Integrating GlassFish with Apache Kafka for Java development

17 Sep 2023

Apache Kafka has become a popular choice for building scalable and distributed streaming applications. Its ability to handle large volumes of data and provide real-time processing makes it an ideal choice for building modern applications. If you are using GlassFish as your Java application server, integrating it with Apache Kafka can offer new possibilities for efficient development. In this blog post, we will explore how to integrate GlassFish with Apache Kafka and utilize its features for Java development.

Getting Started

Before we begin, make sure you have GlassFish and Apache Kafka installed and properly configured on your system. If you haven’t already installed them, you can download them from their respective websites and follow the installation instructions.

Step 1: Adding Kafka Dependencies

To integrate GlassFish with Apache Kafka, you need to include the Kafka dependencies in your GlassFish project. Open your project in your preferred Java IDE and add the following dependencies to your pom.xml file if you are using Maven:

<dependency>
    <groupId>org.apache.kafka</groupId>
    <artifactId>kafka-clients</artifactId>
    <version>2.8.0</version>
</dependency>
<dependency>
    <groupId>org.apache.kafka</groupId>
    <artifactId>kafka_2.13</artifactId>
    <version>2.8.0</version>
</dependency>

If you are not using Maven, you can manually download the Kafka JAR files and add them to your project’s classpath.

Step 2: Creating a Kafka Producer

With the Kafka dependencies added to your project, you can now create a Kafka producer that will publish messages to Kafka topics. Here’s an example code snippet to create a simple Kafka producer using the Kafka Java API:

import org.apache.kafka.clients.producer.*;

public class KafkaProducerExample {
    public static void main(String[] args) {
        String bootstrapServers = "localhost:9092";
        String topicName = "my_topic";
        
        // Set producer properties
        Properties properties = new Properties();
        properties.put("bootstrap.servers", bootstrapServers);
        properties.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        properties.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        
        // Create Kafka producer
        KafkaProducer<String, String> producer = new KafkaProducer<>(properties);
        
        // Publish messages to Kafka topic
        for (int i = 0; i < 10; i++) {
            String message = "Message " + i;
            ProducerRecord<String, String> record = new ProducerRecord<>(topicName, message);
            producer.send(record);
        }
        
        // Close the producer
        producer.close();
    }
}

Step 3: Consuming Kafka Messages

To consume Kafka messages in your GlassFish application, you can create a Kafka consumer. Here’s an example code snippet to create a simple Kafka consumer that subscribes to a topic and processes incoming messages:

import org.apache.kafka.clients.consumer.*;
import java.time.Duration;
import java.util.Collections;
import java.util.Properties;

public class KafkaConsumerExample {
    public static void main(String[] args) {
        String bootstrapServers = "localhost:9092";
        String topicName = "my_topic";
        String groupId = "my_group";
        
        // Set consumer properties
        Properties properties = new Properties();
        properties.put("bootstrap.servers", bootstrapServers);
        properties.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        properties.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        properties.put("group.id", groupId);
        
        // Create Kafka consumer
        KafkaConsumer<String, String> consumer = new KafkaConsumer<>(properties);
        
        // Subscribe to topic
        consumer.subscribe(Collections.singletonList(topicName));
        
        // Consume messages
        while (true) {
            ConsumerRecords<String, String> records = consumer.poll(Duration.ofMillis(100));
            
            for (ConsumerRecord<String, String> record : records) {
                System.out.println("Received message: " + record.value());
            }
        }
    }
}

Conclusion

Integrating GlassFish with Apache Kafka provides an excellent opportunity for building efficient and scalable Java applications. By leveraging the power of Kafka’s distributed streaming capabilities, you can enhance your development process and handle large volumes of data with ease. Whether you are building real-time analytics dashboards, event-driven applications, or data streaming pipelines, the integration of GlassFish and Apache Kafka can pave the way for seamless and performant Java development.

#GlassFish #ApacheKafka