Using Kafka in Spring Boot Application

Kafka Consumer and Producer in Spring Boot

1. Dependency Required

You need to include the following dependency in your pom.xml or build.gradle:

<dependency>
    <groupId>org.springframework.kafka</groupId>
    <artifactId>spring-kafka</artifactId>
    <version>2.7.0</version>
</dependency>

Also See: How to Setup Kafka Locally on Windows

2. Kafka Configuration in application.properties

You need to configure Kafka for both Producer and Consumer in your application.properties:

# Kafka Producer configuration
spring.kafka.bootstrap-servers=localhost:9092
# Kafka Consumer configuration
spring.kafka.consumer.group-id=my-group

3. Configuring Kafka Producer with @KafkaTemplate

To configure a Kafka producer, you can use the @KafkaTemplate annotation. You can serialize the message to JSON format using the JsonSerializer:

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.support.serializer.JsonSerializer;
import org.springframework.stereotype.Component;

@Component
public class MyKafkaProducer {

    @Autowired
    private KafkaTemplate<String, Object> kafkaTemplate;

    public void sendMessage(String topic, Object message) {
        kafkaTemplate.send(topic, message);
    }
}

4. Configuring Kafka Consumer with @KafkaListener

To configure a Kafka consumer, you can use the @KafkaListener annotation. You can deserialize the message from JSON format using the JsonDeserializer:

import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Component;

@Component
public class MyKafkaConsumer {

    @KafkaListener(topics = "my-topic", groupId = "my-group")
    public void listen(String message) {
        System.out.println("Received Message: " + message);
    }
}

Conclusion

Spring Boot makes it easy to implement Kafka consumer and producer using the Spring Kafka library. By using annotations like @KafkaTemplate and @KafkaListener, developers can quickly set up Kafka communication in their applications.