java实现kafka单机版测试 - 51Testing软件测试论坛

import java.util.Date;
import java.util.Properties;
import kafka.javaapi.producer.Producer;
import kafka.producer.KeyedMessage;
import kafka.producer.ProducerConfig;
public class TestProducer {
public static void main(String[] args) {
// 设置配置属性
Properties props = new Properties();
props.put("metadata.broker.list","192.168.3.224:9092");
props.put("serializer.class", "kafka.serializer.StringEncoder");
// key.serializer.class默认为serializer.class
props.put("key.serializer.class", "kafka.serializer.StringEncoder");
// 可选配置，如果不配置，则使用默认的partitioner
// props.put("partitioner.class", "com.catt.kafka.demo.PartitionerDemo");
// 触发acknowledgement机制，否则是fire and forget，可能会引起数据丢失
// 值为0,1,-1,可以参考
// http://kafka.apache.org/08/configuration.html
props.put("request.required.acks", "1");
ProducerConfig config = new ProducerConfig(props);
// 创建producer
Producer<String, String> producer = new Producer<String, String>(config);
// 产生并发送消息
long start=System.currentTimeMillis();
long runtime = new Date().getTime();
String ip = "192.168.3.224" ; //rnd.nextInt(255);
String msg = runtime + "小张666777" + ip;
//如果topic不存在，则会自动创建，默认replication-factor为1，partitions为0
KeyedMessage<String, String> data = new KeyedMessage<String, String>(
"test456", ip, msg);
producer.send(data);
System.out.println("耗时:" + (System.currentTimeMillis() - start));
// 关闭producer
producer.close();
}
}
java消费者：
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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;
public class Consumer extends Thread {
private final ConsumerConnector consumer;
private final String topic;
private final String name;
public Consumer(String name, String topic) {
consumer = kafka.consumer.Consumer
.createJavaConsumerConnector(createConsumerConfig());
this.topic = topic;
this.name = name;
}
private static ConsumerConfig createConsumerConfig() {
Properties props = new Properties();
props.put("zookeeper.connect","192.168.3.224:2181");
props.put("group.id","jd-group");
props.put("zookeeper.session.timeout.ms", "60000");
props.put("zookeeper.sync.time.ms", "2000");
props.put("auto.commit.interval.ms", "1000");
// 每次最少接收的字节数，默认是1
// props.put("fetch.min.bytes", "1024");
// 每次最少等待时间，默认是100
// props.put("fetch.wait.max.ms", "600000");
return new ConsumerConfig(props);
}
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("************" + name + " gets "
+ new String(it.next().message()));
}
}
}
[java] view plain copy
public class KafkaConsumerDemo {
public static void main(String[] args) {
Consumer consumerThread1 = new Consumer("Consumer1","test123");
consumerThread1.start();
}
}

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