zoukankan      html  css  js  c++  java
  • kafka java api生产者

    import java.util.HashMap;

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

    import org.junit.Test;

    import kafka.consumer.Consumer;
    import kafka.consumer.ConsumerConfig;
    import kafka.consumer.ConsumerIterator;
    import kafka.consumer.KafkaStream;
    import kafka.javaapi.consumer.ConsumerConnector;
    import kafka.javaapi.producer.Producer;
    import kafka.producer.KeyedMessage;
    import kafka.producer.ProducerConfig;


    public class KafkaProducer {

    private final Producer<String, String> producer;
    public final static String TOPIC = "test";

    private KafkaProducer(){

    Properties props = new Properties();

    // 此处配置的是kafka的broker地址:端口列表
    props.put("metadata.broker.list", "192.168.170.185:9092,192.168.170.185:9093,192.168.170.185:9094");

    //配置value的序列化类
    props.put("serializer.class", "kafka.serializer.StringEncoder");

    //配置key的序列化类
    props.put("key.serializer.class", "kafka.serializer.StringEncoder");

    //request.required.acks
    //0, which means that the producer never waits for an acknowledgement from the broker (the same behavior as 0.7). This option provides the lowest latency but the weakest durability guarantees (some data will be lost when a server fails).
    //1, which means that the producer gets an acknowledgement after the leader replica has received the data. This option provides better durability as the client waits until the server acknowledges the request as successful (only messages that were written to the now-dead leader but not yet replicated will be lost).
    //-1, which means that the producer gets an acknowledgement after all in-sync replicas have received the data. This option provides the best durability, we guarantee that no messages will be lost as long as at least one in sync replica remains.
    // props.put("request.required.acks","-1");

    producer = new Producer<String, String>(new ProducerConfig(props));
    }

    void produce() {
    int messageNo = 1;
    final int COUNT = 101;

    int messageCount = 0;
    while (messageNo < COUNT) {
    String key = String.valueOf(messageNo);
    String data = "Hello kafka message :" + key;
    producer.send(new KeyedMessage<String, String>(TOPIC, key ,data));
    System.out.println(data);
    messageNo ++;
    messageCount++;
    }

    System.out.println("Producer端一共产生了" + messageCount + "条消息!");
    }

    public static void main( String[] args )
    {
    new KafkaProducer().produce();
    }

    }

  • 相关阅读:
    spring2.5 mvc使用注解upload上传文件
    从5点来分析搜索引擎算法
    搜索引擎算法研究专题六:HITS算法
    搜索引擎算法研究专题五:TFIDF详解
    搜索引擎算法研究专题二:HITS算法及其衍生算法分析
    搜索引擎算法研究专题一:基于页面分块的搜索引擎排序算法改进
    搜索引擎算法研究专题三:聚集索引与非聚集索引介绍
    Spring最佳实践9.1 集成邮件服务
    搜索引擎算法研究专题四:随机冲浪模型介绍
    搜索引擎算法研究专题七:Hilltop算法
  • 原文地址:https://www.cnblogs.com/wangjing666/p/6860748.html
Copyright © 2011-2022 走看看