Examples with Producer kafka.javaapi.producer.Producer used on opensource projects

Example 6 with Producer

use of kafka.javaapi.producer.Producer in project pinot by linkedin.

the class BaseClusterIntegrationTest method pushRandomAvroIntoKafka.

public static void pushRandomAvroIntoKafka(File avroFile, String kafkaBroker, String kafkaTopic, int rowCount, Random random) {
    Properties properties = new Properties();
    properties.put("metadata.broker.list", kafkaBroker);
    properties.put("serializer.class", "kafka.serializer.DefaultEncoder");
    properties.put("request.required.acks", "1");
    ProducerConfig producerConfig = new ProducerConfig(properties);
    Producer<String, byte[]> producer = new Producer<String, byte[]>(producerConfig);
    try {
        ByteArrayOutputStream outputStream = new ByteArrayOutputStream(65536);
        DataFileStream<GenericRecord> reader = AvroUtils.getAvroReader(avroFile);
        BinaryEncoder binaryEncoder = new EncoderFactory().directBinaryEncoder(outputStream, null);
        Schema avroSchema = reader.getSchema();
        GenericDatumWriter<GenericRecord> datumWriter = new GenericDatumWriter<GenericRecord>(avroSchema);
        int recordCount = 0;
        int rowsRemaining = rowCount;
        int messagesInThisBatch = 0;
        while (rowsRemaining > 0) {
            int rowsInThisBatch = Math.min(rowsRemaining, MAX_MESSAGES_PER_BATCH);
            List<KeyedMessage<String, byte[]>> messagesToWrite = new ArrayList<KeyedMessage<String, byte[]>>(rowsInThisBatch);
            GenericRecord genericRecord = new GenericData.Record(avroSchema);
            for (int i = 0; i < rowsInThisBatch; ++i) {
                generateRandomRecord(genericRecord, avroSchema, random);
                outputStream.reset();
                datumWriter.write(genericRecord, binaryEncoder);
                binaryEncoder.flush();
                byte[] bytes = outputStream.toByteArray();
                KeyedMessage<String, byte[]> data = new KeyedMessage<String, byte[]>(kafkaTopic, bytes);
                if (BATCH_KAFKA_MESSAGES) {
                    messagesToWrite.add(data);
                    messagesInThisBatch++;
                    if (MAX_MESSAGES_PER_BATCH <= messagesInThisBatch) {
                        messagesInThisBatch = 0;
                        producer.send(messagesToWrite);
                        messagesToWrite.clear();
                        Uninterruptibles.sleepUninterruptibly(1, TimeUnit.SECONDS);
                    }
                } else {
                    producer.send(data);
                }
                recordCount += 1;
            }
            if (BATCH_KAFKA_MESSAGES) {
                producer.send(messagesToWrite);
            }
            //        System.out.println("rowsRemaining = " + rowsRemaining);
            rowsRemaining -= rowsInThisBatch;
        }
        outputStream.close();
        reader.close();
        LOGGER.info("Finished writing " + recordCount + " records from " + avroFile.getName() + " into Kafka topic " + kafkaTopic);
        int totalRecordCount = totalAvroRecordWrittenCount.addAndGet(recordCount);
        LOGGER.info("Total records written so far " + totalRecordCount);
    } catch (Exception e) {
        e.printStackTrace();
        throw new RuntimeException(e);
    }
}

Example 7 with Producer

use of kafka.javaapi.producer.Producer in project avro-kafka-storm by ransilberman.

the class MainTest method testGenericRecord.

@Test
public void testGenericRecord() throws IOException, InterruptedException {
    Schema.Parser parser = new Schema.Parser();
    Schema schema = parser.parse(getClass().getResourceAsStream("LPEvent.avsc"));
    GenericRecord datum = new GenericData.Record(schema);
    datum.put("revision", 1L);
    datum.put("siteId", "28280110");
    datum.put("eventType", "PLine");
    datum.put("timeStamp", System.currentTimeMillis());
    datum.put("sessionId", "123456II");
    Map<String, Schema> unions = new HashMap<String, Schema>();
    List<Schema> typeList = schema.getField("subrecord").schema().getTypes();
    for (Schema sch : typeList) {
        unions.put(sch.getName(), sch);
    }
    GenericRecord plineDatum = new GenericData.Record(unions.get("pline"));
    plineDatum.put("text", "How can I help you?");
    plineDatum.put("lineType", 1);
    plineDatum.put("repId", "REPID12345");
    datum.put("subrecord", plineDatum);
    ByteArrayOutputStream out = new ByteArrayOutputStream();
    DatumWriter<GenericRecord> writer = new GenericDatumWriter<GenericRecord>(schema);
    Encoder encoder = EncoderFactory.get().binaryEncoder(out, null);
    writer.write(datum, encoder);
    encoder.flush();
    out.close();
    Message message = new Message(out.toByteArray());
    Properties props = new Properties();
    props.put("zk.connect", zkConnection);
    Producer<Message, Message> producer = new kafka.javaapi.producer.Producer<Message, Message>(new ProducerConfig(props));
    producer.send(new ProducerData<Message, Message>(topic, message));
}