加入收藏 | 设为首页 | 会员中心 | 我要投稿 李大同 (https://www.lidatong.com.cn/)- 科技、建站、经验、云计算、5G、大数据,站长网!
当前位置: 首页 > 综合聚焦 > 服务器 > 安全 > 正文

scala – 如何使用Akka Streams和HTTP将HTTP资源下载到文件?

发布时间:2020-12-16 08:56:17 所属栏目:安全 来源:网络整理
导读:在过去的几天里,我一直试图找出使用Akka Streams和HTTP将HTTP资源下载到文件的最佳方法. 最初我从Future-Based Variant开始,看起来像这样: def downloadViaFutures(uri: Uri,file: File): Future[Long] = { val request = Get(uri) val responseFuture = Ht
在过去的几天里,我一直试图找出使用Akka Streams和HTTP将HTTP资源下载到文件的最佳方法.

最初我从Future-Based Variant开始,看起来像这样:

def downloadViaFutures(uri: Uri,file: File): Future[Long] = {
  val request = Get(uri)
  val responseFuture = Http().singleRequest(request)
  responseFuture.flatMap { response =>
    val source = response.entity.dataBytes
    source.runWith(FileIO.toFile(file))
  }
}

这有点好,但是一旦我了解了更多关于纯Akka Streams的信息,我想尝试使用Flow-Based Variant从Source [HttpRequest]开始创建一个流.起初,这完全困扰了我,直到我偶然发现flatMapConcat流转换.这最终变得更加冗长:

def responSEOrFail[T](in: (Try[HttpResponse],T)): (HttpResponse,T) = in match {
  case (responseTry,context) => (responseTry.get,context)
}

def responseToByteSource[T](in: (HttpResponse,T)): Source[ByteString,Any] = in match {
  case (response,_) => response.entity.dataBytes
}

def downloadViaFlow(uri: Uri,file: File): Future[Long] = {
  val request = Get(uri)
  val source = Source.single((request,()))
  val requestResponseFlow = Http().superPool[Unit]()
  source.
    via(requestResponseFlow).
    map(responSEOrFail).
    flatMapConcat(responseToByteSource).
    runWith(FileIO.toFile(file))
}

然后我想要有点棘手并使用Content-Disposition标头.

回到基于未来的变体:

def destinationFile(downloadDir: File,response: HttpResponse): File = {
  val fileName = response.header[ContentDisposition].get.value
  val file = new File(downloadDir,fileName)
  file.createNewFile()
  file
}

def downloadViaFutures2(uri: Uri,downloadDir: File): Future[Long] = {
  val request = Get(uri)
  val responseFuture = Http().singleRequest(request)
  responseFuture.flatMap { response =>
    val file = destinationFile(downloadDir,response)
    val source = response.entity.dataBytes
    source.runWith(FileIO.toFile(file))
  }
}

但现在我不知道如何使用Future-Based Variant来做到这一点.这是我得到的:

def responseToByteSourceWithDest[T](in: (HttpResponse,T),downloadDir: File): Source[(ByteString,File),_) =>
    val source = responseToByteSource(in)
    val file = destinationFile(downloadDir,response)
    source.map((_,file))
}

def downloadViaFlow2(uri: Uri,downloadDir: File): Future[Long] = {
  val request = Get(uri)
  val source = Source.single((request,()))
  val requestResponseFlow = Http().superPool[Unit]()
  val sourceWithDest: Source[(ByteString,Unit] = source.
    via(requestResponseFlow).
    map(responSEOrFail).
    flatMapConcat(responseToByteSourceWithDest(_,downloadDir))
  sourceWithDest.runWith(???)
}

所以现在我有一个Source会为每个文件发出一个或多个(ByteString,File)元素(我说每个文件,因为没有理由原始Source必须是单个HttpRequest).

无论如何都要采取这些并将它们路由到动态的接收器?

我在想像flatMapConcat,比如:

def runWithMap[T,Mat2](f: T => Graph[SinkShape[Out],Mat2])(implicit materializer: Materializer): Mat2 = ???

这样我就可以完成downloadViaFlow2:

def destToSink(destination: File): Sink[(ByteString,Future[Long]] = {
  val sink = FileIO.toFile(destination,true)
  Flow[(ByteString,File)].map(_._1).toMat(sink)(Keep.right)
}
sourceWithDest.runWithMap {
  case (_,file) => destToSink(file)
}

解决方法

该解决方案不需要flatMapConcat.如果您不需要文件写入的任何返回值,那么您可以使用 Sink.foreach

def writeFile(downloadDir : File)(httpResponse : HttpResponse) : Future[Long] = {
  val file = destinationFile(downloadDir,httpResponse)
  httpResponse.entity.dataBytes.runWith(FileIO.toFile(file))
}

def downloadViaFlow2(uri: Uri,downloadDir: File) : Future[Unit] = {
  val request = HttpRequest(uri=uri)
  val source = Source.single((request,()))
  val requestResponseFlow = Http().superPool[Unit]()

  source.via(requestResponseFlow)
        .map(responSEOrFail)
        .map(_._1)
        .runWith(Sink.foreach(writeFile(downloadDir)))
}

请注意,Sink.foreach从writeFile函数创建Futures.因此,没有太大的背压. writeFile可能会被硬盘驱动器放慢速度,但是流会继续生成Futures.要控制它,您可以使用Flow.mapAsyncUnordered(或Flow.mapAsync):

val parallelism = 10

source.via(requestResponseFlow)
      .map(responSEOrFail)
      .map(_._1)
      .mapAsyncUnordered(parallelism)(writeFile(downloadDir))
      .runWith(Sink.ignore)

如果要累计总计数的Long值,则需要与Sink.fold结合使用:

source.via(requestResponseFlow)
      .map(responSEOrFail)
      .map(_._1)
      .mapAsyncUnordered(parallelism)(writeFile(downloadDir))
      .runWith(Sink.fold(0L)(_ + _))

折叠将保持运行总和,并在请求源干涸时发出最终值.

(编辑:李大同)

【声明】本站内容均来自网络,其相关言论仅代表作者个人观点,不代表本站立场。若无意侵犯到您的权利,请及时与联系站长删除相关内容!

    推荐文章
      热点阅读