Hazelcast is an open-source in-memory data grid platform that provides distributed data structures, caching capabilities, and distributed computing features. One of the key features of Hazelcast is its support for distributed event journaling, which allows developers to track and process events in a distributed manner.

In this blog post, we will explore how to use Hazelcast’s distributed event journal in Java applications to store and process event data efficiently.

What is Hazelcast Distributed Event Journal?

Hazelcast Distributed Event Journal is a powerful feature that enables capturing and storing a stream of events in a distributed and fault-tolerant manner. It offers automatic replication and persistence of events, ensuring high availability and durability of the event data.

The distributed event journal provides real-time access to events, allowing you to perform various operations such as filtering, querying, and analyzing event data. It serves as a reliable source of truth for event-driven applications, enabling you to build robust and scalable systems.

Setting up Hazelcast Distributed Event Journal

To use the distributed event journal in your Java application, you need to add the Hazelcast library as a dependency in your project. You can do this by including the Maven/Gradle coordinates in your build configuration.

dependencies {
    implementation 'com.hazelcast:hazelcast-all:4.2.1'
}

After adding the dependency, you can create an instance of the Hazelcast client or server in your Java code, and then get the distributed event journal instance from it.

Config config = new Config();
HazelcastInstance hazelcastInstance = Hazelcast.newHazelcastInstance(config);
EventJournal<String> eventJournal = hazelcastInstance.getEventJournal("event-journal");

Writing Events to the Distributed Event Journal

Once you have obtained the event journal instance, you can start writing events to it. Each event added to the journal is automatically replicated across the Hazelcast cluster, ensuring fault tolerance and high availability.

for (int i = 0; i < 100; i++) {
    String event = "Event " + i;
    eventJournal.add(event);
}

In the above code snippet, we are adding 100 events to the event journal. Each event is a simple string, but you can store any serializable object as an event.

Reading Events from the Distributed Event Journal

To read events from the distributed event journal, you can use the readFromEventJournal method provided by the event journal instance. You can specify various parameters such as the offset, number of events to read, and filter criteria to retrieve specific events.

JournalCursor<String> cursor = eventJournal.readFromEventJournal(0, 100);
while (cursor.hasNext()) {
    EventJournalMapEvent<String> event = cursor.next();
    System.out.println("Received event: " + event.getNewValue());
}

In the above code snippet, we are reading the first 100 events from the event journal and printing the value of each event. The EventJournalMapEvent provides access to the old and new values of the event, allowing you to perform additional processing or transformations if needed.

Conclusion

Using Hazelcast distributed event journal in Java applications provides a reliable and scalable way to capture, store, and process event data in a distributed environment. It enables building event-driven systems that can handle large volumes of events and ensures data integrity and availability.

In this blog post, we have covered the basics of using the Hazelcast distributed event journal in Java applications. You can explore more advanced features and optimizations offered by Hazelcast to further enhance your event processing capabilities.

#distributedeventjournal #hazelcast