@[TOC]

依赖

<!--kafka-->
<dependency>
    <groupId>org.springframework.kafka</groupId>
    <artifactId>spring-kafka</artifactId>
    <version>xxx</version>
</dependency>

配置文件

spring:
  kafka:
    producer:
      value-serializer: org.springframework.kafka.support.serializer.JsonSerializer
    bootstrap-servers: 192.168.20.75:9907

kafka:
  spark:
    task:
      topic: platform-model-spark-topic1

生产者

方法一：添加@RunWith(SpringRunner.class)、@SpringBootTest(classes = DataComputingModelApplication.class)实现初始化配置注入kafkaTemplate，调用send()
@Autowired
private KafkaTemplate kafkaTemplate;

    @Test
    public void kafkaSend() {
        final ProducerRecord<String, String> record = new ProducerRecord("test20201228", "{\"key\":\"27\"}");
        kafkaTemplate.send(record);
        log.info("------------send success!----------------");
    }
    
方法二：不需要注解@RunWith、@SpringBootTest，但是初始化Properties，同样调用send()
@Test
    public void kafkaSend2() {
        Properties props = new Properties();
        props.put("bootstrap.servers", "192.168.20.75:9907");
        props.put("key.serializer", StringSerializer.class);
        props.put("value.serializer", StringSerializer.class);
        KafkaProducer<String,String> producer = new KafkaProducer<>(props);
        ProducerRecord record = new ProducerRecord<String, String>("test20201228", "key", "{\"key\":\"20\"}");
        producer.send(record);
        log.info("------------send success!----------------");
        producer.close();
    }

消费者

==说明：
① Topic主题用来区分不同类型的消息
② GroupId用来解决同一个Topic主题下重复消费问题，比如一条消费需要多个消费者接收到，就可以通过设置不同的GroupId实现，实际消息是存一份的，只是通过逻辑上设置标识来区分，系统会记录Topic主题下–》GroupId分组下–》partition分区下的offsert，来标识是否消费过。==

@KafkaListener(topics = "big_data_task_state", groupId = "bigDataTaskState")
    public void taskStateConsumer(String msg) {
        log.info("----receive:{}----", msg);
    }

重要信息