Kafka入门实例

摘要:本文主要讲了Kafka的一个简单入门实例

源码下载：https://github.com/appleappleapple/BigDataLearning

kafka安装过程看这里：Kafka在Windows安装运行

整个工程目录如下：

1、pom文件

[html]   view plain  copy <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"       xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">       <modelVersion>4.0.0</modelVersion>       <groupId>com.lin</groupId>       <artifactId>Kafka-Demo</artifactId>       <version>0.0.1-SNAPSHOT</version>          <dependencies>           <dependency>               <groupId>org.apache.kafka</groupId>               <artifactId>kafka_2.10</artifactId>               <version>0.9.0.0</version>           </dependency>              <dependency>               <groupId>org.opentsdb</groupId>               <artifactId>java-client</artifactId>               <version>2.1.0-SNAPSHOT</version>               <exclusions>                   <exclusion>                       <groupId>org.slf4j</groupId>                       <artifactId>slf4j-log4j12</artifactId>                   </exclusion>                   <exclusion>                       <groupId>log4j</groupId>                       <artifactId>log4j</artifactId>                   </exclusion>                   <exclusion>                       <groupId>org.slf4j</groupId>                       <artifactId>jcl-over-slf4j</artifactId>                   </exclusion>               </exclusions>           </dependency>              <dependency>               <groupId>com.alibaba</groupId>               <artifactId>fastjson</artifactId>               <version>1.2.4</version>           </dependency>             </dependencies>   </project>  

2、生产者

[html]   view plain  copy package com.lin.demo.producer;      import java.util.Properties;      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 = "linlin";          private KafkaProducer() {           Properties props = new Properties();           // 此处配置的是kafka的端口           props.put("metadata.broker.list", "127.0.0.1:9092");           props.put("zk.connect", "127.0.0.1:2181");                // 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");              props.put("request.required.acks", "-1");              producer = new Producer<String, String>(new ProducerConfig(props));       }          void produce() {           int messageNo = 1000;           final int COUNT = 10000;              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++;           }       }          public static void main(String[] args) {           new KafkaProducer().produce();       }   }  

右键：run as Java application

运行结果：

3、消费者

[java]   view plain  copy package com.lin.demo.consumer;      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;   import kafka.serializer.StringDecoder;   import kafka.utils.VerifiableProperties;      import com.lin.demo.producer.KafkaProducer;      public class KafkaConsumer {          private final ConsumerConnector consumer;          private KafkaConsumer() {           Properties props = new Properties();           // zookeeper 配置           props.put("zookeeper.connect", "127.0.0.1:2181");              // group 代表一个消费组           props.put("group.id", "lingroup");              // zk连接超时           props.put("zookeeper.session.timeout.ms", "4000");           props.put("zookeeper.sync.time.ms", "200");           props.put("rebalance.max.retries", "5");           props.put("rebalance.backoff.ms", "1200");                             props.put("auto.commit.interval.ms", "1000");           props.put("auto.offset.reset", "smallest");           // 序列化类           props.put("serializer.class", "kafka.serializer.StringEncoder");              ConsumerConfig config = new ConsumerConfig(props);              consumer = kafka.consumer.Consumer.createJavaConsumerConnector(config);       }          void consume() {           Map<String, Integer> topicCountMap = new HashMap<String, Integer>();           topicCountMap.put(KafkaProducer.TOPIC, new Integer(1));              StringDecoder keyDecoder = new StringDecoder(new VerifiableProperties());           StringDecoder valueDecoder = new StringDecoder(new VerifiableProperties());              Map<String, List<KafkaStream<String, String>>> consumerMap = consumer.createMessageStreams(topicCountMap, keyDecoder, valueDecoder);           KafkaStream<String, String> stream = consumerMap.get(KafkaProducer.TOPIC).get(0);           ConsumerIterator<String, String> it = stream.iterator();           while (it.hasNext())               System.out.println("<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<" + it.next().message() + "<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<");       }          public static void main(String[] args) {           new KafkaConsumer().consume();       }   }  

运行结果：

监控页面

源码下载：https://github.com/appleappleapple/BigDataLearning