Packages

  • package root
    Definition Classes
    root
  • package akka
    Definition Classes
    root
  • package stream
    Definition Classes
    akka
  • package scaladsl

    Scala API: The flow DSL allows the formulation of stream transformations based on some input.

    Scala API: The flow DSL allows the formulation of stream transformations based on some input. The starting point is called Source and can be a collection, an iterator, a block of code which is evaluated repeatedly or a org.reactivestreams.Publisher. A flow with an attached input and open output is also a Source.

    A flow may also be defined without an attached input or output and that is then a Flow. The Flow can be connected to the Source later by using Source#via with the flow as argument, and it remains a Source.

    Transformations can be appended to Source and Flow with the operations defined in FlowOps. Each DSL element produces a new flow that can be further transformed, building up a description of the complete transformation pipeline.

    The termination point of a flow is called Sink and can for example be a Future or org.reactivestreams.Subscriber. A flow with an attached output and open input is also a Sink.

    If a flow has both an attached input and an attached output it becomes a RunnableGraph. In order to execute this pipeline the flow must be materialized by calling RunnableGraph#run on it.

    You can create your Source, Flow and Sink in any order and then wire them together before they are materialized by connecting them using Flow#via and Flow#to, or connecting them into a GraphDSL with fan-in and fan-out elements.

    See Reactive Streams for details on org.reactivestreams.Publisher and org.reactivestreams.Subscriber.

    It should be noted that the streams modeled by this library are “hot”, meaning that they asynchronously flow through a series of processors without detailed control by the user. In particular it is not predictable how many elements a given transformation step might buffer before handing elements downstream, which means that transformation functions may be invoked more often than for corresponding transformations on strict collections like List. *An important consequence* is that elements that were produced into a stream may be discarded by later processors, e.g. when using the #take operator.

    By default every operation is executed within its own akka.actor.Actor to enable full pipelining of the chained set of computations. This behavior is determined by the akka.stream.Materializer which is required by those methods that materialize the Flow into a series of org.reactivestreams.Processor instances. The returned reactive stream is fully started and active.

    Definition Classes
    stream
  • object JavaFlowSupport

    For use only with JDK 9+.

    For use only with JDK 9+.

    Provides support for java.util.concurrent.Flow.* interfaces which mirror the Reactive Streams interfaces from org.reactivestreams. See: [http://www.reactive-streams.org/](reactive-streams.org).

    Definition Classes
    scaladsl
  • Flow
  • Sink
  • Source

object Flow

akka.stream.scaladsl.Flow factories operating with java.util.concurrent.Flow.* interfaces.

Source
JavaFlowSupport.scala
Linear Supertypes
AnyRef, Any
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Value Members

  1. def fromProcessor[I, O](processorFactory: () => Processor[I, O]): Flow[I, O, NotUsed]

    Creates a Flow from a Reactive Streams org.reactivestreams.Processor

  2. def fromProcessorMat[I, O, M](processorFactory: () => (Processor[I, O], M)): Flow[I, O, M]

    Creates a Flow from a Reactive Streams java.util.concurrent.Flow.Processor and returns a materialized value.

  3. def toProcessor[In, Out, Mat](self: Flow[In, Out, Mat]): RunnableGraph[Processor[In, Out]]

    Converts this Flow to a RunnableGraph that materializes to a Reactive Streams java.util.concurrent.Flow.Processor which implements the operations encapsulated by this Flow.

    Converts this Flow to a RunnableGraph that materializes to a Reactive Streams java.util.concurrent.Flow.Processor which implements the operations encapsulated by this Flow. Every materialization results in a new Processor instance, i.e. the returned RunnableGraph is reusable.

    returns

    A RunnableGraph that materializes to a Processor when run() is called on it.