Spring集成Kafka之spring-kafka

配置文件的方式实现spring整和kafka:

    此文主要讲述的内容:

     1,连接kafka服务器的配置

    2,kafka-customer:消费者配置

    3,kafka-provider:提供者配置

    4,KfkaUtils:根据topic发送消息

    5,消费者根据topic处理消息

一，安装kafka

      网上百度一下,一大堆,在这里我就不赘述了（新版本的kafka集成了zookeeper插件，所以只需配置kafka安装包下的zookeeper.properties即可,）,下载地址：http://kafka.apache.org/downloads

注意在启动kafka-service之前需启动zookeeper插件

二，配置maven仓库

   由于是基于spring集成的kafka的方式 ，所以在添加spring依赖的同时，还需   

  org.springframework.kafka
  spring-kafka
  2.1.4.RELEASE


  org.apache.kafka
  kafka-clients
  1.0.0

三，kafka服务器配置

#brokers集群
bootstrap.servers=192.168.11.38:9092,192.168.11.40:9092
#即所有副本都同步到数据时send方法才返回, 以此来完全判断数据是否发送成功, 理论上来讲数据不会丢失.
acks=all
#发送失败重试次数
retries=10
#批处理条数：当多个记录被发送到同一个分区时，生产者会尝试将记录合并到更少的请求中。这有助于客户端和服务器的性能。
batch.size=1638
#批处理延迟时间上限：即1ms过后，不管是否达到批处理数，都直接发送一次请求
linger.ms=1
#即32MB的批处理缓冲区
buffer.memory=33554432
#消费者群组ID，发布-订阅模式，即如果一个生产者，多个消费者都要消费，那么需要定义自己的群组，同一群组内的消费者只有一个能消费到消息
group.id=order-beta
#如果为true，消费者的偏移量将在后台定期提交。
enable.auto.commit=true
#如何设置为自动提交（enable.auto.commit=true），这里设置自动提交周期
auto.commit.interval.ms=1000
#在使用Kafka的组管理时，用于检测消费者故障的超时
session.timeout.ms=15000
#消费监听器容器并发数
concurrency = 3

四，customer配置

xml version="1.0" encoding="UTF-8"?>
xmlns="http://www.springframework.org/schema/beans"
       xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:context="http://www.springframework.org/schema/context"
       xsi:schemaLocation="http://www.springframework.org/schema/beans
         http://www.springframework.org/schema/beans/spring-beans-3.0.xsd
         http://www.springframework.org/schema/context
         http://www.springframework.org/schema/context/spring-context.xsd">
    <context:property-placeholder location="classpath*:kafka.properties " />
    
    id="consumerProperties" class="java.util.HashMap">
        
                            key="bootstrap.servers" value="${bootstrap.servers}" />
                key="group.id" value="${group.id}" />
                key="enable.auto.commit" value="${enable.auto.commit}" />
                key="session.timeout.ms" value="${session.timeout.ms}" />
                key="key.deserializer"
                       value="org.apache.kafka.common.serialization.StringDeserializer" />
                key="value.deserializer"
                       value="org.apache.kafka.common.serialization.StringDeserializer" />
            
        
    

    
    id="consumerFactory"
          class="org.springframework.kafka.core.DefaultKafkaConsumerFactory" >
        
            bean="consumerProperties" />
        
    

    
    id="kafkaConsumerService" class="KafkaSendMessageServiceImpl" />

    
    id="containerProperties" class="org.springframework.kafka.listener.config.ContainerProperties">
        
        name="topics">
            
                topic1
                topic2
               
            
        
        name="messageListener" ref="kafkaConsumerService" />
    
    
    id="messageListenerContainer" class="org.springframework.kafka.listener.ConcurrentMessageListenerContainer" init-method="doStart" >
        ref="consumerFactory" />
        ref="containerProperties" />
        name="concurrency" value="${concurrency}" />
    
    

五，provider配置

xml version="1.0" encoding="UTF-8"?>
xmlns="http://www.springframework.org/schema/beans"
       xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:context="http://www.springframework.org/schema/context"
       xsi:schemaLocation="http://www.springframework.org/schema/beans
         http://www.springframework.org/schema/beans/spring-beans-3.0.xsd
         http://www.springframework.org/schema/context
         http://www.springframework.org/schema/context/spring-context.xsd">
    <context:property-placeholder location="classpath*:kafka.properties " />
    
    id="producerProperties" class="java.util.HashMap">
        
                            key="bootstrap.servers" value="${bootstrap.servers}" />
                key="group.id" value="${group.id}" />
                key="retries" value="${retries}" />
                key="batch.size" value="${batch.size}" />
                key="linger.ms" value="${linger.ms}" />
                key="buffer.memory" value="${buffer.memory}" />
                key="acks" value="${acks}" />
                key="key.serializer"
                       value="org.apache.kafka.common.serialization.StringSerializer" />
                key="value.serializer"
                       value="org.apache.kafka.common.serialization.StringSerializer" />
            
        
    

    
    id="producerFactory"
          class="org.springframework.kafka.core.DefaultKafkaProducerFactory">
        
            bean="producerProperties" />
        
    

    
    id="kafkaTemplate" class="org.springframework.kafka.core.KafkaTemplate">
        ref="producerFactory" />
        name="autoFlush" value="true" />
        name="defaultTopic" value="default" />
    

六，简单的KafkaUtils，发送kafka主题消息

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.context.support.ClassPathXmlApplicationContext;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.kafka.support.SendResult;
import org.springframework.util.concurrent.FailureCallback;
import org.springframework.util.concurrent.ListenableFuture;
import org.springframework.util.concurrent.SuccessCallback;

public class KafkaSendMsgUtils {
    public static final  ClassPathXmlApplicationContext CONTEXT = new ClassPathXmlApplicationContext("/kafka-provider.xml");

    public static <K,T>void sendMessage(String topic, Integer partition, Long timestamp,  K key, T data) {
        KafkaTemplate<K, T> kafkaTemplate = (KafkaTemplate<K, T>) CONTEXT.getBean("kafkaTemplate");
        ListenableFutureK, T>> listenableFuture = null;
        if (kafkaTemplate.getDefaultTopic().equals(topic)) {
            listenableFuture =  kafkaTemplate.sendDefault(partition,timestamp,key,data);
        }else {
            listenableFuture = kafkaTemplate.send(topic, partition, timestamp, key, data);
        }
        //发送成功回调
        SuccessCallbackK, T>> successCallback = new SuccessCallbackK, T>>() {
            @Override
            public void onSuccess(SendResult<K, T> result) {
                //成功业务逻辑
                System.out.println("成功");
            }
        };
        //发送失败回调
        FailureCallback failureCallback = new FailureCallback() {
            @Override
            public void onFailure(Throwable ex) {
                //失败业务逻辑
                throw new RuntimeException(ex);
            }
        };
        listenableFuture.addCallback(successCallback, failureCallback);
    }

    public static void main(String[] args) {
        for (int i = 0; i < 5; i++) {
            try {
                Thread.sleep(10000);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
            //KafkaTemplate kafkaTemplate = (KafkaTemplate) CONTEXT.getBean("kafkaTemplate");
            KafkaSendMsgUtils.sendMessage("topic1",0,null,"key","kafka-test");
        }
    }
}

七,消费者接受消息

import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.springframework.kafka.listener.MessageListener;

public class KafkaSendMessageServiceImpl implements MessageListener,String> {

    @Override
    public void onMessage(ConsumerRecord, String> data) {
            //根据不同主题，消费
            System.out.println("========");
            if("topic1".equals(data.topic())){
                //逻辑1
                System.out.println(data.value()+"被消费");
            }else if("topic2".equals(data.topic())){
                //逻辑2
                System.out.println(data.value()+"主题2 被消费");
            }
        }
}