SpringBoot中使用Kafka

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已于 2022-10-06 00:52:06 修改

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文章标签： kafka 大数据分布式 java spring boot

于 2022-10-06 00:51:17 首次发布

本文链接：https://blog.youkuaiyun.com/xiaozhang_man/article/details/127178949

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本文介绍如何在Spring Boot项目中整合Kafka消息中间件，包括添加依赖、配置属性、编写启动类及实现生产者与消费者功能。

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1.添加对应依赖

    <dependencies>
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        <dependency>
            <groupId>org.springframework.kafka</groupId>
            <artifactId>spring-kafka</artifactId>
        </dependency>

        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
        <dependency>
            <groupId>org.springframework.kafka</groupId>
            <artifactId>spring-kafka-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>

2.编写application.properties

spring.application.name=springboot-kafka-02
server.port=8080
# 用于建立初始连接的broker地址
spring.kafka.bootstrap-servers=localhost:9092
# producer用到的key和value的序列化类
spring.kafka.producer.key-serializer=org.apache.kafka.common.serialization.IntegerSerializer
spring.kafka.producer.value-serializer=org.apache.kafka.common.serialization.StringSerializer
# 默认的批处理记录数
spring.kafka.producer.batch-size=16384 
# 32MB的总发送缓存
spring.kafka.producer.buffer-memory=33554432 
# consumer用到的key和value的反序列化类
spring.kafka.consumer.key- deserializer=org.apache.kafka.common.serialization.IntegerDeserializer
spring.kafka.consumer.value- deserializer=org.apache.kafka.common.serialization.StringDeserializer
# consumer的消费组id
spring.kafka.consumer.group-id=spring-kafka-02-consumer
# 是否自动提交消费者偏移量
spring.kafka.consumer.enable-auto-commit=true 
# 每隔100ms向broker提交一次偏移量
spring.kafka.consumer.auto-commit-interval=100 
# 如果该消费者的偏移量不存在，则自动设置为最早的偏移量
spring.kafka.consumer.auto-offset-reset=earliest

3.编写启动类

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

4.生产者producer测试方法

同步等待broker的响应

@RestController
public class KafkaSyncProducerController {

    @Autowired
    private KafkaTemplate<Integer,String> template;

    @RequestMapping("send/sync/{message}") public String sendSync(@PathVariable String message) {
        ListenableFuture<SendResult<Integer, String>> future = template.send(new ProducerRecord<Integer, String>(
                "topic_1",
                0,
                1,
                message
        ));
        try {
            SendResult<Integer, String> result = future.get();
            RecordMetadata metadata = result.getRecordMetadata();
            System.out.println(metadata.serializedKeySize());
            System.out.println(metadata.serializedValueSize());
            System.out.println(metadata.topic());
            System.out.println(metadata.partition());
            System.out.println(metadata.offset());
        } catch (InterruptedException e) {
            e.printStackTrace();
        } catch (ExecutionException e) {
            e.printStackTrace();
        }
        return "success";
    }

}

添加回调，异步等待响应

@RestController
public class KafkaASyncProducerController {

    @Autowired
    private KafkaTemplate<Integer,String> template;

    @RequestMapping("send/sync/{message}") public String sendSync(@PathVariable String message) {
        ListenableFuture<SendResult<Integer, String>> future = template.send(new ProducerRecord<Integer, String>(
                "topic_1",
                0,
                1,
                message
        ));
        future.addCallback(new ListenableFutureCallback<SendResult<Integer, String>>() {
            @Override
            public void onFailure(Throwable ex) {
                System.out.println("消息发送失败！"+ ex);
            }

            @Override
            public void onSuccess(SendResult<Integer, String> result) {
                RecordMetadata metadata = result.getRecordMetadata();
                System.out.println(metadata.serializedKeySize());
                System.out.println(metadata.serializedValueSize());
                System.out.println(metadata.topic());
                System.out.println(metadata.partition());
                System.out.println(metadata.offset());
                System.out.println("消息发送成功！");
            }
        });
        return "success";
    }

}

5.消费者Consumer测试方法

@Component
public class MyConsumer {

    @KafkaListener(topics="topic_1")
    public void onMessage(ConsumerRecord<Integer,String> record){
        System.out.println(record.topic());
        System.out.println(record.offset());
        System.out.println(record.partition());
        System.out.println(record.serializedKeySize());
        System.out.println(record.serializedValueSize());
        System.out.println(record.key());
        System.out.println(record.value());
    }
}