轉(zhuǎn)自：http://chengjianxiaoxue.iteye.com/blog/2190488

1 kafka集群搭建

1.zookeeper集群 搭建在110， 111,112

2.kafka使用3個(gè)節(jié)點(diǎn)110， 111,112修改配置文件config/server.properties

broker.id=110host.name=192.168.1.110log.dirs=/usr/local/kafka_2.10-0.8.2.0/logs

復(fù)制到其他兩個(gè)節(jié)點(diǎn)，然后修改對(duì)應(yīng)節(jié)點(diǎn)上的config/server.pro3.啟動(dòng),在三個(gè)節(jié)點(diǎn)分別執(zhí)行

bin/kafka-server-start.sh config/server.properties >/dev/null 2>&1 &

4創(chuàng)建主題

bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 3 --partitions 3 --topic test5查看主題詳細(xì)

bin/kafka-topics.sh --describe --zookeeper localhost:2181 --topic test--topic test

Topic:test PartitionCount:3 ReplicationFactor:3Configs:

Topic: test Partition:0 Leader: 110 Replicas: 110,111,112 Isr: 110,111,112Topic: test Partition:1 Leader: 111 Replicas: 111,112,110 Isr: 111,112,110Topic: 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 ---->查看注冊(cè)在zk內(nèi)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調(diào)用：

2.1 java端生產(chǎn)數(shù)據(jù)， kafka集群消費(fèi)數(shù)據(jù)：

1 創(chuàng)建maven工程，pom.xml中增加如下：

org.apache.kafka

kafka_2.10

0.8.2.0

2 java代碼： 向主題test內(nèi)寫(xiě)入數(shù)據(jù)

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(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");//聲明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");// 聲明kafka broker

return new Producer(new ProducerConfig(properties));

}

public static void main(String[] args) {

new kafkaProducer("test").start();// 使用kafka集群中創(chuàng)建好的主題 test

}

}

3 kafka集群中消費(fèi)主題test的數(shù)據(jù)：

[root@h2master kafka]# bin/kafka-console-consumer.sh --zookeeper localhost:2181 --topic test --from-beginnin

4 啟動(dòng)java代碼，然后在看集群消費(fèi)的數(shù)據(jù)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寫(xiě)消費(fèi)者，這樣 先運(yùn)行kafkaProducer ，在運(yùn)行kafkaConsumer，即可得到生產(chǎn)者的數(shù)據(jù)：

importjava.util.HashMap;importjava.util.List;importjava.util.Map;importjava.util.Properties;importkafka.consumer.Consumer;importkafka.consumer.ConsumerConfig;importkafka.consumer.ConsumerIterator;importkafka.consumer.KafkaStream;importkafka.javaapi.consumer.ConsumerConnector;/*** 接收數(shù)據(jù)

* 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

*@authorzm

**/

public class kafkaConsumer extendsThread{privateString topic;publickafkaConsumer(String topic){super();this.topic =topic;

}

@Overridepublic voidrun() {

ConsumerConnector consumer=createConsumer();

Map topicCountMap = new HashMap();

topicCountMap.put(topic,1); //一次從主題中獲取一個(gè)數(shù)據(jù)

Map>> messageStreams =consumer.createMessageStreams(topicCountMap);

KafkaStream stream = messageStreams.get(topic).get(0);//獲取每次接收到的這個(gè)數(shù)據(jù)

ConsumerIterator iterator =stream.iterator();while(iterator.hasNext()){

String message= newString(iterator.next().message());

System.out.println("接收到: " +message);

}

}privateConsumerConnector createConsumer() {

Properties properties= newProperties();

properties.put("zookeeper.connect", "192.168.1.110:2181,192.168.1.111:2181,192.168.1.112:2181");//聲明zk

properties.put("group.id", "group1");//必須要使用別的組名稱(chēng)， 如果生產(chǎn)者和消費(fèi)者都在同一組，則不能訪問(wèn)同一組內(nèi)的topic數(shù)據(jù)

return Consumer.createJavaConsumerConnector(newConsumerConfig(properties));

}public static voidmain(String[] args) {new kafkaConsumer("test").start();//使用kafka集群中創(chuàng)建好的主題 test

}

}