Using Different Deserializers for Multiple Topics in Kafka with Spring Boot

Learn how to configure different deserializers for various Kafka topics in Spring Boot, enabling seamless message consumption from diverse formats like Avro and JSON.
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Different Deserializers for Different Topics in Kafka with Spring Boot

When working with Apache Kafka in a Spring Boot application, you might encounter situations where you need to consume messages from multiple topics that utilize different data formats. An example of this is when you need to handle one topic with messages in Avro format and another with messages in JSON format. In this guide, we'll explore how to configure your Spring Boot application to utilize different deserializers for these distinct topics.

The Challenge

In your current setup, you are successfully consuming messages from various Kafka topics using the @ KafkaListener annotation, and all these messages are in Avro format via the KafkaAvroDeserializer. However, with the introduction of a new topic containing messages in JSON format, you now face the challenge of integrating a different deserializer while maintaining your existing functionality for the legacy topics.

The Solution

To address this challenge, you will need to configure your Kafka consumer settings to differentiate between the deserializers for the two types of messages: one using JsonDeserializer for the new topic, and the other using KafkaAvroDeserializer for the legacy topics. Here’s how you can achieve this step-by-step.

1. Configuration Class

Create a configuration class in your Spring Boot application to define the KafkaListener containers. Below is an example of how to set up the class:

[[See Video to Reveal this Text or Code Snippet]]

2. Generating a Consumer Factory

In the configuration above, the generateFactory method creates a consumer factory using the specified key-value deserializers. You will need to create separate factory beans for each topic depending on its deserializer requirements:

For the JSON topic, we use JsonDeserializer as shown.

For the Avro topics, you will need to define and implement a similar consumer factory that utilizes KafkaAvroDeserializer.

3. Configuring the Kafka Listener

Once you have defined your container factories, you can declare your @ KafkaListener for the JSON topic as follows:

[[See Video to Reveal this Text or Code Snippet]]

Make sure the containerFactory reference corresponds to the bean name defined in your configuration (kafkaListenerContainerFactoryJson). This setup will correctly deserialize messages using JsonDeserializer when consuming from the JSON topic.

Conclusion

By implementing these configurations, you can effectively manage multiple Kafka topics with varying message formats using Spring Boot's Kafka support. The key takeaway here is that by defining separate consumer factories for distinct deserializers, your application remains flexible and capable of handling a variety of data formats with ease. Whether you are dealing with Avro or JSON, your Kafka listeners can be tailored to suit your messaging needs.

By following the outlined steps, you will ensure your Spring Boot application remains robust and ready to tackle any new requirements as they arise. Happy coding!