Hazelcast IMDG (In-Memory Data Grid) is a distributed computing system that provides fast and scalable in-memory data storage. It allows you to distribute and store data across multiple nodes in a cluster, providing high availability and fault tolerance.

One of the key features of Hazelcast IMDG is its support for Continuous Queries. Continuous Queries allow you to define predicates that are continuously evaluated on the distributed data. When a change occurs on the data that matches the predicate, a notification event is triggered, providing you with the most up-to-date data in real-time.

In this article, we will explore how to work with Hazelcast IMDG Continuous Queries in Java.

Step 1: Set up Hazelcast IMDG cluster

Before we can start working with Continuous Queries, we need to set up a Hazelcast IMDG cluster. Here’s an example of how to create a basic cluster with two nodes:

import com.hazelcast.config.Config;
import com.hazelcast.config.XmlConfigBuilder;
import com.hazelcast.core.Hazelcast;
import com.hazelcast.core.HazelcastInstance;

public class HazelcastCluster {
    public static void main(String[] args) {
        Config config = new XmlConfigBuilder().build();
        HazelcastInstance instance = Hazelcast.newHazelcastInstance(config);

        // Additional code for cluster setup, data loading, etc.
    }
}

Step 2: Create Continuous Query

Once the Hazelcast IMDG cluster is set up, we can define a Continuous Query to monitor the data changes. Here’s an example of how to create a Continuous Query that matches data with a specific condition:

import com.hazelcast.core.HazelcastInstance;
import com.hazelcast.core.IMap;
import com.hazelcast.core.EntryEvent;
import com.hazelcast.map.listener.EntryAddedListener;

public class ContinuousQueryExample {
    public static void main(String[] args) {
        // Get Hazelcast instance
        HazelcastInstance instance = Hazelcast.newHazelcastInstance();

        // Get the distributed map
        IMap<String, Integer> map = instance.getMap("myMap");

        // Create Continuous Query
        map.addEntryListener(new EntryAddedListener<String, Integer>() {
            @Override
            public void entryAdded(EntryEvent<String, Integer> event) {
                String key = event.getKey();
                Integer value = event.getValue();
                System.out.println("New entry added - Key: " + key + ", Value: " + value);
            }
        }, true);
        
        // Additional code for data manipulation, etc.
    }
}

In this example, we are adding an entry listener to the distributed map. The listener will be notified whenever a new entry is added to the map. We can then perform any desired actions based on the received event.

Step 3: Perform Data Operations

Once the Continuous Query is set up, we can perform data operations on the distributed map and observe the events being triggered. Here’s an example of how to add data to the map:

map.put("key1", 10);
map.put("key2", 20);

When these put operations are executed, the Continuous Query will be triggered if the conditions defined in the predicate are met.

Conclusion

Hazelcast IMDG Continuous Queries provide a powerful way to receive real-time notifications for data changes in a distributed environment. By using Continuous Queries, you can build reactive applications that respond to data modifications in real-time.

By following the steps outlined in this article, you can get started with using Hazelcast IMDG Continuous Queries in your Java applications. Experiment with different predicates and event handlers to make the most out of this powerful feature.

#Java #Hazelcast #ContinuousQueries