漫游kafka实战篇之搭建Kafka开发环境

上篇文章中我们搭建了kafka的服务器，并可以使用Kafka的命令行工具创建topic，发送和接收消息。下面我们来搭建kafka的开发环境。

 

添加依赖

 

搭建开发环境需要引入kafka的jar包，一种方式是将Kafka安装包中lib下的jar包加入到项目的classpath中，这种比较简单了。不过我们使用另一种更加流行的方式：使用maven管理jar包依赖。

创建好maven项目后，在pom.xml中添加以下依赖：

               

<dependency>
         <groupId> org.apache.kafka</groupId >
         <artifactId> kafka_2.10</artifactId >
         <version> 0.8.0</ version>
</dependency>

添加依赖后你会发现有两个jar包的依赖找不到。没关系我都帮你想好了，点击这里下载这两个jar包，解压后你有两种选择，第一种是使用mvn的install命令将jar包安装到本地仓库，另一种是直接将解压后的文件夹拷贝到mvn本地仓库的com文件夹下，比如我的本地仓库是d:mvn,完成后我的目录结构是这样的：

 

 

配置程序

 

首先是一个充当配置文件作用的接口,配置了Kafka的各种连接参数：

package com.sohu.kafkademon;

public interface KafkaProperties
{
    final static String zkConnect = "10.22.10.139:2181";
    final static String groupId = "group1";
    final static String topic = "topic1";
    final static String kafkaServerURL = "10.22.10.139";
    final static int kafkaServerPort = 9092;
    final static int kafkaProducerBufferSize = 64 * 1024;
    final static int connectionTimeOut = 20000;
    final static int reconnectInterval = 10000;
    final static String topic2 = "topic2";
    final static String topic3 = "topic3";
    final static String clientId = "SimpleConsumerDemoClient";
}

producer

 

package com.sohu.kafkademon;

import java.util.Properties;

import kafka.producer.KeyedMessage;
import kafka.producer.ProducerConfig;

/**
 * @author leicui bourne_cui@163.com
 */
public class KafkaProducer extends Thread
{
    private final kafka.javaapi.producer.Producer<Integer, String> producer;
    private final String topic;
    private final Properties props = new Properties();

    public KafkaProducer(String topic)
    {
        props.put("serializer.class", "kafka.serializer.StringEncoder");
        props.put("metadata.broker.list", "10.22.10.139:9092");
        producer = new kafka.javaapi.producer.Producer<Integer, String>(new ProducerConfig(props));
        this.topic = topic;
    }

    @Override
    public void run() {
        int messageNo = 1;
        while (true)
        {
            String messageStr = new String("Message_" + messageNo);
            System.out.println("Send:" + messageStr);
            producer.send(new KeyedMessage<Integer, String>(topic, messageStr));
            messageNo++;
            try {
                sleep(3000);
            } catch (InterruptedException e) {
                // TODO Auto-generated catch block
                e.printStackTrace();
            }
        }
    }

}

 

consumer

 

package com.sohu.kafkademon;

import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Properties;

import kafka.consumer.ConsumerConfig;
import kafka.consumer.ConsumerIterator;
import kafka.consumer.KafkaStream;
import kafka.javaapi.consumer.ConsumerConnector;

/**
 * @author leicui bourne_cui@163.com
 */
public class KafkaConsumer extends Thread
{
    private final ConsumerConnector consumer;
    private final String topic;

    public KafkaConsumer(String topic)
    {
        consumer = kafka.consumer.Consumer.createJavaConsumerConnector(
                createConsumerConfig());
        this.topic = topic;
    }

    private static ConsumerConfig createConsumerConfig()
    {
        Properties props = new Properties();
        props.put("zookeeper.connect", KafkaProperties.zkConnect);
        props.put("group.id", KafkaProperties.groupId);
        props.put("zookeeper.session.timeout.ms", "40000");
        props.put("zookeeper.sync.time.ms", "200");
        props.put("auto.commit.interval.ms", "1000");
        return new ConsumerConfig(props);
    }

    @Override
    public void run() {
        Map<String, Integer> topicCountMap = new HashMap<String, Integer>();
        topicCountMap.put(topic, new Integer(1));
        Map<String, List<KafkaStream<byte[], byte[]>>> consumerMap = consumer.createMessageStreams(topicCountMap);
        KafkaStream<byte[], byte[]> stream = consumerMap.get(topic).get(0);
        ConsumerIterator<byte[], byte[]> it = stream.iterator();
        while (it.hasNext()) {
            System.out.println("receive：" + new String(it.next().message()));
            try {
                sleep(3000);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
        }
    }
}

简单的发送接收

 

运行下面这个程序，就可以进行简单的发送接收消息了：

package com.sohu.kafkademon;

/**
 * @author leicui bourne_cui@163.com
 */
public class KafkaConsumerProducerDemo
{
    public static void main(String[] args)
    {
        KafkaProducer producerThread = new KafkaProducer(KafkaProperties.topic);
        producerThread.start();

        KafkaConsumer consumerThread = new KafkaConsumer(KafkaProperties.topic);
        consumerThread.start();
    }
}

高级别的consumer

 

下面是比较负载的发送接收的程序：

package com.sohu.kafkademon;

import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Properties;

import kafka.consumer.ConsumerConfig;
import kafka.consumer.ConsumerIterator;
import kafka.consumer.KafkaStream;
import kafka.javaapi.consumer.ConsumerConnector;

/**
 * @author leicui bourne_cui@163.com
 */
public class KafkaConsumer extends Thread
{
    private final ConsumerConnector consumer;
    private final String topic;

    public KafkaConsumer(String topic)
    {
        consumer = kafka.consumer.Consumer.createJavaConsumerConnector(
                createConsumerConfig());
        this.topic = topic;
    }

    private static ConsumerConfig createConsumerConfig()
    {
        Properties props = new Properties();
        props.put("zookeeper.connect", KafkaProperties.zkConnect);
        props.put("group.id", KafkaProperties.groupId);
        props.put("zookeeper.session.timeout.ms", "40000");
        props.put("zookeeper.sync.time.ms", "200");
        props.put("auto.commit.interval.ms", "1000");
        return new ConsumerConfig(props);
    }

    @Override
    public void run() {
        Map<String, Integer> topicCountMap = new HashMap<String, Integer>();
        topicCountMap.put(topic, new Integer(1));
        Map<String, List<KafkaStream<byte[], byte[]>>> consumerMap = consumer.createMessageStreams(topicCountMap);
        KafkaStream<byte[], byte[]> stream = consumerMap.get(topic).get(0);
        ConsumerIterator<byte[], byte[]> it = stream.iterator();
        while (it.hasNext()) {
            System.out.println("receive：" + new String(it.next().message()));
            try {
                sleep(3000);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
        }
    }
}