Spring Boot集成Kafka消息系統

Spring Boot集成Kafka消息系統是一個相對簡單的過程。下面是一個基本的步驟指南，幫助你完成這個集成。

1. 添加依賴

首先，在你的pom.xml文件中添加Spring Boot和Kafka的依賴。

<dependencies>
    <!-- Spring Boot Starter Web -->
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-web</artifactId>
    </dependency>

    <!-- Spring Boot Starter Kafka -->
    <dependency>
        <groupId>org.springframework.kafka</groupId>
        <artifactId>spring-kafka</artifactId>
    </dependency>

    <!-- Other dependencies -->
</dependencies>

2. 配置Kafka

在你的application.properties或application.yml文件中配置Kafka相關的屬性。

application.properties

spring.kafka.bootstrap-servers=localhost:9092
spring.kafka.consumer.group-id=my-group
spring.kafka.consumer.auto-offset-reset=earliest
spring.kafka.consumer.key-deserializer=org.apache.kafka.common.serialization.StringDeserializer
spring.kafka.consumer.value-deserializer=org.apache.kafka.common.serialization.StringDeserializer

spring.kafka.producer.key-serializer=org.apache.kafka.common.serialization.StringSerializer
spring.kafka.producer.value-serializer=org.apache.kafka.common.serialization.StringSerializer

application.yml

spring:
  kafka:
    bootstrap-servers: localhost:9092
    consumer:
      group-id: my-group
      auto-offset-reset: earliest
      key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
      value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
    producer:
      key-serializer: org.apache.kafka.common.serialization.StringSerializer
      value-serializer: org.apache.kafka.common.serialization.StringSerializer

3. 創建Kafka配置類

創建一個配置類來定義Kafka相關的Bean。

import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.common.serialization.StringDeserializer;
import org.apache.kafka.common.serialization.StringSerializer;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.annotation.KafkaListenerConfigurer;
import org.springframework.kafka.config.ConcurrentKafkaListenerContainerFactory;
import org.springframework.kafka.config.KafkaListenerEndpointRegistrar;
import org.springframework.kafka.config.MethodKafkaListenerEndpoint;
import org.springframework.kafka.core.ConsumerFactory;
import org.springframework.kafka.core.DefaultKafkaConsumerFactory;
import org.springframework.kafka.core.DefaultKafkaProducerFactory;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.core.ProducerFactory;
import org.springframework.kafka.listener.ConcurrentMessageListenerContainer;
import org.springframework.kafka.listener.config.MethodKafkaListenerEndpointRegistrar;
import org.springframework.kafka.listener.config.MethodKafkaListenerEndpointRegistry;
import org.springframework.kafka.support.serializer.ErrorHandlingDeserializer;
import org.springframework.kafka.support.serializer.JsonDeserializer;
import org.springframework.kafka.support.serializer.JsonSerializer;

import java.util.HashMap;
import java.util.Map;

@Configuration
public class KafkaConfig implements KafkaListenerConfigurer {

    @Bean
    public Map<String, Object> consumerConfigs() {
        Map<String, Object> props = new HashMap<>();
        props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
        props.put(ConsumerConfig.GROUP_ID_CONFIG, "my-group");
        props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, StringDeserializer.class);
        props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
        return props;
    }

    @Bean
    public ConsumerFactory<String, String> consumerFactory() {
        return new DefaultKafkaConsumerFactory<>(consumerConfigs());
    }

    @Bean
    public ConcurrentKafkaListenerContainerFactory<String, String> kafkaListenerContainerFactory() {
        ConcurrentKafkaListenerContainerFactory<String, String> factory = new ConcurrentKafkaListenerContainerFactory<>();
        factory.setConsumerFactory(consumerFactory());
        return factory;
    }

    @Bean
    public Map<String, Object> producerConfigs() {
        Map<String, Object> props = new HashMap<>();
        props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
        props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        return props;
    }

    @Bean
    public ProducerFactory<String, String> producerFactory() {
        return new DefaultKafkaProducerFactory<>(producerConfigs());
    }

    @Bean
    public KafkaTemplate<String, String> kafkaTemplate() {
        return new KafkaTemplate<>(producerFactory());
    }

    @Override
    public void configureKafkaListeners(KafkaListenerEndpointRegistrar registrar) {
        MethodKafkaListenerEndpointRegistry registry = new MethodKafkaListenerEndpointRegistry();
        registrar.setEndpointRegistrar(registry);
        registry.registerEndpoints(getKafkaListenerEndpoints());
    }

    private MethodKafkaListenerEndpoint[] getKafkaListenerEndpoints() {
        // Add your Kafka listener endpoints here
        return new MethodKafkaListenerEndpoint[0];
    }
}

4. 創建Kafka監聽器

創建一個監聽器類來處理Kafka消息。

import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Service;

@Service
public class KafkaConsumer {

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

5. 創建Kafka生產者

創建一個生產者類來發送消息到Kafka。

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.stereotype.Service;

@Service
public class KafkaProducer {

    @Autowired
    private KafkaTemplate<String, String> kafkaTemplate;

    public void sendMessage(String topic, String message) {
        kafkaTemplate.send(topic, message);
    }
}

6. 測試集成

你可以使用Kafka自帶的工具（如kafka-console-producer.sh和kafka-console-consumer.sh）來測試你的集成。

生產者測試

kafka-console-producer.sh --broker-list localhost:9092 --topic my-topic

在另一個終端中運行生產者：

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RestController;

@RestController
public class KafkaProducerController {

    @Autowired
    private KafkaProducer kafkaProducer;

    @GetMapping("/send")
    public String sendMessage() {
        kafkaProducer.sendMessage("my-topic", "Hello, Kafka!");
        return "Message sent!";
    }
}

消費者測試

kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic my-topic --from-beginning

啟動你的Spring Boot應用程序，然后訪問/send端點，你應該會在消費者終端中看到接收到的消息。

總結

通過以上步驟，你已經成功地將Spring Boot集成到了Kafka消息系統中。你可以根據需要擴展這個集成，例如添加更多的Kafka配置、創建更多的監聽器和生產者等。