文章目录
提示:这里可以添加本文要记录的大概内容:
一、 pom.xml依赖包
java
<dependency>
<groupId>org.springframework.kafka</groupId>
<artifactId>spring-kafka</artifactId>
<version>2.8.0</version>
</dependency>
二、yml配置文件
yml
spring:
kafka:
listener:
concurrency: 3 #线程数
ack-mode: manual_immediate
type: batch #批量
bootstrap-servers: 192.168.1.214:9092
# 生产者配置
producer:
# retries: 1 # 消息发送重试次数
batch-size: 16384
buffer-memory: 33554432
value-serializer: org.apache.kafka.common.serialization.StringSerializer
key-serializer: org.apache.kafka.common.serialization.StringSerializer
#消费者需配置,生产者不需要
consumer:
key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
group-id: goodwe-touring-car-groupid-1
auto-offset-reset: earliest #latest, earliest, none
enable-auto-commit: false
auto-commit-interval: 5000
max-poll-records: 1000 #批量消费最大数量
topic: portable_performance
#自定义项目run, 运行kafka.
custom:
run:
kafka: true
############################### 参数说明 #########################################
consumer:
# 自动提交的时间间隔 在spring boot 2.X 版本中这里采用的是值的类型为Duration 需要符合特定的格式,如1S,1M,2H,5D
auto-commit-interval: 1S
# 该属性指定了消费者在读取一个没有偏移量的分区或者偏移量无效的情况下该作何处理:
# latest(默认值)在偏移量无效的情况下,消费者将从最新的记录开始读取数据(在消费者启动之后生成的记录)
# earliest :在偏移量无效的情况下,消费者将从起始位置读取分区的记录
auto-offset-reset: earliest
# 是否自动提交偏移量,默认值是true,为了避免出现重复数据和数据丢失,可以把它设置为false,然后手动提交偏移量
enable-auto-commit: false
# 键的反序列化方式
key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
# 值的反序列化方式
value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
listener:
# 在侦听器容器中运行的线程数。
concurrency: 5
#listner负责ack,每调用一次,就立即commit
ack-mode: manual_immediate
missing-topics-fatal: false
三、消费者
java
import com.alibaba.fastjson.JSON;
import com.baomidou.mybatisplus.core.toolkit.CollectionUtils;
import com.goodwe.kafkaapi.model.constant.RedisConst;
import com.goodwe.kafkaapi.model.entity.ConsumerMessageData;
import lombok.extern.slf4j.Slf4j;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.springframework.context.annotation.Configuration;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.kafka.support.Acknowledgment;
import javax.annotation.Resource;
import java.util.*;
import java.util.stream.Collectors;
/**
* @Description : kafka消费者
*
* @Author : LiYan
* @CreateTime : 2023/8/16 8:35
*/
@Slf4j
@Configuration
public class KafkaConsumer {
private static final String REDIS_KEY = RedisConst.getREDIS_PREFIX() + RedisConst.getKEY();
@Resource
private RedisTemplate<String,String> redisTemplate;
@KafkaListener(topics = "#{'${spring.kafka.topic}'}", autoStartup = "${custom.run.kafka}")
public void receive(List<ConsumerRecord<String, String>> listMessage, Acknowledgment ack) {
try {
log.info("----------------------开始消费消息--------------------------");
if (CollectionUtils.isNotEmpty(listMessage)) {
Map<String, ConsumerMessageData> dataMap = listMessage.stream()
.map(message -> JSON.parseObject(message.value(), ConsumerMessageData.class))
.collect(Collectors.toMap(ConsumerMessageData::getSn, data -> data, (oldValue, newValue) -> newValue));
dataMap.forEach((key, value) -> {
redisTemplate.opsForZSet().add(REDIS_KEY, JSON.toJSONString(value), System.currentTimeMillis());
});
}
} catch (Exception ex) {
log.info("【断点续传处理】消费断点续传数据error;", ex);
} finally {
ack.acknowledge();
}
}
}
四、生产者
java
@SpringBootTest
class KafkaApiApplicationTests {
@Resource
private KafkaTemplate<String, String> kafkaTemplate;
@Test
public void testRedis(){
List<ConsumerMessageData> messageData = messageData();
for (ConsumerMessageData data : messageData) {
String topic = "portable_performance";
kafkaTemplate.send(topic, JSON.toJSONString(data));
}
}
}
@RestController
public class KafkaController {
@Autowired
private KafkaTemplate<String, String> kafkaTemplate;
@PostMapping("/send")
public void sendMessage(@RequestBody String message) {
kafkaTemplate.send("my-topic", message);
}
}
总结
================== 好记性不如烂笔头=========================