kafka生产者和消费者的javaAPI的示例代码

写了个kafka的java demo 顺便记录下，仅供参考

1.创建maven项目

目录如下：

2.pom文件：

  4.0.0
  Kafka-Maven
  Kafka-Maven
  0.0.1-SNAPSHOT
  
    
      org.apache.kafka
      kafka_2.11
      0.10.1.1
    
    
      org.apache.hadoop
      hadoop-common
      2.2.0
    
    
      org.apache.hadoop
      hadoop-hdfs
      2.2.0
    
    
      org.apache.hadoop
      hadoop-client
      2.2.0
    
    
      org.apache.hbase
      hbase-client
      1.0.3
    
    
      org.apache.hbase
      hbase-server
      1.0.3
    
    
      org.apache.hadoop
      hadoop-hdfs
      2.2.0
    
    
      jdk.tools
      jdk.tools
      1.7
      system
      ${JAVA_HOME}/lib/tools.jar
    
    
      org.apache.httpcomponents
      httpclient
      4.3.6
    
  
  
    
      
 org.apache.maven.plugins
 maven-compiler-plugin
 
   1.7
   1.7
 
      
    
  

3.kafka生产者KafkaProduce:

package com.lijie.producer;

import java.io.File;
import java.io.FileInputStream;
import java.util.Properties;

import org.apache.kafka.clients.producer.Callback;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.clients.producer.Recordmetadata;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

public class KafkaProduce {
  private static Properties properties;

  static {
    properties = new Properties();
    String path = KafkaProducer.class.getResource("/").getFile().toString()
 + "kafka.properties";
    try {
      FileInputStream fis = new FileInputStream(new File(path));
      properties.load(fis);
    } catch (Exception e) {
      e.printStackTrace();
    }
  }

  
  public void sendMsg(String topic, byte[] key, byte[] value) {

    // 实例化produce
    KafkaProducer kp = new KafkaProducer(
 properties);

    // 消息封装
    ProducerRecord pr = new ProducerRecord(
 topic, key, value);

    // 发送数据
    kp.send(pr, new Callback() {
      // 回调函数
      @Override
      public void onCompletion(Recordmetadata metadata,
   Exception exception) {
 if (null != exception) {
   System.out.println("记录的offset在:" + metadata.offset());
   System.out.println(exception.getMessage() + exception);
 }
      }
    });

    // 关闭produce
    kp.close();
  }
}

4.kafka消费者KafkaConsume：

package com.lijie.consumer;

import java.io.File;
import java.io.FileInputStream;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Properties;

import org.apache.htrace.fasterxml.jackson.databind.ObjectMapper;

import com.lijie.pojo.User;
import com.lijie.utils.JsonUtils;

import kafka.consumer.ConsumerConfig;
import kafka.consumer.ConsumerIterator;
import kafka.consumer.KafkaStream;
import kafka.javaapi.consumer.ConsumerConnector;
import kafka.serializer.StringDecoder;
import kafka.utils.VerifiableProperties;

public class KafkaConsume {

  private final static String TOPIC = "lijietest";

  private static Properties properties;

  static {
    properties = new Properties();
    String path = KafkaConsume.class.getResource("/").getFile().toString()
 + "kafka.properties";
    try {
      FileInputStream fis = new FileInputStream(new File(path));
      properties.load(fis);
    } catch (Exception e) {
      e.printStackTrace();
    }
  }

  
  public void getMsg() throws Exception {
    ConsumerConfig config = new ConsumerConfig(properties);

    ConsumerConnector consumer = kafka.consumer.Consumer
 .createJavaConsumerConnector(config);

    Map topicCountMap = new HashMap();

    topicCountMap.put(TOPIC, new Integer(1));

    StringDecoder keyDecoder = new StringDecoder(new VerifiableProperties());

    StringDecoder valueDecoder = new StringDecoder(
 new VerifiableProperties());

    Map>> consumerMap = consumer
 .createMessageStreams(topicCountMap, keyDecoder, valueDecoder);

    KafkaStream stream = consumerMap.get(TOPIC).get(0);

    ConsumerIterator it = stream.iterator();

    while (it.hasNext()) {
      String json = it.next().message();
      User user = (User) JsonUtils.JsonToObj(json, User.class);
      System.out.println(user);
    }
  }
}

5.kafka.properties文件

##produce
bootstrap.servers=192.168.80.123:9092
producer.type=sync
request.required.acks=1
serializer.class=kafka.serializer.DefaultEncoder
key.serializer=org.apache.kafka.common.serialization.ByteArraySerializer
value.serializer=org.apache.kafka.common.serialization.ByteArraySerializer
bak.partitioner.class=kafka.producer.DefaultPartitioner
bak.key.serializer=org.apache.kafka.common.serialization.StringSerializer
bak.value.serializer=org.apache.kafka.common.serialization.StringSerializer

##consume
zookeeper.connect=192.168.80.123:2181 
group.id=lijiegroup 
zookeeper.session.timeout.ms=4000 
zookeeper.sync.time.ms=200 
auto.commit.interval.ms=1000 
auto.offset.reset=smallest 
serializer.class=kafka.serializer.StringEncoder 

以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持考高分网。