Spring Boot 4 Microservices & REST APIs · 강의

Kafka 컨슈머 만들기

Kafka 토픽의 메시지를 구독하고 처리하는 Spring Kafka 컨슈머를 개발합니다.

Kafka 컨슈머 만들기은(는) CoddyKit의 무료 Spring Boot 4 Microservices & REST APIs 강의입니다. 이것은 3개 중 2번째 강의입니다. 아래에서 전체 강의를 무료로 읽을 수 있으며, 내장 코드 에디터와 24/7 AI 튜터와 함께 브라우저에서 직접 실습할 수 있습니다. 이 강의는 Spring Boot 4 Microservices & REST APIs 학습 경로의 일부이며, 진행 상황이 웹과 CoddyKit 앱에 동기화됩니다. Spring Boot 4 Microservices & REST APIs 강의에는 총 3개의 강의가 포함되어 있습니다.

이 강의의 일부는 아직 번역되지 않았으며 영어로 표시됩니다.

Kafka Consumers: The Listeners

In event-driven architectures, Kafka Consumers are the components responsible for reading messages (records) from Kafka topics. Think of them as listeners waiting for new events!

They subscribe to one or more topics and process the incoming data, enabling different parts of your application or other services to react to events.

Spring Boot & Kafka Config

To build a Kafka consumer in Spring Boot, first, you need the spring-kafka dependency. Add it to your pom.xml:

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

Next, configure your Kafka broker details in application.properties. This tells your Spring Boot app where to find the Kafka server.

spring.kafka.bootstrap-servers=localhost:9092

Meet @KafkaListener

Spring for Apache Kafka provides the powerful @KafkaListener annotation. This annotation marks a method to be a Kafka listener, meaning it will automatically consume messages from specified topics.

topics: The Kafka topic(s) to listen to.
groupId: Identifies the consumer group. Essential for scaling.

It handles all the low-level Kafka API details for you!

Your First Kafka Listener

Let's create a simple consumer that listens to a topic named my-first-topic and prints any incoming string messages to the console.

Notice the groupId. All consumers with the same groupId are part of a consumer group.

package com.coddykit.kafka;

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 KafkaConsumerApp {
  public static void main(String[] args) {
    SpringApplication.run(KafkaConsumerApp.class, args);
  }
}

@Component
class SimpleKafkaListener {

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

Understanding Deserialization

Kafka messages are stored as byte arrays. When a consumer reads a message, it needs to convert these bytes back into a usable object (like a String or a custom Java object).

This process is called deserialization. You configure deserializers in application.properties:

spring.kafka.consumer.key-deserializer=org.apache.kafka.common.serialization.StringDeserializer
spring.kafka.consumer.value-deserializer=org.apache.kafka.common.serialization.StringDeserializer

The choice of deserializer depends on how the producer serialized the message.

Consumer Groups for Scale

Consumer groups are key to Kafka's scalability. Multiple consumer instances can belong to the same group, sharing the workload of consuming messages from a topic.

Each message in a topic partition is delivered to only one consumer instance within a group.
If you have more consumers than partitions, some consumers will be idle.
If a consumer fails, another consumer in the same group automatically takes over its partitions.

This allows for both high availability and horizontal scaling.

Listening for JSON Data

Often, you'll send complex data as JSON. To consume JSON, you'll need to define a Java class (POJO) that matches the JSON structure and use Spring Kafka's JsonDeserializer.

Add spring.kafka.consumer.value-deserializer=org.springframework.kafka.support.serializer.JsonDeserializer to your config.

package com.coddykit.kafka;

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;

// Define a simple DTO matching the JSON structure
class MyEvent {
  private String name;
  private int value;

  // Default constructor required for deserialization
  public MyEvent() {}

  public MyEvent(String name, int value) {
    this.name = name;
    this.value = value;
  }

  public String getName() { return name; }
  public void setName(String name) { this.name = name; }
  public int getValue() { return value; }
  public void setValue(int value) { this.value = value; }

  @Override
  public String toString() {
    return "MyEvent{" +
           "name='" + name + '\'' +
           ", value=" + value +
           '}';
  }
}

@SpringBootApplication
@EnableKafka
public class KafkaJsonConsumerApp {
  public static void main(String[] args) {
    SpringApplication.run(KafkaJsonConsumerApp.class, args);
  }
}

@Component
class JsonKafkaListener {

  @KafkaListener(topics = "my-json-topic", groupId = "json-group")
  public void listenJson(MyEvent event) {
    System.out.println("Received JSON Event: " + event);
  }
}

Graceful Error Handling

What happens if a message is malformed or your processing logic throws an error? Consumers need robust error handling.

For simple errors, a try-catch block within your listener method is effective. For more advanced scenarios, Spring Kafka offers error handlers:

DefaultErrorHandler: Retries messages with backoff.
DeadLetterPublishingRecoverer: Sends failed messages to a dead-letter topic.

These prevent a single bad message from stopping your entire consumer.

Peeking at Message Metadata

Sometimes, you need more than just the message payload. Kafka messages come with useful metadata, such as the topic name, partition, and offset.

You can access this metadata directly in your @KafkaListener method using annotations like @Header or by accepting a ConsumerRecord object.

@KafkaListener(topics = "my-topic", groupId = "my-group")
public void listenWithInfo(
  String message,
  @Header(org.springframework.kafka.support.KafkaHeaders.RECEIVED_TOPIC) String topic,
  @Header(org.springframework.kafka.support.KafkaHeaders.RECEIVED_PARTITION_ID) int partition
) {
  System.out.println("From topic " + topic + ", partition " + partition + ": " + message);
}

Quick Check: Kafka Consumers

Which of the following is the primary annotation used in Spring Kafka to mark a method as a message listener for a specific topic?

Recap: Building Kafka Consumers

Great job! You've learned how to build Spring Kafka consumers to process messages from topics.

We set up Spring Kafka and used @KafkaListener to create message-consuming methods.
We explored deserialization and how to consume both simple strings and complex JSON objects.
You also understand the importance of consumer groups for scaling and handling errors.

Next up, we'll dive deeper into integrating producers and consumers to build full event-driven microservices!

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Kafka 토픽의 메시지를 구독하고 처리하는 Spring Kafka 컨슈머를 개발합니다. 브라우저에서 직접 실행하는 실습 코드로 Spring Boot 4 Microservices & REST APIs을(를) 배우며, 24/7 AI 튜터가 강의를 진행하면서 질문에 답변해줍니다.

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