kafka java简单例子

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) {
String value = "message: "+ i++;
System.out.println("value:" + value);
producer.send(new KeyedMessage<Integer, String>(topic, value));
try {
TimeUnit.SECONDS.sleep(5);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}

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

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

}

}

value:message: 0
value:message: 1
value:message: 2
value:message: 3
value:message: 4
value:message: 5
value:message: 6

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",
"x.x.x.x:2181,x.x.x.x: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
properties.put("zookeeper.session.timeout.ms", "15000");
properties.put("zookeeper.sync.time.ms", "200");
properties.put("auto.commit.interval.ms", "1000");
return Consumer.createJavaConsumerConnector(new ConsumerConfig(
properties));
}

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

}

}

接收到: message: 0
接收到: message: 1
接收到: message: 2
接收到: message: 3
接收到: message: 4
接收到: message: 5
接收到: message: 6