point in time.

In this blog post, we will explore how to implement event sourcing using the Java Streams API, a functional programming paradigm introduced in Java 8. We will leverage the Stream API’s powerful features to process and manipulate event streams efficiently.

Prerequisites

To follow along with the examples in this post, you need:

Java 8 or above installed on your machine.
A basic understanding of event sourcing principles.

Setting Up the Project

Before diving into the implementation, let’s set up a new Maven project with the necessary dependencies. Open your favorite IDE and create a new Maven project. Add the following dependencies to your pom.xml file:

<dependencies>
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter</artifactId>
        <version>2.5.4</version>
    </dependency>
</dependencies>

Implementing Event Sourcing

Creating the Event class

To start with event sourcing, we need to define the Event class. This class represents a single event in our system. An event typically contains a unique identifier, a timestamp, and relevant data. Here’s an example implementation:

public class Event {
    private UUID eventId;
    private LocalDateTime timestamp;
    private String data;

    public Event(UUID eventId, LocalDateTime timestamp, String data) {
        this.eventId = eventId;
        this.timestamp = timestamp;
        this.data = data;
    }

    // Getters and setters
}

Generating Event streams

Next, let’s generate a stream of events using the Java Streams API. We can use the Stream.generate() method to create an infinite stream of events. For simplicity, in this example, we’ll create a stream with a fixed number of events. Here’s an example:

Stream<Event> eventStream = Stream.generate(() ->
    new Event(UUID.randomUUID(), LocalDateTime.now(), "Sample event data")
).limit(100);

Processing Event streams

Now that we have our event stream, we can process and manipulate it using various operations provided by the Stream API. Let’s consider a scenario where we want to filter events based on certain criteria and perform some operations on the filtered stream. Here’s an example:

eventStream
    .filter(event -> event.getData().contains("important"))
    .map(Event::getTimestamp)
    .forEach(System.out::println);

In the above example, we filtered events containing the word “important” in their data and extracted their timestamps using the map() function. Then, we printed the timestamps to the console using the forEach() function.

Conclusion

In this blog post, we explored how to implement event sourcing using the Java Streams API. We learned how to generate an event stream and perform operations on it using the powerful features of the Stream API. Event sourcing can provide a robust foundation for building scalable and resilient systems, and by leveraging the Java Streams API, we can process event streams efficiently and effectively.

Implementing event sourcing with the Java Streams API opens up a world of possibilities for building event-driven applications. It allows for seamless event processing, filtering, and manipulation using a functional programming paradigm. By using streams, you can ensure that your event-driven system efficiently handles large volumes of events.

#eventSourcing #Java