java实现Kafka生产者示例

使用java实现Kafka的生产者

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package com.lisg.kafkatest;   import java.util.Properties;   import kafka.javaapi.producer.Producer; import kafka.producer.KeyedMessage; import kafka.producer.Partitioner; import kafka.producer.ProducerConfig; import kafka.serializer.StringEncoder;   /**  * Kafka生产者  * @author lisg  *  */ public class KafkaProducer {       public static void main(String[] args) {                   Properties props = new Properties();         //根据这个配置获取metadata,不必是kafka集群上的所有broker,但最好至少有两个         props.put("metadata.broker.list", "vm1:9092,vm2:9092");         //消息传递到broker时的序列化方式         props.put("serializer.class", StringEncoder.class.getName());         //zk集群         props.put("zookeeper.connect", "vm1:2181");         //是否获取反馈         //0是不获取反馈(消息有可能传输失败)         //1是获取消息传递给leader后反馈(其他副本有可能接受消息失败)         //-1是所有in-sync replicas接受到消息时的反馈         props.put("request.required.acks", "1"); //      props.put("partitioner.class", MyPartition.class.getName());                   //创建Kafka的生产者, key是消息的key的类型, value是消息的类型         Producer<Integer, String> producer = new Producer<Integer, String>(                 new ProducerConfig(props));                   int count = 0;         while(true) {             String message = "message-" + ++count;             //消息主题是test             KeyedMessage<Integer, String> keyedMessage = new KeyedMessage<Integer, String>("test", message);             //message可以带key, 根据key来将消息分配到指定区, 如果没有key则随机分配到某个区 //          KeyedMessage<Integer, String> keyedMessage = new KeyedMessage<Integer, String>("test", 1, message);             producer.send(keyedMessage);             System.out.println("send: " + message);             try {                 Thread.sleep(1000);             } catch (InterruptedException e) {                 e.printStackTrace();             }         }           //      producer.close();     }   }   /**  * 自定义分区类  *  */ class MyPartition implements Partitioner {       public int partition(Object key, int numPartitions) {         return key.hashCode()%numPartitions;     }       }

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