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Spring Boot集成Kafka消息系统

发布时间:2024-11-15 12:40:13 来源:亿速云 阅读:78 作者:小樊 栏目:编程语言

Spring Boot集成Kafka消息系统是一个相对简单的过程。下面是一个基本的步骤指南,帮助你完成这个集成。

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>

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

2. 配置Kafka

在你的application.propertiesapplication.yml文件中配置Kafka相关的属性。

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. 创建Kafka配置类

创建一个配置类来定义Kafka相关的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. 创建Kafka监听器

创建一个监听器类来处理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. 创建Kafka生产者

创建一个生产者类来发送消息到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. 测试集成

你可以使用Kafka自带的工具(如kafka-console-producer.shkafka-console-consumer.sh)来测试你的集成。

生产者测试

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

在另一个终端中运行生产者:

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!";
    }
}

消费者测试

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

启动你的Spring Boot应用程序,然后访问/send端点,你应该会在消费者终端中看到接收到的消息。

总结

通过以上步骤,你已经成功地将Spring Boot集成到了Kafka消息系统中。你可以根据需要扩展这个集成,例如添加更多的Kafka配置、创建更多的监听器和生产者等。

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