springboot整合kafka消息队列

一、概述

消息队列,我们“窥探”已久,终于将kafka集成到项目springboot项目里面了,这里记录下操作流程。知识的回顾;

二、kafka服务器的安装

服务端下载地址 ,Linux下,我选择安装最新的版本2.13,但是window系统下 ,该版本无法启动,只能选择安装kafka_2.11-2.0.0.tgz;

 

 

 Linux和window系统下解压该文件

Linux进入cmd启动命令:zk端口默认2181,kafka默认端口9092

./zookeeper-server-start.sh -daemon ../config/zookeeper.properties 

./kafka-server-start.sh -daemon ../config/server.properties  

window进入cmd启动命令cmd:

./window/zookeeper-server-start.sh  ../config/zookeeper.properties 

./window/kafka-server-start.sh -daemon ../config/server.properties  

三、java代码

由于我的项目是springboot版本是1.5.2.RELEASE,kafka的版本只能选择spring-kafka版本1.2.1.RELEASE,否则版本冲突;

<dependency>                    
   <groupId>org.springframework.kafka</groupId>
    <artifactId>spring-kafka</artifactId>
    <version>1.2.1.RELEASE</version>
</dependency>

spring boot 项目配置


#制定kafka服务端地址
spring.kafka.bootstrap-servers=localhost:9092
#Kafkaf--producer---生产者配置
#消息发送失败重试次数
spring.kafka.producer.retries=2
#当有多个消息需要被发送到同一个分区时,生产者会把它们放在同一个批次里。该参数指定了一个批次可以使用的内存大小,按照字节数计算。
spring.kafka.producer.batch-size=16384
#设置生产者内存缓冲区的大小
spring.kafka.producer.buffer-memory=33554432
# 指定消息key和消息体的编解码方式
spring.kafka.producer.key-serializer=org.apache.kafka.common.serialization.StringSerializer
spring.kafka.producer.value-serializer=org.apache.kafka.common.serialization.StringSerializer


#Kafkaf--consumer---消费者配置
# 指定默认消费者group id:commit手动提交
#spring.kafka.consumer.group-id=user-log-group
spring.kafka.consumer.auto-commit-interval=1000
# 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
spring.kafka.consumer.auto-offset-reset=earliest
spring.kafka.consumer.enable-auto-commit=false
# 指定消息key和消息体的编解码方式
spring.kafka.consumer.key-deserializer=org.apache.kafka.common.serialization.StringDeserializer
spring.kafka.consumer.value-deserializer=org.apache.kafka.common.serialization.StringDeserializer


#在侦听器容器配置
##在侦听器容器中运行的线程数
spring.kafka.listener.concurrency=5
#listner负责ack,每调用一次》manual_immediate,就立即commit;record
spring.kafka.listener.ack-mode=manual_immediate
spring.kafka.listener.missing-topics-fatal=false

 

Sprintboot代码编写

producter代码

package com.test.sale.invoicemgr.domain.service.kafka;

import com.szdbgo.framework.core.constant.SaleConstant;
import org.apache.log4j.Logger;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.support.SendResult;
import org.springframework.stereotype.Component;
import org.springframework.transaction.annotation.Transactional;
import org.springframework.util.concurrent.ListenableFuture;
import org.springframework.util.concurrent.ListenableFutureCallback;

/**
 * Description  发票处理
 * Author justin.jia
 * Date 2021/11/27 17:11
 **/
@Component("invoiceProducterService")
public class InvoiceProducterService {

    private static Logger logger = Logger.getLogger(InvoiceProducterService.class);


    @Autowired
    private KafkaTemplate<String, Object> kafkaTemplate;


    //发票上传信息查询
    public void invoiceUploadSend(String key,String value) {
        logger.info("Kafka接口准备上传发送消息为发票ID:"+ key+"****"+value);
        ListenableFuture<SendResult<String, Object>> future = kafkaTemplate.send(SaleConstant.TOPIC_INVOICE_UPLOAD,value);
        future.addCallback(new ListenableFutureCallback<SendResult<String, Object>>() {
            @Override
            public void onFailure(Throwable throwable) {            //发送失败的处理
                logger.error(SaleConstant.TOPIC_INVOICE_UPLOAD + " - 生产者 发送消息失败:" + throwable.getMessage());
            }
            @Override
            public void onSuccess(SendResult<String, Object> stringObjectSendResult) {
                //成功的处理
                logger.info(SaleConstant.TOPIC_INVOICE_UPLOAD + " - 生产者 发送消息成功:" + stringObjectSendResult.toString());
            }
        });
    }
}

customer代码 

package com.test.sale.invoicemgr.domain.service.kafka;
import com.szdbgo.framework.core.constant.SaleConstant;
import com.szdbgo.framework.core.utils.common.CommonStringUtils;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.log4j.Logger;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.annotation.KafkaListener;
import org.springframework.kafka.support.Acknowledgment;
import org.springframework.stereotype.Component;

/**
 * Description  发票上传消费者
 * Author justin.jia
 * Date 2021/11/27 17:12
 **/
@Component("invoiceUploadCustomerService")
public class InvoiceUploadCustomerService {

    private static Logger logger = Logger.getLogger(InvoiceUploadCustomerService.class);//kafka的监听器
   ///KafkaListener配置ack采用手动提交,比如manual_immediate、manual
    @KafkaListener(topics = SaleConstant.TOPIC_INVOICE_UPLOAD,groupId = CacheConstants.KEY_KAFKA_TOPIC_GROUP_SALE)
    public void invoiceUploadCmd(ConsumerRecord<String, String> record, Acknowledgment ack) {

      String value = record.value();
      logger.info("***********接受数据,开始上传发票,发票ID:"+value);
      try{
          if(CommonStringUtils.isNotEmpty(value)) {
                //do something
           }
        }
      catch (Exception exception){
          logger.error("发票上传处理失败");
        }
      finally {
          //手动提交offset
          ack.acknowledge();
       }

    }
  ///KafkaListener配置ack采用非手动提交,比如record
  @KafkaListener(topics = SaleConstant.TOPIC_INVOICE_UPLOAD,groupId = CacheConstants.KEY_KAFKA_TOPIC_GROUP_SALE)
    public void invoiceUploadCmd(ConsumerRecord<String, String> record) {

      String value = record.value();
      logger.info("***********接受数据,开始上传发票,发票ID:"+value);
      try{
          if(CommonStringUtils.isNotEmpty(value)) {
                //do something
           }
        }
      catch (Exception exception){
          logger.error("发票上传处理失败");
        }
      finally {
         
       }

    }
}

 

posted @ 2021-12-01 10:52  jiajinhao  阅读(507)  评论(0编辑  收藏  举报