springboot 整合 kafka 配置步骤 - 问答

在 Spring Boot 中整合 Kafka 相对简单，只需要几个步骤即可完成。以下是详细的配置步骤：

1. 添加依赖

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

<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>
</dependencies>

2. 配置 Kafka

在 application.properties 或 application.yml 文件中配置 Kafka 的相关参数：

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. 创建 Kafka 配置类

创建一个配置类来定义 Kafka 的相关配置：

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.KafkaListenerEndpointRegistry;
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 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 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 ConsumerFactory<String, String> consumerFactory() {
        return new DefaultKafkaConsumerFactory<>(consumerConfigs());
    }

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

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

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

    @Override
    public void configureKafkaListeners(KafkaListenerEndpointRegistrar registrar) {
        registrar.setKafkaListenerEndpointRegistrar(new KafkaListenerEndpointRegistrar() {
            @Override
            public void registerEndpoints(KafkaListenerEndpointRegistry registry) {
                registry.register(kafkaListenerEndpoint());
            }
        });
    }

    @Bean
    public KafkaListenerEndpoint<String, String> kafkaListenerEndpoint() {
        KafkaListenerEndpoint<String, String> endpoint = new KafkaListenerEndpoint<>();
        endpoint.setId("my-endpoint");
        endpoint.setTopics("my-topic");
        endpoint.setMessageHandlerMethodFactory(kafkaListenerEndpointMethodFactory());
        return endpoint;
    }

    @Bean
    public KafkaListenerEndpointMethodFactory<String, String> kafkaListenerEndpointMethodFactory() {
        return new KafkaListenerEndpointMethodFactory<>();
    }
}

4. 创建消费者和生产者

创建一个消费者和生产者类来处理消息：

消费者示例

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);
    }
}

生产者示例

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);
    }
}

5. 启动类

创建一个启动类来启动 Spring Boot 应用：

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;

@SpringBootApplication
public class KafkaApplication {

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

6. 测试

启动应用后，你可以使用 Kafka 工具（如 kafka-console-producer.sh 和 kafka-console-consumer.sh）来测试消息的生产和消费。

总结

以上步骤涵盖了在 Spring Boot 中整合 Kafka 的基本配置。你可以根据具体需求进一步扩展和优化这些配置。

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