Implementing Java RMI with Apache Kafka Streams

14 Sep 2023

Apache Kafka is a popular distributed streaming platform that allows you to send, store, and process streams of records in real-time. One of the powerful features of Kafka is its ability to process data with low latency and high scalability. Java RMI (Remote Method Invocation) is a Java API that allows you to invoke methods on remote objects over a network. In this blog post, we will explore how we can combine the capabilities of Apache Kafka Streams and Java RMI to create distributed stream processing applications.

Getting Started

To get started, you will need to set up a Kafka cluster and have a basic understanding of Kafka concepts such as topics, partitions, and consumers/producers. You will also need to have a good understanding of Java RMI and how to define remote interfaces and implement remote objects.

Setting up the Project

To implement Java RMI with Apache Kafka Streams, you will need to add Kafka Streams and RMI dependencies to your project. Here’s an example pom.xml file with the necessary dependencies:

<dependencies>
    <!-- Kafka Streams -->
    <dependency>
        <groupId>org.apache.kafka</groupId>
        <artifactId>kafka-streams</artifactId>
        <version>2.7.0</version>
    </dependency>

    <!-- Java RMI -->
    <dependency>
        <groupId>javax.rmi</groupId>
        <artifactId>javax.rmi-api</artifactId>
        <version>1.0.2</version>
    </dependency>
</dependencies>

Defining the Remote Interface

First, we need to define the remote interface that our distributed application will use. This interface will specify the methods that can be invoked on the remote objects. For example:

import java.rmi.Remote;
import java.rmi.RemoteException;

public interface RemoteService extends Remote {
    int add(int a, int b) throws RemoteException;
    String concatenate(String a, String b) throws RemoteException;
}

Implementing the Remote Object

Next, we need to implement the remote object that will be invoked by the clients. This object should implement the remote interface and provide the actual implementation of the methods. For example:

import java.rmi.RemoteException;
import java.rmi.server.UnicastRemoteObject;

public class RemoteServiceImpl extends UnicastRemoteObject implements RemoteService {
    protected RemoteServiceImpl() throws RemoteException {
        super();
    }

    @Override
    public int add(int a, int b) throws RemoteException {
        return a + b;
    }

    @Override
    public String concatenate(String a, String b) throws RemoteException {
        return a + b;
    }
}

Creating the Kafka Streams Application

Now, let’s create a Kafka Streams application that will process the input data and invoke the remote methods. Here’s a basic example:

import org.apache.kafka.streams.KafkaStreams;
import org.apache.kafka.streams.StreamsBuilder;
import org.apache.kafka.streams.StreamsConfig;
import org.apache.kafka.streams.kstream.Consumed;

import java.rmi.Naming;
import java.util.Properties;

public class KafkaStreamsRMIApp {
    public static void main(String[] args) throws Exception {
        // Set up Kafka Streams properties
        Properties config = new Properties();
        config.put(StreamsConfig.APPLICATION_ID_CONFIG, "kafka-streams-rmi-app");
        config.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");

        // Create the StreamsBuilder
        StreamsBuilder builder = new StreamsBuilder();

        // Build the Kafka Streams topology
        builder.stream("input-topic", Consumed.with(Serdes.String(), Serdes.String()))
                .foreach((key, value) -> {
                    try {
                        RemoteService remoteService = (RemoteService) Naming.lookup("//localhost/RemoteService");
                        int sum = remoteService.add(Integer.parseInt(key), Integer.parseInt(value));

                        System.out.println("Sum of " + key + " and " + value + " is " + sum);
                    } catch (Exception e) {
                        e.printStackTrace();
                    }
                });

        // Create and start the Kafka Streams application
        KafkaStreams streams = new KafkaStreams(builder.build(), config);
        streams.start();
    }
}

Conclusion

By combining the power of Apache Kafka Streams and Java RMI, you can build distributed stream processing applications that can invoke remote methods on remote objects. This allows you to leverage Kafka’s scalability and fault-tolerance while benefiting from the simplicity and convenience of Java RMI. Keep in mind that when working with distributed systems, it’s important to handle failure scenarios and ensure data consistency.