kafka java production consumer program demo example

Kafka is a message system with huge throughput. It is written in scala, which is different from the production and consumption of ordinary messages. I wrote a demo program for your reference. For the installation of kafka, please refer to the official documentation.

First, we need to create a new maven project, and then reference the kafka jar package in the pom. The reference dependencies are as follows:

    <dependency>
        <groupId>org.apache.kafka</groupId>
        <artifactId>kafka_2.10</artifactId>
        <version>0.8.0</version>
    </dependency>

The version we use is 0.8. Let's look at the code of the production message:

package com.iaiai;

import java.util.Properties;

import kafka.javaapi.producer.Producer;
import kafka.producer.KeyedMessage;
import kafka.producer.ProducerConfig;

/**
 * Hello world!
 *
 */
public class KafkaProducer
{
    private final Producer<String, String> producer;
    public final static String TOPIC = "TEST-TOPIC";

    private KafkaProducer(){
        Properties props = new Properties();
        //The port configured here is kafka
        props.put("metadata.broker.list", "192.168.193.148:9092");

        //Configure the serialization class of value
        props.put("serializer.class", "kafka.serializer.StringEncoder");
        //Configure the serialization class of the key
        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 = 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();
    }
}

The following is the code implementation on the consumer side:

package com.iaiai;

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;

public class KafkaConsumer {

    private final ConsumerConnector consumer;

    private KafkaConsumer() {
        Properties props = new Properties();
        //zookeeper configuration
        props.put("zookeeper.connect", "192.168.193.148:2181");

        //group represents a consumer group
        props.put("group.id", "jd-group");

        //zk connection timeout
        props.put("zookeeper.session.timeout.ms", "4000");
        props.put("zookeeper.sync.time.ms", "200");
        props.put("auto.commit.interval.ms", "1000");
        props.put("auto.offset.reset", "smallest");
        // serialize class
        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();
    }
}

Note that the consumer side needs to be configured with the address of zk, while the production side is configured with the ip and port of kafka.