kafka简单示例

1、Maven依赖

<dependency>
    <groupId>org.apache.kafkagroupId>
    <artifactId>kafka_2.11artifactId>
    <version>0.10.2.0version>
dependency>

2.ConfigureAPI

　　首先是一个配置结构类文件，配置Kafka的相关参数，代码如下所示：

public class ConfigureAPI {
    public interface KafkaProperties {
        public final static String ZK = "127.0.0.1:2181";
        public final static String GROUP_ID = "test_group1";
        public final static String TOPIC = "test";
        public final static String BROKER_LIST = "127.0.0.1:9092";
        public final static int BUFFER_SIZE = 64 * 1024;
        public final static int TIMEOUT = 20000;
        public final static int INTERVAL = 10000;
    }
}

3.Consumer

　　然后是一个消费程序，用于消费Kafka的消息，代码如下所示：

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

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

public class JConsumer extends  Thread{
    private String topic;
    private final int SLEEP = 1000 * 3;
    private ConsumerConnector consumer;

    public JConsumer(String topic) {
        consumer = Consumer.createJavaConsumerConnector(this.consumerConfig());
        this.topic = topic;
    }

    private ConsumerConfig consumerConfig() {
        Properties props = new Properties();
        props.put("bootstrap.servers",  ConfigureAPI.KafkaProperties.BROKER_LIST);
        props.put("zookeeper.connect", ConfigureAPI.KafkaProperties.ZK);
        props.put("group.id", ConfigureAPI.KafkaProperties.GROUP_ID);
        props.put("zookeeper.session.timeout.ms", "40000");
        props.put("enable.auto.commit", "false");
        props.put("zookeeper.sync.time.ms", "200");
        props.put("auto.commit.interval.ms", "1000");
        props.put("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        props.put("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer");
        return new ConsumerConfig(props);
    }

    @Override
    public void run() {
        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);
        List> streams = consumerMap.get(topic);
        for (final KafkaStream stream : streams) {
            ConsumerIterator it = stream.iterator();
            while (it.hasNext()) {
                MessageAndMetadata messageAndMetadata= it.next();
                System.out.println("Receive->[" + new String(messageAndMetadata.message()) + "],topic->["+messageAndMetadata.topic()
                        +"],offset->["+messageAndMetadata.offset()+"],partition->["+messageAndMetadata.partition()
                        +"],timestamp->["+messageAndMetadata.timestamp()+"]");
                consumer.commitOffsets();
                try {
                    sleep(SLEEP);
                } catch (Exception ex) {
                    consumer.commitOffsets();
                    ex.printStackTrace();
                }
            }
        }
        /*Map>> consumerMap = consumer.createMessageStreams(topicCountMap);
        List> streams = consumerMap.get(topic);
        for (final KafkaStream stream : streams) {
            ConsumerIterator it = stream.iterator();
            while (it.hasNext()) {
                MessageAndMetadata messageAndMetadata= it.next();
                System.out.println("Receive->[" + new String(messageAndMetadata.message()) + "],topic->["+messageAndMetadata.topic()
                +"],offset->["+messageAndMetadata.offset()+"],partition->["+messageAndMetadata.partition()
                +"],timestamp->["+messageAndMetadata.timestamp()+"]");
                //consumer.commitOffsets();
                consumer.commitOffsets();
                try {
                    sleep(SLEEP);
                } catch (Exception ex) {
                    consumer.commitOffsets();
                    ex.printStackTrace();
                }
            }
        }*/
    }
}

4.Producer

　　接着是Kafka的生产消息程序，用于产生Kafka的消息供Consumer去消费，具体代码如下所示：

import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.Producer;
import org.apache.kafka.clients.producer.ProducerRecord;
import java.util.Properties;


public class JProducer extends Thread{
    private Producer producer;
    private String topic;
    private Properties props = new Properties();
    private final int SLEEP = 1000 * 3;

    public JProducer(String topic) {
        props.put("serializer.class", "kafka.serializer.StringEncoder");
        //props.put("metadata.broker.list",  ConfigureAPI.KafkaProperties.BROKER_LIST);
        props.put("bootstrap.servers", ConfigureAPI.KafkaProperties.BROKER_LIST);
        props.put("acks", "all");
        props.put("retries", 0);
        props.put("batch.size", 16384);
        props.put("linger.ms", 1);
        props.put("buffer.memory", 33554432);
        props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        producer = new KafkaProducer(props);
        this.topic = topic;
    }

    @Override
    public void run() {
        int offsetNo = 1;
        boolean flag = true;
        while (flag) {
            String msg = new String("Message_" + offsetNo);
            System.out.println("Send->[" + msg + "]");
            producer.send(new ProducerRecord(topic, String.valueOf(offsetNo), msg));
            offsetNo++;
            if(offsetNo == 210){
                flag = false;
            }
            try {
                sleep(SLEEP);
            } catch (Exception ex) {
                producer.close();
                ex.printStackTrace();
            }
        }
        producer.close();
    }
}

5.截图预览

　　在开发完Consumer和Producer的代码后，我们来测试相关应用，下面给大家编写了一个Client去测试Consumer和Producer，具体代码如下所示：

public class KafkaClient {
    public static void main(String[] args) {
        JProducer pro = new JProducer(ConfigureAPI.KafkaProperties.TOPIC);
        pro.start();

        JConsumer con = new JConsumer(ConfigureAPI.KafkaProperties.TOPIC);
        con.start();
    }
}

运行截图如下所示：

6.总结

　　大家在开发Kafka的应用时，需要注意相关事项。若是使用Maven项目工程，在添加相关Kafka依赖JAR包时，有可能依赖JAR会下载失败，若出现这种情况，可手动将Kafka的依赖JAR包添加到Maven仓库即可，在编写Consumer和Producer程序，这里只是给出一个示例让大家先熟悉Kafka的代码如何去编写，后面会给大家更加详细复杂的代码模块案例