Kafka 0.8 的高级消费者 API 生命周期

Question

我找不到高级消费者的生命周期描述。我在 0.8.2.2 上，我不能使用来自 kafka-clients 的“现代”消费者。这是我的代码：

def consume(numberOfEvents: Int, await: Duration = 100.millis): List[MessageEnvelope] = {
    val consumerProperties = new Properties()
    consumerProperties.put("zookeeper.connect", kafkaConfig.zooKeeperConnectString)
    consumerProperties.put("group.id", consumerGroup)
    consumerProperties.put("auto.offset.reset", "smallest")

    val consumer = Consumer.create(new ConsumerConfig(consumerProperties))

    try {
      val messageStreams = consumer.createMessageStreams(
        Predef.Map(kafkaConfig.topic -> 1),
        new DefaultDecoder,
        new MessageEnvelopeDecoder)

      val receiveMessageFuture = Future[List[MessageEnvelope]] {
        messageStreams(kafkaConfig.topic)
          .flatMap(stream => stream.take(numberOfEvents).map(_.message()))
      }

      Await.result(receiveMessageFuture, await)
    } finally {
      consumer.shutdown()
    }

我不清楚。我应该在每次消息检索后关闭消费者还是我可以保留实例并将其重用于消息获取？我想重用实例是正确的方法，但找不到一些文章/最佳实践。

我正在尝试重用消费者和/或消息流。这对我来说效果不佳，我找不到原因。

如果我尝试重用 messageStreams，我会得到异常：

2017-04-17_19:57:57.088 ERROR MessageEnvelopeConsumer - Error while awaiting for messages java.lang.IllegalStateException: Iterator is in failed state
java.lang.IllegalStateException: Iterator is in failed state
    at kafka.utils.IteratorTemplate.hasNext(IteratorTemplate.scala:54)
    at scala.collection.IterableLike$class.take(IterableLike.scala:134)
    at kafka.consumer.KafkaStream.take(KafkaStream.scala:25)

发生在这里：

def consume(numberOfEvents: Int, await: Duration = 100.millis): List[MessageEnvelope] = {
    try {
      val receiveMessageFuture = Future[List[MessageEnvelope]] {
        messageStreams(kafkaConfig.topic)
          .flatMap(stream => stream.take(numberOfEvents).map(_.message()))
      }
      Try(Await.result(receiveMessageFuture, await)) match {
        case Success(result) => result
        case Failure(_: TimeoutException) => List.empty
        case Failure(e) =>
          // ===> never got any message from topic
          logger.error(s"Error while awaiting for messages ${e.getClass.getName}: ${e.getMessage}", e)
          List.empty

      }
    } catch {
      case e: Exception =>
        logger.warn(s"Error while consuming messages", e)
        List.empty
    }
  }

我每次都尝试创建 messageStreams：

运气不好……

2017-04-17_20:02:44.236 WARN  MessageEnvelopeConsumer - Error while consuming messages
kafka.common.MessageStreamsExistException: ZookeeperConsumerConnector can create message streams at most once
    at kafka.consumer.ZookeeperConsumerConnector.createMessageStreams(ZookeeperConsumerConnector.scala:151)
    at MessageEnvelopeConsumer.consume(MessageEnvelopeConsumer.scala:47)

发生在这里：

def consume(numberOfEvents: Int, await: Duration = 100.millis): List[MessageEnvelope] = {
    try {

      val messageStreams = consumer.createMessageStreams(
        Predef.Map(kafkaConfig.topic -> 1),
        new DefaultDecoder,
        new MessageEnvelopeDecoder)

      val receiveMessageFuture = Future[List[MessageEnvelope]] {
        messageStreams(kafkaConfig.topic)
          .flatMap(stream => stream.take(numberOfEvents).map(_.message()))
      }
      Try(Await.result(receiveMessageFuture, await)) match {
        case Success(result) => result
        case Failure(_: TimeoutException) => List.empty
        case Failure(e) =>
          logger.error(s"Error while awaiting for messages ${e.getClass.getName}: ${e.getMessage}", e)
          List.empty

      }
    } catch {
      case e: Exception =>
        // ===> now exception raised here
        logger.warn(s"Error while consuming messages", e)
        List.empty
    }
  }

UPD

我使用了基于迭代器的方法。看起来是这样的：

// consumerProperties.put("consumer.timeout.ms", "100")    

private lazy val consumer: ConsumerConnector = Consumer.create(new ConsumerConfig(consumerProperties))

  private lazy val messageStreams: Seq[KafkaStream[Array[Byte], MessageEnvelope]] =
    consumer.createMessageStreamsByFilter(Whitelist(kafkaConfig.topic), 1, new DefaultDecoder, new MessageEnvelopeDecoder)


  private lazy val iterator: ConsumerIterator[Array[Byte], MessageEnvelope] = {
    val stream = messageStreams.head
    stream.iterator()
  }

  def consume(): List[MessageEnvelope] = {
    try {
      if (iterator.hasNext) {
        val fromKafka: MessageAndMetadata[Array[Byte], MessageEnvelope] = iterator.next
        List(fromKafka.message())
      } else {
        List.empty
      }

    } catch {
      case _: ConsumerTimeoutException =>
        List.empty

      case e: Exception =>
        logger.warn(s"Error while consuming messages", e)
        List.empty
    }
  }

现在我想弄清楚它是否会自动向 ZK 提交偏移量...

Answer 1

持续关闭会导致不必要的消费者组重新平衡，从而极大地影响性能。有关最佳实践，请参阅本文：https://cwiki.apache.org/confluence/display/KAFKA/Consumer+Group+Example

Answer 2

我的回答是最新的问题更新。迭代器方法按预期对我有用。