我想实现一个Flow来处理分页的结果（例如，底层服务返回一些结果，但也通过发出另一个请求来指示更多的结果，例如传递一个游标）。
到目前为止我做的事情：
1.我已经实现了下面的流程和测试，但是流程没有完成。

object AdditionalRequestsFlow {
  private def keepRequest[Request, Response](flow: Flow[Request, Response, NotUsed]): Flow[Request, (Request, Response), NotUsed] = {
    Flow.fromGraph(GraphDSL.create() { implicit builder: GraphDSL.Builder[NotUsed] =>
      import GraphDSL.Implicits._
      val in = builder.add(Flow[Request])
      val bcast = builder.add(Broadcast[Request](2))
      val merge = builder.add(Zip[Request, Response]())
      in ~> bcast         ~> merge.in0
            bcast ~> flow ~> merge.in1
      FlowShape(in.in, merge.out)
    })
  }
  def flow[Request, Response, Output](
    inputFlow: Flow[Request, Response, NotUsed],
    anotherRequest: (Request, Response) => Option[Request],
    extractOutput: Response => Output,
    mergeOutput: (Output, Output) => Output
  ): Flow[Request, Output, NotUsed] = {
    Flow.fromGraph(GraphDSL.create() { implicit b =>
      import GraphDSL.Implicits._
      val start = b.add(Flow[Request])
      val merge = b.add(Merge[Request](2))
      val underlying = b.add(keepRequest(inputFlow))
      val unOption = b.add(Flow[Option[Request]].mapConcat(_.toList))
      val unzip = b.add(UnzipWith[(Request, Response), Response, Option[Request]] { case (req, res) =>
        (res, anotherRequest(req, res))
      })
      val finish = b.add(Flow[Response].map(extractOutput)) // this is wrong as we don't keep to 1 Request -> 1 Output, but first let's get the flow to work
      start ~> merge ~> underlying ~> unzip.in
                                      unzip.out0            ~>  finish
               merge <~ unOption   <~ unzip.out1
      FlowShape(start.in, finish.out)
    })
  }       
}

字符串
测试：

import akka.NotUsed
    import akka.actor.ActorSystem
    import akka.stream.ActorMaterializer
    import akka.stream.scaladsl.{Flow, Sink, Source}
    import org.scalatest.FlatSpec
    import org.scalatest.Matchers._
    import cats.syntax.option._
    import org.scalatest.concurrent.ScalaFutures.whenReady
    class AdditionalRequestsFlowSpec extends FlatSpec {
      implicit val system = ActorSystem()
      implicit val materializer = ActorMaterializer()
      case class Request(max: Int, batchSize: Int, offset: Option[Int] = None)
      case class Response(values: List[Int], nextOffset: Option[Int])
      private val flow: Flow[Request, Response, NotUsed] = {
        Flow[Request]
          .map { request =>
            val start = request.offset.getOrElse(0)
            val end = Math.min(request.max, start + request.batchSize)
            val nextOffset = if (end == request.max) None else Some(end)
            val result = Response((start until end).toList, nextOffset)
            result
          }
      }
      "AdditionalRequestsFlow" should "collect additional responses" in {
        def anotherRequest(request: Request, response: Response): Option[Request] = {
          response.nextOffset.map { nextOffset => request.copy(offset = nextOffset.some) }
        }
        def extract(x: Response): List[Int] = x.values
        def merge(a: List[Int], b: List[Int]): List[Int] = a ::: b
        val requests =
          Request(max = 35, batchSize = 10) ::
          Request(max = 5, batchSize = 10) ::
          Request(max = 100, batchSize = 1) ::
          Nil
        val expected = requests.map { x =>
          (0 until x.max).toList
        }
        val future = Source(requests)
          .via(AdditionalRequestsFlow.flow(flow, anotherRequest, extract, merge))
          .runWith(Sink.seq)
        whenReady(future) { x =>
          x shouldEqual expected
        }
      }
    }

型
1.以一种可怕的、阻塞的方式实现了相同的流，以说明我试图实现的目标：

def uglyHackFlow[Request, Response, Output](
    inputFlow: Flow[Request, Response, NotUsed],
    anotherRequest: (Request, Response) => Option[Request],
    extractOutput: Response => Output,
    mergeOutput: (Output, Output) => Output
  ): Flow[Request, Output, NotUsed] = {
    implicit val system = ActorSystem()
    implicit val materializer = ActorMaterializer()
    Flow[Request]
      .map { x =>
        def grab(request: Request): Output = {
          val response = Await.result(Source.single(request).via(inputFlow).runWith(Sink.head), 10.seconds) // :(
          val another = anotherRequest(request, response)
          val output = extractOutput(response)
          another.map { another =>
            mergeOutput(output, grab(another))
          } getOrElse output
        }
        grab(x)
      }
  }

型
这是可行的（但我们不应该在这一点上实现任何/Await-ing）。
1.查看了http://doc.akka.io/docs/akka/2.4/scala/stream/stream-graphs.html#Graph_cycles__liveness_and_deadlocks，我相信它包含了答案，但我似乎找不到它。在我的情况下，我希望循环在大多数时候应该包含一个元素，所以缓冲区溢出或完全饥饿都不应该发生-但显然确实如此。
1.尝试使用.withAttributes(Attributes(LogLevels(...)))调试流，但它不会导致任何输出，尽管似乎正确配置了记录器。
我正在寻找如何修复flow方法的提示，以保持相同的签名和语义（测试将通过）。
或者我在这里做了一些完全不合适的事情（例如，在akka-stream-contrib中有一个现有的特性可以解决这个问题）？