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Kafka怎么发送JAVA对象并在消费者端解析出JAVA对象--示例

news 2026/3/31 4:44:34

1、在pom.xml中加入依赖

        <dependency><groupId>org.springframework.cloud</groupId><artifactId>spring-cloud-starter-stream-kafka</artifactId><version>3.1.6</version></dependency>

2、配置application.yml

加入Kafka的配置

springkafka:#Kafka地址，可以是一个，也可以是Kafka集群的地址，多个地址用逗号分隔bootstrap-servers: 192.168.57.1xx:9093,192.168.57.1xx:9094,192.168.57.1xx:9095producer:# 消息确认模式：0=不等待确认，1=等待leader确认，all=所有副本确认acks: 1# 发送失败时的重试次数，0表示不重试retries: 0# 批量发送时的批次大小（字节）batch-size: 30720000 # 30MB# 生产者的内存缓冲区大小（字节）buffer-memory: 33554432 # 32MB# Key的序列化器类key-serializer: org.apache.kafka.common.serialization.StringSerializer# Value的序列化器类value-serializer: org.apache.kafka.common.serialization.StringSerializerconsumer:# 消费者所属的组IDgroup-id: test-kafka# 禁用自动提交offset，改为手动提交enable-auto-commit: false# 偏移量重置策略：# earliest：从最早的记录开始消费# latest：从最新的记录开始消费auto-offset-reset: earliest# Key的反序列化器类key-deserializer: org.apache.kafka.common.serialization.StringDeserializer# Value的反序列化器类value-deserializer: org.apache.kafka.common.serialization.StringDeserializer# 每次poll()调用返回的最大消息条数max-poll-records: 2session:# 消费者会话超时时间，超时未发送心跳将被认为失联（毫秒）timeout:ms: 300000 # 5分钟listener:# 如果指定的主题不存在，是否让应用启动失败，false表示不会报错missing-topics-fatal: false# 消费模式：single=单条消息，batch=批量消费type: single# 消费确认模式：# manual_immediate：手动确认消息，立即提交offsetack-mode: manual_immediate

这里的生产者value的序列化器用org.apache.kafka.common.serialization.StringSerializer
，消费者value的序列化器用org.apache.kafka.common.serialization.StringDeserializer即可。

（这里不需要自定义序列化器，但在代码需要将JAVA对象转化为JSON字符串发送）

3、config、producer、consumer代码

3.1、User.java

import lombok.AllArgsConstructor;
import lombok.Builder;
import lombok.Data;
import lombok.NoArgsConstructor;@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
public class User {private int id;private String name;
}

3.2、Task.java

import lombok.AllArgsConstructor;
import lombok.Builder;
import lombok.Data;
import lombok.NoArgsConstructor;@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
public
class Task {private int id;private String description;private User assignedUser;
}

模拟嵌套类

3.3、KafkaConfig.java

import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.kafka.annotation.EnableKafka;
import org.springframework.kafka.config.ConcurrentKafkaListenerContainerFactory;
import org.springframework.kafka.core.ConsumerFactory;@EnableKafka
@Configuration
public class KafkaConfig {// 单条消费监听器工厂，手动提交offset@Beanpublic ConcurrentKafkaListenerContainerFactory<String, String> singleFactory(ConsumerFactory<String, String> consumerFactory) {ConcurrentKafkaListenerContainerFactory<String, String> factory =new ConcurrentKafkaListenerContainerFactory<>();factory.setConsumerFactory(consumerFactory);factory.getContainerProperties().setAckMode(org.springframework.kafka.listener.ContainerProperties.AckMode.MANUAL_IMMEDIATE);return factory;}}

3.4、KafkaProducer.java

import com.fasterxml.jackson.databind.ObjectMapper;
import org.springframework.boot.CommandLineRunner;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.context.annotation.Bean;
import org.springframework.kafka.core.KafkaTemplate;@SpringBootApplication
public class KafkaProducer {public static void main(String[] args) {SpringApplication.run(KafkaProducer.class, args);}@BeanCommandLineRunner commandLineRunner(KafkaTemplate<String, String> kafkaTemplate) {return args -> {String topic = "task-topic";ObjectMapper objectMapper = new ObjectMapper();for (int i = 1; i <= 5; i++) {// 定义一个对象实例User user = User.builder().id(1).name("Alice").build();Task task = Task.builder().id(101).description("Complete report").assignedUser(user).build();//JAVA对象转化为JSON字符串String message =  objectMapper.writeValueAsString(task);kafkaTemplate.send(topic, message);System.out.println("Sent: " + message);Thread.sleep(500); // 模拟消息发送间隔}};}
}

序列化：使用 Jackson 的 ObjectMapper 将 Task 对象转化为 JSON 字符串，方法 writeValueAsString() 将 Java 对象转为 JSON 字符串。

3.5、SingleConsumer.java

import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.kafka.support.Acknowledgment;
import org.springframework.stereotype.Service;@Service
public class SingleConsumer {@KafkaListener(topics = "task-topic", groupId = "test-group", containerFactory = "singleFactory", autoStartup = "true")public void listen(ConsumerRecord<String, String> record, Acknowledgment acknowledgment) throws JsonProcessingException {String message = record.value();ObjectMapper objectMapper = new ObjectMapper();Task task = objectMapper.readValue(message,Task.class);// 取出System.out.println("User - Received: " + task.getAssignedUser());// 手动提交offsetacknowledgment.acknowledge();}
}

反序列化： 使用 ObjectMapper 将 JSON 字符串 message 转换回 Task 对象，方法 readValue() 可以将 JSON 字符串解析为指定的 Java 对象类型。

4、测试

启动KafkaProducer.java

可以解析出JAVA对象中User

成功！