kafka与Spring集成

kafka与Spring的集成配置生产者：前提kafka安装完成，及创建好主题

pom文件配置：

<!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka -->
<dependency>
    <groupId>org.apache.kafka</groupId>
    <artifactId>kafka_2.12</artifactId>
    <version>2.1.0</version>
    <exclusions>
        <exclusion>
            <artifactId>jmxri</artifactId>
            <groupId>com.sun.jmx</groupId>
        </exclusion>
        <exclusion>
            <artifactId>jms</artifactId>
            <groupId>javax.jms</groupId>
        </exclusion>
        <exclusion>
            <artifactId>jmxtools</artifactId>
            <groupId>com.sun.jdmk</groupId>
        </exclusion>
    </exclusions>
</dependency>
<dependency>
    <groupId>org.apache.kafka</groupId>
    <artifactId>kafka-clients</artifactId>
    <version>2.1.0</version>
</dependency>
<dependency>
    <groupId>org.springframework.kafka</groupId>
    <artifactId>spring-kafka</artifactId>
    <version>2.1.11.RELEASE</version><!--2.1.11.RELEASE  2.2以上版本不支持 指定具体监听类-->
</dependency>

config.properties:

#kafka
#kafka访问地址
kafka.serverHost=192.168.3.117:9092
#kafka主题名称
kafka.topic=goods

spring-kafkaProducer.xml：

<?xml version="1.0" encoding="UTF-8"?>
<beans 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.xsd
         http://www.springframework.org/schema/context
         http://www.springframework.org/schema/context/spring-context.xsd">

   <!--基本配置 -->
    <bean id="producerProperties" class="java.util.HashMap">
        <constructor-arg>
            <map>
                <!-- kafka服务地址，可能是集群-->
                <entry key="bootstrap.servers" value="${kafka.serverHost}" />
                <entry key="group.id" value="0"/>
                <!-- 有可能导致broker接收到重复的消息,默认值为3-->
                <entry key="retries" value="10" />
                <!-- 每次批量发送消息的数量-->
                <entry key="batch.size" value="1638" />
                <!-- 默认0ms，在异步IO线程被触发后（任何一个topic，partition满都可以触发）-->
                <entry key="linger.ms" value="1" />
                <!--producer可以用来缓存数据的内存大小。如果数据产生速度大于向broker发送的速度，producer会阻塞或者抛出异常 -->
                <entry key="buffer.memory" value="33554432 " />
                <!-- producer需要server接收到数据之后发出的确认接收的信号，此项配置就是指procuder需要多少个这样的确认信号-->
                <entry key="acks" value="all" />
                <entry key="key.serializer" value="org.apache.kafka.common.serialization.StringSerializer" />
                <entry key="value.serializer" value="org.apache.kafka.common.serialization.StringSerializer" />
            </map>
        </constructor-arg>
    </bean>

    <!-- 创建kafkatemplate需要使用的producerfactory bean -->
    <bean id="producerFactory"
          class="org.springframework.kafka.core.DefaultKafkaProducerFactory">
        <constructor-arg>
            <ref bean="producerProperties" />
        </constructor-arg>
    </bean>

    <!-- 创建kafkatemplate bean，使用的时候，只需要注入这个bean，即可使用template的send消息方法 -->
    <bean id="KafkaTemplate" class="org.springframework.kafka.core.KafkaTemplate">
        <constructor-arg ref="producerFactory" />
        <constructor-arg name="autoFlush" value="true" />
        <!--设置对应topic-->
        <property name="defaultTopic" value="${kafka.topic}" />
    </bean>
    <bean id="producerListener" class="com.hanshow.wise.base.goods.servlet.KafkaProducerListener" />
</beans>

spring.xml:

<?xml version="1.0" encoding="UTF-8"?>
<beans 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-4.0.xsd
		http://www.springframework.org/schema/context 
		http://www.springframework.org/schema/context/spring-context-4.0.xsd">

	<!-- 引入config.properties属性文件 -->
	<context:property-placeholder location="classpath:config.properties"/>

	<!-- 自动扫描(自动注入)，扫描这个包以及它的子包的所有使用@Service注解标注的类 -->
	<context:component-scan base-package="com.hanshow.wise.base.*.service" />
	
	<context:component-scan base-package="com.hanshow.wise.base.goods.servlet"/>
	<import resource="classpath:spring-kafkaProducer.xml" />
</beans>

KafkaProducerListener监听:

package com.hanshow.wise.base.goods.servlet;

import org.apache.kafka.clients.producer.RecordMetadata;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.kafka.support.ProducerListener;
 
/**
 * kafkaProducer监听器，在producer配置文件中开启
 * @author 
 *
 */
@SuppressWarnings("rawtypes")
public class KafkaProducerListener implements ProducerListener{
    protected final Logger LOG = LoggerFactory.getLogger("kafkaProducer");
    /**
     * 发送消息成功后调用
     */
    public void onSuccess(String topic, Integer partition, Object key,
            Object value, RecordMetadata recordMetadata) {
        LOG.info("==========kafka发送数据成功（日志开始）==========");
        LOG.info("----------topic:"+topic);
        LOG.info("----------partition:"+partition);
        LOG.info("----------key:"+key);
        LOG.info("----------value:"+value);
        LOG.info("----------RecordMetadata:"+recordMetadata);
        LOG.info("~~~~~~~~~~kafka发送数据成功（日志结束）~~~~~~~~~~");
    }
 
    /**
     * 发送消息错误后调用
     */
    public void onError(String topic, Integer partition, Object key,
            Object value, Exception exception) {
        LOG.info("==========kafka发送数据错误（日志开始）==========");
        LOG.info("----------topic:"+topic);
        LOG.info("----------partition:"+partition);
        LOG.info("----------key:"+key);
        LOG.info("----------value:"+value);
        LOG.info("----------Exception:"+exception);
        LOG.info("~~~~~~~~~~kafka发送数据错误（日志结束）~~~~~~~~~~");
        exception.printStackTrace();
    }
 
    /**
     * 方法返回值代表是否启动kafkaProducer监听器
     */
    public boolean isInterestedInSuccess() {
        LOG.info("///kafkaProducer监听器启动///");
        return true;
    }
 
}

KafkaProducerService接口：

package com.hanshow.wise.base.goods.service;

import java.util.Map;

import com.hanshow.wise.base.goods.model.dto.StoreGoodsDTO;
import com.hanshow.wise.common.jo.BaseDTO;

/**
 * kafka接口
 * 
 * @author 
 * @date 2018年6月2日
 * @since 1.0.0
 */
public interface KafkaProducerService {

	BaseDTO<Map<String, Object>> getProducer(StoreGoodsDTO storeGoodsDTO);

}

KafkaProducerServiceImpl实现：

package com.hanshow.wise.base.goods.service.impl;

import java.util.Map;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.kafka.core.KafkaTemplate;
import org.springframework.stereotype.Service;

import com.hanshow.wise.base.goods.model.dto.StoreGoodsDTO;
import com.hanshow.wise.base.goods.service.KafkaProducerService;
import com.hanshow.wise.base.goods.util.ConfigUtils;
import com.hanshow.wise.common.jo.BaseDTO;

/**
 * 提供商品分类信息查询支持Service实现
 * 
 * @author 
 * @date 2018年6月2日
 * @since 1.0.0
 */
@Service
public class KafkaProducerServiceImpl implements KafkaProducerService {
	
	Logger logger = LoggerFactory.getLogger(KafkaProducerServiceImpl.class);
	
	@Autowired
    private KafkaTemplate<String, String> kafkaTemplate;

	@Override
	public void getProducer() {
		kafkaTemplate.send(ConfigUtils.getType("kafka.topic"), "内容");
	}
}

测试调用结果：

以上是kafka与Spring的集成内容。

附加简单测试生产者与消费者，无需spring配置。前提kafka安装完成，及创建好主题。

ProducerDemo.java,生产者：

package com.hanshow.wise.base.goods;

import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.Producer;
import org.apache.kafka.clients.producer.ProducerRecord;

import java.util.Properties;


public class ProducerDemo {
    public static String serverHost="192.168.3.117:9092";
    public static void main(String[] args) {
        Properties props = new Properties();
        props.put("bootstrap.servers", serverHost);
        //The "all" setting we have specified will result in blocking on the full commit of the record, the slowest but most durable setting.
        //“所有”设置将导致记录的完整提交阻塞，最慢的，但最持久的设置。
        props.put("acks", "all");
        //如果请求失败，生产者也会自动重试，即使设置成０ the producer can automatically retry.
        props.put("retries", 0);
        //The producer maintains buffers of unsent records for each partition.
        props.put("batch.size", 16384);
        //默认立即发送，这里这是延时毫秒数
        props.put("linger.ms", 1);
        //生产者缓冲大小，当缓冲区耗尽后，额外的发送调用将被阻塞。时间超过max.block.ms将抛出TimeoutException
        props.put("buffer.memory", 33554432);
        //The key.serializer and value.serializer instruct how to turn the key and value objects the user provides with their ProducerRecord into bytes.
        props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        
        //创建kafka的生产者类
        Producer<String, String> producer = new KafkaProducer<String, String>(props);
        for (int i = 0; i < 10; i++) {
            // 这里平均写入４个分区
        	// producer.send(new ProducerRecord<String, String>("test", i % 4, Integer.toString(i), Integer.toString(i)));
            // 因为没有建立集群所以只能是0个分区
            producer.send(new ProducerRecord<String, String>("my-first-topic", 0, Integer.toString(i), Integer.toString(i)));
        }
        producer.close();
    }
}

ConsumerDemo.java消费者

package com.hanshow.wise.base.goods;

import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;

import java.util.Arrays;
import java.util.Properties;

public class ConsumerDemo {

    public static void main(String[] args) {
        Properties props = new Properties();

        props.put("bootstrap.servers", ProducerDemo.serverHost);
        System.out.println("this is the group part test 1");
        //消费者的组id
        props.put("group.id", "GroupA");//这里是GroupA或者GroupB
        props.put("enable.auto.commit", "true");
        props.put("auto.commit.interval.ms", "1000");

        //从poll(拉)的回话处理时长
        props.put("session.timeout.ms", "30000");
        //poll的数量限制
        //props.put("max.poll.records", "100");
        props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");

        KafkaConsumer<String, String> consumer = new KafkaConsumer<String, String>(props);
        //订阅主题列表topic
        consumer.subscribe(Arrays.asList("my-first-topic"));
        while (true) {
            ConsumerRecords<String, String> records = consumer.poll(100);
            for (ConsumerRecord<String, String> record : records)
                //　正常这里应该使用线程池处理，不应该在这里处理
                System.out.printf("offset = %d, key = %s, value = %s", record.offset(), record.key(), record.value() + "\n");

        }
    }

}

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