Kafka--06---Springboot中使⽤Kafka

Posted 2022-01-18 高高for 循环

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文章目录

• Springboot中使⽤Kafka
• • 1.引⼊依赖
  • 2.编写配置⽂件-----yml
  • 3.消息⽣产者
  • 4.消费者
  • 5.消费者中配置消费主题、分区和偏移量

---

Springboot中使⽤Kafka

1.引⼊依赖

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

2.编写配置⽂件-----yml

server:
  port: 8080

spring:
  kafka:
    bootstrap-servers: 172.16.253.38:9092,172.16.253.38:9093,172.16.253.38:9094
    producer:
      retries: 3
      batch-size: 16384
      buffer-memory: 33554432
      acks: 1
      key-serializer: org.apache.kafka.common.serialization.StringSerializer
      value-serializer: org.apache.kafka.common.serialization.StringSerializer
    consumer:
      group-id: default-group
      enable-auto-commit: false
      auto-offset-reset: earliest
      key-deserializer: org.apache.kafka.common.serialization.StringDeserializer
      value-deserializer: org.apache.kafka.common.serialization.StringDeserializer
      max-poll-records: 500
    listener:
      # 当每⼀条记录被消费者监听器（ListenerConsumer）处理之后提交
      # RECORD
      # 当每⼀批poll()的数据被消费者监听器（ListenerConsumer）处理之后提交
      # BATCH
      # 当每⼀批poll()的数据被消费者监听器（ListenerConsumer）处理之后，距离上次提交时间⼤于TIME时提交
      # TIME
      # 当每⼀批poll()的数据被消费者监听器（ListenerConsumer）处理之后，被处理record数量⼤于等于COUNT时提交
      # COUNT
      # TIME |　COUNT　有⼀个条件满⾜时提交
      # COUNT_TIME
      # 当每⼀批poll()的数据被消费者监听器（ListenerConsumer）处理之后, ⼿动调⽤Acknowledgment.acknowledge()后提交
      # MANUAL
      # ⼿动调⽤Acknowledgment.acknowledge()后⽴即提交，⼀般使⽤这种
      # MANUAL_IMMEDIATE
      ack-mode: MANUAL_IMMEDIATE
  redis:
    host: 172.16.253.21

3.消息⽣产者

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;

@RestController
@RequestMapping("/msg")
public class MyKafkaController 

    private final static String TOPIC_NAME = "my-replicated-topic";

    @Autowired
    private KafkaTemplate<String, String> kafkaTemplate;

    @RequestMapping("/send")
    public String sendMessage() 

        kafkaTemplate.send(TOPIC_NAME, 0, "key", "this is a message!");

        return "send success!";

    

4.消费者

package com.example.demo.consumer;

import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.kafka.annotation.PartitionOffset;
import org.springframework.kafka.annotation.TopicPartition;
import org.springframework.kafka.support.Acknowledgment;
import org.springframework.stereotype.Component;

@Component
public class MyConsumer 

    @KafkaListener(topics = "my-replicated-topic", groupId = "MyGroup1")
    public void listenGroup(ConsumerRecord<String, String> record, Acknowledgment ack) 
        String value = record.value();
        System.out.println(value);
        System.out.println(record);
        //手动提交offset
        ack.acknowledge();
    


 //不同的方式
  @KafkaListener(topics = "my-replicated-topic", groupId = "MyGroup2")
  public void listensGroup(ConsumerRecords<String, String> records, Acknowledgment ack) 
    for (ConsumerRecord<String, String> record : records) 
      System.out.printf(record.value());
    
    //手动提交offset
    ack.acknowledge();
  

5.消费者中配置消费主题、分区和偏移量

package com.example.demo.consumer;

import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.kafka.annotation.PartitionOffset;
import org.springframework.kafka.annotation.TopicPartition;
import org.springframework.kafka.support.Acknowledgment;
import org.springframework.stereotype.Component;

@Component
public class MyConsumer 

    @KafkaListener(groupId = "testGroup", topicPartitions = 
            @TopicPartition(topic = "topic1", partitions = "0", "1"),//concurrency就是同组下的消费者个数，就是并发消费数，建议小于等于分区总数
            @TopicPartition(topic = "topic2", partitions = "0", partitionOffsets = @PartitionOffset(partition = "1", initialOffset = "100")), concurrency = "3")
    public void listenGroupPro(ConsumerRecord<String, String> record, Acknowledgment ack) 
        String value = record.value();
        System.out.println(value);
        System.out.println(record);
        //手动提交offset
        ack.acknowledge();