Class SubFlow<In,Out,Mat>
- java.lang.Object
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- akka.stream.javadsl.SubFlow<In,Out,Mat>
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public final class SubFlow<In,Out,Mat> extends java.lang.Object
A “stream of streams” sub-flow of data elements, e.g. produced bygroupBy
. SubFlows cannot contribute to the super-flow’s materialized value since they are materialized later, during the runtime of the flow graph processing.
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Deprecated Methods Modifier and Type Method Description SubFlow<In,Out,Mat>
addAttributes(Attributes attr)
Add the given attributes to this Source.<Agg,Emit>
SubFlow<In,Emit,Mat>aggregateWithBoundary(java.util.function.Supplier<Agg> allocate, Function2<Agg,Out,Pair<Agg,java.lang.Object>> aggregate, Function<Agg,Emit> harvest, Pair<java.util.function.Predicate<Agg>,java.time.Duration> emitOnTimer)
Aggregate input elements into an arbitrary data structure that can be completed and emitted downstream when custom condition is met which can be triggered by aggregate or timer.SubFlow<In,Out,Mat>
alsoTo(Graph<SinkShape<Out>,?> that)
SubFlow<In,Out,Mat>
alsoToAll(Graph<SinkShape<Out>,?>... those)
SubFlow<In,Out,Mat>
alsoToAll(scala.collection.immutable.Seq<Graph<SinkShape<Out>,?>> those)
SubFlow<Out,Mat,Flow<In,java.lang.Object,Mat>,Sink<In,Mat>>
asScala()
Converts this Flow to its Scala DSL counterpartSubFlow<In,Out,Mat>
async()
Put an asynchronous boundary around thisSubFlow
SubFlow<In,Out,Mat>
backpressureTimeout(java.time.Duration timeout)
If the time between the emission of an element and the following downstream demand exceeds the provided timeout, the stream is failed with aBackpressureTimeoutException
.SubFlow<In,Out,Mat>
backpressureTimeout(scala.concurrent.duration.FiniteDuration timeout)
Deprecated.Use the overloaded one which accepts java.time.Duration instead.<S> SubFlow<In,S,Mat>
batch(long max, Function<Out,S> seed, Function2<S,Out,S> aggregate)
Allows a faster upstream to progress independently of a slower subscriber by aggregating elements into batches until the subscriber is ready to accept them.<S> SubFlow<In,S,Mat>
batchWeighted(long max, Function<Out,java.lang.Long> costFn, Function<Out,S> seed, Function2<S,Out,S> aggregate)
Allows a faster upstream to progress independently of a slower subscriber by aggregating elements into batches until the subscriber is ready to accept them.SubFlow<In,Out,Mat>
buffer(int size, OverflowStrategy overflowStrategy)
Adds a fixed size buffer in the flow that allows to store elements from a faster upstream until it becomes full.<T> SubFlow<In,T,Mat>
collect(scala.PartialFunction<Out,T> pf)
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.<T> SubFlow<In,T,Mat>
collectType(java.lang.Class<T> clazz)
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.SubFlow<In,Out,Mat>
completionTimeout(java.time.Duration timeout)
If the completion of the stream does not happen until the provided timeout, the stream is failed with aCompletionTimeoutException
.SubFlow<In,Out,Mat>
completionTimeout(scala.concurrent.duration.FiniteDuration timeout)
Deprecated.Use the overloaded one which accepts java.time.Duration instead.<M> SubFlow<In,Out,Mat>
concat(Graph<SourceShape<Out>,M> that)
SubFlow<In,Out,Mat>
concatAllLazy(Graph<SourceShape<Out>,?>... those)
SubFlow<In,Out,Mat>
concatAllLazy(scala.collection.immutable.Seq<Graph<SourceShape<Out>,?>> those)
<M> SubFlow<In,Out,Mat>
concatLazy(Graph<SourceShape<Out>,M> that)
Flow<In,Out,Mat>
concatSubstreams()
Flatten the sub-flows back into the super-flow by concatenating them.SubFlow<In,Out,Mat>
conflate(Function2<Out,Out,Out> aggregate)
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.<S> SubFlow<In,S,Mat>
conflateWithSeed(Function<Out,S> seed, Function2<S,Out,S> aggregate)
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.SubFlow<In,Out,Mat>
delay(java.time.Duration of, DelayOverflowStrategy strategy)
Shifts elements emission in time by a specified amount.SubFlow<In,Out,Mat>
delay(scala.concurrent.duration.FiniteDuration of, DelayOverflowStrategy strategy)
Deprecated.Use the overloaded one which accepts java.time.Duration instead.SubFlow<In,Out,Mat>
delayWith(java.util.function.Supplier<DelayStrategy<Out>> delayStrategySupplier, DelayOverflowStrategy overFlowStrategy)
Shifts elements emission in time by an amount individually determined through delay strategy a specified amount.SubFlow<In,Out,Mat>
detach()
Detaches upstream demand from downstream demand without detaching the stream rates; in other words acts like a buffer of size 1.SubFlow<In,Out,Mat>
divertTo(Graph<SinkShape<Out>,?> that, Predicate<Out> when)
SubFlow<In,Out,Mat>
drop(long n)
Discard the given number of elements at the beginning of the stream.SubFlow<In,Out,Mat>
dropWhile(Predicate<Out> p)
Discard elements at the beginning of the stream while predicate is true.SubFlow<In,Out,Mat>
dropWithin(java.time.Duration duration)
Discard the elements received within the given duration at beginning of the stream.SubFlow<In,Out,Mat>
dropWithin(scala.concurrent.duration.FiniteDuration duration)
Deprecated.Use the overloaded one which accepts java.time.Duration instead.<U> SubFlow<In,U,Mat>
expand(Function<Out,java.util.Iterator<U>> expander)
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.SubFlow<In,Out,Mat>
extrapolate(Function<Out,java.util.Iterator<Out>> extrapolator)
Allows a faster downstream to progress independent of a slower upstream.SubFlow<In,Out,Mat>
extrapolate(Function<Out,java.util.Iterator<Out>> extrapolator, Out initial)
Allows a faster downstream to progress independent of a slower upstream.SubFlow<In,Out,Mat>
filter(Predicate<Out> p)
Only pass on those elements that satisfy the given predicate.SubFlow<In,Out,Mat>
filterNot(Predicate<Out> p)
Only pass on those elements that NOT satisfy the given predicate.<T,M>
SubFlow<In,T,Mat>flatMapConcat(Function<Out,? extends Graph<SourceShape<T>,M>> f)
Transform each input element into aSource
of output elements that is then flattened into the output stream by concatenation, fully consuming one Source after the other.<T,M>
SubFlow<In,T,Mat>flatMapMerge(int breadth, Function<Out,? extends Graph<SourceShape<T>,M>> f)
Transform each input element into aSource
of output elements that is then flattened into the output stream by merging, where at mostbreadth
substreams are being consumed at any given time.<Out2,Mat2>
SubFlow<In,Out2,Mat>flatMapPrefix(int n, Function<java.lang.Iterable<Out>,Flow<Out,Out2,Mat2>> f)
Takes up ton
elements from the stream (less thann
only if the upstream completes before emittingn
elements), then applyf
on these elements in order to obtain a flow, this flow is then materialized and the rest of the input is processed by this flow (similar to via).<T> SubFlow<In,T,Mat>
fold(T zero, Function2<T,Out,T> f)
Similar toscan
but only emits its result when the upstream completes, after which it also completes.<T> SubFlow<In,T,Mat>
foldAsync(T zero, Function2<T,Out,java.util.concurrent.CompletionStage<T>> f)
Similar tofold
but with an asynchronous function.SubFlow<In,java.util.List<Out>,Mat>
grouped(int n)
Chunk up this stream into groups of the given size, with the last group possibly smaller than requested due to end-of-stream.SubFlow<In,java.util.List<Out>,Mat>
groupedWeighted(long minWeight, Function<Out,java.lang.Long> costFn)
Chunk up this stream into groups of elements that have a cumulative weight greater than or equal to theminWeight
, with the last group possibly smaller than requestedminWeight
due to end-of-stream.SubFlow<In,java.util.List<Out>,Mat>
groupedWeightedWithin(long maxWeight, int maxNumber, Function<Out,java.lang.Long> costFn, java.time.Duration duration)
Chunk up this stream into groups of elements received within a time window, or limited by the weight and number of the elements, whatever happens first.SubFlow<In,java.util.List<Out>,Mat>
groupedWeightedWithin(long maxWeight, Function<Out,java.lang.Long> costFn, java.time.Duration duration)
Chunk up this stream into groups of elements received within a time window, or limited by the weight of the elements, whatever happens first.SubFlow<In,java.util.List<Out>,Mat>
groupedWeightedWithin(long maxWeight, Function<Out,java.lang.Long> costFn, scala.concurrent.duration.FiniteDuration duration)
Deprecated.Use the overloaded one which accepts java.time.Duration instead.SubFlow<In,java.util.List<Out>,Mat>
groupedWithin(int maxNumber, java.time.Duration duration)
Chunk up this stream into groups of elements received within a time window, or limited by the given number of elements, whatever happens first.SubFlow<In,java.util.List<Out>,Mat>
groupedWithin(int maxNumber, scala.concurrent.duration.FiniteDuration duration)
Deprecated.Use the overloaded one which accepts java.time.Duration instead.SubFlow<In,Out,Mat>
idleTimeout(java.time.Duration timeout)
If the time between two processed elements exceeds the provided timeout, the stream is failed with aStreamIdleTimeoutException
.SubFlow<In,Out,Mat>
idleTimeout(scala.concurrent.duration.FiniteDuration timeout)
Deprecated.Use the overloaded one which accepts java.time.Duration instead.SubFlow<In,Out,Mat>
initialDelay(java.time.Duration delay)
Delays the initial element by the specified duration.SubFlow<In,Out,Mat>
initialDelay(scala.concurrent.duration.FiniteDuration delay)
Deprecated.Use the overloaded one which accepts java.time.Duration instead.SubFlow<In,Out,Mat>
initialTimeout(java.time.Duration timeout)
If the first element has not passed through this operator before the provided timeout, the stream is failed with aInitialTimeoutException
.SubFlow<In,Out,Mat>
initialTimeout(scala.concurrent.duration.FiniteDuration timeout)
Deprecated.Use the overloaded one which accepts java.time.Duration instead.SubFlow<In,Out,Mat>
interleave(Graph<SourceShape<Out>,?> that, int segmentSize)
SubFlow<In,Out,Mat>
interleaveAll(java.util.List<? extends Graph<SourceShape<Out>,?>> those, int segmentSize, boolean eagerClose)
SubFlow<In,Out,Mat>
intersperse(Out inject)
Intersperses stream with provided element, similar to howscala.collection.immutable.List.mkString
injects a separator between a List's elements.SubFlow<In,Out,Mat>
intersperse(Out start, Out inject, Out end)
Intersperses stream with provided element, similar to howscala.collection.immutable.List.mkString
injects a separator between a List's elements.SubFlow<In,Out,Mat>
keepAlive(java.time.Duration maxIdle, Creator<Out> injectedElem)
Injects additional elements if upstream does not emit for a configured amount of time.SubFlow<In,Out,Mat>
keepAlive(scala.concurrent.duration.FiniteDuration maxIdle, Creator<Out> injectedElem)
Deprecated.Use the overloaded one which accepts java.time.Duration instead.SubFlow<In,Out,Mat>
limit(long n)
Ensure stream boundedness by limiting the number of elements from upstream.SubFlow<In,Out,Mat>
limitWeighted(long n, Function<Out,java.lang.Long> costFn)
Ensure stream boundedness by evaluating the cost of incoming elements using a cost function.SubFlow<In,Out,Mat>
log(java.lang.String name)
Logs elements flowing through the stream as well as completion and erroring.SubFlow<In,Out,Mat>
log(java.lang.String name, LoggingAdapter log)
Logs elements flowing through the stream as well as completion and erroring.SubFlow<In,Out,Mat>
log(java.lang.String name, Function<Out,java.lang.Object> extract)
Logs elements flowing through the stream as well as completion and erroring.SubFlow<In,Out,Mat>
log(java.lang.String name, Function<Out,java.lang.Object> extract, LoggingAdapter log)
Logs elements flowing through the stream as well as completion and erroring.SubFlow<In,Out,Mat>
logWithMarker(java.lang.String name, Function<Out,LogMarker> marker)
Logs elements flowing through the stream as well as completion and erroring.SubFlow<In,Out,Mat>
logWithMarker(java.lang.String name, Function<Out,LogMarker> marker, MarkerLoggingAdapter log)
Logs elements flowing through the stream as well as completion and erroring.SubFlow<In,Out,Mat>
logWithMarker(java.lang.String name, Function<Out,LogMarker> marker, Function<Out,java.lang.Object> extract)
Logs elements flowing through the stream as well as completion and erroring.SubFlow<In,Out,Mat>
logWithMarker(java.lang.String name, Function<Out,LogMarker> marker, Function<Out,java.lang.Object> extract, MarkerLoggingAdapter log)
Logs elements flowing through the stream as well as completion and erroring.<T> SubFlow<In,T,Mat>
map(Function<Out,T> f)
Transform this stream by applying the given function to each of the elements as they pass through this processing step.<T> SubFlow<In,T,Mat>
mapAsync(int parallelism, Function<Out,java.util.concurrent.CompletionStage<T>> f)
Transform this stream by applying the given function to each of the elements as they pass through this processing step.<T> SubFlow<In,T,Mat>
mapAsyncUnordered(int parallelism, Function<Out,java.util.concurrent.CompletionStage<T>> f)
Transform this stream by applying the given function to each of the elements as they pass through this processing step.<T> SubFlow<In,T,Mat>
mapConcat(Function<Out,java.lang.Iterable<T>> f)
Transform each input element into anIterable
of output elements that is then flattened into the output stream.<E extends java.lang.Throwable>
SubFlow<In,Out,Mat>mapError(java.lang.Class<E> clazz, Function<E,java.lang.Throwable> f)
While similar torecover(scala.PartialFunction<java.lang.Throwable,Out>)
this operator can be used to transform an error signal to a different one *without* logging it as an error in the process.SubFlow<In,Out,Mat>
mapError(scala.PartialFunction<java.lang.Throwable,java.lang.Throwable> pf)
While similar torecover(scala.PartialFunction<java.lang.Throwable,Out>)
this operator can be used to transform an error signal to a different one *without* logging it as an error in the process.<R,T>
SubFlow<In,T,Mat>mapWithResource(java.util.function.Supplier<R> create, java.util.function.BiFunction<R,Out,T> f, java.util.function.Function<R,java.util.Optional<T>> close)
Transform each stream element with the help of a resource.SubFlow<In,Out,Mat>
merge(Graph<SourceShape<Out>,?> that)
SubFlow<In,Out,Mat>
mergeAll(java.util.List<? extends Graph<SourceShape<Out>,?>> those, boolean eagerComplete)
<M> SubFlow<In,java.util.List<Out>,Mat>
mergeLatest(Graph<SourceShape<Out>,M> that, boolean eagerComplete)
MergeLatest joins elements from N input streams into stream of lists of size N.<M> SubFlow<In,Out,Mat>
mergePreferred(Graph<SourceShape<Out>,M> that, boolean preferred, boolean eagerComplete)
Merge two sources.<M> SubFlow<In,Out,Mat>
mergePrioritized(Graph<SourceShape<Out>,M> that, int leftPriority, int rightPriority, boolean eagerComplete)
Merge two sources.<M> SubFlow<In,Out,Mat>
mergeSorted(Graph<SourceShape<Out>,M> that, java.util.Comparator<Out> comp)
Flow<In,Out,Mat>
mergeSubstreams()
Flatten the sub-flows back into the super-flow by performing a merge without parallelism limit (i.e.Flow<In,Out,Mat>
mergeSubstreamsWithParallelism(int parallelism)
Flatten the sub-flows back into the super-flow by performing a merge with the given parallelism limit.SubFlow<In,Out,Mat>
named(java.lang.String name)
Add aname
attribute to this Flow.
<M> SubFlow<In,Out,Mat>
orElse(Graph<SourceShape<Out>,M> secondary)
Provides a secondary source that will be consumed if this source completes without any elements passing by.SubFlow<In,Pair<java.util.List<Out>,Source<Out,NotUsed>>,Mat>
prefixAndTail(int n)
Takes up ton
elements from the stream (less thann
only if the upstream completes before emittingn
elements) and returns a pair containing a strict sequence of the taken element and a stream representing the remaining elements.<M> SubFlow<In,Out,Mat>
prepend(Graph<SourceShape<Out>,M> that)
<M> SubFlow<In,Out,Mat>
prependLazy(Graph<SourceShape<Out>,M> that)
SubFlow<In,Out,Mat>
recover(scala.PartialFunction<java.lang.Throwable,Out> pf)
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.SubFlow<In,Out,Mat>
recoverWith(scala.PartialFunction<java.lang.Throwable,Graph<SourceShape<Out>,NotUsed>> pf)
Deprecated.Use recoverWithRetries instead.SubFlow<In,Out,Mat>
recoverWithRetries(int attempts, scala.PartialFunction<java.lang.Throwable,Graph<SourceShape<Out>,NotUsed>> pf)
RecoverWithRetries allows to switch to alternative Source on flow failure.SubFlow<In,Out,Mat>
reduce(Function2<Out,Out,Out> f)
Similar tofold
but uses first element as zero element.<T> SubFlow<In,T,Mat>
scan(T zero, Function2<T,Out,T> f)
Similar tofold
but is not a terminal operation, emits its current value which starts atzero
and then applies the current and next value to the given functionf
, emitting the next current value.<T> SubFlow<In,T,Mat>
scanAsync(T zero, Function2<T,Out,java.util.concurrent.CompletionStage<T>> f)
Similar toscan
but with a asynchronous function, emits its current value which starts atzero
and then applies the current and next value to the given functionf
, emitting aFuture
that resolves to the next current value.SubFlow<In,java.util.List<Out>,Mat>
sliding(int n, int step)
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.int
sliding$default$2()
<S,T>
SubFlow<In,T,Mat>statefulMap(Creator<S> create, Function2<S,Out,Pair<S,T>> f, Function<S,java.util.Optional<T>> onComplete)
Transform each stream element with the help of a state.<T> SubFlow<In,T,Mat>
statefulMapConcat(Creator<Function<Out,java.lang.Iterable<T>>> f)
Transform each input element into anIterable
of output elements that is then flattened into the output stream.SubFlow<In,Out,Mat>
take(long n)
Terminate processing (and cancel the upstream publisher) after the given number of elements.SubFlow<In,Out,Mat>
takeWhile(Predicate<Out> p)
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.SubFlow<In,Out,Mat>
takeWhile(Predicate<Out> p, boolean inclusive)
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.SubFlow<In,Out,Mat>
takeWithin(java.time.Duration duration)
Terminate processing (and cancel the upstream publisher) after the given duration.SubFlow<In,Out,Mat>
takeWithin(scala.concurrent.duration.FiniteDuration duration)
Deprecated.Use the overloaded one which accepts java.time.Duration instead.SubFlow<In,Out,Mat>
throttle(int elements, java.time.Duration per)
Sends elements downstream with speed limited toelements/per
.SubFlow<In,Out,Mat>
throttle(int cost, java.time.Duration per, int maximumBurst, Function<Out,java.lang.Integer> costCalculation, ThrottleMode mode)
Sends elements downstream with speed limited tocost/per
.SubFlow<In,Out,Mat>
throttle(int elements, java.time.Duration per, int maximumBurst, ThrottleMode mode)
Sends elements downstream with speed limited toelements/per
.SubFlow<In,Out,Mat>
throttle(int cost, java.time.Duration per, Function<Out,java.lang.Integer> costCalculation)
Sends elements downstream with speed limited tocost/per
.SubFlow<In,Out,Mat>
throttle(int cost, scala.concurrent.duration.FiniteDuration per, int maximumBurst, Function<Out,java.lang.Integer> costCalculation, ThrottleMode mode)
Deprecated.Use the overloaded one which accepts java.time.Duration instead.SubFlow<In,Out,Mat>
throttle(int elements, scala.concurrent.duration.FiniteDuration per, int maximumBurst, ThrottleMode mode)
Deprecated.Use the overloaded one which accepts java.time.Duration instead.SubFlow<In,Out,Mat>
throttleEven(int cost, java.time.Duration per, Function<Out,java.lang.Integer> costCalculation, ThrottleMode mode)
Deprecated.Use throttle without `maximumBurst` parameter instead.SubFlow<In,Out,Mat>
throttleEven(int elements, java.time.Duration per, ThrottleMode mode)
Deprecated.Use throttle without `maximumBurst` parameter instead.SubFlow<In,Out,Mat>
throttleEven(int cost, scala.concurrent.duration.FiniteDuration per, Function<Out,java.lang.Integer> costCalculation, ThrottleMode mode)
Deprecated.Use throttle without `maximumBurst` parameter instead.SubFlow<In,Out,Mat>
throttleEven(int elements, scala.concurrent.duration.FiniteDuration per, ThrottleMode mode)
Deprecated.Use throttle without `maximumBurst` parameter instead.Sink<In,Mat>
to(Graph<SinkShape<Out>,?> sink)
static <In,SuperOut,Out extends SuperOut,M>
SubFlow<In,SuperOut,M>upcast(SubFlow<In,Out,M> flow)
Upcast a stream of elements to a stream of supertypes of that element.<T,M>
SubFlow<In,T,Mat>via(Graph<FlowShape<Out,T>,M> flow)
Transform thisFlow
by appending the given processing steps.SubFlow<In,Out,Mat>
wireTap(Procedure<Out> f)
This is a simplified version ofwireTap(Sink)
that takes only a simple procedure.SubFlow<In,Out,Mat>
wireTap(Graph<SinkShape<Out>,?> that)
SubFlow<In,Out,Mat>
withAttributes(Attributes attr)
Change the attributes of thisSource
to the given ones and seal the list of attributes.<T> SubFlow<In,Pair<Out,T>,Mat>
zip(Graph<SourceShape<T>,?> source)
<U,A>
SubFlow<In,Pair<A,U>,Mat>zipAll(Graph<SourceShape<U>,?> that, A thisElem, U thatElem)
Combine the elements of current flow and the givenSource
into a stream of tuples.<T> SubFlow<In,Pair<Out,T>,Mat>
zipLatest(Graph<SourceShape<T>,?> source)
<Out2,Out3>
SubFlow<In,Out3,Mat>zipLatestWith(Graph<SourceShape<Out2>,?> that, Function2<Out,Out2,Out3> combine)
<Out2,Out3>
SubFlow<In,Out3,Mat>zipWith(Graph<SourceShape<Out2>,?> that, Function2<Out,Out2,Out3> combine)
SubFlow<In,Pair<Out,java.lang.Long>,Mat>
zipWithIndex()
Combine the elements of currentFlow
into a stream of tuples consisting of all elements paired with their index.
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Method Detail
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upcast
public static <In,SuperOut,Out extends SuperOut,M> SubFlow<In,SuperOut,M> upcast(SubFlow<In,Out,M> flow)
Upcast a stream of elements to a stream of supertypes of that element. Useful in combination with fan-in operators where you do not want to pay the cost of casting each element in amap
.- Returns:
- A flow that accepts
In
and outputs elements of the super type
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concatAllLazy
public SubFlow<In,Out,Mat> concatAllLazy(Graph<SourceShape<Out>,?>... those)
Concatenate the givenSource
s to thisFlow
, 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
s are materialized together with this Flow. Iflazy
materialization is what is needed the operator can be combined with for exampleSource.lazySource
to defer materialization ofthat
until the time when this source completes.The second source is then kept from producing elements by asserting back-pressure until its time comes.
For a concat operator that is detached, use
concat(akka.stream.Graph<akka.stream.SourceShape<Out>, M>)
If this
Flow
gets upstream error - no elements from the givenSource
s will be pulled.'''Emits when''' element is available from current stream or from the given
Source
s when current is completed'''Backpressures when''' downstream backpressures
'''Completes when''' given all those
Source
s completes'''Cancels when''' downstream cancels
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alsoToAll
public SubFlow<In,Out,Mat> alsoToAll(Graph<SinkShape<Out>,?>... those)
Attaches the givenSink
s to thisFlow
, meaning that elements that passes through will also be sent to all thoseSink
s.It is similar to
wireTap(akka.japi.function.Procedure<Out>)
but will backpressure instead of dropping elements when the givenSink
s is not ready.'''Emits when''' element is available and demand exists both from the Sinks and the downstream.
'''Backpressures when''' downstream or any of the
Sink
s backpressures'''Completes when''' upstream completes
'''Cancels when''' downstream or any of the
Sink
s cancels
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asScala
public SubFlow<Out,Mat,Flow<In,java.lang.Object,Mat>,Sink<In,Mat>> asScala()
Converts this Flow to its Scala DSL counterpart
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mergeSubstreams
public Flow<In,Out,Mat> mergeSubstreams()
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)
.
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mergeSubstreamsWithParallelism
public Flow<In,Out,Mat> mergeSubstreamsWithParallelism(int parallelism)
Flatten the sub-flows back into the super-flow by performing a merge with the given parallelism limit. This means that only up toparallelism
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.
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concatSubstreams
public Flow<In,Out,Mat> concatSubstreams()
Flatten the sub-flows back into the super-flow by concatenating them. This is usually a bad idea when combined withgroupBy
since it can easily lead to deadlock—the concatenation does not consume from the second substream until the first has finished and thegroupBy
operator will get back-pressure from the second stream.This is identical in effect to
mergeSubstreamsWithParallelism(1)
.
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via
public <T,M> SubFlow<In,T,Mat> via(Graph<FlowShape<Out,T>,M> flow)
Transform thisFlow
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), useviaMat
if a different strategy is needed.
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to
public Sink<In,Mat> to(Graph<SinkShape<Out>,?> sink)
Connect thisSubFlow
to aSink
, 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 exampleasync
will not have any effect as the returned graph is the entire, closed graph.
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map
public <T> SubFlow<In,T,Mat> map(Function<Out,T> f)
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
-
wireTap
public SubFlow<In,Out,Mat> wireTap(Procedure<Out> f)
This is a simplified version ofwireTap(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(akka.stream.Graph<akka.stream.SinkShape<Out>, ?>)
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(java.lang.String,akka.japi.function.Function<Out,java.lang.Object>,akka.event.LoggingAdapter)
operator instead, along with appropriateActorAttributes.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
-
mapConcat
public <T> SubFlow<In,T,Mat> mapConcat(Function<Out,java.lang.Iterable<T>> f)
Transform each input element into anIterable
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 withConcurrentModificationException
or other more subtle errors may occur.The returned
Iterable
MUST NOT containnull
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
-
statefulMap
public <S,T> SubFlow<In,T,Mat> statefulMap(Creator<S> create, Function2<S,Out,Pair<S,T>> f, Function<S,java.util.Optional<T>> onComplete)
Transform each stream element with the help of a state.The state creation function is invoked once when the stream is materialized and the returned state is passed to the mapping function for mapping the first element. The mapping function returns a mapped element to emit downstream and a state to pass to the next mapping function. The state can be the same for each mapping return, be a new immutable state but it is also safe to use a mutable state. The returned
T
MUST NOT benull
as it is illegal as stream element - according to the Reactive Streams specification. Anull
state is not allowed and will fail the stream.For stateless variant see
<T>map(akka.japi.function.Function<Out,T>)
.The
onComplete
function is called only once when the upstream or downstream finished, You can do some clean-up here, and if the returned value is not empty, it will be emitted to the downstream if available, otherwise the value will be dropped.Adheres to the
ActorAttributes.SupervisionStrategy
attribute.'''Emits when''' the mapping function returns an element and downstream is ready to consume it
'''Backpressures when''' downstream backpressures
'''Completes when''' upstream completes
'''Cancels when''' downstream cancels
- Parameters:
create
- a function that creates the initial statef
- a function that transforms the upstream element and the state into a pair of next state and output elementonComplete
- a function that transforms the ongoing state into an optional output element
-
mapWithResource
public <R,T> SubFlow<In,T,Mat> mapWithResource(java.util.function.Supplier<R> create, java.util.function.BiFunction<R,Out,T> f, java.util.function.Function<R,java.util.Optional<T>> close)
Transform each stream element with the help of a resource.The resource creation function is invoked once when the stream is materialized and the returned resource is passed to the mapping function for mapping the first element. The mapping function returns a mapped element to emit downstream. The returned
T
MUST NOT benull
as it is illegal as stream element - according to the Reactive Streams specification.The
close
function is called only once when the upstream or downstream finishes or fails. You can do some clean-up here, and if the returned value is not empty, it will be emitted to the downstream if available, otherwise the value will be dropped.Early completion can be done with combination of the
takeWhile(akka.japi.function.Predicate<Out>)
operator.Adheres to the
ActorAttributes.SupervisionStrategy
attribute.You can configure the default dispatcher for this Source by changing the
akka.stream.materializer.blocking-io-dispatcher
or set it for a given Source by usingActorAttributes
.'''Emits when''' the mapping function returns an element and downstream is ready to consume it
'''Backpressures when''' downstream backpressures
'''Completes when''' upstream completes
'''Cancels when''' downstream cancels
- Parameters:
create
- function that creates the resourcef
- function that transforms the upstream element and the resource to output elementclose
- function that closes the resource, optionally outputting a last element
-
statefulMapConcat
public <T> SubFlow<In,T,Mat> statefulMapConcat(Creator<Function<Out,java.lang.Iterable<T>>> f)
Transform each input element into anIterable
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 seemapConcat(akka.japi.function.Function<Out, java.lang.Iterable<T>>)
.Make sure that the
Iterable
is immutable or at least not modified after being used as an output sequence. Otherwise the stream may fail withConcurrentModificationException
or other more subtle errors may occur.The returned
Iterable
MUST NOT containnull
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
-
mapAsync
public <T> SubFlow<In,T,Mat> mapAsync(int parallelism, Function<Out,java.util.concurrent.CompletionStage<T>> f)
Transform this stream by applying the given function to each of the elements as they pass through this processing step. The function returns aCompletionStage
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 tomapAsync
. 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 theCompletionStage
is completed with failure and the supervision decision isSupervision.stop()
the stream will be completed with failure.If the function
f
throws an exception or if theCompletionStage
is completed with failure and the supervision decision isSupervision.resume()
orSupervision.restart()
the element is dropped and the stream continues.If the
CompletionStage
is completed withnull
, it is ignored and the next element is processed.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
-
mapAsyncUnordered
public <T> SubFlow<In,T,Mat> mapAsyncUnordered(int parallelism, Function<Out,java.util.concurrent.CompletionStage<T>> f)
Transform this stream by applying the given function to each of the elements as they pass through this processing step. The function returns aCompletionStage
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 tomapAsyncUnordered
. 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 theCompletionStage
is completed with failure and the supervision decision isSupervision.stop()
the stream will be completed with failure.If the function
f
throws an exception or if theCompletionStage
is completed with failure and the supervision decision isSupervision.resume()
orSupervision.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 byf
might be emitted in a different order).If the
CompletionStage
is completed withnull
, it is ignored and the next element is processed.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
-
filter
public SubFlow<In,Out,Mat> filter(Predicate<Out> p)
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
-
filterNot
public SubFlow<In,Out,Mat> filterNot(Predicate<Out> p)
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
-
collect
public <T> SubFlow<In,T,Mat> collect(scala.PartialFunction<Out,T> pf)
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
-
collectType
public <T> SubFlow<In,T,Mat> collectType(java.lang.Class<T> clazz)
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
-
grouped
public SubFlow<In,java.util.List<Out>,Mat> grouped(int n)
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
-
groupedWeighted
public SubFlow<In,java.util.List<Out>,Mat> groupedWeighted(long minWeight, Function<Out,java.lang.Long> costFn)
Chunk up this stream into groups of elements that have a cumulative weight greater than or equal to theminWeight
, with the last group possibly smaller than requestedminWeight
due to end-of-stream.minWeight
must be positive, otherwise IllegalArgumentException is thrown.costFn
must return a non-negative result for all inputs, otherwise the stage will fail with an IllegalArgumentException.'''Emits when''' the cumulative weight of elements is greater than or equal to the
minWeight
or upstream completed'''Backpressures when''' a buffered group weighs more than
minWeight
and downstream backpressures'''Completes when''' upstream completes
'''Cancels when''' downstream cancels
-
limit
public SubFlow<In,Out,Mat> limit(long n)
Ensure stream boundedness by limiting the number of elements from upstream. If the number of incoming elements exceeds max, it will signal upstream failureStreamLimitException
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
-
limitWeighted
public SubFlow<In,Out,Mat> limitWeighted(long n, Function<Out,java.lang.Long> costFn)
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 failureStreamLimitException
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
-
sliding
public SubFlow<In,java.util.List<Out>,Mat> sliding(int n, int step)
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
-
sliding$default$2
public int sliding$default$2()
-
scan
public <T> SubFlow<In,T,Mat> scan(T zero, Function2<T,Out,T> f)
Similar tofold
but is not a terminal operation, emits its current value which starts atzero
and then applies the current and next value to the given functionf
, emitting the next current value.If the function
f
throws an exception and the supervision decision isSupervision.restart()
current value starts atzero
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
-
scanAsync
public <T> SubFlow<In,T,Mat> scanAsync(T zero, Function2<T,Out,java.util.concurrent.CompletionStage<T>> f)
Similar toscan
but with a asynchronous function, emits its current value which starts atzero
and then applies the current and next value to the given functionf
, emitting aFuture
that resolves to the next current value.If the function
f
throws an exception and the supervision decision isakka.stream.Supervision.Restart
current value starts atzero
again the stream will continue.If the function
f
throws an exception and the supervision decision isakka.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
-
fold
public <T> SubFlow<In,T,Mat> fold(T zero, Function2<T,Out,T> f)
Similar toscan
but only emits its result when the upstream completes, after which it also completes. Applies the given functionf
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 isSupervision.restart()
current value starts atzero
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
-
foldAsync
public <T> SubFlow<In,T,Mat> foldAsync(T zero, Function2<T,Out,java.util.concurrent.CompletionStage<T>> f)
Similar tofold
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 isakka.stream.Supervision.Restart
current value starts atzero
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
-
reduce
public SubFlow<In,Out,Mat> reduce(Function2<Out,Out,Out> f)
Similar tofold
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
-
intersperse
public SubFlow<In,Out,Mat> intersperse(Out start, Out inject, Out end)
Intersperses stream with provided element, similar to howscala.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 (SeeSource.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
-
intersperse
public SubFlow<In,Out,Mat> intersperse(Out inject)
Intersperses stream with provided element, similar to howscala.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
-
groupedWithin
public SubFlow<In,java.util.List<Out>,Mat> groupedWithin(int maxNumber, scala.concurrent.duration.FiniteDuration duration)
Deprecated.Use the overloaded one which accepts java.time.Duration instead. Since 2.5.12.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
maxNumber
must be positive, andduration
must be greater than 0 seconds, otherwise IllegalArgumentException is thrown.
-
groupedWithin
public SubFlow<In,java.util.List<Out>,Mat> groupedWithin(int maxNumber, java.time.Duration duration)
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
maxNumber
must be positive, andduration
must be greater than 0 seconds, otherwise IllegalArgumentException is thrown.
-
groupedWeightedWithin
public SubFlow<In,java.util.List<Out>,Mat> groupedWeightedWithin(long maxWeight, Function<Out,java.lang.Long> costFn, scala.concurrent.duration.FiniteDuration duration)
Deprecated.Use the overloaded one which accepts java.time.Duration instead. Since 2.5.12.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, andduration
must be greater than 0 seconds, otherwise IllegalArgumentException is thrown.
-
groupedWeightedWithin
public SubFlow<In,java.util.List<Out>,Mat> groupedWeightedWithin(long maxWeight, Function<Out,java.lang.Long> costFn, java.time.Duration duration)
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, andduration
must be greater than 0 seconds, otherwise IllegalArgumentException is thrown.
-
groupedWeightedWithin
public SubFlow<In,java.util.List<Out>,Mat> groupedWeightedWithin(long maxWeight, int maxNumber, Function<Out,java.lang.Long> costFn, java.time.Duration duration)
Chunk up this stream into groups of elements received within a time window, or limited by the weight and number 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
or has more thanmaxNumber
elements'''Completes when''' upstream completes (emits last group)
'''Cancels when''' downstream completes
maxWeight
must be positive,maxNumber
must be positive, andduration
must be greater than 0 seconds, otherwise IllegalArgumentException is thrown.
-
delay
public SubFlow<In,Out,Mat> delay(scala.concurrent.duration.FiniteDuration of, DelayOverflowStrategy strategy)
Deprecated.Use the overloaded one which accepts java.time.Duration instead. Since 2.5.12.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 definedDelayOverflowStrategy
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
- Parameters:
of
- time to shift all messagesstrategy
- Strategy that is used when incoming elements cannot fit inside the buffer
-
delay
public SubFlow<In,Out,Mat> delay(java.time.Duration of, DelayOverflowStrategy strategy)
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 definedDelayOverflowStrategy
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
- Parameters:
of
- time to shift all messagesstrategy
- Strategy that is used when incoming elements cannot fit inside the buffer
-
delayWith
public SubFlow<In,Out,Mat> delayWith(java.util.function.Supplier<DelayStrategy<Out>> delayStrategySupplier, DelayOverflowStrategy overFlowStrategy)
Shifts elements emission in time by an amount individually determined through delay strategy a specified amount. It allows to store elements in internal buffer while waiting for next element to be emitted. Depending on the definedDelayOverflowStrategy
it might drop elements or backpressure the upstream if there is no space available in the buffer.It determines delay for each ongoing element invoking
DelayStrategy.nextDelay(elem: T): FiniteDuration
.Note that elements are not re-ordered: if an element is given a delay much shorter than its predecessor, it will still have to wait for the preceding element before being emitted. It is also important to notice that
DelayStrategy
can be stateful.Delay precision is 10ms to avoid unnecessary timer scheduling cycles.
Internal buffer has default capacity 16. You can set buffer size by calling
addAttributes(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 have been drained
'''Cancels when''' downstream cancels
- Parameters:
delayStrategySupplier
- creates newDelayStrategy
object for each materializationoverFlowStrategy
- Strategy that is used when incoming elements cannot fit inside the buffer
-
drop
public SubFlow<In,Out,Mat> drop(long n)
Discard the given number of elements at the beginning of the stream. No elements will be dropped ifn
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
-
dropWithin
public SubFlow<In,Out,Mat> dropWithin(scala.concurrent.duration.FiniteDuration duration)
Deprecated.Use the overloaded one which accepts java.time.Duration instead. Since 2.5.12.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
-
dropWithin
public SubFlow<In,Out,Mat> dropWithin(java.time.Duration duration)
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
-
takeWhile
public SubFlow<In,Out,Mat> takeWhile(Predicate<Out> p)
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
-
takeWhile
public SubFlow<In,Out,Mat> takeWhile(Predicate<Out> p, boolean inclusive)
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
-
dropWhile
public SubFlow<In,Out,Mat> dropWhile(Predicate<Out> p)
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
-
recover
public SubFlow<In,Out,Mat> recover(scala.PartialFunction<java.lang.Throwable,Out> pf)
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
-
recoverWith
public SubFlow<In,Out,Mat> recoverWith(scala.PartialFunction<java.lang.Throwable,Graph<SourceShape<Out>,NotUsed>> pf)
Deprecated.Use recoverWithRetries instead. Since 2.4.4.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 thepf
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
-
recoverWithRetries
public SubFlow<In,Out,Mat> recoverWithRetries(int attempts, scala.PartialFunction<java.lang.Throwable,Graph<SourceShape<Out>,NotUsed>> pf)
RecoverWithRetries allows to switch to alternative Source on flow failure. It will stay in effect after a failure has been recovered up toattempts
number of times so that each time there is a failure it is fed into thepf
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 asrecoverWith
.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
-
mapError
public SubFlow<In,Out,Mat> mapError(scala.PartialFunction<java.lang.Throwable,java.lang.Throwable> pf)
While similar torecover(scala.PartialFunction<java.lang.Throwable,Out>)
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 torecover(t => throw t2)
since recover would log thet2
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(scala.PartialFunction<java.lang.Throwable,Out>)
throwing an exception insidemapError
_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
-
mapError
public <E extends java.lang.Throwable> SubFlow<In,Out,Mat> mapError(java.lang.Class<E> clazz, Function<E,java.lang.Throwable> f)
While similar torecover(scala.PartialFunction<java.lang.Throwable,Out>)
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 torecover(t => throw t2)
since recover would log thet2
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(scala.PartialFunction<java.lang.Throwable,Out>)
throwing an exception insidemapError
_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
-
take
public SubFlow<In,Out,Mat> take(long n)
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
-
takeWithin
public SubFlow<In,Out,Mat> takeWithin(scala.concurrent.duration.FiniteDuration duration)
Deprecated.Use the overloaded one which accepts java.time.Duration instead. Since 2.5.12.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(long)
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
-
takeWithin
public SubFlow<In,Out,Mat> takeWithin(java.time.Duration 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(long)
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
-
conflateWithSeed
public <S> SubFlow<In,S,Mat> conflateWithSeed(Function<Out,S> seed, Function2<S,Out,S> aggregate)
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
- Parameters:
seed
- Provides the first state for a conflated value using the first unconsumed element as a startaggregate
- Takes the currently aggregated value and the current pending element to produce a new aggregate
-
conflate
public SubFlow<In,Out,Mat> conflate(Function2<Out,Out,Out> aggregate)
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
- Parameters:
aggregate
- Takes the currently aggregated value and the current pending element to produce a new aggregate
-
batch
public <S> SubFlow<In,S,Mat> batch(long max, Function<Out,S> seed, Function2<S,Out,S> aggregate)
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
- Parameters:
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 startaggregate
- Takes the currently batched value and the current pending element to produce a new aggregate
-
batchWeighted
public <S> SubFlow<In,S,Mat> batchWeighted(long max, Function<Out,java.lang.Long> costFn, Function<Out,S> seed, Function2<S,Out,S> aggregate)
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 concatenateByteString
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
- Parameters:
max
- maximum weight of elements to batch before backpressuring upstream (must be positive non-zero)costFn
- a function to compute a single element weightseed
- Provides the first state for a batched value using the first unconsumed element as a startaggregate
- Takes the currently batched value and the current pending element to produce a new batch
-
expand
public <U> SubFlow<In,U,Mat> expand(Function<Out,java.util.Iterator<U>> expander)
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
Supervision.restart()
andSupervision.resume()
. Exceptions from theexpander
function will complete the stream with failure.See also
extrapolate(akka.japi.function.Function<Out, java.util.Iterator<Out>>)
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
- Parameters:
expander
- Takes the current extrapolation state to produce an output element and the next extrapolation state.
-
extrapolate
public SubFlow<In,Out,Mat> extrapolate(Function<Out,java.util.Iterator<Out>> extrapolator)
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
Supervision.restart()
andSupervision.resume()
. Exceptions from theextrapolate
function will complete the stream with failure.See also
expand(akka.japi.function.Function<Out, java.util.Iterator<U>>)
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
- Parameters:
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(akka.japi.function.Function<Out, java.util.Iterator<U>>)
-
extrapolate
public SubFlow<In,Out,Mat> extrapolate(Function<Out,java.util.Iterator<Out>> extrapolator, Out initial)
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
Supervision.restart()
andSupervision.resume()
. Exceptions from theextrapolate
function will complete the stream with failure.See also
expand(akka.japi.function.Function<Out, java.util.Iterator<U>>)
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
- Parameters:
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(akka.japi.function.Function<Out, java.util.Iterator<U>>)
-
buffer
public SubFlow<In,Out,Mat> buffer(int size, OverflowStrategy overflowStrategy)
Adds a fixed size buffer in the flow that allows to store elements from a faster upstream until it becomes full. Depending on the definedOverflowStrategy
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
- Parameters:
size
- The size of the buffer in element countoverflowStrategy
- Strategy that is used when incoming elements cannot fit inside the buffer
-
prefixAndTail
public SubFlow<In,Pair<java.util.List<Out>,Source<Out,NotUsed>>,Mat> prefixAndTail(int n)
Takes up ton
elements from the stream (less thann
only if the upstream completes before emittingn
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
-
flatMapPrefix
public <Out2,Mat2> SubFlow<In,Out2,Mat> flatMapPrefix(int n, Function<java.lang.Iterable<Out>,Flow<Out,Out2,Mat2>> f)
Takes up ton
elements from the stream (less thann
only if the upstream completes before emittingn
elements), then applyf
on these elements in order to obtain a flow, this flow is then materialized and the rest of the input is processed by this flow (similar to via). This method returns a flow consuming the rest of the stream producing the materialized flow's output.'''Emits when''' the materialized flow emits. Notice the first
n
elements are buffered internally before materializing the flow and connecting it to the rest of the upstream - producing elements at its own discretion (might 'swallow' or multiply elements).'''Backpressures when''' downstream backpressures
'''Completes when''' the materialized flow completes. If upstream completes before producing
n
elements,f
will be applied with the provided elements, the resulting flow will be materialized and signalled for upstream completion, it can then complete or continue to emit elements at its own discretion.'''Cancels when''' the materialized flow cancels. Notice that when downstream cancels prior to prefix completion, the cancellation cause is stashed until prefix completion (or upstream completion) and then handed to the materialized flow.
- Parameters:
n
- the number of elements to accumulate before materializing the downstream flow.f
- a function that produces the downstream flow based on the upstream's prefix.
-
flatMapConcat
public <T,M> SubFlow<In,T,Mat> flatMapConcat(Function<Out,? extends Graph<SourceShape<T>,M>> f)
Transform each input element into aSource
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
-
flatMapMerge
public <T,M> SubFlow<In,T,Mat> flatMapMerge(int breadth, Function<Out,? extends Graph<SourceShape<T>,M>> f)
Transform each input element into aSource
of output elements that is then flattened into the output stream by merging, where at mostbreadth
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
-
concat
public <M> SubFlow<In,Out,Mat> concat(Graph<SourceShape<Out>,M> that)
Concatenate the givenSource
to thisFlow
, 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 is "detached" meaning it will in effect behave as a one element buffer in front of both the sources, that eagerly demands an element on start (so it can not be combined withSource.lazy
to defer materialization ofthat
).The second source is then kept from producing elements by asserting back-pressure until its time comes.
When needing a concat operator that is not detached use
concatLazy(akka.stream.Graph<akka.stream.SourceShape<Out>, M>)
'''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
-
concatLazy
public <M> SubFlow<In,Out,Mat> concatLazy(Graph<SourceShape<Out>,M> that)
Concatenate the givenSource
to thisFlow
, 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. Iflazy
materialization is what is needed the operator can be combined with for exampleSource.lazySource
to defer materialization ofthat
until the time when this source completes.The second source is then kept from producing elements by asserting back-pressure until its time comes.
For a concat operator that is detached, use
concat(akka.stream.Graph<akka.stream.SourceShape<Out>, M>)
If this
Flow
gets upstream error - no elements from the givenSource
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
-
concatAllLazy
public SubFlow<In,Out,Mat> concatAllLazy(scala.collection.immutable.Seq<Graph<SourceShape<Out>,?>> those)
Concatenate the givenSource
s to thisFlow
, 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
s are materialized together with this Flow. Iflazy
materialization is what is needed the operator can be combined with for exampleSource.lazySource
to defer materialization ofthat
until the time when this source completes.The second source is then kept from producing elements by asserting back-pressure until its time comes.
For a concat operator that is detached, use
concat(akka.stream.Graph<akka.stream.SourceShape<Out>, M>)
If this
Flow
gets upstream error - no elements from the givenSource
s will be pulled.'''Emits when''' element is available from current stream or from the given
Source
s when current is completed'''Backpressures when''' downstream backpressures
'''Completes when''' given all those
Source
s completes'''Cancels when''' downstream cancels
-
prepend
public <M> SubFlow<In,Out,Mat> prepend(Graph<SourceShape<Out>,M> that)
Prepend the givenSource
to thisFlow
, 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 the
Source
is materialized together with this Flow and is "detached" meaning in effect behave as a one element buffer in front of both the sources, that eagerly demands an element on start (so it can not be combined withSource.lazy
to defer materialization ofthat
).This flow will then be kept from producing elements by asserting back-pressure until its time comes.
When needing a prepend operator that is not detached use
prependLazy(akka.stream.Graph<akka.stream.SourceShape<Out>, M>)
'''Emits when''' element is available from the given
Source
or from current stream when theSource
is completed'''Backpressures when''' downstream backpressures
'''Completes when''' this
Flow
completes'''Cancels when''' downstream cancels
-
prependLazy
public <M> SubFlow<In,Out,Mat> prependLazy(Graph<SourceShape<Out>,M> that)
Prepend the givenSource
to thisFlow
, 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 the
Source
is materialized together with this Flow and will then be kept from producing elements by asserting back-pressure until its time comes.When needing a prepend operator that is also detached use
prepend(akka.stream.Graph<akka.stream.SourceShape<Out>, M>)
If the given
Source
gets upstream error - no elements from thisFlow
will be pulled.'''Emits when''' element is available from the given
Source
or from current stream when theSource
is completed'''Backpressures when''' downstream backpressures
'''Completes when''' this
Flow
completes'''Cancels when''' downstream cancels
-
orElse
public <M> SubFlow<In,Out,Mat> orElse(Graph<SourceShape<Out>,M> secondary)
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.
-
alsoTo
public SubFlow<In,Out,Mat> alsoTo(Graph<SinkShape<Out>,?> that)
Attaches the givenSink
to thisFlow
, meaning that elements that passes through will also be sent to theSink
.It is similar to
wireTap(akka.japi.function.Procedure<Out>)
but will backpressure instead of dropping elements when the givenSink
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
-
alsoToAll
public SubFlow<In,Out,Mat> alsoToAll(scala.collection.immutable.Seq<Graph<SinkShape<Out>,?>> those)
Attaches the givenSink
s to thisFlow
, meaning that elements that passes through will also be sent to all thoseSink
s.It is similar to
wireTap(akka.japi.function.Procedure<Out>)
but will backpressure instead of dropping elements when the givenSink
s is not ready.'''Emits when''' element is available and demand exists both from the Sinks and the downstream.
'''Backpressures when''' downstream or any of the
Sink
s backpressures'''Completes when''' upstream completes
'''Cancels when''' downstream or any of the
Sink
s cancels
-
divertTo
public SubFlow<In,Out,Mat> divertTo(Graph<SinkShape<Out>,?> that, Predicate<Out> when)
Attaches the givenSink
to thisFlow
, meaning that elements will be sent to theSink
instead of being passed through if the predicatewhen
returnstrue
.'''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
-
wireTap
public SubFlow<In,Out,Mat> wireTap(Graph<SinkShape<Out>,?> that)
Attaches the givenSink
to thisFlow
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(akka.stream.Graph<akka.stream.SinkShape<Out>, ?>)
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
-
merge
public SubFlow<In,Out,Mat> merge(Graph<SourceShape<Out>,?> that)
Merge the givenSource
to thisFlow
, 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
-
mergeAll
public SubFlow<In,Out,Mat> mergeAll(java.util.List<? extends Graph<SourceShape<Out>,?>> those, boolean eagerComplete)
Merge the givenSource
s to thisFlow
, 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 (eagerComplete=false) or one upstream completes (eagerComplete=true), default value is
false
'''Cancels when''' downstream cancels
-
interleave
public SubFlow<In,Out,Mat> interleave(Graph<SourceShape<Out>,?> that, int segmentSize)
Interleave is a deterministic merge of the givenSource
with elements of thisFlow
. It first emitssegmentSize
number of elements from this flow to downstream, then - same amount forthat
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 givenSource
completes'''Cancels when''' downstream cancels
-
interleaveAll
public SubFlow<In,Out,Mat> interleaveAll(java.util.List<? extends Graph<SourceShape<Out>,?>> those, int segmentSize, boolean eagerClose)
Interleave is a deterministic merge of the givenSource
s with elements of thisFlow
. It first emitssegmentSize
number of elements from this flow to downstream, then - same amount forthat
source, then repeat process.If eagerClose is false and one of the upstreams complete the elements from the other upstream will continue passing through the interleave operator. If eagerClose is true and one of the upstream complete interleave will cancel the other upstream and complete itself.
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 givenSource
completes'''Cancels when''' downstream cancels
-
mergeLatest
public <M> SubFlow<In,java.util.List<Out>,Mat> mergeLatest(Graph<SourceShape<Out>,M> that, boolean eagerComplete)
MergeLatest joins elements from N input streams into stream of lists of size N. i-th element in list is the latest emitted element from i-th input stream. MergeLatest emits list for each element emitted from some input stream, but only after each input stream emitted at least one element.'''Emits when''' an element is available from some input and each input emits at least one element from stream start
'''Completes when''' all upstreams complete (eagerClose=false) or one upstream completes (eagerClose=true)
-
mergePreferred
public <M> SubFlow<In,Out,Mat> mergePreferred(Graph<SourceShape<Out>,M> that, boolean preferred, boolean eagerComplete)
Merge two sources. Prefer one source if both sources have elements ready.'''emits''' when one of the inputs has an element available. If multiple have elements available, prefer the 'right' one when 'preferred' is 'true', or the 'left' one when 'preferred' is 'false'.
'''backpressures''' when downstream backpressures
'''completes''' when all upstreams complete (This behavior is changeable to completing when any upstream completes by setting
eagerComplete=true
.)
-
mergePrioritized
public <M> SubFlow<In,Out,Mat> mergePrioritized(Graph<SourceShape<Out>,M> that, int leftPriority, int rightPriority, boolean eagerComplete)
Merge two sources. Prefer the sources depending on the 'priority' parameters.'''emits''' when one of the inputs has an element available, preferring inputs based on the 'priority' parameters if both have elements available
'''backpressures''' when downstream backpressures
'''completes''' when both upstreams complete (This behavior is changeable to completing when any upstream completes by setting
eagerComplete=true
.)
-
mergeSorted
public <M> SubFlow<In,Out,Mat> mergeSorted(Graph<SourceShape<Out>,M> that, java.util.Comparator<Out> comp)
Merge the givenSource
to thisFlow
, 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
-
zipAll
public <U,A> SubFlow<In,Pair<A,U>,Mat> zipAll(Graph<SourceShape<U>,?> that, A thisElem, U thatElem)
Combine the elements of current flow and the givenSource
into a stream of tuples.'''Emits when''' at first emits when both inputs emit, and then as long as any input emits (coupled to the default value of the completed input).
'''Backpressures when''' downstream backpressures
'''Completes when''' all upstream completes
'''Cancels when''' downstream cancels
-
zipLatest
public <T> SubFlow<In,Pair<Out,T>,Mat> zipLatest(Graph<SourceShape<T>,?> source)
Combine the elements of currentFlow
and the givenSource
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
-
zipWith
public <Out2,Out3> SubFlow<In,Out3,Mat> zipWith(Graph<SourceShape<Out2>,?> that, Function2<Out,Out2,Out3> combine)
Put together the elements of currentFlow
and the givenSource
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
-
zipLatestWith
public <Out2,Out3> SubFlow<In,Out3,Mat> zipLatestWith(Graph<SourceShape<Out2>,?> that, Function2<Out,Out2,Out3> combine)
Put together the elements of currentFlow
and the givenSource
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
-
zipWithIndex
public SubFlow<In,Pair<Out,java.lang.Long>,Mat> zipWithIndex()
Combine the elements of currentFlow
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
-
initialTimeout
public SubFlow<In,Out,Mat> initialTimeout(scala.concurrent.duration.FiniteDuration timeout)
Deprecated.Use the overloaded one which accepts java.time.Duration instead. Since 2.5.12.If the first element has not passed through this operator before the provided timeout, the stream is failed with aInitialTimeoutException
.'''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
-
initialTimeout
public SubFlow<In,Out,Mat> initialTimeout(java.time.Duration timeout)
If the first element has not passed through this operator before the provided timeout, the stream is failed with aInitialTimeoutException
.'''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
-
completionTimeout
public SubFlow<In,Out,Mat> completionTimeout(scala.concurrent.duration.FiniteDuration timeout)
Deprecated.Use the overloaded one which accepts java.time.Duration instead. Since 2.5.12.If the completion of the stream does not happen until the provided timeout, the stream is failed with aCompletionTimeoutException
.'''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
-
completionTimeout
public SubFlow<In,Out,Mat> completionTimeout(java.time.Duration timeout)
If the completion of the stream does not happen until the provided timeout, the stream is failed with aCompletionTimeoutException
.'''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
-
idleTimeout
public SubFlow<In,Out,Mat> idleTimeout(scala.concurrent.duration.FiniteDuration timeout)
Deprecated.Use the overloaded one which accepts java.time.Duration instead. Since 2.5.12.If the time between two processed elements exceeds the provided timeout, the stream is failed with aStreamIdleTimeoutException
. 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
-
idleTimeout
public SubFlow<In,Out,Mat> idleTimeout(java.time.Duration timeout)
If the time between two processed elements exceeds the provided timeout, the stream is failed with aStreamIdleTimeoutException
. 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
-
backpressureTimeout
public SubFlow<In,Out,Mat> backpressureTimeout(scala.concurrent.duration.FiniteDuration timeout)
Deprecated.Use the overloaded one which accepts java.time.Duration instead. Since 2.5.12.If the time between the emission of an element and the following downstream demand exceeds the provided timeout, the stream is failed with aBackpressureTimeoutException
. 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
-
backpressureTimeout
public SubFlow<In,Out,Mat> backpressureTimeout(java.time.Duration timeout)
If the time between the emission of an element and the following downstream demand exceeds the provided timeout, the stream is failed with aBackpressureTimeoutException
. 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
-
keepAlive
public SubFlow<In,Out,Mat> keepAlive(scala.concurrent.duration.FiniteDuration maxIdle, Creator<Out> injectedElem)
Deprecated.Use the overloaded one which accepts java.time.Duration instead. Since 2.5.12.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
-
keepAlive
public SubFlow<In,Out,Mat> keepAlive(java.time.Duration maxIdle, Creator<Out> injectedElem)
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
-
throttle
public SubFlow<In,Out,Mat> throttle(int elements, java.time.Duration per)
Sends elements downstream with speed limited toelements/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 20The throttle
mode
isakka.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
-
throttle
public SubFlow<In,Out,Mat> throttle(int elements, scala.concurrent.duration.FiniteDuration per, int maximumBurst, ThrottleMode mode)
Deprecated.Use the overloaded one which accepts java.time.Duration instead. Since 2.5.12.Sends elements downstream with speed limited toelements/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: -akka.stream.ThrottleMode.Shaping
makes pauses before emitting messages to meet throttle rate -akka.stream.ThrottleMode.Enforcing
fails with exception when upstream is faster than throttle rateIt 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 overloadedthrottle
method withoutmaximumBurst
parameter to automatically calculate themaximumBurst
based on the given rate (cost/per
). In other words the throttler always enforces the rate limit whenmaximumBurst
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
-
throttle
public SubFlow<In,Out,Mat> throttle(int elements, java.time.Duration per, int maximumBurst, ThrottleMode mode)
Sends elements downstream with speed limited toelements/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: -akka.stream.ThrottleMode.Shaping
makes pauses before emitting messages to meet throttle rate -akka.stream.ThrottleMode.Enforcing
fails with exception when upstream is faster than throttle rateIt 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 overloadedthrottle
method withoutmaximumBurst
parameter to automatically calculate themaximumBurst
based on the given rate (cost/per
). In other words the throttler always enforces the rate limit whenmaximumBurst
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
-
throttle
public SubFlow<In,Out,Mat> throttle(int cost, java.time.Duration per, Function<Out,java.lang.Integer> costCalculation)
Sends elements downstream with speed limited tocost/per
. Cost is calculating for each element individually by callingcalculateCost
function. This operator works for streams when elements have different cost(length). Streams ofByteString
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 20The throttle
mode
isakka.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
-
throttle
public SubFlow<In,Out,Mat> throttle(int cost, scala.concurrent.duration.FiniteDuration per, int maximumBurst, Function<Out,java.lang.Integer> costCalculation, ThrottleMode mode)
Deprecated.Use the overloaded one which accepts java.time.Duration instead. Since 2.5.12.Sends elements downstream with speed limited tocost/per
. Cost is calculating for each element individually by callingcalculateCost
function. This operator works for streams when elements have different cost(length). Streams ofByteString
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: -akka.stream.ThrottleMode.Shaping
makes pauses before emitting messages to meet throttle rate -akka.stream.ThrottleMode.Enforcing
fails with exception when upstream is faster than throttle rate. Enforcing cannot emit elements that cost more than the maximumBurstIt 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 overloadedthrottle
method withoutmaximumBurst
parameter to automatically calculate themaximumBurst
based on the given rate (cost/per
). In other words the throttler always enforces the rate limit whenmaximumBurst
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
-
throttle
public SubFlow<In,Out,Mat> throttle(int cost, java.time.Duration per, int maximumBurst, Function<Out,java.lang.Integer> costCalculation, ThrottleMode mode)
Sends elements downstream with speed limited tocost/per
. Cost is calculating for each element individually by callingcalculateCost
function. This operator works for streams when elements have different cost(length). Streams ofByteString
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: -akka.stream.ThrottleMode.Shaping
makes pauses before emitting messages to meet throttle rate -akka.stream.ThrottleMode.Enforcing
fails with exception when upstream is faster than throttle rate. Enforcing cannot emit elements that cost more than the maximumBurstIt 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 overloadedthrottle
method withoutmaximumBurst
parameter to automatically calculate themaximumBurst
based on the given rate (cost/per
). In other words the throttler always enforces the rate limit whenmaximumBurst
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
-
throttleEven
public SubFlow<In,Out,Mat> throttleEven(int elements, scala.concurrent.duration.FiniteDuration per, ThrottleMode mode)
Deprecated.Use throttle without `maximumBurst` parameter instead. Since 2.5.12.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(int,java.time.Duration)
with maximumBurst attribute.- See Also:
throttle(int, java.time.Duration)
-
throttleEven
public SubFlow<In,Out,Mat> throttleEven(int elements, java.time.Duration per, ThrottleMode mode)
Deprecated.Use throttle without `maximumBurst` parameter instead. Since 2.5.12.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(int,java.time.Duration)
with maximumBurst attribute.- See Also:
throttle(int, java.time.Duration)
-
throttleEven
public SubFlow<In,Out,Mat> throttleEven(int cost, scala.concurrent.duration.FiniteDuration per, Function<Out,java.lang.Integer> costCalculation, ThrottleMode mode)
Deprecated.Use throttle without `maximumBurst` parameter instead. Since 2.5.12.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(int,java.time.Duration)
with maximumBurst attribute.- See Also:
throttle(int, java.time.Duration)
-
throttleEven
public SubFlow<In,Out,Mat> throttleEven(int cost, java.time.Duration per, Function<Out,java.lang.Integer> costCalculation, ThrottleMode mode)
Deprecated.Use throttle without `maximumBurst` parameter instead. Since 2.5.12.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(int,java.time.Duration)
with maximumBurst attribute.- See Also:
throttle(int, java.time.Duration)
-
detach
public SubFlow<In,Out,Mat> detach()
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
-
initialDelay
public SubFlow<In,Out,Mat> initialDelay(scala.concurrent.duration.FiniteDuration delay)
Deprecated.Use the overloaded one which accepts java.time.Duration instead. Since 2.5.12.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
-
initialDelay
public SubFlow<In,Out,Mat> initialDelay(java.time.Duration delay)
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
-
withAttributes
public SubFlow<In,Out,Mat> withAttributes(Attributes attr)
Change the attributes of thisSource
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).
-
addAttributes
public SubFlow<In,Out,Mat> addAttributes(Attributes attr)
Add the given attributes to this Source. Further calls towithAttributes
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).
-
log
public SubFlow<In,Out,Mat> log(java.lang.String name, Function<Out,java.lang.Object> extract, LoggingAdapter log)
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
-
log
public SubFlow<In,Out,Mat> log(java.lang.String name, Function<Out,java.lang.Object> extract)
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 usesakka.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
-
log
public SubFlow<In,Out,Mat> log(java.lang.String name, LoggingAdapter log)
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
-
log
public SubFlow<In,Out,Mat> log(java.lang.String name)
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 usesakka.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
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logWithMarker
public SubFlow<In,Out,Mat> logWithMarker(java.lang.String name, Function<Out,LogMarker> marker, Function<Out,java.lang.Object> extract, MarkerLoggingAdapter log)
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
MarkerLoggingAdapter
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
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logWithMarker
public SubFlow<In,Out,Mat> logWithMarker(java.lang.String name, Function<Out,LogMarker> marker, Function<Out,java.lang.Object> extract)
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
MarkerLoggingAdapter
which usesakka.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
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logWithMarker
public SubFlow<In,Out,Mat> logWithMarker(java.lang.String name, Function<Out,LogMarker> marker, MarkerLoggingAdapter log)
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
MarkerLoggingAdapter
for logging.'''Emits when''' the mapping function returns an element
'''Backpressures when''' downstream backpressures
'''Completes when''' upstream completes
'''Cancels when''' downstream cancels
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logWithMarker
public SubFlow<In,Out,Mat> logWithMarker(java.lang.String name, Function<Out,LogMarker> marker)
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
MarkerLoggingAdapter
which usesakka.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
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aggregateWithBoundary
public <Agg,Emit> SubFlow<In,Emit,Mat> aggregateWithBoundary(java.util.function.Supplier<Agg> allocate, Function2<Agg,Out,Pair<Agg,java.lang.Object>> aggregate, Function<Agg,Emit> harvest, Pair<java.util.function.Predicate<Agg>,java.time.Duration> emitOnTimer)
Aggregate input elements into an arbitrary data structure that can be completed and emitted downstream when custom condition is met which can be triggered by aggregate or timer. It can be thought of a more generalgroupedWeightedWithin(long,akka.japi.function.Function<Out,java.lang.Long>,scala.concurrent.duration.FiniteDuration)
.'''Emits when''' the aggregation function decides the aggregate is complete or the timer function returns true
'''Backpressures when''' downstream backpressures and the aggregate is complete
'''Completes when''' upstream completes and the last aggregate has been emitted downstream
'''Cancels when''' downstream cancels
- Parameters:
allocate
- allocate the initial data structure for aggregated elementsaggregate
- update the aggregated elements, return true if ready to emit after update.harvest
- this is invoked before emit within the current stage/operatoremitOnTimer
- decide whether the current aggregated elements can be emitted, the custom function is invoked on every interval
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