class SubFlow[In, Out, Mat] extends AnyRef

A “stream of streams” sub-flow of data elements, e.g. produced by groupBy. SubFlows cannot contribute to the super-flow’s materialized value since they are materialized later, during the runtime of the flow graph processing.

Source
SubFlow.scala
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Instance Constructors

  1. new SubFlow(delegate: scaladsl.SubFlow[Out, Mat, [+O]scaladsl.Flow[In, O, Mat], scaladsl.Sink[In, Mat]])

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. def +(other: String): String
    Implicit
    This member is added by an implicit conversion from SubFlow[In, Out, Mat] to any2stringadd[SubFlow[In, Out, Mat]] performed by method any2stringadd in scala.Predef.
    Definition Classes
    any2stringadd
  4. def ->[B](y: B): (SubFlow[In, Out, Mat], B)
    Implicit
    This member is added by an implicit conversion from SubFlow[In, Out, Mat] to ArrowAssoc[SubFlow[In, Out, Mat]] performed by method ArrowAssoc in scala.Predef.
    Definition Classes
    ArrowAssoc
    Annotations
    @inline()
  5. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  6. def addAttributes(attr: Attributes): SubFlow[In, Out, Mat]

    Add the given attributes to this Source.

    Add the given attributes to this Source. Further calls to withAttributes will not remove these attributes. Note that this operation has no effect on an empty Flow (because the attributes apply only to the contained processing operators).

  7. def alsoTo(that: Graph[SinkShape[Out], _]): SubFlow[In, Out, Mat]

    Attaches the given Sink to this Flow, meaning that elements that passes through will also be sent to the Sink.

    Attaches the given Sink to this Flow, meaning that elements that passes through will also be sent to the Sink.

    It is similar to #wireTap but will backpressure instead of dropping elements when the given Sink is not ready.

    Emits when element is available and demand exists both from the Sink and the downstream.

    Backpressures when downstream or Sink backpressures

    Completes when upstream completes

    Cancels when downstream or Sink cancels

  8. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  9. def asScala: scaladsl.SubFlow[Out, Mat, [+O]scaladsl.Flow[In, O, Mat], scaladsl.Sink[In, Mat]]

    Converts this Flow to its Scala DSL counterpart

  10. def async: SubFlow[In, Out, Mat]

    Put an asynchronous boundary around this SubFlow

  11. def backpressureTimeout(timeout: Duration): SubFlow[In, Out, Mat]

    If the time between the emission of an element and the following downstream demand exceeds the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException.

    If the time between the emission of an element and the following downstream demand exceeds the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException. The timeout is checked periodically, so the resolution of the check is one period (equals to timeout value).

    Emits when upstream emits an element

    Backpressures when downstream backpressures

    Completes when upstream completes or fails if timeout elapses between element emission and downstream demand.

    Cancels when downstream cancels

    Annotations
    @silent()
  12. def batch[S](max: Long, seed: Function[Out, S], aggregate: Function2[S, Out, S]): SubFlow[In, S, Mat]

    Allows a faster upstream to progress independently of a slower subscriber by aggregating elements into batches until the subscriber is ready to accept them.

    Allows a faster upstream to progress independently of a slower subscriber by aggregating elements into batches until the subscriber is ready to accept them. For example a batch step might store received elements in an array up to the allowed max limit if the upstream publisher is faster.

    This element only rolls up elements if the upstream is faster, but if the downstream is faster it will not duplicate elements.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when downstream stops backpressuring and there is an aggregated element available

    Backpressures when there are max batched elements and 1 pending element and downstream backpressures

    Completes when upstream completes and there is no batched/pending element waiting

    Cancels when downstream cancels

    See also SubFlow.conflate, SubFlow.batchWeighted

    max

    maximum number of elements to batch before backpressuring upstream (must be positive non-zero)

    seed

    Provides the first state for a batched value using the first unconsumed element as a start

    aggregate

    Takes the currently batched value and the current pending element to produce a new aggregate

  13. def batchWeighted[S](max: Long, costFn: Function[Out, Long], seed: Function[Out, S], aggregate: Function2[S, Out, S]): SubFlow[In, S, Mat]

    Allows a faster upstream to progress independently of a slower subscriber by aggregating elements into batches until the subscriber is ready to accept them.

    Allows a faster upstream to progress independently of a slower subscriber by aggregating elements into batches until the subscriber is ready to accept them. For example a batch step might concatenate ByteString elements up to the allowed max limit if the upstream publisher is faster.

    This element only rolls up elements if the upstream is faster, but if the downstream is faster it will not duplicate elements.

    Batching will apply for all elements, even if a single element cost is greater than the total allowed limit. In this case, previous batched elements will be emitted, then the "heavy" element will be emitted (after being applied with the seed function) without batching further elements with it, and then the rest of the incoming elements are batched.

    Emits when downstream stops backpressuring and there is a batched element available

    Backpressures when there are max weighted batched elements + 1 pending element and downstream backpressures

    Completes when upstream completes and there is no batched/pending element waiting

    Cancels when downstream cancels

    See also SubFlow.conflate, SubFlow.batch

    max

    maximum weight of elements to batch before backpressuring upstream (must be positive non-zero)

    costFn

    a function to compute a single element weight

    seed

    Provides the first state for a batched value using the first unconsumed element as a start

    aggregate

    Takes the currently batched value and the current pending element to produce a new batch

  14. def buffer(size: Int, overflowStrategy: OverflowStrategy): SubFlow[In, Out, Mat]

    Adds a fixed size buffer in the flow that allows to store elements from a faster upstream until it becomes full.

    Adds a fixed size buffer in the flow that allows to store elements from a faster upstream until it becomes full. Depending on the defined akka.stream.OverflowStrategy it might drop elements or backpressure the upstream if there is no space available

    Emits when downstream stops backpressuring and there is a pending element in the buffer

    Backpressures when downstream backpressures or depending on OverflowStrategy:

    • Backpressure - backpressures when buffer is full
    • DropHead, DropTail, DropBuffer - never backpressures
    • Fail - fails the stream if buffer gets full

    Completes when upstream completes and buffered elements has been drained

    Cancels when downstream cancels

    size

    The size of the buffer in element count

    overflowStrategy

    Strategy that is used when incoming elements cannot fit inside the buffer

  15. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate() @throws( ... )
  16. def collect[T](pf: PartialFunction[Out, T]): SubFlow[In, T, Mat]

    Transform this stream by applying the given partial function to each of the elements on which the function is defined as they pass through this processing step.

    Transform this stream by applying the given partial function to each of the elements on which the function is defined as they pass through this processing step. Non-matching elements are filtered out.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when the provided partial function is defined for the element

    Backpressures when the partial function is defined for the element and downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  17. def collectType[T](clazz: Class[T]): SubFlow[In, T, Mat]

    Transform this stream by testing the type of each of the elements on which the element is an instance of the provided type as they pass through this processing step.

    Transform this stream by testing the type of each of the elements on which the element is an instance of the provided type as they pass through this processing step. Non-matching elements are filtered out.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when the element is an instance of the provided type

    Backpressures when the element is an instance of the provided type and downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  18. def completionTimeout(timeout: Duration): SubFlow[In, Out, Mat]

    If the completion of the stream does not happen until the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException.

    If the completion of the stream does not happen until the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException.

    Emits when upstream emits an element

    Backpressures when downstream backpressures

    Completes when upstream completes or fails if timeout elapses before upstream completes

    Cancels when downstream cancels

    Annotations
    @silent()
  19. def concat[M](that: Graph[SourceShape[Out], M]): SubFlow[In, Out, Mat]

    Concatenate the given Source to this Flow, meaning that once this Flow’s input is exhausted and all result elements have been generated, the Source’s elements will be produced.

    Concatenate the given Source to this Flow, meaning that once this Flow’s input is exhausted and all result elements have been generated, the Source’s elements will be produced.

    Note that the Source is materialized together with this Flow and just kept from producing elements by asserting back-pressure until its time comes.

    If this Flow gets upstream error - no elements from the given Source will be pulled.

    Emits when element is available from current stream or from the given Source when current is completed

    Backpressures when downstream backpressures

    Completes when given Source completes

    Cancels when downstream cancels

  20. def concatSubstreams(): Flow[In, Out, Mat]

    Flatten the sub-flows back into the super-flow by concatenating them.

    Flatten the sub-flows back into the super-flow by concatenating them. This is usually a bad idea when combined with groupBy since it can easily lead to deadlock—the concatenation does not consume from the second substream until the first has finished and the groupBy operator will get back-pressure from the second stream.

    This is identical in effect to mergeSubstreamsWithParallelism(1).

  21. def conflate(aggregate: Function2[Out, Out, Out]): SubFlow[In, Out, Mat]

    Allows a faster upstream to progress independently of a slower subscriber by conflating elements into a summary until the subscriber is ready to accept them.

    Allows a faster upstream to progress independently of a slower subscriber by conflating elements into a summary until the subscriber is ready to accept them. For example a conflate step might average incoming numbers if the upstream publisher is faster.

    This version of conflate does not change the output type of the stream. See SubFlow.conflateWithSeed for a more flexible version that can take a seed function and transform elements while rolling up.

    This element only rolls up elements if the upstream is faster, but if the downstream is faster it will not duplicate elements.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when downstream stops backpressuring and there is a conflated element available

    Backpressures when never

    Completes when upstream completes

    Cancels when downstream cancels

    see also SubFlow.conflateWithSeed SubFlow.batch SubFlow.batchWeighted

    aggregate

    Takes the currently aggregated value and the current pending element to produce a new aggregate

  22. def conflateWithSeed[S](seed: Function[Out, S], aggregate: Function2[S, Out, S]): SubFlow[In, S, Mat]

    Allows a faster upstream to progress independently of a slower subscriber by conflating elements into a summary until the subscriber is ready to accept them.

    Allows a faster upstream to progress independently of a slower subscriber by conflating elements into a summary until the subscriber is ready to accept them. For example a conflate step might average incoming numbers if the upstream publisher is faster.

    This version of conflate allows to derive a seed from the first element and change the aggregated type to be different than the input type. See Flow.conflate for a simpler version that does not change types.

    This element only rolls up elements if the upstream is faster, but if the downstream is faster it will not duplicate elements.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when downstream stops backpressuring and there is a conflated element available

    Backpressures when never

    Completes when upstream completes

    Cancels when downstream cancels

    see also SubFlow.conflate SubFlow.batch SubFlow.batchWeighted

    seed

    Provides the first state for a conflated value using the first unconsumed element as a start

    aggregate

    Takes the currently aggregated value and the current pending element to produce a new aggregate

  23. def delay(of: Duration, strategy: DelayOverflowStrategy): SubFlow[In, Out, Mat]

    Shifts elements emission in time by a specified amount.

    Shifts elements emission in time by a specified amount. It allows to store elements in internal buffer while waiting for next element to be emitted. Depending on the defined akka.stream.DelayOverflowStrategy it might drop elements or backpressure the upstream if there is no space available in the buffer.

    Delay precision is 10ms to avoid unnecessary timer scheduling cycles

    Internal buffer has default capacity 16. You can set buffer size by calling withAttributes(inputBuffer)

    Emits when there is a pending element in the buffer and configured time for this element elapsed * EmitEarly - strategy do not wait to emit element if buffer is full

    Backpressures when depending on OverflowStrategy * Backpressure - backpressures when buffer is full * DropHead, DropTail, DropBuffer - never backpressures * Fail - fails the stream if buffer gets full

    Completes when upstream completes and buffered elements has been drained

    Cancels when downstream cancels

    of

    time to shift all messages

    strategy

    Strategy that is used when incoming elements cannot fit inside the buffer

    Annotations
    @silent()
  24. def detach: SubFlow[In, Out, Mat]

    Detaches upstream demand from downstream demand without detaching the stream rates; in other words acts like a buffer of size 1.

    Detaches upstream demand from downstream demand without detaching the stream rates; in other words acts like a buffer of size 1.

    Emits when upstream emits an element

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  25. def divertTo(that: Graph[SinkShape[Out], _], when: Predicate[Out]): SubFlow[In, Out, Mat]

    Attaches the given Sink to this Flow, meaning that elements will be sent to the Sink instead of being passed through if the predicate when returns true.

    Attaches the given Sink to this Flow, meaning that elements will be sent to the Sink instead of being passed through if the predicate when returns true.

    Emits when emits when an element is available from the input and the chosen output has demand

    Backpressures when the currently chosen output back-pressures

    Completes when upstream completes and no output is pending

    Cancels when any of the downstreams cancel

  26. def drop(n: Long): SubFlow[In, Out, Mat]

    Discard the given number of elements at the beginning of the stream.

    Discard the given number of elements at the beginning of the stream. No elements will be dropped if n is zero or negative.

    Emits when the specified number of elements has been dropped already

    Backpressures when the specified number of elements has been dropped and downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  27. def dropWhile(p: Predicate[Out]): SubFlow[In, Out, Mat]

    Discard elements at the beginning of the stream while predicate is true.

    Discard elements at the beginning of the stream while predicate is true. All elements will be taken after predicate returns false first time.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when predicate returned false and for all following stream elements

    Backpressures when predicate returned false and downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  28. def dropWithin(d: Duration): SubFlow[In, Out, Mat]

    Discard the elements received within the given duration at beginning of the stream.

    Discard the elements received within the given duration at beginning of the stream.

    Emits when the specified time elapsed and a new upstream element arrives

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

    Annotations
    @silent()
  29. def ensuring(cond: (SubFlow[In, Out, Mat]) ⇒ Boolean, msg: ⇒ Any): SubFlow[In, Out, Mat]
    Implicit
    This member is added by an implicit conversion from SubFlow[In, Out, Mat] to Ensuring[SubFlow[In, Out, Mat]] performed by method Ensuring in scala.Predef.
    Definition Classes
    Ensuring
  30. def ensuring(cond: (SubFlow[In, Out, Mat]) ⇒ Boolean): SubFlow[In, Out, Mat]
    Implicit
    This member is added by an implicit conversion from SubFlow[In, Out, Mat] to Ensuring[SubFlow[In, Out, Mat]] performed by method Ensuring in scala.Predef.
    Definition Classes
    Ensuring
  31. def ensuring(cond: Boolean, msg: ⇒ Any): SubFlow[In, Out, Mat]
    Implicit
    This member is added by an implicit conversion from SubFlow[In, Out, Mat] to Ensuring[SubFlow[In, Out, Mat]] performed by method Ensuring in scala.Predef.
    Definition Classes
    Ensuring
  32. def ensuring(cond: Boolean): SubFlow[In, Out, Mat]
    Implicit
    This member is added by an implicit conversion from SubFlow[In, Out, Mat] to Ensuring[SubFlow[In, Out, Mat]] performed by method Ensuring in scala.Predef.
    Definition Classes
    Ensuring
  33. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  34. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  35. def expand[U](expander: Function[Out, Iterator[U]]): SubFlow[In, U, Mat]

    Allows a faster downstream to progress independently of a slower upstream by extrapolating elements from an older element until new element comes from the upstream.

    Allows a faster downstream to progress independently of a slower upstream by extrapolating elements from an older element until new element comes from the upstream. For example an expand step might repeat the last element for the subscriber until it receives an update from upstream.

    This element will never "drop" upstream elements as all elements go through at least one extrapolation step. This means that if the upstream is actually faster than the upstream it will be backpressured by the downstream subscriber.

    Expand does not support akka.stream.Supervision#restart and akka.stream.Supervision#resume. Exceptions from the expander function will complete the stream with failure.

    See also #extrapolate for a version that always preserves the original element and allows for an initial "startup" element.

    Emits when downstream stops backpressuring

    Backpressures when downstream backpressures or iterator runs empty

    Completes when upstream completes

    Cancels when downstream cancels

    expander

    Takes the current extrapolation state to produce an output element and the next extrapolation state.

    See also

    #extrapolate for a version that always preserves the original element and allows for an initial "startup" element.

  36. def extrapolate(extrapolator: Function[Out, Iterator[Out]], initial: Out): SubFlow[In, Out, Mat]

    Allows a faster downstream to progress independent of a slower upstream.

    Allows a faster downstream to progress independent of a slower upstream.

    This is achieved by introducing "extrapolated" elements - based on those from upstream - whenever downstream signals demand.

    Extrapolate does not support akka.stream.Supervision#restart and akka.stream.Supervision#resume. Exceptions from the extrapolate function will complete the stream with failure.

    See also #expand for a version that can overwrite the original element.

    Emits when downstream stops backpressuring, AND EITHER upstream emits OR initial element is present OR extrapolate is non-empty and applicable

    Backpressures when downstream backpressures or current extrapolate runs empty

    Completes when upstream completes and current extrapolate runs empty

    Cancels when downstream cancels

    extrapolator

    takes the current upstream element and provides a sequence of "extrapolated" elements based on the original, to be emitted in case downstream signals demand.

    initial

    the initial element to be emitted, in case upstream is able to stall the entire stream.

    See also

    #expand

  37. def extrapolate(extrapolator: Function[Out, Iterator[Out]]): SubFlow[In, Out, Mat]

    Allows a faster downstream to progress independent of a slower upstream.

    Allows a faster downstream to progress independent of a slower upstream.

    This is achieved by introducing "extrapolated" elements - based on those from upstream - whenever downstream signals demand.

    Extrapolate does not support akka.stream.Supervision#restart and akka.stream.Supervision#resume. Exceptions from the extrapolate function will complete the stream with failure.

    See also #expand for a version that can overwrite the original element.

    Emits when downstream stops backpressuring, AND EITHER upstream emits OR initial element is present OR extrapolate is non-empty and applicable

    Backpressures when downstream backpressures or current extrapolate runs empty

    Completes when upstream completes and current extrapolate runs empty

    Cancels when downstream cancels

    extrapolator

    takes the current upstream element and provides a sequence of "extrapolated" elements based on the original, to be emitted in case downstream signals demand.

    See also

    #expand

  38. def filter(p: Predicate[Out]): SubFlow[In, Out, Mat]

    Only pass on those elements that satisfy the given predicate.

    Only pass on those elements that satisfy the given predicate.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when the given predicate returns true for the element

    Backpressures when the given predicate returns true for the element and downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  39. def filterNot(p: Predicate[Out]): SubFlow[In, Out, Mat]

    Only pass on those elements that NOT satisfy the given predicate.

    Only pass on those elements that NOT satisfy the given predicate.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when the given predicate returns false for the element

    Backpressures when the given predicate returns false for the element and downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  40. def flatMapConcat[T, M](f: Function[Out, _ <: Graph[SourceShape[T], M]]): SubFlow[In, T, Mat]

    Transform each input element into a Source of output elements that is then flattened into the output stream by concatenation, fully consuming one Source after the other.

    Transform each input element into a Source of output elements that is then flattened into the output stream by concatenation, fully consuming one Source after the other.

    Emits when a currently consumed substream has an element available

    Backpressures when downstream backpressures

    Completes when upstream completes and all consumed substreams complete

    Cancels when downstream cancels

  41. def flatMapMerge[T, M](breadth: Int, f: Function[Out, _ <: Graph[SourceShape[T], M]]): SubFlow[In, T, Mat]

    Transform each input element into a Source of output elements that is then flattened into the output stream by merging, where at most breadth substreams are being consumed at any given time.

    Transform each input element into a Source of output elements that is then flattened into the output stream by merging, where at most breadth substreams are being consumed at any given time.

    Emits when a currently consumed substream has an element available

    Backpressures when downstream backpressures

    Completes when upstream completes and all consumed substreams complete

    Cancels when downstream cancels

  42. def fold[T](zero: T)(f: Function2[T, Out, T]): SubFlow[In, T, Mat]

    Similar to scan but only emits its result when the upstream completes, after which it also completes.

    Similar to scan but only emits its result when the upstream completes, after which it also completes. Applies the given function f towards its current and next value, yielding the next current value.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    If the function f throws an exception and the supervision decision is akka.stream.Supervision#restart current value starts at zero again the stream will continue.

    Note that the zero value must be immutable.

    Emits when upstream completes

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  43. def foldAsync[T](zero: T)(f: Function2[T, Out, CompletionStage[T]]): SubFlow[In, T, Mat]

    Similar to fold but with an asynchronous function.

    Similar to fold but with an asynchronous function. Applies the given function towards its current and next value, yielding the next current value.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    If the function f returns a failure and the supervision decision is akka.stream.Supervision.Restart current value starts at zero again the stream will continue.

    Note that the zero value must be immutable.

    Emits when upstream completes

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  44. def formatted(fmtstr: String): String
    Implicit
    This member is added by an implicit conversion from SubFlow[In, Out, Mat] to StringFormat[SubFlow[In, Out, Mat]] performed by method StringFormat in scala.Predef.
    Definition Classes
    StringFormat
    Annotations
    @inline()
  45. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  46. def grouped(n: Int): SubFlow[In, List[Out], Mat]

    Chunk up this stream into groups of the given size, with the last group possibly smaller than requested due to end-of-stream.

    Chunk up this stream into groups of the given size, with the last group possibly smaller than requested due to end-of-stream.

    n must be positive, otherwise IllegalArgumentException is thrown.

    Emits when the specified number of elements has been accumulated or upstream completed

    Backpressures when a group has been assembled and downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  47. def groupedWeightedWithin(maxWeight: Long, costFn: Function[Out, Long], d: Duration): SubFlow[In, List[Out], Mat]

    Chunk up this stream into groups of elements received within a time window, or limited by the weight of the elements, whatever happens first.

    Chunk up this stream into groups of elements received within a time window, or limited by the weight of the elements, whatever happens first. Empty groups will not be emitted if no elements are received from upstream. The last group before end-of-stream will contain the buffered elements since the previously emitted group.

    Emits when the configured time elapses since the last group has been emitted or weight limit reached

    Backpressures when downstream backpressures, and buffered group (+ pending element) weighs more than maxWeight

    Completes when upstream completes (emits last group)

    Cancels when downstream completes

    maxWeight must be positive, and d must be greater than 0 seconds, otherwise IllegalArgumentException is thrown.

    Annotations
    @silent()
  48. def groupedWithin(n: Int, d: Duration): SubFlow[In, List[Out], Mat]

    Chunk up this stream into groups of elements received within a time window, or limited by the given number of elements, whatever happens first.

    Chunk up this stream into groups of elements received within a time window, or limited by the given number of elements, whatever happens first. Empty groups will not be emitted if no elements are received from upstream. The last group before end-of-stream will contain the buffered elements since the previously emitted group.

    Emits when the configured time elapses since the last group has been emitted or n elements is buffered

    Backpressures when downstream backpressures, and there are n+1 buffered elements

    Completes when upstream completes (emits last group)

    Cancels when downstream completes

    n must be positive, and d must be greater than 0 seconds, otherwise IllegalArgumentException is thrown.

    Annotations
    @silent()
  49. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  50. def idleTimeout(timeout: Duration): SubFlow[In, Out, Mat]

    If the time between two processed elements exceeds the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException.

    If the time between two processed elements exceeds the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException. The timeout is checked periodically, so the resolution of the check is one period (equals to timeout value).

    Emits when upstream emits an element

    Backpressures when downstream backpressures

    Completes when upstream completes or fails if timeout elapses between two emitted elements

    Cancels when downstream cancels

    Annotations
    @silent()
  51. def initialDelay(delay: Duration): SubFlow[In, Out, Mat]

    Delays the initial element by the specified duration.

    Delays the initial element by the specified duration.

    Emits when upstream emits an element if the initial delay is already elapsed

    Backpressures when downstream backpressures or initial delay is not yet elapsed

    Completes when upstream completes

    Cancels when downstream cancels

    Annotations
    @silent()
  52. def initialTimeout(timeout: Duration): SubFlow[In, Out, Mat]

    If the first element has not passed through this operator before the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException.

    If the first element has not passed through this operator before the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException.

    Emits when upstream emits an element

    Backpressures when downstream backpressures

    Completes when upstream completes or fails if timeout elapses before first element arrives

    Cancels when downstream cancels

    Annotations
    @silent()
  53. def interleave(that: Graph[SourceShape[Out], _], segmentSize: Int): SubFlow[In, Out, Mat]

    Interleave is a deterministic merge of the given Source with elements of this Flow.

    Interleave is a deterministic merge of the given Source with elements of this Flow. It first emits segmentSize number of elements from this flow to downstream, then - same amount for that source, then repeat process.

    Example:

    Source(List(1, 2, 3)).interleave(List(4, 5, 6, 7), 2) // 1, 2, 4, 5, 3, 6, 7

    After one of upstreams is complete than all the rest elements will be emitted from the second one

    If it gets error from one of upstreams - stream completes with failure.

    Emits when element is available from the currently consumed upstream

    Backpressures when downstream backpressures. Signal to current upstream, switch to next upstream when received segmentSize elements

    Completes when the Flow and given Source completes

    Cancels when downstream cancels

  54. def intersperse(inject: Out): SubFlow[In, Out, Mat]

    Intersperses stream with provided element, similar to how scala.collection.immutable.List.mkString injects a separator between a List's elements.

    Intersperses stream with provided element, similar to how scala.collection.immutable.List.mkString injects a separator between a List's elements.

    Additionally can inject start and end marker elements to stream.

    Examples:

    Source<Integer, ?> nums = Source.from(Arrays.asList(0, 1, 2, 3));
    nums.intersperse(",");            //   1 , 2 , 3
    nums.intersperse("[", ",", "]");  // [ 1 , 2 , 3 ]

    Emits when upstream emits (or before with the start element if provided)

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  55. def intersperse(start: Out, inject: Out, end: Out): SubFlow[In, Out, Mat]

    Intersperses stream with provided element, similar to how scala.collection.immutable.List.mkString injects a separator between a List's elements.

    Intersperses stream with provided element, similar to how scala.collection.immutable.List.mkString injects a separator between a List's elements.

    Additionally can inject start and end marker elements to stream.

    Examples:

    Source<Integer, ?> nums = Source.from(Arrays.asList(0, 1, 2, 3));
    nums.intersperse(",");            //   1 , 2 , 3
    nums.intersperse("[", ",", "]");  // [ 1 , 2 , 3 ]

    In case you want to only prepend or only append an element (yet still use the intercept feature to inject a separator between elements, you may want to use the following pattern instead of the 3-argument version of intersperse (See Source.concat for semantics details):

    Source.single(">> ").concat(flow.intersperse(","))
    flow.intersperse(",").concat(Source.single("END"))

    Emits when upstream emits (or before with the start element if provided)

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  56. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  57. def keepAlive(maxIdle: Duration, injectedElem: Creator[Out]): SubFlow[In, Out, Mat]

    Injects additional elements if upstream does not emit for a configured amount of time.

    Injects additional elements if upstream does not emit for a configured amount of time. In other words, this operator attempts to maintains a base rate of emitted elements towards the downstream.

    If the downstream backpressures then no element is injected until downstream demand arrives. Injected elements do not accumulate during this period.

    Upstream elements are always preferred over injected elements.

    Emits when upstream emits an element or if the upstream was idle for the configured period

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

    Annotations
    @silent()
  58. def limit(n: Long): SubFlow[In, Out, Mat]

    Ensure stream boundedness by limiting the number of elements from upstream.

    Ensure stream boundedness by limiting the number of elements from upstream. If the number of incoming elements exceeds max, it will signal upstream failure StreamLimitException downstream.

    Due to input buffering some elements may have been requested from upstream publishers that will then not be processed downstream of this step.

    The stream will be completed without producing any elements if n is zero or negative.

    Emits when the specified number of elements to take has not yet been reached

    Backpressures when downstream backpressures

    Completes when the defined number of elements has been taken or upstream completes

    Cancels when the defined number of elements has been taken or downstream cancels

    See also Flow.take, Flow.takeWithin, Flow.takeWhile

  59. def limitWeighted(n: Long)(costFn: Function[Out, Long]): SubFlow[In, Out, Mat]

    Ensure stream boundedness by evaluating the cost of incoming elements using a cost function.

    Ensure stream boundedness by evaluating the cost of incoming elements using a cost function. Exactly how many elements will be allowed to travel downstream depends on the evaluated cost of each element. If the accumulated cost exceeds max, it will signal upstream failure StreamLimitException downstream.

    Due to input buffering some elements may have been requested from upstream publishers that will then not be processed downstream of this step.

    The stream will be completed without producing any elements if n is zero or negative.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when the specified number of elements to take has not yet been reached

    Backpressures when downstream backpressures

    Completes when the defined number of elements has been taken or upstream completes

    Cancels when the defined number of elements has been taken or downstream cancels

    See also Flow.take, Flow.takeWithin, Flow.takeWhile

  60. def log(name: String): SubFlow[In, Out, Mat]

    Logs elements flowing through the stream as well as completion and erroring.

    Logs elements flowing through the stream as well as completion and erroring.

    By default element and completion signals are logged on debug level, and errors are logged on Error level. This can be adjusted according to your needs by providing a custom Attributes.LogLevels attribute on the given Flow.

    Uses an internally created LoggingAdapter which uses akka.stream.Log as it's source (use this class to configure slf4j loggers).

    Emits when the mapping function returns an element

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  61. def log(name: String, log: LoggingAdapter): SubFlow[In, Out, Mat]

    Logs elements flowing through the stream as well as completion and erroring.

    Logs elements flowing through the stream as well as completion and erroring.

    By default element and completion signals are logged on debug level, and errors are logged on Error level. This can be adjusted according to your needs by providing a custom Attributes.LogLevels attribute on the given Flow:

    Uses the given LoggingAdapter for logging.

    Emits when the mapping function returns an element

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  62. def log(name: String, extract: Function[Out, Any]): SubFlow[In, Out, Mat]

    Logs elements flowing through the stream as well as completion and erroring.

    Logs elements flowing through the stream as well as completion and erroring.

    By default element and completion signals are logged on debug level, and errors are logged on Error level. This can be adjusted according to your needs by providing a custom Attributes.LogLevels attribute on the given Flow:

    The extract function will be applied to each element before logging, so it is possible to log only those fields of a complex object flowing through this element.

    Uses an internally created LoggingAdapter which uses akka.stream.Log as it's source (use this class to configure slf4j loggers).

    Emits when the mapping function returns an element

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  63. def log(name: String, extract: Function[Out, Any], log: LoggingAdapter): SubFlow[In, Out, Mat]

    Logs elements flowing through the stream as well as completion and erroring.

    Logs elements flowing through the stream as well as completion and erroring.

    By default element and completion signals are logged on debug level, and errors are logged on Error level. This can be adjusted according to your needs by providing a custom Attributes.LogLevels attribute on the given Flow:

    The extract function will be applied to each element before logging, so it is possible to log only those fields of a complex object flowing through this element.

    Uses the given LoggingAdapter for logging.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when the mapping function returns an element

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  64. def map[T](f: Function[Out, T]): SubFlow[In, T, Mat]

    Transform this stream by applying the given function to each of the elements as they pass through this processing step.

    Transform this stream by applying the given function to each of the elements as they pass through this processing step.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when the mapping function returns an element

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  65. def mapAsync[T](parallelism: Int, f: Function[Out, CompletionStage[T]]): SubFlow[In, T, Mat]

    Transform this stream by applying the given function to each of the elements as they pass through this processing step.

    Transform this stream by applying the given function to each of the elements as they pass through this processing step. The function returns a CompletionStage and the value of that future will be emitted downstream. The number of CompletionStages that shall run in parallel is given as the first argument to mapAsync. These CompletionStages may complete in any order, but the elements that are emitted downstream are in the same order as received from upstream.

    If the function f throws an exception or if the CompletionStage is completed with failure and the supervision decision is akka.stream.Supervision#stop the stream will be completed with failure.

    If the function f throws an exception or if the CompletionStage is completed with failure and the supervision decision is akka.stream.Supervision#resume or akka.stream.Supervision#restart the element is dropped and the stream continues.

    The function f is always invoked on the elements in the order they arrive.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when the CompletionStage returned by the provided function finishes for the next element in sequence

    Backpressures when the number of CompletionStages reaches the configured parallelism and the downstream backpressures or the first CompletionStage is not completed

    Completes when upstream completes and all CompletionStages has been completed and all elements has been emitted

    Cancels when downstream cancels

    See also

    #mapAsyncUnordered

  66. def mapAsyncUnordered[T](parallelism: Int, f: Function[Out, CompletionStage[T]]): SubFlow[In, T, Mat]

    Transform this stream by applying the given function to each of the elements as they pass through this processing step.

    Transform this stream by applying the given function to each of the elements as they pass through this processing step. The function returns a CompletionStage and the value of that future will be emitted downstream. The number of CompletionStages that shall run in parallel is given as the first argument to mapAsyncUnordered. Each processed element will be emitted downstream as soon as it is ready, i.e. it is possible that the elements are not emitted downstream in the same order as received from upstream.

    If the function f throws an exception or if the CompletionStage is completed with failure and the supervision decision is akka.stream.Supervision#stop the stream will be completed with failure.

    If the function f throws an exception or if the CompletionStage is completed with failure and the supervision decision is akka.stream.Supervision#resume or akka.stream.Supervision#restart the element is dropped and the stream continues.

    The function f is always invoked on the elements in the order they arrive (even though the result of the CompletionStages returned by f might be emitted in a different order).

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when any of the CompletionStages returned by the provided function complete

    Backpressures when the number of CompletionStages reaches the configured parallelism and the downstream backpressures

    Completes when upstream completes and all CompletionStages have been completed and all elements has been emitted

    Cancels when downstream cancels

    See also

    #mapAsync

  67. def mapConcat[T](f: Function[Out, Iterable[T]]): SubFlow[In, T, Mat]

    Transform each input element into an Iterable of output elements that is then flattened into the output stream.

    Transform each input element into an Iterable of output elements that is then flattened into the output stream.

    Make sure that the Iterable is immutable or at least not modified after being used as an output sequence. Otherwise the stream may fail with ConcurrentModificationException or other more subtle errors may occur.

    The returned Iterable MUST NOT contain null values, as they are illegal as stream elements - according to the Reactive Streams specification.

    Emits when the mapping function returns an element or there are still remaining elements from the previously calculated collection

    Backpressures when downstream backpressures or there are still remaining elements from the previously calculated collection

    Completes when upstream completes and all remaining elements has been emitted

    Cancels when downstream cancels

  68. def mapError(pf: PartialFunction[Throwable, Throwable]): SubFlow[In, Out, Mat]

    While similar to recover this operator can be used to transform an error signal to a different one *without* logging it as an error in the process.

    While similar to recover this operator can be used to transform an error signal to a different one *without* logging it as an error in the process. So in that sense it is NOT exactly equivalent to recover(t => throw t2) since recover would log the t2 error.

    Since the underlying failure signal onError arrives out-of-band, it might jump over existing elements. This operator can recover the failure signal, but not the skipped elements, which will be dropped.

    Similarly to recover throwing an exception inside mapError _will_ be logged.

    Emits when element is available from the upstream or upstream is failed and pf returns an element

    Backpressures when downstream backpressures

    Completes when upstream completes or upstream failed with exception pf can handle

    Cancels when downstream cancels

  69. def merge(that: Graph[SourceShape[Out], _]): SubFlow[In, Out, Mat]

    Merge the given Source to this Flow, taking elements as they arrive from input streams, picking randomly when several elements ready.

    Merge the given Source to this Flow, taking elements as they arrive from input streams, picking randomly when several elements ready.

    Emits when one of the inputs has an element available

    Backpressures when downstream backpressures

    Completes when all upstreams complete

    Cancels when downstream cancels

  70. def mergeSorted[M](that: Graph[SourceShape[Out], M], comp: Comparator[Out]): SubFlow[In, Out, Mat]

    Merge the given Source to this Flow, taking elements as they arrive from input streams, picking always the smallest of the available elements (waiting for one element from each side to be available).

    Merge the given Source to this Flow, taking elements as they arrive from input streams, picking always the smallest of the available elements (waiting for one element from each side to be available). This means that possible contiguity of the input streams is not exploited to avoid waiting for elements, this merge will block when one of the inputs does not have more elements (and does not complete).

    Emits when all of the inputs have an element available

    Backpressures when downstream backpressures

    Completes when all upstreams complete

    Cancels when downstream cancels

  71. def mergeSubstreams(): Flow[In, Out, Mat]

    Flatten the sub-flows back into the super-flow by performing a merge without parallelism limit (i.e.

    Flatten the sub-flows back into the super-flow by performing a merge without parallelism limit (i.e. having an unbounded number of sub-flows active concurrently).

    This is identical in effect to mergeSubstreamsWithParallelism(Integer.MAX_VALUE).

  72. def mergeSubstreamsWithParallelism(parallelism: Int): Flow[In, Out, Mat]

    Flatten the sub-flows back into the super-flow by performing a merge with the given parallelism limit.

    Flatten the sub-flows back into the super-flow by performing a merge with the given parallelism limit. This means that only up to parallelism substreams will be executed at any given time. Substreams that are not yet executed are also not materialized, meaning that back-pressure will be exerted at the operator that creates the substreams when the parallelism limit is reached.

  73. def named(name: String): SubFlow[In, Out, Mat]

    Add a name attribute to this Flow.

  74. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  75. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  76. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  77. def orElse[M](secondary: Graph[SourceShape[Out], M]): SubFlow[In, Out, Mat]

    Provides a secondary source that will be consumed if this source completes without any elements passing by.

    Provides a secondary source that will be consumed if this source completes without any elements passing by. As soon as the first element comes through this stream, the alternative will be cancelled.

    Note that this Flow will be materialized together with the Source and just kept from producing elements by asserting back-pressure until its time comes or it gets cancelled.

    On errors the operator is failed regardless of source of the error.

    Emits when element is available from first stream or first stream closed without emitting any elements and an element is available from the second stream

    Backpressures when downstream backpressures

    Completes when the primary stream completes after emitting at least one element, when the primary stream completes without emitting and the secondary stream already has completed or when the secondary stream completes

    Cancels when downstream cancels and additionally the alternative is cancelled as soon as an element passes by from this stream.

  78. def prefixAndTail(n: Int): SubFlow[In, Pair[List[Out], Source[Out, NotUsed]], Mat]

    Takes up to n elements from the stream (less than n only if the upstream completes before emitting n elements) and returns a pair containing a strict sequence of the taken element and a stream representing the remaining elements.

    Takes up to n elements from the stream (less than n only if the upstream completes before emitting n elements) and returns a pair containing a strict sequence of the taken element and a stream representing the remaining elements. If n is zero or negative, then this will return a pair of an empty collection and a stream containing the whole upstream unchanged.

    In case of an upstream error, depending on the current state

    • the master stream signals the error if less than n elements has been seen, and therefore the substream has not yet been emitted
    • the tail substream signals the error after the prefix and tail has been emitted by the main stream (at that point the main stream has already completed)

    Emits when the configured number of prefix elements are available. Emits this prefix, and the rest as a substream

    Backpressures when downstream backpressures or substream backpressures

    Completes when prefix elements has been consumed and substream has been consumed

    Cancels when downstream cancels or substream cancels

  79. def prepend[M](that: Graph[SourceShape[Out], M]): SubFlow[In, Out, Mat]

    Prepend the given Source to this Flow, meaning that before elements are generated from this Flow, the Source's elements will be produced until it is exhausted, at which point Flow elements will start being produced.

    Prepend the given Source to this Flow, meaning that before elements are generated from this Flow, the Source's elements will be produced until it is exhausted, at which point Flow elements will start being produced.

    Note that this Flow will be materialized together with the Source and just kept from producing elements by asserting back-pressure until its time comes.

    If the given Source gets upstream error - no elements from this Flow will be pulled.

    Emits when element is available from the given Source or from current stream when the Source is completed

    Backpressures when downstream backpressures

    Completes when this Flow completes

    Cancels when downstream cancels

  80. def recover(pf: PartialFunction[Throwable, Out]): SubFlow[In, Out, Mat]

    Recover allows to send last element on failure and gracefully complete the stream Since the underlying failure signal onError arrives out-of-band, it might jump over existing elements.

    Recover allows to send last element on failure and gracefully complete the stream Since the underlying failure signal onError arrives out-of-band, it might jump over existing elements. This operator can recover the failure signal, but not the skipped elements, which will be dropped.

    Throwing an exception inside recover _will_ be logged on ERROR level automatically.

    Emits when element is available from the upstream or upstream is failed and pf returns an element

    Backpressures when downstream backpressures

    Completes when upstream completes or upstream failed with exception pf can handle

    Cancels when downstream cancels

  81. def recoverWithRetries(attempts: Int, pf: PartialFunction[Throwable, Graph[SourceShape[Out], NotUsed]]): SubFlow[In, Out, Mat]

    RecoverWithRetries allows to switch to alternative Source on flow failure.

    RecoverWithRetries allows to switch to alternative Source on flow failure. It will stay in effect after a failure has been recovered up to attempts number of times so that each time there is a failure it is fed into the pf and a new Source may be materialized. Note that if you pass in 0, this won't attempt to recover at all.

    A negative attempts number is interpreted as "infinite", which results in the exact same behavior as recoverWith.

    Since the underlying failure signal onError arrives out-of-band, it might jump over existing elements. This operator can recover the failure signal, but not the skipped elements, which will be dropped.

    Throwing an exception inside recoverWithRetries _will_ be logged on ERROR level automatically.

    Emits when element is available from the upstream or upstream is failed and element is available from alternative Source

    Backpressures when downstream backpressures

    Completes when upstream completes or upstream failed with exception pf can handle

    Cancels when downstream cancels

  82. def reduce(f: Function2[Out, Out, Out]): SubFlow[In, Out, Mat]

    Similar to fold but uses first element as zero element.

    Similar to fold but uses first element as zero element. Applies the given function towards its current and next value, yielding the next current value.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when upstream completes

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  83. def scan[T](zero: T)(f: Function2[T, Out, T]): SubFlow[In, T, Mat]

    Similar to fold but is not a terminal operation, emits its current value which starts at zero and then applies the current and next value to the given function f, emitting the next current value.

    Similar to fold but is not a terminal operation, emits its current value which starts at zero and then applies the current and next value to the given function f, emitting the next current value.

    If the function f throws an exception and the supervision decision is akka.stream.Supervision#restart current value starts at zero again the stream will continue.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Note that the zero value must be immutable.

    Emits when the function scanning the element returns a new element

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  84. def scanAsync[T](zero: T)(f: Function2[T, Out, CompletionStage[T]]): SubFlow[In, T, Mat]

    Similar to scan but with a asynchronous function, emits its current value which starts at zero and then applies the current and next value to the given function f, emitting a Future that resolves to the next current value.

    Similar to scan but with a asynchronous function, emits its current value which starts at zero and then applies the current and next value to the given function f, emitting a Future that resolves to the next current value.

    If the function f throws an exception and the supervision decision is akka.stream.Supervision.Restart current value starts at zero again the stream will continue.

    If the function f throws an exception and the supervision decision is akka.stream.Supervision.Resume current value starts at the previous current value, or zero when it doesn't have one, and the stream will continue.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Note that the zero value must be immutable.

    Emits when the future returned by f completes

    Backpressures when downstream backpressures

    Completes when upstream completes and the last future returned by f completes

    Cancels when downstream cancels

    See also FlowOps.scan

  85. def sliding(n: Int, step: Int = 1): SubFlow[In, List[Out], Mat]

    Apply a sliding window over the stream and return the windows as groups of elements, with the last group possibly smaller than requested due to end-of-stream.

    Apply a sliding window over the stream and return the windows as groups of elements, with the last group possibly smaller than requested due to end-of-stream.

    n must be positive, otherwise IllegalArgumentException is thrown. step must be positive, otherwise IllegalArgumentException is thrown.

    Emits when enough elements have been collected within the window or upstream completed

    Backpressures when a window has been assembled and downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  86. def statefulMapConcat[T](f: Creator[Function[Out, Iterable[T]]]): SubFlow[In, T, Mat]

    Transform each input element into an Iterable of output elements that is then flattened into the output stream.

    Transform each input element into an Iterable of output elements that is then flattened into the output stream. The transformation is meant to be stateful, which is enabled by creating the transformation function anew for every materialization — the returned function will typically close over mutable objects to store state between invocations. For the stateless variant see #mapConcat.

    Make sure that the Iterable is immutable or at least not modified after being used as an output sequence. Otherwise the stream may fail with ConcurrentModificationException or other more subtle errors may occur.

    The returned Iterable MUST NOT contain null values, as they are illegal as stream elements - according to the Reactive Streams specification.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when the mapping function returns an element or there are still remaining elements from the previously calculated collection

    Backpressures when downstream backpressures or there are still remaining elements from the previously calculated collection

    Completes when upstream completes and all remaining elements has been emitted

    Cancels when downstream cancels

  87. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  88. def take(n: Long): SubFlow[In, Out, Mat]

    Terminate processing (and cancel the upstream publisher) after the given number of elements.

    Terminate processing (and cancel the upstream publisher) after the given number of elements. Due to input buffering some elements may have been requested from upstream publishers that will then not be processed downstream of this step.

    The stream will be completed without producing any elements if n is zero or negative.

    Emits when the specified number of elements to take has not yet been reached

    Backpressures when downstream backpressures

    Completes when the defined number of elements has been taken or upstream completes

    Cancels when the defined number of elements has been taken or downstream cancels

  89. def takeWhile(p: Predicate[Out], inclusive: Boolean): SubFlow[In, Out, Mat]

    Terminate processing (and cancel the upstream publisher) after predicate returns false for the first time, including the first failed element iff inclusive is true Due to input buffering some elements may have been requested from upstream publishers that will then not be processed downstream of this step.

    Terminate processing (and cancel the upstream publisher) after predicate returns false for the first time, including the first failed element iff inclusive is true Due to input buffering some elements may have been requested from upstream publishers that will then not be processed downstream of this step.

    The stream will be completed without producing any elements if predicate is false for the first stream element.

    Adheres to the ActorAttributes.SupervisionStrategy attribute.

    Emits when the predicate is true

    Backpressures when downstream backpressures

    Completes when predicate returned false (or 1 after predicate returns false if inclusive or upstream completes

    Cancels when predicate returned false or downstream cancels

  90. def takeWhile(p: Predicate[Out]): SubFlow[In, Out, Mat]

    Terminate processing (and cancel the upstream publisher) after predicate returns false for the first time, Due to input buffering some elements may have been requested from upstream publishers that will then not be processed downstream of this step.

    Terminate processing (and cancel the upstream publisher) after predicate returns false for the first time, Due to input buffering some elements may have been requested from upstream publishers that will then not be processed downstream of this step.

    The stream will be completed without producing any elements if predicate is false for the first stream element.

    Emits when the predicate is true

    Backpressures when downstream backpressures

    Completes when predicate returned false (or 1 after predicate returns false if inclusive or upstream completes

    Cancels when predicate returned false or downstream cancels

  91. def takeWithin(d: Duration): SubFlow[In, Out, Mat]

    Terminate processing (and cancel the upstream publisher) after the given duration.

    Terminate processing (and cancel the upstream publisher) after the given duration. Due to input buffering some elements may have been requested from upstream publishers that will then not be processed downstream of this step.

    Note that this can be combined with #take to limit the number of elements within the duration.

    Emits when an upstream element arrives

    Backpressures when downstream backpressures

    Completes when upstream completes or timer fires

    Cancels when downstream cancels or timer fires

    Annotations
    @silent()
  92. def throttle(cost: Int, per: Duration, maximumBurst: Int, costCalculation: Function[Out, Integer], mode: ThrottleMode): SubFlow[In, Out, Mat]

    Sends elements downstream with speed limited to cost/per.

    Sends elements downstream with speed limited to cost/per. Cost is calculating for each element individually by calling calculateCost function. This operator works for streams when elements have different cost(length). Streams of ByteString for example.

    Throttle implements the token bucket model. There is a bucket with a given token capacity (burst size or maximumBurst). Tokens drops into the bucket at a given rate and can be spared for later use up to bucket capacity to allow some burstiness. Whenever stream wants to send an element, it takes as many tokens from the bucket as element costs. If there isn't any, throttle waits until the bucket accumulates enough tokens. Elements that costs more than the allowed burst will be delayed proportionally to their cost minus available tokens, meeting the target rate. Bucket is full when stream just materialized and started.

    Parameter mode manages behavior when upstream is faster than throttle rate:

    It is recommended to use non-zero burst sizes as they improve both performance and throttling precision by allowing the implementation to avoid using the scheduler when input rates fall below the enforced limit and to reduce most of the inaccuracy caused by the scheduler resolution (which is in the range of milliseconds).

    WARNING: Be aware that throttle is using scheduler to slow down the stream. This scheduler has minimal time of triggering next push. Consequently it will slow down the stream as it has minimal pause for emitting. This can happen in case burst is 0 and speed is higher than 30 events per second. You need to increase the maximumBurst if elements arrive with small interval (30 milliseconds or less). Use the overloaded throttle method without maximumBurst parameter to automatically calculate the maximumBurst based on the given rate (cost/per). In other words the throttler always enforces the rate limit when maximumBurst parameter is given, but in certain cases (mostly due to limited scheduler resolution) it enforces a tighter bound than what was prescribed.

    Emits when upstream emits an element and configured time per each element elapsed

    Backpressures when downstream backpressures or the incoming rate is higher than the speed limit

    Completes when upstream completes

    Cancels when downstream cancels

  93. def throttle(cost: Int, per: Duration, costCalculation: Function[Out, Integer]): SubFlow[In, Out, Mat]

    Sends elements downstream with speed limited to cost/per.

    Sends elements downstream with speed limited to cost/per. Cost is calculating for each element individually by calling calculateCost function. This operator works for streams when elements have different cost(length). Streams of ByteString for example.

    Throttle implements the token bucket model. There is a bucket with a given token capacity (burst size). Tokens drops into the bucket at a given rate and can be spared for later use up to bucket capacity to allow some burstiness. Whenever stream wants to send an element, it takes as many tokens from the bucket as element costs. If there isn't any, throttle waits until the bucket accumulates enough tokens. Elements that costs more than the allowed burst will be delayed proportionally to their cost minus available tokens, meeting the target rate. Bucket is full when stream just materialized and started.

    The burst size is calculated based on the given rate (cost/per) as 0.1 * rate, for example: - rate < 20/second => burst size 1 - rate 20/second => burst size 2 - rate 100/second => burst size 10 - rate 200/second => burst size 20

    The throttle mode is akka.stream.ThrottleMode.Shaping, which makes pauses before emitting messages to meet throttle rate.

    Emits when upstream emits an element and configured time per each element elapsed

    Backpressures when downstream backpressures or the incoming rate is higher than the speed limit

    Completes when upstream completes

    Cancels when downstream cancels

  94. def throttle(elements: Int, per: Duration, maximumBurst: Int, mode: ThrottleMode): SubFlow[In, Out, Mat]

    Sends elements downstream with speed limited to elements/per.

    Sends elements downstream with speed limited to elements/per. In other words, this operator set the maximum rate for emitting messages. This operator works for streams where all elements have the same cost or length.

    Throttle implements the token bucket model. There is a bucket with a given token capacity (burst size or maximumBurst). Tokens drops into the bucket at a given rate and can be spared for later use up to bucket capacity to allow some burstiness. Whenever stream wants to send an element, it takes as many tokens from the bucket as element costs. If there isn't any, throttle waits until the bucket accumulates enough tokens. Elements that costs more than the allowed burst will be delayed proportionally to their cost minus available tokens, meeting the target rate. Bucket is full when stream just materialized and started.

    Parameter mode manages behavior when upstream is faster than throttle rate:

    It is recommended to use non-zero burst sizes as they improve both performance and throttling precision by allowing the implementation to avoid using the scheduler when input rates fall below the enforced limit and to reduce most of the inaccuracy caused by the scheduler resolution (which is in the range of milliseconds).

    WARNING: Be aware that throttle is using scheduler to slow down the stream. This scheduler has minimal time of triggering next push. Consequently it will slow down the stream as it has minimal pause for emitting. This can happen in case burst is 0 and speed is higher than 30 events per second. You need to increase the maximumBurst if elements arrive with small interval (30 milliseconds or less). Use the overloaded throttle method without maximumBurst parameter to automatically calculate the maximumBurst based on the given rate (cost/per). In other words the throttler always enforces the rate limit when maximumBurst parameter is given, but in certain cases (mostly due to limited scheduler resolution) it enforces a tighter bound than what was prescribed.

    Emits when upstream emits an element and configured time per each element elapsed

    Backpressures when downstream backpressures or the incoming rate is higher than the speed limit

    Completes when upstream completes

    Cancels when downstream cancels

  95. def throttle(elements: Int, per: Duration): SubFlow[In, Out, Mat]

    Sends elements downstream with speed limited to elements/per.

    Sends elements downstream with speed limited to elements/per. In other words, this operator set the maximum rate for emitting messages. This operator works for streams where all elements have the same cost or length.

    Throttle implements the token bucket model. There is a bucket with a given token capacity (burst size). Tokens drops into the bucket at a given rate and can be spared for later use up to bucket capacity to allow some burstiness. Whenever stream wants to send an element, it takes as many tokens from the bucket as element costs. If there isn't any, throttle waits until the bucket accumulates enough tokens. Elements that costs more than the allowed burst will be delayed proportionally to their cost minus available tokens, meeting the target rate. Bucket is full when stream just materialized and started.

    The burst size is calculated based on the given rate (cost/per) as 0.1 * rate, for example: - rate < 20/second => burst size 1 - rate 20/second => burst size 2 - rate 100/second => burst size 10 - rate 200/second => burst size 20

    The throttle mode is akka.stream.ThrottleMode.Shaping, which makes pauses before emitting messages to meet throttle rate.

    Emits when upstream emits an element and configured time per each element elapsed

    Backpressures when downstream backpressures or the incoming rate is higher than the speed limit

    Completes when upstream completes

    Cancels when downstream cancels

  96. def to(sink: Graph[SinkShape[Out], _]): Sink[In, Mat]

    Connect this SubFlow to a Sink, concatenating the processing steps of both.

    Connect this SubFlow to a Sink, concatenating the processing steps of both. This means that all sub-flows that result from the previous sub-stream operator will be attached to the given sink.

        +----------------------------+
        | Resulting Sink             |
        |                            |
        |  +------+        +------+  |
        |  |      |        |      |  |
    In ~~> | flow | ~Out~> | sink |  |
        |  |      |        |      |  |
        |  +------+        +------+  |
        +----------------------------+

    Note that attributes set on the returned graph, including async boundaries are now for the entire graph and not the SubFlow. for example async will not have any effect as the returned graph is the entire, closed graph.

  97. def toString(): String
    Definition Classes
    AnyRef → Any
  98. def via[T, M](flow: Graph[FlowShape[Out, T], M]): SubFlow[In, T, Mat]

    Transform this Flow by appending the given processing steps.

    Transform this Flow by appending the given processing steps.

        +----------------------------+
        | Resulting Flow             |
        |                            |
        |  +------+        +------+  |
        |  |      |        |      |  |
    In ~~> | this | ~Out~> | flow | ~~> T
        |  |      |        |      |  |
        |  +------+        +------+  |
        +----------------------------+

    The materialized value of the combined Flow will be the materialized value of the current flow (ignoring the other Flow’s value), use viaMat if a different strategy is needed.

  99. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  100. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @throws( ... )
  101. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  102. def wireTap(that: Graph[SinkShape[Out], _]): SubFlow[In, Out, Mat]

    Attaches the given Sink to this Flow as a wire tap, meaning that elements that pass through will also be sent to the wire-tap Sink, without the latter affecting the mainline flow.

    Attaches the given Sink to this Flow as a wire tap, meaning that elements that pass through will also be sent to the wire-tap Sink, without the latter affecting the mainline flow. If the wire-tap Sink backpressures, elements that would've been sent to it will be dropped instead.

    It is similar to #alsoTo which does backpressure instead of dropping elements.

    Emits when element is available and demand exists from the downstream; the element will also be sent to the wire-tap Sink if there is demand.

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  103. def wireTap(f: Procedure[Out]): SubFlow[In, Out, Mat]

    This is a simplified version of wireTap(Sink) that takes only a simple procedure.

    This is a simplified version of wireTap(Sink) that takes only a simple procedure. Elements will be passed into this "side channel" function, and any of its results will be ignored.

    If the wire-tap operation is slow (it backpressures), elements that would've been sent to it will be dropped instead. It is similar to #alsoTo which does backpressure instead of dropping elements.

    This operation is useful for inspecting the passed through element, usually by means of side-effecting operations (such as println, or emitting metrics), for each element without having to modify it.

    For logging signals (elements, completion, error) consider using the log operator instead, along with appropriate ActorAttributes.logLevels.

    Emits when upstream emits an element; the same element will be passed to the attached function, as well as to the downstream operator

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  104. def withAttributes(attr: Attributes): SubFlow[In, Out, Mat]

    Change the attributes of this Source to the given ones and seal the list of attributes.

    Change the attributes of this Source to the given ones and seal the list of attributes. This means that further calls will not be able to remove these attributes, but instead add new ones. Note that this operation has no effect on an empty Flow (because the attributes apply only to the contained processing operators).

  105. def zip[T](source: Graph[SourceShape[T], _]): SubFlow[In, Pair[Out, T], Mat]

    Combine the elements of current Flow and the given Source into a stream of tuples.

    Combine the elements of current Flow and the given Source into a stream of tuples.

    Emits when all of the inputs has an element available

    Backpressures when downstream backpressures

    Completes when any upstream completes

    Cancels when downstream cancels

  106. def zipLatest[T](source: Graph[SourceShape[T], _]): SubFlow[In, Pair[Out, T], Mat]

    Combine the elements of current Flow and the given Source into a stream of tuples, picking always the latest element of each.

    Combine the elements of current Flow and the given Source into a stream of tuples, picking always the latest element of each.

    Emits when all of the inputs have at least an element available, and then each time an element becomes available on either of the inputs

    Backpressures when downstream backpressures

    Completes when any upstream completes

    Cancels when downstream cancels

  107. def zipLatestWith[Out2, Out3](that: Graph[SourceShape[Out2], _], combine: Function2[Out, Out2, Out3]): SubFlow[In, Out3, Mat]

    Put together the elements of current Flow and the given Source into a stream of combined elements using a combiner function, picking always the latest element of each.

    Put together the elements of current Flow and the given Source into a stream of combined elements using a combiner function, picking always the latest element of each.

    Emits when all of the inputs have at least an element available, and then each time an element becomes available on either of the inputs

    Backpressures when downstream backpressures

    Completes when any upstream completes

    Cancels when downstream cancels

  108. def zipWith[Out2, Out3](that: Graph[SourceShape[Out2], _], combine: Function2[Out, Out2, Out3]): SubFlow[In, Out3, Mat]

    Put together the elements of current Flow and the given Source into a stream of combined elements using a combiner function.

    Put together the elements of current Flow and the given Source into a stream of combined elements using a combiner function.

    Emits when all of the inputs has an element available

    Backpressures when downstream backpressures

    Completes when any upstream completes

    Cancels when downstream cancels

  109. def zipWithIndex: SubFlow[In, Pair[Out, Long], Mat]

    Combine the elements of current Flow into a stream of tuples consisting of all elements paired with their index.

    Combine the elements of current Flow into a stream of tuples consisting of all elements paired with their index. Indices start at 0.

    Emits when upstream emits an element and is paired with their index

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

  110. def [B](y: B): (SubFlow[In, Out, Mat], B)
    Implicit
    This member is added by an implicit conversion from SubFlow[In, Out, Mat] to ArrowAssoc[SubFlow[In, Out, Mat]] performed by method ArrowAssoc in scala.Predef.
    Definition Classes
    ArrowAssoc

Deprecated Value Members

  1. def backpressureTimeout(timeout: FiniteDuration): SubFlow[In, Out, Mat]

    If the time between the emission of an element and the following downstream demand exceeds the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException.

    If the time between the emission of an element and the following downstream demand exceeds the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException. The timeout is checked periodically, so the resolution of the check is one period (equals to timeout value).

    Emits when upstream emits an element

    Backpressures when downstream backpressures

    Completes when upstream completes or fails if timeout elapses between element emission and downstream demand.

    Cancels when downstream cancels

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use the overloaded one which accepts java.time.Duration instead.

  2. def completionTimeout(timeout: FiniteDuration): SubFlow[In, Out, Mat]

    If the completion of the stream does not happen until the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException.

    If the completion of the stream does not happen until the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException.

    Emits when upstream emits an element

    Backpressures when downstream backpressures

    Completes when upstream completes or fails if timeout elapses before upstream completes

    Cancels when downstream cancels

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use the overloaded one which accepts java.time.Duration instead.

  3. def delay(of: FiniteDuration, strategy: DelayOverflowStrategy): SubFlow[In, Out, Mat]

    Shifts elements emission in time by a specified amount.

    Shifts elements emission in time by a specified amount. It allows to store elements in internal buffer while waiting for next element to be emitted. Depending on the defined akka.stream.DelayOverflowStrategy it might drop elements or backpressure the upstream if there is no space available in the buffer.

    Delay precision is 10ms to avoid unnecessary timer scheduling cycles

    Internal buffer has default capacity 16. You can set buffer size by calling withAttributes(inputBuffer)

    Emits when there is a pending element in the buffer and configured time for this element elapsed * EmitEarly - strategy do not wait to emit element if buffer is full

    Backpressures when depending on OverflowStrategy * Backpressure - backpressures when buffer is full * DropHead, DropTail, DropBuffer - never backpressures * Fail - fails the stream if buffer gets full

    Completes when upstream completes and buffered elements has been drained

    Cancels when downstream cancels

    of

    time to shift all messages

    strategy

    Strategy that is used when incoming elements cannot fit inside the buffer

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use the overloaded one which accepts java.time.Duration instead.

  4. def dropWithin(d: FiniteDuration): SubFlow[In, Out, Mat]

    Discard the elements received within the given duration at beginning of the stream.

    Discard the elements received within the given duration at beginning of the stream.

    Emits when the specified time elapsed and a new upstream element arrives

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use the overloaded one which accepts java.time.Duration instead.

  5. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @Deprecated @deprecated @throws( classOf[java.lang.Throwable] )
    Deprecated

    (Since version ) see corresponding Javadoc for more information.

  6. def groupedWeightedWithin(maxWeight: Long, costFn: Function[Out, Long], d: FiniteDuration): SubFlow[In, List[Out], Mat]

    Chunk up this stream into groups of elements received within a time window, or limited by the weight of the elements, whatever happens first.

    Chunk up this stream into groups of elements received within a time window, or limited by the weight of the elements, whatever happens first. Empty groups will not be emitted if no elements are received from upstream. The last group before end-of-stream will contain the buffered elements since the previously emitted group.

    Emits when the configured time elapses since the last group has been emitted or weight limit reached

    Backpressures when downstream backpressures, and buffered group (+ pending element) weighs more than maxWeight

    Completes when upstream completes (emits last group)

    Cancels when downstream completes

    maxWeight must be positive, and d must be greater than 0 seconds, otherwise IllegalArgumentException is thrown.

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use the overloaded one which accepts java.time.Duration instead.

  7. def groupedWithin(n: Int, d: FiniteDuration): SubFlow[In, List[Out], Mat]

    Chunk up this stream into groups of elements received within a time window, or limited by the given number of elements, whatever happens first.

    Chunk up this stream into groups of elements received within a time window, or limited by the given number of elements, whatever happens first. Empty groups will not be emitted if no elements are received from upstream. The last group before end-of-stream will contain the buffered elements since the previously emitted group.

    Emits when the configured time elapses since the last group has been emitted or n elements is buffered

    Backpressures when downstream backpressures, and there are n+1 buffered elements

    Completes when upstream completes (emits last group)

    Cancels when downstream completes

    n must be positive, and d must be greater than 0 seconds, otherwise IllegalArgumentException is thrown.

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use the overloaded one which accepts java.time.Duration instead.

  8. def idleTimeout(timeout: FiniteDuration): SubFlow[In, Out, Mat]

    If the time between two processed elements exceeds the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException.

    If the time between two processed elements exceeds the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException. The timeout is checked periodically, so the resolution of the check is one period (equals to timeout value).

    Emits when upstream emits an element

    Backpressures when downstream backpressures

    Completes when upstream completes or fails if timeout elapses between two emitted elements

    Cancels when downstream cancels

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use the overloaded one which accepts java.time.Duration instead.

  9. def initialDelay(delay: FiniteDuration): SubFlow[In, Out, Mat]

    Delays the initial element by the specified duration.

    Delays the initial element by the specified duration.

    Emits when upstream emits an element if the initial delay is already elapsed

    Backpressures when downstream backpressures or initial delay is not yet elapsed

    Completes when upstream completes

    Cancels when downstream cancels

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use the overloaded one which accepts java.time.Duration instead.

  10. def initialTimeout(timeout: FiniteDuration): SubFlow[In, Out, Mat]

    If the first element has not passed through this operator before the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException.

    If the first element has not passed through this operator before the provided timeout, the stream is failed with a java.util.concurrent.TimeoutException.

    Emits when upstream emits an element

    Backpressures when downstream backpressures

    Completes when upstream completes or fails if timeout elapses before first element arrives

    Cancels when downstream cancels

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use the overloaded one which accepts java.time.Duration instead.

  11. def keepAlive(maxIdle: FiniteDuration, injectedElem: Creator[Out]): SubFlow[In, Out, Mat]

    Injects additional elements if upstream does not emit for a configured amount of time.

    Injects additional elements if upstream does not emit for a configured amount of time. In other words, this operator attempts to maintains a base rate of emitted elements towards the downstream.

    If the downstream backpressures then no element is injected until downstream demand arrives. Injected elements do not accumulate during this period.

    Upstream elements are always preferred over injected elements.

    Emits when upstream emits an element or if the upstream was idle for the configured period

    Backpressures when downstream backpressures

    Completes when upstream completes

    Cancels when downstream cancels

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use the overloaded one which accepts java.time.Duration instead.

  12. def recoverWith(pf: PartialFunction[Throwable, Graph[SourceShape[Out], NotUsed]]): SubFlow[In, Out, Mat]

    RecoverWith allows to switch to alternative Source on flow failure.

    RecoverWith allows to switch to alternative Source on flow failure. It will stay in effect after a failure has been recovered so that each time there is a failure it is fed into the pf and a new Source may be materialized.

    Since the underlying failure signal onError arrives out-of-band, it might jump over existing elements. This operator can recover the failure signal, but not the skipped elements, which will be dropped.

    Throwing an exception inside recoverWith _will_ be logged on ERROR level automatically.

    Emits when element is available from the upstream or upstream is failed and element is available from alternative Source

    Backpressures when downstream backpressures

    Completes when upstream completes or upstream failed with exception pf can handle

    Cancels when downstream cancels

    Annotations
    @deprecated
    Deprecated

    (Since version 2.4.4) Use recoverWithRetries instead.

  13. def takeWithin(d: FiniteDuration): SubFlow[In, Out, Mat]

    Terminate processing (and cancel the upstream publisher) after the given duration.

    Terminate processing (and cancel the upstream publisher) after the given duration. Due to input buffering some elements may have been requested from upstream publishers that will then not be processed downstream of this step.

    Note that this can be combined with #take to limit the number of elements within the duration.

    Emits when an upstream element arrives

    Backpressures when downstream backpressures

    Completes when upstream completes or timer fires

    Cancels when downstream cancels or timer fires

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use the overloaded one which accepts java.time.Duration instead.

  14. def throttle(cost: Int, per: FiniteDuration, maximumBurst: Int, costCalculation: Function[Out, Integer], mode: ThrottleMode): SubFlow[In, Out, Mat]

    Sends elements downstream with speed limited to cost/per.

    Sends elements downstream with speed limited to cost/per. Cost is calculating for each element individually by calling calculateCost function. This operator works for streams when elements have different cost(length). Streams of ByteString for example.

    Throttle implements the token bucket model. There is a bucket with a given token capacity (burst size or maximumBurst). Tokens drops into the bucket at a given rate and can be spared for later use up to bucket capacity to allow some burstiness. Whenever stream wants to send an element, it takes as many tokens from the bucket as element costs. If there isn't any, throttle waits until the bucket accumulates enough tokens. Elements that costs more than the allowed burst will be delayed proportionally to their cost minus available tokens, meeting the target rate. Bucket is full when stream just materialized and started.

    Parameter mode manages behavior when upstream is faster than throttle rate:

    It is recommended to use non-zero burst sizes as they improve both performance and throttling precision by allowing the implementation to avoid using the scheduler when input rates fall below the enforced limit and to reduce most of the inaccuracy caused by the scheduler resolution (which is in the range of milliseconds).

    WARNING: Be aware that throttle is using scheduler to slow down the stream. This scheduler has minimal time of triggering next push. Consequently it will slow down the stream as it has minimal pause for emitting. This can happen in case burst is 0 and speed is higher than 30 events per second. You need to increase the maximumBurst if elements arrive with small interval (30 milliseconds or less). Use the overloaded throttle method without maximumBurst parameter to automatically calculate the maximumBurst based on the given rate (cost/per). In other words the throttler always enforces the rate limit when maximumBurst parameter is given, but in certain cases (mostly due to limited scheduler resolution) it enforces a tighter bound than what was prescribed.

    Emits when upstream emits an element and configured time per each element elapsed

    Backpressures when downstream backpressures or the incoming rate is higher than the speed limit

    Completes when upstream completes

    Cancels when downstream cancels

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use the overloaded one which accepts java.time.Duration instead.

  15. def throttle(elements: Int, per: FiniteDuration, maximumBurst: Int, mode: ThrottleMode): SubFlow[In, Out, Mat]

    Sends elements downstream with speed limited to elements/per.

    Sends elements downstream with speed limited to elements/per. In other words, this operator set the maximum rate for emitting messages. This operator works for streams where all elements have the same cost or length.

    Throttle implements the token bucket model. There is a bucket with a given token capacity (burst size or maximumBurst). Tokens drops into the bucket at a given rate and can be spared for later use up to bucket capacity to allow some burstiness. Whenever stream wants to send an element, it takes as many tokens from the bucket as element costs. If there isn't any, throttle waits until the bucket accumulates enough tokens. Elements that costs more than the allowed burst will be delayed proportionally to their cost minus available tokens, meeting the target rate. Bucket is full when stream just materialized and started.

    Parameter mode manages behavior when upstream is faster than throttle rate:

    It is recommended to use non-zero burst sizes as they improve both performance and throttling precision by allowing the implementation to avoid using the scheduler when input rates fall below the enforced limit and to reduce most of the inaccuracy caused by the scheduler resolution (which is in the range of milliseconds).

    WARNING: Be aware that throttle is using scheduler to slow down the stream. This scheduler has minimal time of triggering next push. Consequently it will slow down the stream as it has minimal pause for emitting. This can happen in case burst is 0 and speed is higher than 30 events per second. You need to increase the maximumBurst if elements arrive with small interval (30 milliseconds or less). Use the overloaded throttle method without maximumBurst parameter to automatically calculate the maximumBurst based on the given rate (cost/per). In other words the throttler always enforces the rate limit when maximumBurst parameter is given, but in certain cases (mostly due to limited scheduler resolution) it enforces a tighter bound than what was prescribed.

    Emits when upstream emits an element and configured time per each element elapsed

    Backpressures when downstream backpressures or the incoming rate is higher than the speed limit

    Completes when upstream completes

    Cancels when downstream cancels

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use the overloaded one which accepts java.time.Duration instead.

  16. def throttleEven(cost: Int, per: Duration, costCalculation: Function[Out, Integer], mode: ThrottleMode): SubFlow[In, Out, Mat]

    This is a simplified version of throttle that spreads events evenly across the given time interval.

    This is a simplified version of throttle that spreads events evenly across the given time interval.

    Use this operator when you need just slow down a stream without worrying about exact amount of time between events.

    If you want to be sure that no time interval has no more than specified number of events you need to use throttle() with maximumBurst attribute.

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use throttle without maximumBurst parameter instead.

    See also

    #throttle

  17. def throttleEven(cost: Int, per: FiniteDuration, costCalculation: Function[Out, Integer], mode: ThrottleMode): SubFlow[In, Out, Mat]

    This is a simplified version of throttle that spreads events evenly across the given time interval.

    This is a simplified version of throttle that spreads events evenly across the given time interval.

    Use this operator when you need just slow down a stream without worrying about exact amount of time between events.

    If you want to be sure that no time interval has no more than specified number of events you need to use throttle() with maximumBurst attribute.

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use throttle without maximumBurst parameter instead.

    See also

    #throttle

  18. def throttleEven(elements: Int, per: Duration, mode: ThrottleMode): SubFlow[In, Out, Mat]

    This is a simplified version of throttle that spreads events evenly across the given time interval.

    This is a simplified version of throttle that spreads events evenly across the given time interval.

    Use this operator when you need just slow down a stream without worrying about exact amount of time between events.

    If you want to be sure that no time interval has no more than specified number of events you need to use throttle() with maximumBurst attribute.

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use throttle without maximumBurst parameter instead.

    See also

    #throttle

  19. def throttleEven(elements: Int, per: FiniteDuration, mode: ThrottleMode): SubFlow[In, Out, Mat]

    This is a simplified version of throttle that spreads events evenly across the given time interval.

    This is a simplified version of throttle that spreads events evenly across the given time interval.

    Use this operator when you need just slow down a stream without worrying about exact amount of time between events.

    If you want to be sure that no time interval has no more than specified number of events you need to use throttle() with maximumBurst attribute.

    Annotations
    @Deprecated @deprecated
    Deprecated

    (Since version 2.5.12) Use throttle without maximumBurst parameter instead.

    See also

    #throttle

Inherited from AnyRef

Inherited from Any

Inherited by implicit conversion any2stringadd from SubFlow[In, Out, Mat] to any2stringadd[SubFlow[In, Out, Mat]]

Inherited by implicit conversion StringFormat from SubFlow[In, Out, Mat] to StringFormat[SubFlow[In, Out, Mat]]

Inherited by implicit conversion Ensuring from SubFlow[In, Out, Mat] to Ensuring[SubFlow[In, Out, Mat]]

Inherited by implicit conversion ArrowAssoc from SubFlow[In, Out, Mat] to ArrowAssoc[SubFlow[In, Out, Mat]]

Ungrouped