Java IntegerSerializer类代码示例

import org.apache.kafka.common.serialization.IntegerSerializer; //导入依赖的package包/类
public void publishDummyDataNumbers() {
    final String topic = "NumbersTopic";

    // Create publisher
    final Map<String, Object> config = new HashMap<>();
    config.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, IntegerSerializer.class);
    config.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, IntegerSerializer.class);
    config.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");

    final KafkaProducer<Integer, Integer> producer = new KafkaProducer<>(config);
    for (int value = 0; value < 10000; value++) {
        producer.send(new ProducerRecord<>(topic, value, value));
    }
    producer.flush();
    producer.close();
}
 

import org.apache.kafka.common.serialization.IntegerSerializer; //导入依赖的package包/类
private static void produceRecords(String bootstrapServers) {
    Properties properties = new Properties();
    properties.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
    properties.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, IntegerSerializer.class.getName());
    properties.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getName());

    Producer<Integer, String> producer = new KafkaProducer<>(properties);

    IntStream.rangeClosed(1, 100).boxed()
            .map(number ->
                    new ProducerRecord<>(
                            TOPIC,
                            number, //Key
                            String.format("record-%s", number))) //Value
            .forEach(record -> producer.send(record));
    producer.close();
}
 

import org.apache.kafka.common.serialization.IntegerSerializer; //导入依赖的package包/类
private static void produceRecords(String bootstrapServers) {
    Properties properties = new Properties();
    properties.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
    properties.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, IntegerSerializer.class.getName());
    properties.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getName());

    Producer<Integer, String> producer = new KafkaProducer<>(properties);

    IntStream.rangeClosed(1, 10000).boxed()
            .map(number ->
                    new ProducerRecord<>(
                            TOPIC,
                            1, //Key
                            String.format("record-%s", number))) //Value
            .forEach(record -> producer.send(record));
    producer.close();
}
 

import org.apache.kafka.common.serialization.IntegerSerializer; //导入依赖的package包/类
private static void produceRecords(String bootstrapServers) {
    Properties properties = new Properties();
    properties.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
    properties.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, IntegerSerializer.class.getName());
    properties.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getName());

    Producer<Integer, String> producer = new KafkaProducer<>(properties);

    IntStream
            .rangeClosed(1, 100000).boxed()
            .map(number ->
                    new ProducerRecord<>(
                            TOPIC,
                            1, //Key
                            String.format("record-%s", number))) //Value
            .forEach(record -> producer.send(record));
    producer.close();
}
 

import org.apache.kafka.common.serialization.IntegerSerializer; //导入依赖的package包/类
private static void produceRecords() {
    Properties properties = new Properties();
    properties.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
    properties.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, IntegerSerializer.class.getName());
    properties.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, ByteArraySerializer.class.getName());

    Producer<Integer, byte[]> producer = new KafkaProducer<>(properties);

    IntStream.rangeClosed(1, 10000).boxed()
            .map(number ->
                    new ProducerRecord<>(
                            TOPIC,
                            1, //Key
                            KafkaProducerUtil.createMessage(1000))) //Value
            .forEach(record -> {
                producer.send(record);
                try {
                    Thread.sleep(1000);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            });
    producer.close();
}
 

import org.apache.kafka.common.serialization.IntegerSerializer; //导入依赖的package包/类
private static void produceRecords(String bootstrapServers) {
    Properties properties = new Properties();
    properties.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
    properties.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, IntegerSerializer.class.getName());
    properties.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, ByteArraySerializer.class.getName());

    Producer<Integer, byte[]> producer = new KafkaProducer<>(properties);

    IntStream.rangeClosed(1, 10000).boxed()
            .map(number ->
                    new ProducerRecord<>(
                            TOPIC,
                            1, //Key
                            KafkaProducerUtil.createMessage(1000))) //Value
            .forEach(record -> {
                producer.send(record);
                try {
                    Thread.sleep(1000);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
            });
    producer.close();
}
 

import org.apache.kafka.common.serialization.IntegerSerializer; //导入依赖的package包/类
private static void produceRecords(String bootstrapServers) {
    Properties properties = new Properties();
    properties.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, bootstrapServers);
    properties.put(ProducerConfig.ACKS_CONFIG, "all");
    properties.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, IntegerSerializer.class.getName());
    properties.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, StringSerializer.class.getName());

    Producer<Integer, String> producer = new KafkaProducer<>(properties);

    IntStream.rangeClosed(1, 100).boxed()
            .map(number ->
                    new ProducerRecord<>(
                            TOPIC,
                            number, //Key
                            String.format("record-%s", number))) //Value
            .forEach(record -> {
                try {
                    Thread.sleep(1000);
                } catch (InterruptedException e) {
                    e.printStackTrace();
                }
                producer.send(record);
            });
    producer.close();
}
 

import org.apache.kafka.common.serialization.IntegerSerializer; //导入依赖的package包/类
private void produceMessages(final long timestamp)
    throws ExecutionException, InterruptedException {
    IntegrationTestUtils.produceKeyValuesSynchronouslyWithTimestamp(
        streamOneInput,
        Arrays.asList(
            new KeyValue<>(1, "A"),
            new KeyValue<>(2, "B"),
            new KeyValue<>(3, "C"),
            new KeyValue<>(4, "D"),
            new KeyValue<>(5, "E")),
        TestUtils.producerConfig(
            CLUSTER.bootstrapServers(),
            IntegerSerializer.class,
            StringSerializer.class,
            new Properties()),
        timestamp);
}
 

import org.apache.kafka.common.serialization.IntegerSerializer; //导入依赖的package包/类
private void produceStreamTwoInputTo(final String streamTwoInput)
    throws ExecutionException, InterruptedException {
    IntegrationTestUtils.produceKeyValuesSynchronously(
        streamTwoInput,
        Arrays.asList(
            new KeyValue<>(1, "A"),
            new KeyValue<>(2, "B"),
            new KeyValue<>(3, "C"),
            new KeyValue<>(4, "D"),
            new KeyValue<>(5, "E")),
        TestUtils.producerConfig(
            CLUSTER.bootstrapServers(),
            IntegerSerializer.class,
            StringSerializer.class,
            new Properties()),
        mockTime);
}
 

import org.apache.kafka.common.serialization.IntegerSerializer; //导入依赖的package包/类
private void produceToStreamOne()
    throws ExecutionException, InterruptedException {
    IntegrationTestUtils.produceKeyValuesSynchronously(
        streamOneInput,
        Arrays.asList(
            new KeyValue<>(10L, 1),
            new KeyValue<>(5L, 2),
            new KeyValue<>(12L, 3),
            new KeyValue<>(15L, 4),
            new KeyValue<>(20L, 5),
            new KeyValue<Long, Integer>(70L, null)), // nulls should be filtered
        TestUtils.producerConfig(
            CLUSTER.bootstrapServers(),
            LongSerializer.class,
            IntegerSerializer.class,
            new Properties()),
        mockTime);
}
 

import org.apache.kafka.common.serialization.IntegerSerializer; //导入依赖的package包/类
private void produceMessages(long timestamp)
    throws ExecutionException, InterruptedException {
    IntegrationTestUtils.produceKeyValuesSynchronouslyWithTimestamp(
        streamOneInput,
        Arrays.asList(
            new KeyValue<>(1, "A"),
            new KeyValue<>(2, "B"),
            new KeyValue<>(3, "C"),
            new KeyValue<>(4, "D"),
            new KeyValue<>(5, "E")),
        TestUtils.producerConfig(
            CLUSTER.bootstrapServers(),
            IntegerSerializer.class,
            StringSerializer.class,
            new Properties()),
        timestamp);
}
 

import org.apache.kafka.common.serialization.IntegerSerializer; //导入依赖的package包/类
private Properties setProduceConsumeProperties(final String clientId) {
    Properties props = new Properties();
    props.put(ProducerConfig.CLIENT_ID_CONFIG, clientId);
    props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, kafka);
    props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, IntegerSerializer.class);
    props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, ByteArraySerializer.class);
    // the socket buffer needs to be large, especially when running in AWS with
    // high latency. if running locally the default is fine.
    props.put(ProducerConfig.SEND_BUFFER_CONFIG, SOCKET_SIZE_BYTES);
    props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, IntegerDeserializer.class);
    props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, ByteArrayDeserializer.class);
    props.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, "false");
    // the socket buffer needs to be large, especially when running in AWS with
    // high latency. if running locally the default is fine.
    props.put(ConsumerConfig.RECEIVE_BUFFER_CONFIG, SOCKET_SIZE_BYTES);
    props.put(ConsumerConfig.MAX_POLL_RECORDS_CONFIG, MAX_POLL_RECORDS);
    return props;
}
 

import org.apache.kafka.common.serialization.IntegerSerializer; //导入依赖的package包/类
@Test
public void testSinkWithInteger() throws InterruptedException {
    KafkaUsage usage = new KafkaUsage();
    String topic = UUID.randomUUID().toString();
    CountDownLatch latch = new CountDownLatch(1);
    AtomicInteger expected = new AtomicInteger(2);
    usage.consumeIntegers(topic, 10, 10, TimeUnit.SECONDS,
        latch::countDown,
        (k, v) -> v == expected.getAndIncrement());


    KafkaSink<Integer> sink = new KafkaSink<>(vertx,
        getKafkaConfig()
            .put("topic", topic)
            .put("value.serializer", IntegerSerializer.class.getName())
            .put("value.deserializer", IntegerDeserializer.class.getName())
    );


    Source.from(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
        .transformPayload(i -> i + 1)
        .to(sink);

    assertThat(latch.await(1, TimeUnit.MINUTES)).isTrue();
}
 

import org.apache.kafka.common.serialization.IntegerSerializer; //导入依赖的package包/类
@Test
public void testSource() throws InterruptedException {
  KafkaUsage usage = new KafkaUsage();
  String topic = UUID.randomUUID().toString();
  List<Integer> results = new ArrayList<>();
  KafkaSource<Integer> source = new KafkaSource<>(vertx,
    getKafkaConfig()
      .put("topic", topic)
      .put("value.serializer", IntegerSerializer.class.getName())
      .put("value.deserializer", IntegerDeserializer.class.getName())
  );
  source
    .transformPayload(i -> i + 1)
    .to(Sink.forEachPayload(results::add));

  AtomicInteger counter = new AtomicInteger();
  usage.produceIntegers(10, null,
    () -> new ProducerRecord<>(topic, counter.getAndIncrement()));

  await().atMost(1, TimeUnit.MINUTES).until(() -> results.size() >= 10);
  assertThat(results).containsExactly(1, 2, 3, 4, 5, 6, 7, 8, 9, 10);
}
 

import org.apache.kafka.common.serialization.IntegerSerializer; //导入依赖的package包/类
@Test
public void testCommonHeaders(TestContext context) throws InterruptedException {
  Async async = context.async();
  KafkaUsage usage = new KafkaUsage();
  String topic = UUID.randomUUID().toString();

  KafkaSource<Integer> source = new KafkaSource<>(vertx,
    getKafkaConfig()
      .put("topic", topic)
      .put("value.serializer", IntegerSerializer.class.getName())
      .put("value.deserializer", IntegerDeserializer.class.getName())
  );

  source
    .to(data -> {
      KafkaConsumerRecord record = original(data);
      assertThat(record).isNotNull();
      assertThat(key(data)).isNotNull();
      async.complete();
      return complete();
    });

  usage.produceIntegers(1, null,
    () -> new ProducerRecord<>(topic, "key", 1));
}