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Advanced Spring Boot 4: Event-Driven Architecture (Kafka) · Lezione

Creare container listener Kafka

Crei metodi `@KafkaListener` per consumare automaticamente i messaggi dai topic specificati e ne configuri le proprietà.

Creare container listener Kafka è una lezione Advanced Spring Boot 4: Event-Driven Architecture (Kafka) gratuita su CoddyKit. Questa è la lezione 1 di 4. Puoi leggere la lezione completa qui gratuitamente — poi esercitati direttamente nel browser con un editor di codice integrato e un tutor IA disponibile 24/7. Fa parte del percorso di apprendimento Advanced Spring Boot 4: Event-Driven Architecture (Kafka), e i tuoi progressi si sincronizzano tra il web e l'app CoddyKit. Il corso Advanced Spring Boot 4: Event-Driven Architecture (Kafka) include 4 lezioni in totale.

Parti di questa lezione non sono ancora state tradotte e vengono mostrate in inglese.

Welcome to Kafka Consumers!

In event-driven systems, producers send events, and consumers react to them. Spring Boot makes it easy to build Kafka consumers.

We'll learn how to create methods that automatically listen for and process messages from Kafka topics using the @KafkaListener annotation.

The @KafkaListener Annotation

The @KafkaListener annotation is the core of consuming messages in Spring Boot. You place it on a method, telling Spring which Kafka topic(s) to listen to.

  • It automatically sets up the necessary infrastructure.
  • The method parameter receives the message payload.
  • You must specify a topics and groupId.

Basic Listener: String Messages

Let's create a simple Kafka listener that consumes plain string messages. Remember, you'd typically have Kafka dependencies and configuration in your Spring Boot project.

Here, my-topic is the Kafka topic, and my-group is the consumer group ID.

package com.example.kafkaconsumer;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.kafka.annotation.EnableKafka;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Component;

@SpringBootApplication
@EnableKafka
public class KafkaConsumerApplication {
  public static void main(String[] args) {
    // In a real app, SpringApplication.run() starts the context
    // and registers the @KafkaListener methods.
    System.out.println("Spring Boot Kafka Consumer App Started (simulated)");
    // For a runnable snippet, we just show the listener logic.
    // In a full app, this would run indefinitely, waiting for messages.
  }
}

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

Understanding Consumer Groups

The groupId property is crucial for Kafka consumers. It defines a group of consumers that work together to process messages from one or more topics.

  • Load Balancing: Messages from a topic are distributed among consumers in the same group.
  • Fault Tolerance: If a consumer fails, another in the group takes over its partitions.
  • Unique Processing: Each message is processed by only one consumer within a group.

Listening to Multiple Topics

A single @KafkaListener method can listen to multiple topics. You can specify them as an array of strings in the topics attribute.

This is useful when different topics carry related types of messages that can be handled by the same logic.

package com.example.kafkaconsumer;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.kafka.annotation.EnableKafka;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Component;

@SpringBootApplication
@EnableKafka
public class KafkaConsumerApplication {
  public static void main(String[] args) {
    System.out.println("Spring Boot Kafka Consumer App Started (simulated)");
  }
}

@Component
class MultiTopicListener {
  @KafkaListener(topics = {"topic-a", "topic-b"}, groupId = "multi-group")
  public void listenMultipleTopics(String message) {
    System.out.println("Received from multiple topics: " + message);
  }
}

Receiving Custom Objects

Kafka messages often contain structured data, not just strings. Spring Kafka can automatically convert JSON or Avro messages into Java objects (POJOs).

You just need to define a POJO that matches the structure of your Kafka messages and use it as the method parameter.

Code: Custom Object Listener

Here's how to set up a listener for a custom MyEvent object. Spring Boot handles the deserialization, assuming you have the correct deserializer configured (e.g., JSON deserializer).

package com.example.kafkaconsumer;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.kafka.annotation.EnableKafka;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Component;

// A simple data class representing an event
class MyEvent {
  private String id;
  private String description;

  // Getters and setters are essential for deserialization
  public String getId() { return id; }
  public void setId(String id) { this.id = id; }
  public String getDescription() { return description; }
  public void setDescription(String description) { this.description = description; }

  @Override
  public String toString() {
    return "MyEvent{id='" + id + "', description='" + description + "'}";
  }
}

@SpringBootApplication
@EnableKafka
public class KafkaConsumerApplication {
  public static void main(String[] args) {
    System.out.println("Spring Boot Kafka Consumer App Started (simulated)");
  }
}

@Component
class MyObjectListener {
  @KafkaListener(topics = "object-topic", groupId = "object-group")
  public void listenObject(MyEvent event) {
    System.out.println("Received object: " + event);
  }
}

Accessing Message Metadata

Beyond the message payload, Kafka messages carry useful metadata like topic, partition, offset, and headers. You can access these in your listener method:

  • @Payload: The message body (default).
  • @Header: Access specific Kafka headers.
  • ConsumerRecord: The raw Kafka record, giving access to all metadata.
package com.example.kafkaconsumer;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.kafka.annotation.EnableKafka;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.messaging.handler.annotation.Header;
import org.springframework.messaging.handler.annotation.Payload;
import org.springframework.stereotype.Component;

@SpringBootApplication
@EnableKafka
public class KafkaConsumerApplication {
  public static void main(String[] args) {
    System.out.println("Spring Boot Kafka Consumer App Started (simulated)");
  }
}

@Component
class MyMetadataListener {
  @KafkaListener(topics = "metadata-topic", groupId = "meta-group")
  public void listenWithMetadata(
      @Payload String message,
      @Header("kafka_receivedTopic") String topic,
      @Header("kafka_receivedPartitionId") int partition,
      @Header("kafka_offset") long offset) {
    System.out.println("Topic: " + topic + ", Partition: " + partition + ", Offset: " + offset);
    System.out.println("Message: " + message);
  }
}

Configuring Listener Properties

While @KafkaListener handles many defaults, you can customize consumer behavior. Properties like bootstrap.servers, auto.offset.reset, and key.deserializer are typically set in your application.properties or application.yml file.

  • Spring Boot automatically picks up these configurations.
  • They apply to all @KafkaListeners unless overridden.

Test Your Kafka Listener Knowledge!

Which of the following statements about Spring Boot's @KafkaListener annotation is TRUE?

Recap: Building Kafka Listeners

You've taken the first step into consuming Kafka messages with Spring Boot!

  • The @KafkaListener annotation simplifies consumer creation.
  • You specify topics and a groupId to organize consumers.
  • Listeners can handle String messages, custom objects, and access metadata.
  • Configuration is often managed through application.properties.

Next, we'll explore how consumer groups work in more detail to achieve scalable and fault-tolerant message processing!

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Tutte le lezioni di questo corso

  1. Creare container listener Kafka
  2. Gestione dei gruppi di consumatori
  3. Deserializzazione e conversione dei messaggi
  4. Consumo in batch e modalità di acknowledgment
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