Akka 为什么不'；难道我看不到反应型卡夫卡的高性能吗？（0.11版本）

为什么我看不到项目作者制作的反应式Kafa的高TPS（事务/秒）性能

这段代码源于反应式kafka项目中的基准代码，是在单个分区主题中填充的2M条记录的运行。运行时，我得到约140K的TPS。这并不可怕，但远低于人们所希望的1000人中的100人

这里我最关心的是这只是一个1分区的主题，它实际上不是一个真正的测试用例

case class RunTest4(msgCount: Int, producer: com.foo.Producer, kafkaHost: String, groupId: String, topic: String)(implicit system: ActorSystem) {

  // Pre-populate a topic w/some records (2 million)
  producer.populate(msgCount, topic)
  Thread.sleep(2000)
  partitionInfo(topic)
  val partitionTarget = msgCount - 1

  val settings = ConsumerSettings(system, new ByteArrayDeserializer, new StringDeserializer)
    .withBootstrapServers(kafkaHost)
    .withGroupId(groupId)
    .withProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest")

  def consumerAtLeastOnceBatched(batchSize: Int)(implicit mat: Materializer): Unit = {
    val promise = Promise[Unit]
    val control = Consumer.committableSource(settings, Subscriptions.topics(topic))
      .map {
        msg => msg.committableOffset
      }
      .batch(batchSize.toLong, first => CommittableOffsetBatch.empty.updated(first)) { (batch, elem) =>
        batch.updated(elem)
      }
      .mapAsync(3) { m =>
        m.commitScaladsl().map(_ => m)(ExecutionContexts.sameThreadExecutionContext)
      }
      .toMat(Sink.foreach { batch =>
        if (batch.offsets().head._2 >= partitionTarget)
          promise.complete(Success(()))
      })(Keep.left)
      .run()

    println("Control is: " + control.getClass.getName)
    val now = System.currentTimeMillis()
    Await.result(promise.future, 30.seconds)
    val later = System.currentTimeMillis()
    println("TPS: " + (msgCount / ((later - now) / 1000.0)))
    control.shutdown()

    groupInfo(groupId)
  }

  private def partitionInfo(topic: String) =
    kafka.tools.GetOffsetShell.main(Array("--topic", topic, "--broker-list", kafkaHost, "--time", "-1"))
  private def groupInfo(group: String) =
    kafka.admin.ConsumerGroupCommand.main(Array("--describe", "--group", group, "--bootstrap-server", kafkaHost, "--new-consumer"))

}

这个测试（我希望）是一个处理每个主题多个分区的好方法——一个更现实的情况。当我在批量大小为10000的情况下运行此测试，并且在4个主题分区中填充了一个主题w/2M记录时，我的测试超时，等待时间为30秒，这意味着无论何时完成测试，TPS都为

case class RunTest3(msgCount: Int, producer: com.foo.Producer, kafkaHost: String, groupId: String, topic: String)(implicit system: ActorSystem) {

  // Pre-populate a topic w/some records (2 million)
  producer.populate(msgCount, topic)
  Thread.sleep(2000)
  partitionInfo(topic)
  val partitionTarget = msgCount - 1

  val settings = ConsumerSettings(system, new ByteArrayDeserializer, new StringDeserializer)
    .withBootstrapServers(kafkaHost)
    .withGroupId(groupId)
    .withProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest")

  def consumerAtLeastOnceBatched(batchSize: Int)(implicit mat: Materializer): Unit = {
    val promise = Promise[Unit]
    val control = Consumer.committablePartitionedSource(settings, Subscriptions.topics(topic))
      .flatMapMerge(4, _._2)
      .map {
        msg => msg.committableOffset
      }
      .batch(batchSize.toLong, first => CommittableOffsetBatch.empty.updated(first)) { (batch, elem) =>
        batch.updated(elem)
      }
      .mapAsync(3) { m =>
        m.commitScaladsl().map(_ => m)(ExecutionContexts.sameThreadExecutionContext)
      }
      .toMat(Sink.foreach { batch =>
        if (batch.offsets().head._2 >= partitionTarget)
          promise.complete(Success(()))
      })(Keep.left)
      .run()

    println("Control is: " + control.getClass.getName)
    val now = System.currentTimeMillis()
    Await.result(promise.future, 30.seconds)
    val later = System.currentTimeMillis()
    println("TPS: " + (msgCount / ((later - now) / 1000.0)))
    control.shutdown()

    groupInfo(groupId)
  }

  private def partitionInfo(topic: String) =
    kafka.tools.GetOffsetShell.main(Array("--topic", topic, "--broker-list", kafkaHost, "--time", "-1"))
  private def groupInfo(group: String) =
    kafka.admin.ConsumerGroupCommand.main(Array("--describe", "--group", group, "--bootstrap-server", kafkaHost, "--new-consumer"))

}