Processing Kafka Message after the defined time in message in Spring Boot KafkaListener

As developers, we often encounter scenarios where we need to process Kafka messages after a certain delay or at a specific time. This can be achieved by making use of Spring Boot’s KafkaListener and custom deserialization. In this article, we will explore how to process Kafka messages after the time defined in the message itself using Spring Boot KafkaListener.

Why do we need this?

In many real-world scenarios, we might need to process messages after a certain delay or at a specific time. For example, let’s consider an e-commerce platform that sends order confirmations to customers via email. The confirmation email should be sent after a certain delay, say 30 minutes, to ensure that the order has been successfully processed. Similarly, in a banking application, payment notifications might need to be sent after a certain delay to ensure that the payment has been successfully processed.

How does it work?

The idea is to include a timestamp or delay in the Kafka message itself. When the message is consumed by the KafkaListener, it checks the timestamp or delay and decides whether to process the message immediately or schedule it for later processing. This can be achieved by using Spring Boot’s KafkaListener and custom deserialization.

Creating a custom deserializer

To include the timestamp or delay in the Kafka message, we need to create a custom deserializer that can deserialize the message and extract the timestamp or delay. Let’s create a custom deserializer for our Kafka message:

<code>
public class CustomDeserializer implements Deserializer<MyMessage> {

    @Override
    public void configure(Map<String, ?> configs, boolean isKey) {
        // No-op
    }

    @Override
    public MyMessage deserialize(String topic, byte[] data) {
        try {
            MyMessage message = Json.mapper.readValue(data, MyMessage.class);
            return message;
        } catch (Exception e) {
            throw new SerializationException("Error deserializing message", e);
        }
    }

    @Override
    public void close() {
        // No-op
    }
}
</code>

Creating a KafkaListener

Now that we have our custom deserializer, let’s create a KafkaListener that can consume messages from a Kafka topic:

<code>
@KafkaListener(topics = "my-topic")
public class MyKafkaListener {

    @Autowired
    private MyService myService;

    @OnError
    public void onError(Throwable t) {
        // Log the error
    }

    @Override
    public void onMessage(MyMessage message) {
        // Check if the message needs to be processed immediately or scheduled for later
        if (message.getDelay() > 0) {
            // Schedule the message for later processing
            myService.scheduleMessageForProcessing(message);
        } else {
            // Process the message immediately
            myService.processMessage(message);
        }
    }
}
</code>

Scheduling messages for later processing

To schedule messages for later processing, we can use Spring Boot’sScheduledAnnotationBeanPostProcessor to schedule the message processing. Let’s create a service that can schedule messages for later processing:

<code>
@Service
public class MyService {

    @Autowired
    private TaskScheduler taskScheduler;

    public void scheduleMessageForProcessing(MyMessage message) {
        long delay = message.getDelay();
        taskScheduler.schedule(() -> processMessage(message), new Date(System.currentTimeMillis() + delay));
    }

    public void processMessage(MyMessage message) {
        // Process the message
        System.out.println("Processing message: " + message);
    }
}
</code>

Configuring the KafkaListener

To configure the KafkaListener, we need to specify the custom deserializer and the Kafka topic. Let’s add the following configuration to our application configuration file:

<code>
spring:
  kafka:
    listener:
      key-deserializer: org.springframework.kafka.support.serializer.StringDeserializer
      value-deserializer: com.example.CustomDeserializer
    consumer:
      bootstrap-servers: localhost:9092
      group-id: my-group
      auto-offset-reset: earliest
      key-deserializer: org.springframework.kafka.support.serializer.StringDeserializer
      value-deserializer: com.example.CustomDeserializer
</code>

Testing the application

To test the application, let’s send a message to the Kafka topic with a delay of 30 seconds:

<code>
public class MyTest {

    @Autowired
    private KafkaTemplate<String, MyMessage> kafkaTemplate;

    @Test
    public void testMessageProcessing() {
        MyMessage message = new MyMessage("Hello, World!", 30000);
        kafkaTemplate.send("my-topic", message);
        // Wait for 30 seconds
        Thread.sleep(30000);
        // Verify that the message has been processed
    }
}
</code>

Conclusion

In this article, we explored how to process Kafka messages after the time defined in the message itself using Spring Boot KafkaListener. We created a custom deserializer to extract the timestamp or delay from the message, and a KafkaListener to consume messages from a Kafka topic. We also scheduled messages for later processing using Spring Boot’s ScheduledAnnotationBeanPostProcessor. By following these steps, you can process Kafka messages after a certain delay or at a specific time, which can be useful in many real-world scenarios.

Benefits

The approach described in this article provides several benefits, including:

• Flexibility: You can define the delay or timestamp in the message itself, giving you more flexibility in processing messages.
• Scalability: By scheduling messages for later processing, you can handle large volumes of messages without affecting the performance of your application.
• Reliability: You can ensure that messages are processed after a certain delay or at a specific time, even in the event of failures or restarts.

Best practices

When implementing this approach, keep the following best practices in mind:

1. Use a consistent format for the timestamp or delay in the message.
2. Error handling: Implement robust error handling to handle cases where the message cannot be processed after the delay.
3. Monitoring: Monitor the scheduled messages to ensure that they are being processed correctly and on time.
4. Testing: Thoroughly test the application to ensure that messages are being processed correctly after the delay.

Scenario	Delay/ Timestamp	Processing Time
Order confirmation	30 minutes	After 30 minutes
Payment notification	1 hour	After 1 hour
Email verification	5 minutes	After 5 minutes

This table illustrates different scenarios where processing Kafka messages after a certain delay or at a specific time is useful. By using the approach described in this article, you can implement such scenarios in your application.

I hope this article has been helpful in explaining how to process Kafka messages after the time defined in the message itself using Spring Boot KafkaListener. If you have any questions or comments, please feel free to ask!

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