Hazelcast Jet is a high-performance distributed computing platform that allows you to process large amounts of data in near real-time. It provides a set of connectors to integrate with various external systems and data sources, making it easier to ingest and process data from different sources.

In this blog post, we will explore how to use Hazelcast Jet connectors in Java applications to seamlessly connect and process data from external systems.

Setting up the Hazelcast Jet Connectors

To start using Hazelcast Jet connectors in your Java application, you need to include the necessary dependencies in your project. You can do this by adding the following Maven dependencies to your pom.xml file:

<dependencies>
    <!-- Hazelcast Jet Core -->
    <dependency>
        <groupId>com.hazelcast.jet</groupId>
        <artifactId>jet-core</artifactId>
        <version>${hazelcast.jet.version}</version>
    </dependency>

    <!-- Hazelcast Jet Connectors -->
    <dependency>
        <groupId>com.hazelcast.jet</groupId>
        <artifactId>jet-connectors</artifactId>
        <version>${hazelcast.jet.version}</version>
    </dependency>
</dependencies>

Make sure to replace ${hazelcast.jet.version} with the appropriate version of Hazelcast Jet.

Using Hazelcast Jet Connectors

Hazelcast Jet provides connectors for various data sources such as Apache Kafka, JDBC databases, Apache Hadoop, and more. Here’s an example of how to use the Hazelcast Jet Kafka connector to consume data from a Kafka topic:

import com.hazelcast.jet.pipeline.Pipeline;
import com.hazelcast.jet.pipeline.Sinks;
import com.hazelcast.jet.pipeline.Sources;
import com.hazelcast.jet.pipeline.StreamSource;

public class KafkaExample {

    public static void main(String[] args) {
        Pipeline pipeline = Pipeline.create();
        StreamSource<String> source = Sources.kafka("bootstrap-servers", "topic");
        pipeline.readFrom(source)
                .writeTo(Sinks.logger());
        
        // Start the Jet job
        JetInstance jet = Jet.newJetInstance();
        jet.newJob(pipeline).join();
    }
}

In the above code, we create a pipeline and define a Kafka source using the Sources.kafka() method. We specify the bootstrap servers and the Kafka topic from which we want to consume data. We then use the writeTo() method to specify the sink, which in this case is a logger sink that will simply log the received data.

Once the pipeline is defined, we create a Hazelcast Jet instance and submit the pipeline as a job using the newJob() method.

Conclusion

Hazelcast Jet connectors provide a convenient way to connect and process data from external systems in your Java applications. By leveraging the connectors provided by Hazelcast Jet, you can easily integrate with various data sources and perform complex data processing tasks.

Start using Hazelcast Jet connectors in your Java applications and unleash the power of distributed computing for your data processing needs.

#hazelcast #jet #connectors