如何使用Avro二进制编码器对Kafka消息进行编码/解码？

我正在尝试使用Avro来读取/写入Kafka的消息.有没有人有一个使用Avro二进制编码器编码/解码将被放在消息队列中的数据的例子？

我需要Avro部件而不是Kafka部件.或者,也许我应该看一个不同的解决方案？基本上,我正试图在空间方面找到更有效的JSON解决方案.刚刚提到Avro,因为它比JSON更紧凑.

这是一个基本的例子.我没有尝试过多个分区/主题.

//示例生产者代码

import org.apache.avro.Schema;
import org.apache.avro.generic.GenericData;
import org.apache.avro.generic.GenericRecord;
import org.apache.avro.io.*;
import org.apache.avro.specific.SpecificDatumReader;
import org.apache.avro.specific.SpecificDatumWriter;
import org.apache.commons.codec.DecoderException;
import org.apache.commons.codec.binary.Hex;
import kafka.javaapi.producer.Producer;
import kafka.producer.KeyedMessage;
import kafka.producer.ProducerConfig;
import java.io.ByteArrayOutputStream;
import java.io.File;
import java.io.IOException;
import java.nio.charset.Charset;
import java.util.Properties;


public class ProducerTest {

    void producer(Schema schema) throws IOException {

        Properties props = new Properties();
        props.put("metadata.broker.list", "0:9092");
        props.put("serializer.class", "kafka.serializer.DefaultEncoder");
        props.put("request.required.acks", "1");
        ProducerConfig config = new ProducerConfig(props);
        Producer producer = new Producer(config);
        GenericRecord payload1 = new GenericData.Record(schema);
        //Step2 : Put data in that genericrecord object
        payload1.put("desc", "'testdata'");
        //payload1.put("name", "?asa");
        payload1.put("name", "dbevent1");
        payload1.put("id", 111);
        System.out.println("Original Message : "+ payload1);
        //Step3 : Serialize the object to a bytearray
        DatumWriterwriter = new SpecificDatumWriter(schema);
        ByteArrayOutputStream out = new ByteArrayOutputStream();
        BinaryEncoder encoder = EncoderFactory.get().binaryEncoder(out, null);
        writer.write(payload1, encoder);
        encoder.flush();
        out.close();

        byte[] serializedBytes = out.toByteArray();
        System.out.println("Sending message in bytes : " + serializedBytes);
        //String serializedHex = Hex.encodeHexString(serializedBytes);
        //System.out.println("Serialized Hex String : " + serializedHex);
        KeyedMessage message = new KeyedMessage("page_views", serializedBytes);
        producer.send(message);
        producer.close();

    }


    public static void main(String[] args) throws IOException, DecoderException {
        ProducerTest test = new ProducerTest();
        Schema schema = new Schema.Parser().parse(new File("src/test_schema.avsc"));
        test.producer(schema);
    }
}

//消费者代码示例

第1部分:使用者组代码:因为您可以为多个分区/主题拥有多个使用者.

import kafka.consumer.ConsumerConfig;
import kafka.consumer.KafkaStream;
import kafka.javaapi.consumer.ConsumerConnector;

import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Properties;
import java.util.concurrent.Executor;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.TimeUnit;

/**
 * Created by  on 9/1/15.
 */
public class ConsumerGroupExample {
   private final ConsumerConnector consumer;
   private final String topic;
   private ExecutorService executor;

   public ConsumerGroupExample(String a_zookeeper, String a_groupId, String a_topic){
      consumer = kafka.consumer.Consumer.createJavaConsumerConnector(
              createConsumerConfig(a_zookeeper, a_groupId));
      this.topic = a_topic;
   }

   private static ConsumerConfig createConsumerConfig(String a_zookeeper, String a_groupId){
       Properties props = new Properties();
       props.put("zookeeper.connect", a_zookeeper);
       props.put("group.id", a_groupId);
       props.put("zookeeper.session.timeout.ms", "400");
       props.put("zookeeper.sync.time.ms", "200");
       props.put("auto.commit.interval.ms", "1000");

       return new ConsumerConfig(props);
   }

    public void shutdown(){
         if (consumer!=null) consumer.shutdown();
        if (executor!=null) executor.shutdown();
        System.out.println("Timed out waiting for consumer threads to shut down, exiting uncleanly");
        try{
          if(!executor.awaitTermination(5000, TimeUnit.MILLISECONDS)){

          }
        }catch(InterruptedException e){
            System.out.println("Interrupted");
        }

    }


    public void run(int a_numThreads){
        //Make a map of topic as key and no. of threads for that topic
        Map topicCountMap = new HashMap();
        topicCountMap.put(topic, new Integer(a_numThreads));
        //Create message streams for each topic
        Map>> consumerMap = consumer.createMessageStreams(topicCountMap);
        List> streams = consumerMap.get(topic);

        //initialize thread pool
        executor = Executors.newFixedThreadPool(a_numThreads);
        //start consuming from thread
        int threadNumber = 0;
        for (final KafkaStream stream : streams) {
            executor.submit(new ConsumerTest(stream, threadNumber));
            threadNumber++;
        }
    }
    public static void main(String[] args) {
        String zooKeeper = args[0];
        String groupId = args[1];
        String topic = args[2];
        int threads = Integer.parseInt(args[3]);

        ConsumerGroupExample example = new ConsumerGroupExample(zooKeeper, groupId, topic);
        example.run(threads);

        try {
            Thread.sleep(10000);
        } catch (InterruptedException ie) {

        }
        example.shutdown();
    }


}

第2部分:实际消费消息的单个消费者.

import kafka.consumer.ConsumerIterator;
import kafka.consumer.KafkaStream;
import kafka.message.MessageAndMetadata;
import org.apache.avro.Schema;
import org.apache.avro.generic.GenericRecord;
import org.apache.avro.generic.IndexedRecord;
import org.apache.avro.io.DatumReader;
import org.apache.avro.io.Decoder;
import org.apache.avro.io.DecoderFactory;
import org.apache.avro.specific.SpecificDatumReader;
import org.apache.commons.codec.binary.Hex;

import java.io.File;
import java.io.IOException;

public class ConsumerTest implements Runnable{

    private KafkaStream m_stream;
    private int m_threadNumber;

    public ConsumerTest(KafkaStream a_stream, int a_threadNumber) {
        m_threadNumber = a_threadNumber;
        m_stream = a_stream;
    }

    public void run(){
        ConsumerIteratorit = m_stream.iterator();
        while(it.hasNext())
        {
            try {
                //System.out.println("Encoded Message received : " + message_received);
                //byte[] input = Hex.decodeHex(it.next().message().toString().toCharArray());
                //System.out.println("Deserializied Byte array : " + input);
                byte[] received_message = it.next().message();
                System.out.println(received_message);
                Schema schema = null;
                schema = new Schema.Parser().parse(new File("src/test_schema.avsc"));
                DatumReader reader = new SpecificDatumReader(schema);
                Decoder decoder = DecoderFactory.get().binaryDecoder(received_message, null);
                GenericRecord payload2 = null;
                payload2 = reader.read(null, decoder);
                System.out.println("Message received : " + payload2);
            }catch (Exception e) {
                e.printStackTrace();
                System.out.println(e);
            }
        }

    }


}

测试AVRO架构:

{
    "namespace": "xyz.test",
     "type": "record",
     "name": "payload",
     "fields":[
         {
            "name": "name", "type": "string"
         },
         {
            "name": "id",  "type": ["int", "null"]
         },
         {
            "name": "desc", "type": ["string", "null"]
         }
     ]
}

需要注意的重要事项是:

你需要标准的kafka和avro jar才能运行这个代码.

非常重要的props.put("serializer.class","kafka.serializer.DefaultEncoder"); 唐t use stringEncoder as that won如果您要发送一个字节数组作为信息科技工作.

您可以将byte []转换为十六进制字符串,然后将该字符串和使用者重新发送十六进制字符串发送到byte [],然后发送到原始消息.

运行如下所述的zookeeper和代理: - http://kafka.apache.org/documentation.html#quickstart并创建一个名为"page_views"的主题或任何你想要的主题.

运行ProducerTest.java,然后运行ConsumerGroupExample.java,查看正在生成和使用的avro数据.

我终于记得要问Kafka邮件列表并得到以下答案,这完美地运作了.

是的,您可以将消息作为字节数组发送.如果你看一下Message类的构造函数,你会看到 -

def this(bytes:Array [Byte])

现在,看一下Producer的send()API -

def send(producerData:ProducerData [K,V]*)

您可以将V设置为Message和K类型,使其成为您想要的密钥.如果您不关心使用密钥进行分区,那么也将其设置为Message类型.

谢谢,Neha

如果要从Avro消息中获取字节数组(已经回答了kafka部分),请使用二进制编码器:

    GenericDatumWriter writer = new GenericDatumWriter(schema); 
    ByteArrayOutputStream os = new ByteArrayOutputStream(); 
    try {
        Encoder e = EncoderFactory.get().binaryEncoder(os, null); 
        writer.write(record, e); 
        e.flush(); 
        byte[] byteData = os.toByteArray(); 
    } finally {
        os.close(); 
    }