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springboot 整合 kafka 消息持久化

小樊
81
2024-12-14 22:36:22
栏目: 大数据

在 Spring Boot 中整合 Kafka 进行消息持久化,你需要遵循以下步骤:

  1. 添加依赖

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

<dependencies>
    <!-- Spring Boot Kafka Starter -->
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-kafka</artifactId>
    </dependency>
</dependencies>
  1. 配置 Kafka

application.propertiesapplication.yml 文件中配置 Kafka 相关属性:

# 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
  1. 创建 Kafka 配置类

创建一个配置类,用于设置 Kafka 生产者和消费者的属性:

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.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;

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

@Configuration
public class KafkaConfig {

    @Value("${spring.kafka.bootstrap-servers}")
    private String bootstrapServers;

    @Bean
    public Map<String, Object> consumerConfigs() {
        Map<String, Object> props = new HashMap<>();
        props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
        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, bootstrapServers);
        props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class);
        return props;
    }
}
  1. 创建 Kafka 生产者和消费者

创建一个生产者类,用于发送消息到 Kafka:

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

@Component
public class KafkaProducer {

    @Autowired
    private KafkaTemplate<String, String> kafkaTemplate;

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

创建一个消费者类,用于从 Kafka 消费消息:

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.stereotype.Component;

@Component
public class KafkaConsumer {

    @Autowired
    private KafkaProducer kafkaProducer;

    @KafkaListener(topics = "my-topic", groupId = "my-group")
    public void listen(String message) {
        System.out.println("Received message: " + message);
        kafkaProducer.sendMessage("another-topic", message);
    }
}
  1. 创建消息发送和接收的示例

创建一个类,用于发送和接收消息:

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.CommandLineRunner;
import org.springframework.stereotype.Component;

@Component
public class KafkaExample implements CommandLineRunner {

    @Autowired
    private KafkaProducer kafkaProducer;

    @Override
    public void run(String... args) throws Exception {
        kafkaProducer.sendMessage("my-topic", "Hello, Kafka!");
    }
}

现在,当你运行你的 Spring Boot 应用时,它将发送一条消息到 my-topic 主题,然后从同一个主题消费消息并将其发送到另一个主题。Kafka 会自动处理消息的持久化,确保消息不会丢失。

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