kafka集群搭建

1.zookeeper集群  搭建在110， 111,112

2.kafka使用3个节点110， 111,112
修改配置文件config/server.properties
broker.id=110
host.name=192.168.1.110
log.dirs=/usr/local/kafka_2.10-0.8.2.0/logs
复制到其他两个节点，然后修改对应节点上的config/server.pro

3.启动,在三个节点分别执行
bin/kafka-server-start.sh  config/server.properties >/dev/null 2>&1 &

4 创建主题
bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 3 --partitions 3 --topic test

5 查看主题详细
bin/kafka-topics.sh --describe --zookeeper localhost:2181 --topic test
 --topic test
Topic:test      PartitionCount:3        ReplicationFactor:3     Configs:
        Topic: test     Partition: 0    Leader: 110     Replicas: 110,111,112  Isr: 110,111,112
        Topic: test     Partition: 1    Leader: 111     Replicas: 111,112,110  Isr: 111,112,110
        Topic: test     Partition: 2    Leader: 112     Replicas: 112,110,111  Isr: 112,110,111


6 去zk上看kafka集群
[zk: localhost:2181(CONNECTED) 5] ls /
[admin, zookeeper, consumers, config, controller, zk-fifo, storm, brokers, controller_epoch]
[zk: localhost:2181(CONNECTED) 6] ls /brokers   ----> 查看注册在zk内的kafka
[topics, ids]
[zk: localhost:2181(CONNECTED) 7] ls /brokers/ids
[112, 110, 111]
[zk: localhost:2181(CONNECTED) 8] ls /brokers/ids/112
[]
[zk: localhost:2181(CONNECTED) 9] ls /brokers/topics
[test]
[zk: localhost:2181(CONNECTED) 10] ls /brokers/topics/test
[partitions]
[zk: localhost:2181(CONNECTED) 11] ls /brokers/topics/test/partitions
[2, 1, 0]
[zk: localhost:2181(CONNECTED) 12]

2  kafka java调用：

2.1 java端生产数据， kafka集群消费数据：

1 创建maven工程，pom.xml中增加如下：
 <dependency>
        <groupId>org.apache.kafka</groupId>
        <artifactId>kafka_2.10</artifactId>
        <version>0.8.2.0</version>
    </dependency>


2 java代码：  向主题test内写入数据

import java.util.Properties;
import java.util.concurrent.TimeUnit;

import kafka.javaapi.producer.Producer;
import kafka.producer.KeyedMessage;
import kafka.producer.ProducerConfig;
import kafka.serializer.StringEncoder;




public class kafkaProducer extends Thread{

    private String topic;

    public kafkaProducer(String topic){
        super();
        this.topic = topic;
    }


    @Override
    public void run() {
        Producer producer = createProducer();
        int i=0;
        while(true){
            producer.send(new KeyedMessage<Integer, String>(topic, "message: " + i++));
            try {
                TimeUnit.SECONDS.sleep(1);
            } catch (InterruptedException e) {
                e.printStackTrace();
            }
        }
    }

    private Producer createProducer() {
        Properties properties = new Properties();
        properties.put("zookeeper.connect", "192.168.1.110:2181,192.168.1.111:2181,192.168.1.112:2181");//声明zk
        properties.put("serializer.class", StringEncoder.class.getName());
        properties.put("metadata.broker.list", "192.168.1.110:9092,192.168.1.111:9093,192.168.1.112:9094");// 声明kafka broker
        return new Producer<Integer, String>(new ProducerConfig(properties));
     }


    public static void main(String[] args) {
        new kafkaProducer("test").start();// 使用kafka集群中创建好的主题 test

    }

}




3  kafka集群中消费主题test的数据：
[root@h2master kafka]# bin/kafka-console-consumer.sh --zookeeper localhost:2181 --topic test --from-beginnin

4   启动java代码，然后在看集群消费的数据如下：

message: 0
message: 1
message: 2
message: 3
message: 4
message: 5
message: 6
message: 7
message: 8
message: 9
message: 10
message: 11
message: 12
message: 13
message: 14
message: 15
message: 16
message: 17
message: 18
message: 19
message: 20
message: 21

 3 kafka 使用Java写消费者，这样 先运行kafkaProducer ，在运行kafkaConsumer，即可得到生产者的数据：

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

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




/**
 * 接收数据
 * 接收到: message: 10
接收到: message: 11
接收到: message: 12
接收到: message: 13
接收到: message: 14
 * @author zm
 *
 */
public class kafkaConsumer extends Thread{

    private String topic;

    public kafkaConsumer(String topic){
        super();
        this.topic = topic;
    }


    @Override
    public void run() {
        ConsumerConnector consumer = createConsumer();
        Map<String, Integer> topicCountMap = new HashMap<String, Integer>();
        topicCountMap.put(topic, 1); // 一次从主题中获取一个数据
         Map<String, List<KafkaStream<byte[], byte[]>>>  messageStreams = consumer.createMessageStreams(topicCountMap);
         KafkaStream<byte[], byte[]> stream = messageStreams.get(topic).get(0);// 获取每次接收到的这个数据
         ConsumerIterator<byte[], byte[]> iterator =  stream.iterator();
         while(iterator.hasNext()){
             String message = new String(iterator.next().message());
             System.out.println("接收到: " + message);
         }
    }

    private ConsumerConnector createConsumer() {
        Properties properties = new Properties();
        properties.put("zookeeper.connect", "192.168.1.110:2181,192.168.1.111:2181,192.168.1.112:2181");//声明zk
        properties.put("group.id", "group1");// 必须要使用别的组名称， 如果生产者和消费者都在同一组，则不能访问同一组内的topic数据
        return Consumer.createJavaConsumerConnector(new ConsumerConfig(properties));
     }


    public static void main(String[] args) {
        new kafkaConsumer("test").start();// 使用kafka集群中创建好的主题 test

    }

}

 

代码见附件：

 

 

• kafka.rar (8.6 KB)
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