Advanced Spring Boot 4: Event-Driven Architecture (Kafka) · レッスン

デシリアライズとメッセージ変換

さまざまなメッセージ形式（String、JSON、カスタムオブジェクト）用のデシリアライザーを設定し、リスナー内でメッセージを変換する方法を学びます。

「デシリアライズとメッセージ変換」はCoddyKit上の無料Advanced Spring Boot 4: Event-Driven Architecture (Kafka)レッスンです。これはレッスン3/4です。下記で完全なレッスンを無料で読むことができます。その後、ブラウザ内の組み込みコードエディタと24時間対応のAIチューターでハンズオン演習できます。これはAdvanced Spring Boot 4: Event-Driven Architecture (Kafka)学習パスの一部であり、ウェブとCoddyKitアプリ全体で進捗が同期されます。 Advanced Spring Boot 4: Event-Driven Architecture (Kafka)コースには全4レッスンが含まれています。

このレッスンの一部はまだ翻訳されておらず、英語で表示されています。

Kafka's Raw Messages

Kafka doesn't care about the format of your data. It treats every message as a raw array of bytes. This is how messages are stored and transmitted.

When a producer sends a message, it's first converted into bytes. When a consumer receives that message, it's still just a bunch of bytes.

This flexibility allows Kafka to handle any data type, but it means consumers need a way to interpret those bytes back into a usable format.

From Bytes to Objects: Deserialization

To make sense of Kafka messages in your Java application, you need to convert these raw bytes back into meaningful Java objects. This crucial process is called deserialization.

A deserializer is a specific component that knows how to read a byte array and reconstruct a Java object from it. Think of it as the reverse of serialization.

Without proper deserialization, your consumer would only ever see byte[], which isn't very useful for application logic.

Default String Deserialization

Spring for Apache Kafka provides sensible defaults to get you started quickly. If you don't specify otherwise, it assumes your message keys and values are simple strings.

Behind the scenes, it uses org.apache.kafka.common.serialization.StringDeserializer to convert message bytes into Java String objects.

This works perfectly for plain text messages, but most real-world applications often need to handle more structured data.

Code: Simple String Consumer

Here's a basic Spring Boot application with a Kafka listener that consumes simple string messages. Notice the String type in the listener method signature.

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

@SpringBootApplication
public class SimpleConsumerApp {
  public static void main(String[] args) {
    SpringApplication.run(SimpleConsumerApp.class, args);
    System.out.println("String consumer app started, listening on my-string-topic...");
  }

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

Configuring Deserializers Explicitly

You can explicitly configure which deserializers to use in your application.properties or application.yml file. This tells Spring Kafka which classes to use for converting bytes for both the message key and value.

spring.kafka.consumer.key-deserializer
spring.kafka.consumer.value-deserializer

For our default string example, these would be set to org.apache.kafka.common.serialization.StringDeserializer.

Working with JSON Data

JSON (JavaScript Object Notation) is a widely used format for exchanging structured data. It's very common for Kafka messages to carry data in JSON format.

To utilize JSON messages effectively in your Java application, you need to convert the incoming JSON string (or bytes) into a Java object, typically a Plain Old Java Object (POJO).

This mapping allows you to easily access data fields directly, like myObject.getId() or myObject.getName(), instead of parsing JSON manually.

Spring's JsonDeserializer

Spring for Apache Kafka provides a powerful org.springframework.kafka.support.serializer.JsonDeserializer to simplify handling JSON messages.

This deserializer leverages the popular Jackson library to automatically map incoming JSON bytes to your specified Java POJO class.

You just need to configure it to know which POJO type to expect, and it handles the complex conversion for you.

Code: Defining an Event POJO

First, let's define a simple Java POJO that will represent our incoming JSON data. The properties of this POJO should match the fields in your JSON messages.

package com.coddykit;

// MyEvent.java
public class MyEvent {
    private String id;
    private String description;

    // Default constructor is crucial for deserialization
    public MyEvent() {}

    public MyEvent(String id, String description) {
        this.id = id;
        this.description = description;
    }

    // Getters and Setters (omitted for brevity, but needed)
    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 + "'}";
    }
}

Code: Consuming JSON Messages

Now, let's update our consumer to use the JsonDeserializer and listen for MyEvent objects. Remember, you'll also need to configure the deserializer in your application.properties.

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Component;
import com.coddykit.MyEvent; // Import your POJO

@SpringBootApplication
public class JsonConsumerApp {
  public static void main(String[] args) {
    SpringApplication.run(JsonConsumerApp.class, args);
    System.out.println("JSON consumer app started, listening on my-json-topic...");
  }

  @Component
  static class MyJsonListener {
    @KafkaListener(topics = "my-json-topic", groupId = "json-group")
    public void listen(MyEvent event) {
      System.out.println("Received JSON Event: " + event.toString());
    }
  }
}
// Required application.properties configuration:
// spring.kafka.consumer.key-deserializer=org.apache.kafka.common.serialization.StringDeserializer
// spring.kafka.consumer.value-deserializer=org.springframework.kafka.support.serializer.JsonDeserializer
// spring.kafka.properties.spring.json.value.default.type=com.coddykit.MyEvent

Deserializer Configuration Quiz

Consider a Spring Boot Kafka consumer application that needs to process messages where the value is a JSON representation of a Product object, defined in com.example.Product. Which configuration is essential in application.properties for this setup?

Deserialization Recap

Great job! In this lesson, you learned that Kafka messages are raw bytes and require deserialization to be used in Java applications.

Spring Kafka uses StringDeserializer by default for simple text messages.
You can configure specific deserializers for keys and values using application.properties.
The JsonDeserializer simplifies mapping JSON messages to Java POJOs automatically.

Understanding deserialization is fundamental to building robust Kafka consumers that can handle various data formats effectively.

よくある質問

「デシリアライズとメッセージ変換」レッスンは無料ですか？

はい。「デシリアライズとメッセージ変換」の完全なテキストはこのウェブで無料で読めます。インタラクティブに演習し（組み込みコードエディタと24時間対応のAIチューター）、Advanced Spring Boot 4: Event-Driven Architecture (Kafka)コースの残りをアンロックするには、CoddyKit PROにアップグレードしてください。 Advanced Spring Boot 4: Event-Driven Architecture (Kafka)コースには全4レッスンが含まれています。

「デシリアライズとメッセージ変換」で何を学びますか？

さまざまなメッセージ形式（String、JSON、カスタムオブジェクト）用のデシリアライザーを設定し、リスナー内でメッセージを変換する方法を学びます。ブラウザで直接実行するハンズオンコードでAdvanced Spring Boot 4: Event-Driven Architecture (Kafka)を演習し、24時間対応のAIチューターがレッスンを進める中での質問に答えます。

Advanced Spring Boot 4: Event-Driven Architecture (Kafka)を始めるのに経験は必要ですか？

事前経験は必要ありません。CoddyKitのAdvanced Spring Boot 4: Event-Driven Architecture (Kafka)は初級者から上級者向けに構成されているため、ここから始めるか最初から始めて、自分のペースで進むことができます。これはレッスン3/4です。

「デシリアライズとメッセージ変換」レッスンにはどのくらい時間がかかりますか？

ほとんどのCoddyKitレッスンは約5～10分かかります。各レッスンはコンパクトでインタラクティブなので、着実に進歩し、ウェブとアプリ全体で正確に前回の場所から再開できます。

このAdvanced Spring Boot 4: Event-Driven Architecture (Kafka)レッスンでコードを書いて実行できますか？

はい。すべてのAdvanced Spring Boot 4: Event-Driven Architecture (Kafka)レッスンに組み込みコードエディタが含まれているため、ブラウザでリアルコードを書いて実行し、即座のAIフィードバックを取得できます。ローカル設定は不要です。

このコースのすべてのレッスン

← Advanced Spring Boot 4: Event-Driven Architecture (Kafka)に戻る