How to encode/decode Kafka messages using Avro binary encoder?

Question

I'm trying to use Avro for messages being read from/written to Kafka. Does anyone have an example of using the Avro binary encoder to encode/decode data that will be put on a message queue?

I need the Avro part more than the Kafka part. Or, perhaps I should look at a different solution? Basically, I'm trying to find a more efficient solution to JSON with regards to space. Avro was just mentioned since it can be more compact than JSON.

Answer 1

This is a basic example. I have not tried it with multiple partitions/topics.

//Sample producer code

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<String, byte[]> producer = new Producer<String, byte[]>(config);         GenericRecord payload1 = new GenericData.Record(schema);         //Step2 : Put data in that genericrecord object         payload1.put("desc", "'testdata'");         //payload1.put("name", "अasa");         payload1.put("name", "dbevent1");         payload1.put("id", 111);         System.out.println("Original Message : "+ payload1);         //Step3 : Serialize the object to a bytearray         DatumWriter<GenericRecord>writer = new SpecificDatumWriter<GenericRecord>(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<String, byte[]> message = new KeyedMessage<String, byte[]>("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);     } } 

//Sample consumer code

Part 1 : Consumer group code : as you can have more than multiple consumers for multiple partitions/ topics.

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<String, Integer> topicCountMap = new HashMap<String, Integer>();         topicCountMap.put(topic, new Integer(a_numThreads));         //Create message streams for each topic         Map<String, List<KafkaStream<byte[], byte[]>>> consumerMap = consumer.createMessageStreams(topicCountMap);         List<KafkaStream<byte[], byte[]>> 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();     }   } 

Part 2 : Indiviual consumer that actually consumes the messages.

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(){         ConsumerIterator<byte[], byte[]>it = 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<GenericRecord> reader = new SpecificDatumReader<GenericRecord>(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);             }         }      }   } 

Test AVRO schema :

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

Important things to note are :

1. Youll need the standard kafka and avro jars to run this code out of the box.

2. Is very important props.put("serializer.class", "kafka.serializer.DefaultEncoder"); Dont use stringEncoder as that wont work if you are sending a byte array as message.

3. You can convert the byte[] to a hex string and send that and on the consumer reconvert hex string to byte[] and then to the original message.

4. Run the zookeeper and the broker as mentioned here :- http://kafka.apache.org/documentation.html#quickstart and create a topic called "page_views" or whatever you want.

5. Run the ProducerTest.java and then the ConsumerGroupExample.java and see the avro data being produced and consumed.