java.lang.Object
- org.apache.pekko.stream.javadsl.SubFlow<In,Out,Mat>

```
public class SubFlow<In,Out,Mat>
extends java.lang.Object
```
A “stream of streams” sub-flow of data elements, e.g. produced by groupBy. SubFlows cannot contribute to the super-flow’s materialized value since they are materialized later, during the runtime of the flow graph processing.

Constructor Summary

Constructors
Constructor Description

SubFlow(SubFlow<Out,Mat,Flow<In,java.lang.Object,Mat>,Sink<In,Mat>> delegate)

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)`	Attaches the given `Sink` to this `Flow`, meaning that elements that passes through will also be sent to the `Sink`.
`SubFlow<In,Out,Mat>`	`alsoToAll(Graph<SinkShape<Out>,?>... those)`	Attaches the given `Sink`s to this `Flow`, meaning that elements that passes through will also be sent to all those `Sink`s.
`SubFlow<In,Out,Mat>`	`alsoToAll(scala.collection.immutable.Seq<Graph<SinkShape<Out>,?>> those)`	Attaches the given `Sink`s to this `Flow`, meaning that elements that passes through will also be sent to all those `Sink`s.
`SubFlow<Out,Mat,Flow<In,java.lang.Object,Mat>,Sink<In,Mat>>`	`asScala()`	Converts this Flow to its Scala DSL counterpart
`SubFlow<In,Out,Mat>`	`async()`	Put an asynchronous boundary around this `SubFlow`
`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 a `TimeoutException`.
`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 a `TimeoutException`.
`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)`	Concatenate the given `Source` to this `Flow`, meaning that once this Flow’s input is exhausted and all result elements have been generated, the Source’s elements will be produced.
`SubFlow<In,Out,Mat>`	`concatAllLazy(Graph<SourceShape<Out>,?>... those)`	Concatenate the given `Source`s to this `Flow`, meaning that once this Flow’s input is exhausted and all result elements have been generated, the Source’s elements will be produced.
`SubFlow<In,Out,Mat>`	`concatAllLazy(scala.collection.immutable.Seq<Graph<SourceShape<Out>,?>> those)`	Concatenate the given `Source`s to this `Flow`, meaning that once this Flow’s input is exhausted and all result elements have been generated, the Source’s elements will be produced.
`<M> SubFlow<In,Out,Mat>`	`concatLazy(Graph<SourceShape<Out>,M> that)`	Concatenate the given `Source` to this `Flow`, meaning that once this Flow’s input is exhausted and all result elements have been generated, the Source’s elements will be produced.
`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)`	Attaches the given `Sink` to this `Flow`, meaning that elements will be sent to the `Sink` instead of being passed through if the predicate `when` returns `true`.
`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 a `Source` 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 a `Source` of output elements that is then flattened into the output stream by merging, where at most `breadth` substreams are being consumed at any given time.
`<Out2,Mat2> SubFlow<In,Out2,Mat>`	`flatMapPrefix(int n, Function<java.lang.Iterable<Out>,Flow<Out,Out2,Mat2>> f)`	Takes up to `n` elements from the stream (less than `n` only if the upstream completes before emitting `n` elements), then apply `f` 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 to `scan` 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 to `fold` 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 the `minWeight`, with the last group possibly smaller than requested `minWeight` 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 a `TimeoutException`.
`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 a `TimeoutException`.
`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)`	Interleave is a deterministic merge of the given `Source` with elements of this `Flow`.
`SubFlow<In,Out,Mat>`	`interleaveAll(java.util.List<? extends Graph<SourceShape<Out>,?>> those, int segmentSize, boolean eagerClose)`	Interleave is a deterministic merge of the given `Source`s with elements of this `Flow`.
`SubFlow<In,Out,Mat>`	`intersperse(Out inject)`	Intersperses stream with provided element, similar to how `scala.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 how `scala.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 an `Iterable` 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 to `recover(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 to `recover(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>`	`merge(Graph<SourceShape<Out>,?> that)`	Merge the given `Source` to this `Flow`, taking elements as they arrive from input streams, picking randomly when several elements ready.
`SubFlow<In,Out,Mat>`	`mergeAll(java.util.List<? extends Graph<SourceShape<Out>,?>> those, boolean eagerComplete)`	Merge the given `Source`s to this `Flow`, taking elements as they arrive from input streams, picking randomly when several elements ready.
`<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)`	Merge the given `Source` to this `Flow`, taking elements as they arrive from input streams, picking always the smallest of the available elements (waiting for one element from each side to be available).
`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 a name 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 to `n` elements from the stream (less than `n` only if the upstream completes before emitting `n` elements) and returns a pair containing a strict sequence of the taken element and a stream representing the remaining elements.
`<M> SubFlow<In,Out,Mat>`	`prepend(Graph<SourceShape<Out>,M> that)`	Prepend the given `Source` to this `Flow`, meaning that before elements are generated from this Flow, the Source's elements will be produced until it is exhausted, at which point Flow elements will start being produced.
`<M> SubFlow<In,Out,Mat>`	`prependLazy(Graph<SourceShape<Out>,M> that)`	Prepend the given `Source` to this `Flow`, meaning that before elements are generated from this Flow, the Source's elements will be produced until it is exhausted, at which point Flow elements will start being produced.
`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)`	RecoverWith allows to switch to alternative Source on flow failure.
`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 to `fold` but uses first element as zero element.
`<T> SubFlow<In,T,Mat>`	`scan(T zero, Function2<T,Out,T> f)`	Similar to `fold` but is not a terminal operation, emits its current value which starts at `zero` and then applies the current and next value to the given function `f`, emitting the next current value.
`<T> SubFlow<In,T,Mat>`	`scanAsync(T zero, Function2<T,Out,java.util.concurrent.CompletionStage<T>> f)`	Similar to `scan` but with a asynchronous function, emits its current value which starts at `zero` and then applies the current and next value to the given function `f`, emitting a `Future` that resolves to the next current value.
`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)`	Deprecated. Use `statefulMap` with `mapConcat` instead.
`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 to `elements/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 to `cost/per`.
`SubFlow<In,Out,Mat>`	`throttle(int elements, java.time.Duration per, int maximumBurst, ThrottleMode mode)`	Sends elements downstream with speed limited to `elements/per`.
`SubFlow<In,Out,Mat>`	`throttle(int cost, java.time.Duration per, Function<Out,java.lang.Integer> costCalculation)`	Sends elements downstream with speed limited to `cost/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)`	Connect this `SubFlow` to a `Sink`, concatenating the processing steps of both.
`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 this `Flow` by appending the given processing steps.
`SubFlow<In,Out,Mat>`	`wireTap(Procedure<Out> f)`	This is a simplified version of `wireTap(Sink)` that takes only a simple procedure.
`SubFlow<In,Out,Mat>`	`wireTap(Graph<SinkShape<Out>,?> that)`	Attaches the given `Sink` to this `Flow` as a wire tap, meaning that elements that pass through will also be sent to the wire-tap Sink, without the latter affecting the mainline flow.
`SubFlow<In,Out,Mat>`	`withAttributes(Attributes attr)`	Change the attributes of this `Source` to the given ones and seal the list of attributes.
`<T> SubFlow<In,Pair<Out,T>,Mat>`	`zip(Graph<SourceShape<T>,?> source)`	Combine the elements of current `Flow` and the given `Source` into a stream of tuples.
`<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 given `Source` into a stream of tuples.
`<T> SubFlow<In,Pair<Out,T>,Mat>`	`zipLatest(Graph<SourceShape<T>,?> source)`	Combine the elements of current `Flow` and the given `Source` into a stream of tuples, picking always the latest element of each.
`<Out2,Out3> SubFlow<In,Out3,Mat>`	`zipLatestWith(Graph<SourceShape<Out2>,?> that, Function2<Out,Out2,Out3> combine)`	Put together the elements of current `Flow` and the given `Source` into a stream of combined elements using a combiner function, picking always the latest element of each.
`<Out2,Out3> SubFlow<In,Out3,Mat>`	`zipWith(Graph<SourceShape<Out2>,?> that, Function2<Out,Out2,Out3> combine)`	Put together the elements of current `Flow` and the given `Source` into a stream of combined elements using a combiner function.
`SubFlow<In,Pair<Out,java.lang.Long>,Mat>`	`zipWithIndex()`	Combine the elements of current `Flow` into a stream of tuples consisting of all elements paired with their index.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
 - SubFlow
```
public SubFlow(SubFlow<Out,Mat,Flow<In,java.lang.Object,Mat>,Sink<In,Mat>> delegate)
```
- Method Detail
 - 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 a map.
 
 Returns:
 
 A flow that accepts In and outputs elements of the super type
 - concatAllLazy
```
public SubFlow<In,Out,Mat> concatAllLazy(Graph<SourceShape<Out>,?>... those)
```
 Concatenate the given Sources to this Flow, meaning that once this Flow’s input is exhausted and all result elements have been generated, the Source’s elements will be produced.
 Note that the Sources are materialized together with this Flow. If lazy materialization is what is needed the operator can be combined with for example Source.lazySource to defer materialization of that 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(org.apache.pekko.stream.Graph<org.apache.pekko.stream.SourceShape<Out>, M>)
 If this Flow gets upstream error - no elements from the given Sources will be pulled.
 '''Emits when''' element is available from current stream or from the given Sources when current is completed
 '''Backpressures when''' downstream backpressures
 '''Completes when''' given all those Sources completes
 '''Cancels when''' downstream cancels
 - alsoToAll
```
public SubFlow<In,Out,Mat> alsoToAll(Graph<SinkShape<Out>,?>... those)
```
 Attaches the given Sinks to this Flow, meaning that elements that passes through will also be sent to all those Sinks.
 It is similar to wireTap(org.apache.pekko.japi.function.Procedure<Out>) but will backpressure instead of dropping elements when the given Sinks 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 Sinks backpressures
 '''Completes when''' upstream completes
 '''Cancels when''' downstream or any of the Sinks cancels
 - asScala
```
public SubFlow<Out,Mat,Flow<In,java.lang.Object,Mat>,Sink<In,Mat>> asScala()
```
 Converts this Flow to its Scala DSL counterpart
 - 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).
 - 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 to parallelism substreams will be executed at any given time. Substreams that are not yet executed are also not materialized, meaning that back-pressure will be exerted at the operator that creates the substreams when the parallelism limit is reached.
 - 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 with groupBy since it can easily lead to deadlock—the concatenation does not consume from the second substream until the first has finished and the groupBy operator will get back-pressure from the second stream.
 This is identical in effect to mergeSubstreamsWithParallelism(1).
 - via
```
public <T,M> SubFlow<In,T,Mat> via(Graph<FlowShape<Out,T>,M> flow)
```
 Transform this Flow by appending the given processing steps.
 
 +----------------------------+ | Resulting Flow | | | | +------+ +------+ | | | | | | | In ~~> | this | ~Out~> | flow | ~~> T | | | | | | | +------+ +------+ | +----------------------------+
 
 The materialized value of the combined Flow will be the materialized value of the current flow (ignoring the other Flow’s value), use viaMat if a different strategy is needed.
 - to
```
public Sink<In,Mat> to(Graph<SinkShape<Out>,?> sink)
```
 Connect this SubFlow to a Sink, concatenating the processing steps of both. This means that all sub-flows that result from the previous sub-stream operator will be attached to the given sink.
 +----------------------------+ | Resulting Sink | | | | +------+ +------+ | | | | | | | In ~~> | flow | ~Out~> | sink | | | | | | | | | +------+ +------+ | +----------------------------+
 
 Note that attributes set on the returned graph, including async boundaries are now for the entire graph and not the SubFlow. for example async will not have any effect as the returned graph is the entire, closed graph.
 - 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 of wireTap(Sink) that takes only a simple procedure. Elements will be passed into this "side channel" function, and any of its results will be ignored.
 If the wire-tap operation is slow (it backpressures), elements that would've been sent to it will be dropped instead. It is similar to alsoTo(org.apache.pekko.stream.Graph<org.apache.pekko.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,org.apache.pekko.japi.function.Function<Out,java.lang.Object>,org.apache.pekko.event.LoggingAdapter) operator instead, along with appropriate ActorAttributes.logLevels.
 '''Emits when''' upstream emits an element; the same element will be passed to the attached function, as well as to the downstream operator
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes
 '''Cancels when''' downstream cancels
 - mapConcat
```
public <T> SubFlow<In,T,Mat> mapConcat(Function<Out,java.lang.Iterable<T>> f)
```
 Transform each input element into an Iterable of output elements that is then flattened into the output stream.
 Make sure that the Iterable is immutable or at least not modified after being used as an output sequence. Otherwise the stream may fail with ConcurrentModificationException or other more subtle errors may occur.
 The returned Iterable MUST NOT contain null values, as they are illegal as stream elements - according to the Reactive Streams specification.
 '''Emits when''' the mapping function returns an element or there are still remaining elements from the previously calculated collection
 '''Backpressures when''' downstream backpressures or there are still remaining elements from the previously calculated collection
 '''Completes when''' upstream completes and all remaining elements has been emitted
 '''Cancels when''' downstream cancels
 - 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 be null as it is illegal as stream element - according to the Reactive Streams specification.
 For stateless variant see <T>map(org.apache.pekko.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 state
 
 f - a function that transforms the upstream element and the state into a pair of next state and output element
 
 onComplete - a function that transforms the ongoing state into an optional output element
 - statefulMapConcat
```
public <T> SubFlow<In,T,Mat> statefulMapConcat(Creator<Function<Out,java.lang.Iterable<T>>> f)
```
 Deprecated.
 Use `statefulMap` with `mapConcat` instead. Since 1.0.2.
 
 Transform each input element into an Iterable of output elements that is then flattened into the output stream. The transformation is meant to be stateful, which is enabled by creating the transformation function anew for every materialization — the returned function will typically close over mutable objects to store state between invocations. For the stateless variant see mapConcat(org.apache.pekko.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 with ConcurrentModificationException or other more subtle errors may occur.
 The returned Iterable MUST NOT contain null values, as they are illegal as stream elements - according to the Reactive Streams specification.
 This operator doesn't handle upstream's completion signal since the state kept in the closure can be lost. Use FlowOps.statefulMap instead.
 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 a CompletionStage and the value of that future will be emitted downstream. The number of CompletionStages that shall run in parallel is given as the first argument to mapAsync. These CompletionStages may complete in any order, but the elements that are emitted downstream are in the same order as received from upstream.
 If the function f throws an exception or if the CompletionStage is completed with failure and the supervision decision is pekko.stream.Supervision#stop the stream will be completed with failure.
 If the function f throws an exception or if the CompletionStage is completed with failure and the supervision decision is pekko.stream.Supervision#resume or pekko.stream.Supervision#restart the element is dropped and the stream continues.
 The function f is always invoked on the elements in the order they arrive.
 Adheres to the ActorAttributes.SupervisionStrategy attribute.
 '''Emits when''' the CompletionStage returned by the provided function finishes for the next element in sequence
 '''Backpressures when''' the number of CompletionStages reaches the configured parallelism and the downstream backpressures or the first CompletionStage is not completed
 '''Completes when''' upstream completes and all CompletionStages has been completed and all elements has been emitted
 '''Cancels when''' downstream cancels
 
 See Also:
 
 mapAsyncUnordered(int, org.apache.pekko.japi.function.Function<Out, java.util.concurrent.CompletionStage<T>>)
 - 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 a CompletionStage and the value of that future will be emitted downstream. The number of CompletionStages that shall run in parallel is given as the first argument to mapAsyncUnordered. Each processed element will be emitted downstream as soon as it is ready, i.e. it is possible that the elements are not emitted downstream in the same order as received from upstream.
 If the function f throws an exception or if the CompletionStage is completed with failure and the supervision decision is pekko.stream.Supervision#stop the stream will be completed with failure.
 If the function f throws an exception or if the CompletionStage is completed with failure and the supervision decision is pekko.stream.Supervision#resume or pekko.stream.Supervision#restart the element is dropped and the stream continues.
 The function f is always invoked on the elements in the order they arrive (even though the result of the CompletionStages returned by f might be emitted in a different order).
 Adheres to the ActorAttributes.SupervisionStrategy attribute.
 '''Emits when''' any of the CompletionStages returned by the provided function complete
 '''Backpressures when''' the number of CompletionStages reaches the configured parallelism and the downstream backpressures
 '''Completes when''' upstream completes and all CompletionStages have been completed and all elements has been emitted
 '''Cancels when''' downstream cancels
 
 See Also:
 
 mapAsync(int, org.apache.pekko.japi.function.Function<Out, java.util.concurrent.CompletionStage<T>>)
 - 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 the minWeight, with the last group possibly smaller than requested minWeight 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 failure StreamLimitException downstream.
 Due to input buffering some elements may have been requested from upstream publishers that will then not be processed downstream of this step.
 The stream will be completed without producing any elements if n is zero or negative.
 '''Emits when''' the specified number of elements to take has not yet been reached
 '''Backpressures when''' downstream backpressures
 '''Completes when''' the defined number of elements has been taken or upstream completes
 '''Cancels when''' the defined number of elements has been taken or downstream cancels
 See also Flow.take, Flow.takeWithin, Flow.takeWhile
 - 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 failure StreamLimitException downstream.
 Due to input buffering some elements may have been requested from upstream publishers that will then not be processed downstream of this step.
 The stream will be completed without producing any elements if n is zero or negative.
 Adheres to the ActorAttributes.SupervisionStrategy attribute.
 '''Emits when''' the specified number of elements to take has not yet been reached
 '''Backpressures when''' downstream backpressures
 '''Completes when''' the defined number of elements has been taken or upstream completes
 '''Cancels when''' the defined number of elements has been taken or downstream cancels
 See also Flow.take, Flow.takeWithin, Flow.takeWhile
 - 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 to fold but is not a terminal operation, emits its current value which starts at zero and then applies the current and next value to the given function f, emitting the next current value.
 If the function f throws an exception and the supervision decision is pekko.stream.Supervision#restart current value starts at zero again the stream will continue.
 Adheres to the ActorAttributes.SupervisionStrategy attribute.
 Note that the zero value must be immutable.
 '''Emits when''' the function scanning the element returns a new element
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes
 '''Cancels when''' downstream cancels
 - scanAsync
```
public <T> SubFlow<In,T,Mat> scanAsync(T zero,
 Function2<T,Out,java.util.concurrent.CompletionStage<T>> f)
```
 Similar to scan but with a asynchronous function, emits its current value which starts at zero and then applies the current and next value to the given function f, emitting a Future that resolves to the next current value.
 If the function f throws an exception and the supervision decision is pekko.stream.Supervision.Restart current value starts at zero again the stream will continue.
 If the function f throws an exception and the supervision decision is pekko.stream.Supervision.Resume current value starts at the previous current value, or zero when it doesn't have one, and the stream will continue.
 Adheres to the ActorAttributes.SupervisionStrategy attribute.
 Note that the zero value must be immutable.
 '''Emits when''' the future returned by f completes
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes and the last future returned by f completes
 '''Cancels when''' downstream cancels
 See also scan(T, org.apache.pekko.japi.function.Function2<T, Out, T>)
 - fold
```
public <T> SubFlow<In,T,Mat> fold(T zero,
 Function2<T,Out,T> f)
```
 Similar to scan but only emits its result when the upstream completes, after which it also completes. Applies the given function f towards its current and next value, yielding the next current value.
 Adheres to the ActorAttributes.SupervisionStrategy attribute.
 If the function f throws an exception and the supervision decision is pekko.stream.Supervision#restart current value starts at zero again the stream will continue.
 Note that the zero value must be immutable.
 '''Emits when''' upstream completes
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes
 '''Cancels when''' downstream cancels
 - foldAsync
```
public <T> SubFlow<In,T,Mat> foldAsync(T zero,
 Function2<T,Out,java.util.concurrent.CompletionStage<T>> f)
```
 Similar to fold but with an asynchronous function. Applies the given function towards its current and next value, yielding the next current value.
 Adheres to the ActorAttributes.SupervisionStrategy attribute.
 If the function f returns a failure and the supervision decision is pekko.stream.Supervision.Restart current value starts at zero again the stream will continue.
 Note that the zero value must be immutable.
 '''Emits when''' upstream completes
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes
 '''Cancels when''' downstream cancels
 - reduce
```
public SubFlow<In,Out,Mat> reduce(Function2<Out,Out,Out> f)
```
 Similar to fold but uses first element as zero element. Applies the given function towards its current and next value, yielding the next current value.
 Adheres to the ActorAttributes.SupervisionStrategy attribute.
 '''Emits when''' upstream completes
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes
 '''Cancels when''' downstream cancels
 - intersperse
```
public SubFlow<In,Out,Mat> intersperse(Out start,
 Out inject,
 Out end)
```
 Intersperses stream with provided element, similar to how scala.collection.immutable.List.mkString injects a separator between a List's elements.
 Additionally can inject start and end marker elements to stream.
 Examples:
 
 Source<Integer, ?> nums = Source.from(Arrays.asList(0, 1, 2, 3)); nums.intersperse(","); // 1 , 2 , 3 nums.intersperse("[", ",", "]"); // [ 1 , 2 , 3 ]
 
 In case you want to only prepend or only append an element (yet still use the intercept feature to inject a separator between elements, you may want to use the following pattern instead of the 3-argument version of intersperse (See Source.concat for semantics details):
 
 Source.single(">> ").concat(flow.intersperse(",")) flow.intersperse(",").concat(Source.single("END"))
 
 '''Emits when''' upstream emits (or before with the start element if provided)
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes
 '''Cancels when''' downstream cancels
 - intersperse
```
public SubFlow<In,Out,Mat> intersperse(Out inject)
```
 Intersperses stream with provided element, similar to how scala.collection.immutable.List.mkString injects a separator between a List's elements.
 Additionally can inject start and end marker elements to stream.
 Examples:
 
 Source<Integer, ?> nums = Source.from(Arrays.asList(0, 1, 2, 3)); nums.intersperse(","); // 1 , 2 , 3 nums.intersperse("[", ",", "]"); // [ 1 , 2 , 3 ]
 
 '''Emits when''' upstream emits (or before with the start element if provided)
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes
 '''Cancels when''' downstream cancels
 - 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 Akka 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, and duration 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, and duration 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 Akka 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, and duration 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, and duration 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 than maxNumber elements
 '''Completes when''' upstream completes (emits last group)
 '''Cancels when''' downstream completes
 maxWeight must be positive, maxNumber must be positive, and duration 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 Akka 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 defined pekko.stream.DelayOverflowStrategy it might drop elements or backpressure the upstream if there is no space available in the buffer.
 Delay precision is 10ms to avoid unnecessary timer scheduling cycles
 Internal buffer has default capacity 16. You can set buffer size by calling withAttributes(inputBuffer)
 '''Emits when''' there is a pending element in the buffer and configured time for this element elapsed * EmitEarly - strategy do not wait to emit element if buffer is full
 '''Backpressures when''' depending on OverflowStrategy * Backpressure - backpressures when buffer is full * DropHead, DropTail, DropBuffer - never backpressures * Fail - fails the stream if buffer gets full
 '''Completes when''' upstream completes and buffered elements has been drained
 '''Cancels when''' downstream cancels
 
 Parameters:
 
 of - time to shift all messages
 
 strategy - 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 defined pekko.stream.DelayOverflowStrategy it might drop elements or backpressure the upstream if there is no space available in the buffer.
 Delay precision is 10ms to avoid unnecessary timer scheduling cycles
 Internal buffer has default capacity 16. You can set buffer size by calling withAttributes(inputBuffer)
 '''Emits when''' there is a pending element in the buffer and configured time for this element elapsed * EmitEarly - strategy do not wait to emit element if buffer is full
 '''Backpressures when''' depending on OverflowStrategy * Backpressure - backpressures when buffer is full * DropHead, DropTail, DropBuffer - never backpressures * Fail - fails the stream if buffer gets full
 '''Completes when''' upstream completes and buffered elements has been drained
 '''Cancels when''' downstream cancels
 
 Parameters:
 
 of - time to shift all messages
 
 strategy - 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 defined pekko.stream.DelayOverflowStrategy 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 new DelayStrategy object for each materialization
 
 overFlowStrategy - 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 if n is zero or negative.
 '''Emits when''' the specified number of elements has been dropped already
 '''Backpressures when''' the specified number of elements has been dropped and downstream backpressures
 '''Completes when''' upstream completes
 '''Cancels when''' downstream cancels
 - dropWithin
```
public SubFlow<In,Out,Mat> dropWithin(scala.concurrent.duration.FiniteDuration duration)
```
 Deprecated.
 Use the overloaded one which accepts java.time.Duration instead. Since Akka 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)
```
 RecoverWith allows to switch to alternative Source on flow failure. It will stay in effect after a failure has been recovered so that each time there is a failure it is fed into the pf and a new Source may be materialized.
 Since the underlying failure signal onError arrives out-of-band, it might jump over existing elements. This operator can recover the failure signal, but not the skipped elements, which will be dropped.
 Throwing an exception inside recoverWith _will_ be logged on ERROR level automatically.
 '''Emits when''' element is available from the upstream or upstream is failed and element is available from alternative Source
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes or upstream failed with exception pf can handle
 '''Cancels when''' downstream cancels
 - 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 to attempts number of times so that each time there is a failure it is fed into the pf and a new Source may be materialized. Note that if you pass in 0, this won't attempt to recover at all.
 A negative attempts number is interpreted as "infinite", which results in the exact same behavior as recoverWith.
 Since the underlying failure signal onError arrives out-of-band, it might jump over existing elements. This operator can recover the failure signal, but not the skipped elements, which will be dropped.
 Throwing an exception inside recoverWithRetries _will_ be logged on ERROR level automatically.
 '''Emits when''' element is available from the upstream or upstream is failed and element is available from alternative Source
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes or upstream failed with exception pf can handle
 '''Cancels when''' downstream cancels
 - mapError
```
public SubFlow<In,Out,Mat> mapError(scala.PartialFunction<java.lang.Throwable,java.lang.Throwable> pf)
```
 While similar to recover(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 to recover(t => throw t2) since recover would log the t2 error.
 Since the underlying failure signal onError arrives out-of-band, it might jump over existing elements. This operator can recover the failure signal, but not the skipped elements, which will be dropped.
 Similarly to recover(scala.PartialFunction<java.lang.Throwable,Out>) throwing an exception inside mapError _will_ be logged.
 '''Emits when''' element is available from the upstream or upstream is failed and pf returns an element
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes or upstream failed with exception pf can handle
 '''Cancels when''' downstream cancels
 - 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 to recover(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 to recover(t => throw t2) since recover would log the t2 error.
 Since the underlying failure signal onError arrives out-of-band, it might jump over existing elements. This operator can recover the failure signal, but not the skipped elements, which will be dropped.
 Similarly to recover(scala.PartialFunction<java.lang.Throwable,Out>) throwing an exception inside mapError _will_ be logged.
 '''Emits when''' element is available from the upstream or upstream is failed and pf returns an element
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes or upstream failed with exception pf can handle
 '''Cancels when''' downstream cancels
 - 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 Akka 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 start
 
 aggregate - 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 start
 
 aggregate - 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 concatenate ByteString elements up to the allowed max limit if the upstream publisher is faster.
 This element only rolls up elements if the upstream is faster, but if the downstream is faster it will not duplicate elements.
 Batching will apply for all elements, even if a single element cost is greater than the total allowed limit. In this case, previous batched elements will be emitted, then the "heavy" element will be emitted (after being applied with the seed function) without batching further elements with it, and then the rest of the incoming elements are batched.
 '''Emits when''' downstream stops backpressuring and there is a batched element available
 '''Backpressures when''' there are max weighted batched elements + 1 pending element and downstream backpressures
 '''Completes when''' upstream completes and there is no batched/pending element waiting
 '''Cancels when''' downstream cancels
 See also SubFlow.conflate, SubFlow.batch
 
 Parameters:
 
 max - maximum weight of elements to batch before backpressuring upstream (must be positive non-zero)
 
 costFn - a function to compute a single element weight
 
 seed - Provides the first state for a batched value using the first unconsumed element as a start
 
 aggregate - Takes the currently batched value and the current pending element to produce a new batch
 - expand
```
public  SubFlow<In,U,Mat> expand(Function<Out,java.util.Iterator> 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 pekko.stream.Supervision#restart and pekko.stream.Supervision#resume. Exceptions from the expander function will complete the stream with failure.
 See also extrapolate(org.apache.pekko.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 pekko.stream.Supervision#restart and pekko.stream.Supervision#resume. Exceptions from the extrapolate function will complete the stream with failure.
 See also expand(org.apache.pekko.japi.function.Function<Out, java.util.Iterator>) 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(org.apache.pekko.japi.function.Function<Out, java.util.Iterator>)
 - 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 pekko.stream.Supervision#restart and pekko.stream.Supervision#resume. Exceptions from the extrapolate function will complete the stream with failure.
 See also expand(org.apache.pekko.japi.function.Function<Out, java.util.Iterator>) 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(org.apache.pekko.japi.function.Function<Out, java.util.Iterator>)
 - 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 defined pekko.stream.OverflowStrategy it might drop elements or backpressure the upstream if there is no space available
 '''Emits when''' downstream stops backpressuring and there is a pending element in the buffer
 '''Backpressures when''' downstream backpressures or depending on OverflowStrategy:
 
 Backpressure - backpressures when buffer is full
 
 DropHead, DropTail, DropBuffer - never backpressures
 
 Fail - fails the stream if buffer gets full
 
 '''Completes when''' upstream completes and buffered elements has been drained
 '''Cancels when''' downstream cancels
 Parameters:
 
 size - The size of the buffer in element count
 
 overflowStrategy - 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 to n elements from the stream (less than n only if the upstream completes before emitting n elements) and returns a pair containing a strict sequence of the taken element and a stream representing the remaining elements. If ''n'' is zero or negative, then this will return a pair of an empty collection and a stream containing the whole upstream unchanged.
 In case of an upstream error, depending on the current state - the master stream signals the error if less than n elements has been seen, and therefore the substream has not yet been emitted - the tail substream signals the error after the prefix and tail has been emitted by the main stream (at that point the main stream has already completed)
 '''Emits when''' the configured number of prefix elements are available. Emits this prefix, and the rest as a substream
 '''Backpressures when''' downstream backpressures or substream backpressures
 '''Completes when''' prefix elements has been consumed and substream has been consumed
 '''Cancels when''' downstream cancels or substream cancels
 - flatMapPrefix
```
public <Out2,Mat2> SubFlow<In,Out2,Mat> flatMapPrefix(int n,
 Function<java.lang.Iterable<Out>,Flow<Out,Out2,Mat2>> f)
```
 Takes up to n elements from the stream (less than n only if the upstream completes before emitting n elements), then apply f 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 a Source of output elements that is then flattened into the output stream by concatenation, fully consuming one Source after the other.
 '''Emits when''' a currently consumed substream has an element available
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes and all consumed substreams complete
 '''Cancels when''' downstream cancels
 - flatMapMerge
```
public <T,M> SubFlow<In,T,Mat> flatMapMerge(int breadth,
 Function<Out,? extends Graph<SourceShape<T>,M>> f)
```
 Transform each input element into a Source of output elements that is then flattened into the output stream by merging, where at most breadth substreams are being consumed at any given time.
 '''Emits when''' a currently consumed substream has an element available
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes and all consumed substreams complete
 '''Cancels when''' downstream cancels
 - concat
```
public <M> SubFlow<In,Out,Mat> concat(Graph<SourceShape<Out>,M> that)
```
 Concatenate the given Source to this Flow, meaning that once this Flow’s input is exhausted and all result elements have been generated, the Source’s elements will be produced.
 Note that the Source is materialized together with this Flow and 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 with Source.lazy to defer materialization of that).
 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(org.apache.pekko.stream.Graph<org.apache.pekko.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 given Source to this Flow, meaning that once this Flow’s input is exhausted and all result elements have been generated, the Source’s elements will be produced.
 Note that the Source is materialized together with this Flow. If lazy materialization is what is needed the operator can be combined with for example Source.lazySource to defer materialization of that 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(org.apache.pekko.stream.Graph<org.apache.pekko.stream.SourceShape<Out>, M>)
 If this Flow gets upstream error - no elements from the given Source will be pulled.
 '''Emits when''' element is available from current stream or from the given Source when current is completed
 '''Backpressures when''' downstream backpressures
 '''Completes when''' given Source completes
 '''Cancels when''' downstream cancels
 - concatAllLazy
```
public SubFlow<In,Out,Mat> concatAllLazy(scala.collection.immutable.Seq<Graph<SourceShape<Out>,?>> those)
```
 Concatenate the given Sources to this Flow, meaning that once this Flow’s input is exhausted and all result elements have been generated, the Source’s elements will be produced.
 Note that the Sources are materialized together with this Flow. If lazy materialization is what is needed the operator can be combined with for example Source.lazySource to defer materialization of that 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(org.apache.pekko.stream.Graph<org.apache.pekko.stream.SourceShape<Out>, M>)
 If this Flow gets upstream error - no elements from the given Sources will be pulled.
 '''Emits when''' element is available from current stream or from the given Sources when current is completed
 '''Backpressures when''' downstream backpressures
 '''Completes when''' given all those Sources completes
 '''Cancels when''' downstream cancels
 - prepend
```
public <M> SubFlow<In,Out,Mat> prepend(Graph<SourceShape<Out>,M> that)
```
 Prepend the given Source to this Flow, meaning that before elements are generated from this Flow, the Source's elements will be produced until it is exhausted, at which point Flow elements will start being produced.
 Note that 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 with Source.lazy to defer materialization of that).
 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(org.apache.pekko.stream.Graph<org.apache.pekko.stream.SourceShape<Out>, M>)
 '''Emits when''' element is available from the given Source or from current stream when the Source is completed
 '''Backpressures when''' downstream backpressures
 '''Completes when''' this Flow completes
 '''Cancels when''' downstream cancels
 - prependLazy
```
public <M> SubFlow<In,Out,Mat> prependLazy(Graph<SourceShape<Out>,M> that)
```
 Prepend the given Source to this Flow, meaning that before elements are generated from this Flow, the Source's elements will be produced until it is exhausted, at which point Flow elements will start being produced.
 Note that 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(org.apache.pekko.stream.Graph<org.apache.pekko.stream.SourceShape<Out>, M>)
 If the given Source gets upstream error - no elements from this Flow will be pulled.
 '''Emits when''' element is available from the given Source or from current stream when the Source is completed
 '''Backpressures when''' downstream backpressures
 '''Completes when''' this Flow completes
 '''Cancels when''' downstream cancels
 - 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 given Sink to this Flow, meaning that elements that passes through will also be sent to the Sink.
 It is similar to wireTap(org.apache.pekko.japi.function.Procedure<Out>) but will backpressure instead of dropping elements when the given Sink is not ready.
 '''Emits when''' element is available and demand exists both from the Sink and the downstream.
 '''Backpressures when''' downstream or Sink backpressures
 '''Completes when''' upstream completes
 '''Cancels when''' downstream or Sink cancels
 - alsoToAll
```
public SubFlow<In,Out,Mat> alsoToAll(scala.collection.immutable.Seq<Graph<SinkShape<Out>,?>> those)
```
 Attaches the given Sinks to this Flow, meaning that elements that passes through will also be sent to all those Sinks.
 It is similar to wireTap(org.apache.pekko.japi.function.Procedure<Out>) but will backpressure instead of dropping elements when the given Sinks 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 Sinks backpressures
 '''Completes when''' upstream completes
 '''Cancels when''' downstream or any of the Sinks cancels
 - divertTo
```
public SubFlow<In,Out,Mat> divertTo(Graph<SinkShape<Out>,?> that,
 Predicate<Out> when)
```
 Attaches the given Sink to this Flow, meaning that elements will be sent to the Sink instead of being passed through if the predicate when returns true.
 '''Emits when''' emits when an element is available from the input and the chosen output has demand
 '''Backpressures when''' the currently chosen output back-pressures
 '''Completes when''' upstream completes and no output is pending
 '''Cancels when''' any of the downstreams cancel
 - wireTap
```
public SubFlow<In,Out,Mat> wireTap(Graph<SinkShape<Out>,?> that)
```
 Attaches the given Sink to this Flow as a wire tap, meaning that elements that pass through will also be sent to the wire-tap Sink, without the latter affecting the mainline flow. If the wire-tap Sink backpressures, elements that would've been sent to it will be dropped instead.
 It is similar to alsoTo(org.apache.pekko.stream.Graph<org.apache.pekko.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 given Source to this Flow, taking elements as they arrive from input streams, picking randomly when several elements ready.
 '''Emits when''' one of the inputs has an element available
 '''Backpressures when''' downstream backpressures
 '''Completes when''' all upstreams complete
 '''Cancels when''' downstream cancels
 - mergeAll
```
public SubFlow<In,Out,Mat> mergeAll(java.util.List<? extends Graph<SourceShape<Out>,?>> those,
 boolean eagerComplete)
```
 Merge the given Sources to this Flow, taking elements as they arrive from input streams, picking randomly when several elements ready.
 '''Emits when''' one of the inputs has an element available
 '''Backpressures when''' downstream backpressures
 '''Completes when''' all upstreams complete (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 given Source with elements of this Flow. It first emits segmentSize number of elements from this flow to downstream, then - same amount for that source, then repeat process.
 Example:
 Source(List(1, 2, 3)).interleave(List(4, 5, 6, 7), 2) // 1, 2, 4, 5, 3, 6, 7
 
 After one of upstreams is complete than all the rest elements will be emitted from the second one
 If it gets error from one of upstreams - stream completes with failure.
 '''Emits when''' element is available from the currently consumed upstream
 '''Backpressures when''' downstream backpressures. Signal to current upstream, switch to next upstream when received segmentSize elements
 '''Completes when''' the Flow and given Source completes
 '''Cancels when''' downstream cancels
 - 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 given Sources with elements of this Flow. It first emits segmentSize number of elements from this flow to downstream, then - same amount for that source, then repeat process.
 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 given Source 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 given Source to this Flow, taking elements as they arrive from input streams, picking always the smallest of the available elements (waiting for one element from each side to be available). This means that possible contiguity of the input streams is not exploited to avoid waiting for elements, this merge will block when one of the inputs does not have more elements (and does not complete).
 '''Emits when''' all of the inputs have an element available
 '''Backpressures when''' downstream backpressures
 '''Completes when''' all upstreams complete
 '''Cancels when''' downstream cancels
 - zip
```
public <T> SubFlow<In,Pair<Out,T>,Mat> zip(Graph<SourceShape<T>,?> source)
```
 Combine the elements of current Flow and the given Source into a stream of tuples.
 '''Emits when''' all of the inputs has an element available
 '''Backpressures when''' downstream backpressures
 '''Completes when''' any upstream completes
 '''Cancels when''' downstream cancels
 - zipAll
```
public <U,A> SubFlow<In,Pair<A,U>,Mat> zipAll(Graph<SourceShape,?> that,
 A thisElem,
 U thatElem)
```
 Combine the elements of current flow and the given Source 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 current Flow and the given Source into a stream of tuples, picking always the latest element of each.
 '''Emits when''' all of the inputs have at least an element available, and then each time an element becomes available on either of the inputs
 '''Backpressures when''' downstream backpressures
 '''Completes when''' any upstream completes
 '''Cancels when''' downstream cancels
 - zipWith
```
public <Out2,Out3> SubFlow<In,Out3,Mat> zipWith(Graph<SourceShape<Out2>,?> that,
 Function2<Out,Out2,Out3> combine)
```
 Put together the elements of current Flow and the given Source into a stream of combined elements using a combiner function.
 '''Emits when''' all of the inputs has an element available
 '''Backpressures when''' downstream backpressures
 '''Completes when''' any upstream completes
 '''Cancels when''' downstream cancels
 - zipLatestWith
```
public <Out2,Out3> SubFlow<In,Out3,Mat> zipLatestWith(Graph<SourceShape<Out2>,?> that,
 Function2<Out,Out2,Out3> combine)
```
 Put together the elements of current Flow and the given Source into a stream of combined elements using a combiner function, picking always the latest element of each.
 '''Emits when''' all of the inputs have at least an element available, and then each time an element becomes available on either of the inputs
 '''Backpressures when''' downstream backpressures
 '''Completes when''' any upstream completes
 '''Cancels when''' downstream cancels
 - zipWithIndex
```
public SubFlow<In,Pair<Out,java.lang.Long>,Mat> zipWithIndex()
```
 Combine the elements of current Flow into a stream of tuples consisting of all elements paired with their index. Indices start at 0.
 '''Emits when''' upstream emits an element and is paired with their index
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes
 '''Cancels when''' downstream cancels
 - initialTimeout
```
public SubFlow<In,Out,Mat> initialTimeout(scala.concurrent.duration.FiniteDuration timeout)
```
 Deprecated.
 Use the overloaded one which accepts java.time.Duration instead. Since Akka 2.5.12.
 
 If the first element has not passed through this operator before the provided timeout, the stream is failed with a TimeoutException.
 '''Emits when''' upstream emits an element
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes or fails if timeout elapses before first element arrives
 '''Cancels when''' downstream cancels
 - 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 a TimeoutException.
 '''Emits when''' upstream emits an element
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes or fails if timeout elapses before first element arrives
 '''Cancels when''' downstream cancels
 - completionTimeout
```
public SubFlow<In,Out,Mat> completionTimeout(scala.concurrent.duration.FiniteDuration timeout)
```
 Deprecated.
 Use the overloaded one which accepts java.time.Duration instead. Since Akka 2.5.12.
 
 If the completion of the stream does not happen until the provided timeout, the stream is failed with a TimeoutException.
 '''Emits when''' upstream emits an element
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes or fails if timeout elapses before upstream completes
 '''Cancels when''' downstream cancels
 - 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 a TimeoutException.
 '''Emits when''' upstream emits an element
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes or fails if timeout elapses before upstream completes
 '''Cancels when''' downstream cancels
 - idleTimeout
```
public SubFlow<In,Out,Mat> idleTimeout(scala.concurrent.duration.FiniteDuration timeout)
```
 Deprecated.
 Use the overloaded one which accepts java.time.Duration instead. Since Akka 2.5.12.
 
 If the time between two processed elements exceeds the provided timeout, the stream is failed with a TimeoutException. The timeout is checked periodically, so the resolution of the check is one period (equals to timeout value).
 '''Emits when''' upstream emits an element
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes or fails if timeout elapses between two emitted elements
 '''Cancels when''' downstream cancels
 - 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 a TimeoutException. The timeout is checked periodically, so the resolution of the check is one period (equals to timeout value).
 '''Emits when''' upstream emits an element
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes or fails if timeout elapses between two emitted elements
 '''Cancels when''' downstream cancels
 - backpressureTimeout
```
public SubFlow<In,Out,Mat> backpressureTimeout(scala.concurrent.duration.FiniteDuration timeout)
```
 Deprecated.
 Use the overloaded one which accepts java.time.Duration instead. Since Akka 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 a TimeoutException. The timeout is checked periodically, so the resolution of the check is one period (equals to timeout value).
 '''Emits when''' upstream emits an element
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes or fails if timeout elapses between element emission and downstream demand.
 '''Cancels when''' downstream cancels
 - 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 a TimeoutException. The timeout is checked periodically, so the resolution of the check is one period (equals to timeout value).
 '''Emits when''' upstream emits an element
 '''Backpressures when''' downstream backpressures
 '''Completes when''' upstream completes or fails if timeout elapses between element emission and downstream demand.
 '''Cancels when''' downstream cancels
 - 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 Akka 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 to elements/per. In other words, this operator set the maximum rate for emitting messages. This operator works for streams where all elements have the same cost or length.
 Throttle implements the token bucket model. There is a bucket with a given token capacity (burst size). Tokens drops into the bucket at a given rate and can be spared for later use up to bucket capacity to allow some burstiness. Whenever stream wants to send an element, it takes as many tokens from the bucket as element costs. If there isn't any, throttle waits until the bucket accumulates enough tokens. Elements that costs more than the allowed burst will be delayed proportionally to their cost minus available tokens, meeting the target rate. Bucket is full when stream just materialized and started.
 The burst size is calculated based on the given rate (cost/per) as 0.1 * rate, for example: - rate < 20/second => burst size 1 - rate 20/second => burst size 2 - rate 100/second => burst size 10 - rate 200/second => burst size 20
 The throttle mode is pekko.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 Akka 2.5.12.
 
 Sends elements downstream with speed limited to elements/per. In other words, this operator set the maximum rate for emitting messages. This operator works for streams where all elements have the same cost or length.
 Throttle implements the token bucket model. There is a bucket with a given token capacity (burst size or maximumBurst). Tokens drops into the bucket at a given rate and can be spared for later use up to bucket capacity to allow some burstiness. Whenever stream wants to send an element, it takes as many tokens from the bucket as element costs. If there isn't any, throttle waits until the bucket accumulates enough tokens. Elements that costs more than the allowed burst will be delayed proportionally to their cost minus available tokens, meeting the target rate. Bucket is full when stream just materialized and started.
 Parameter mode manages behavior when upstream is faster than throttle rate: - pekko.stream.ThrottleMode.Shaping makes pauses before emitting messages to meet throttle rate - pekko.stream.ThrottleMode.Enforcing fails with exception when upstream is faster than throttle rate
 It is recommended to use non-zero burst sizes as they improve both performance and throttling precision by allowing the implementation to avoid using the scheduler when input rates fall below the enforced limit and to reduce most of the inaccuracy caused by the scheduler resolution (which is in the range of milliseconds).
 WARNING: Be aware that throttle is using scheduler to slow down the stream. This scheduler has minimal time of triggering next push. Consequently it will slow down the stream as it has minimal pause for emitting. This can happen in case burst is 0 and speed is higher than 30 events per second. You need to increase the maximumBurst if elements arrive with small interval (30 milliseconds or less). Use the overloaded throttle method without maximumBurst parameter to automatically calculate the maximumBurst based on the given rate (cost/per). In other words the throttler always enforces the rate limit when maximumBurst parameter is given, but in certain cases (mostly due to limited scheduler resolution) it enforces a tighter bound than what was prescribed.
 '''Emits when''' upstream emits an element and configured time per each element elapsed
 '''Backpressures when''' downstream backpressures or the incoming rate is higher than the speed limit
 '''Completes when''' upstream completes
 '''Cancels when''' downstream cancels
 - throttle
```
public SubFlow<In,Out,Mat> throttle(int elements,
 java.time.Duration per,
 int maximumBurst,
 ThrottleMode mode)
```
 Sends elements downstream with speed limited to elements/per. In other words, this operator set the maximum rate for emitting messages. This operator works for streams where all elements have the same cost or length.
 Throttle implements the token bucket model. There is a bucket with a given token capacity (burst size or maximumBurst). Tokens drops into the bucket at a given rate and can be spared for later use up to bucket capacity to allow some burstiness. Whenever stream wants to send an element, it takes as many tokens from the bucket as element costs. If there isn't any, throttle waits until the bucket accumulates enough tokens. Elements that costs more than the allowed burst will be delayed proportionally to their cost minus available tokens, meeting the target rate. Bucket is full when stream just materialized and started.
 Parameter mode manages behavior when upstream is faster than throttle rate: - pekko.stream.ThrottleMode.Shaping makes pauses before emitting messages to meet throttle rate - pekko.stream.ThrottleMode.Enforcing fails with exception when upstream is faster than throttle rate
 It is recommended to use non-zero burst sizes as they improve both performance and throttling precision by allowing the implementation to avoid using the scheduler when input rates fall below the enforced limit and to reduce most of the inaccuracy caused by the scheduler resolution (which is in the range of milliseconds).
 WARNING: Be aware that throttle is using scheduler to slow down the stream. This scheduler has minimal time of triggering next push. Consequently it will slow down the stream as it has minimal pause for emitting. This can happen in case burst is 0 and speed is higher than 30 events per second. You need to increase the maximumBurst if elements arrive with small interval (30 milliseconds or less). Use the overloaded throttle method without maximumBurst parameter to automatically calculate the maximumBurst based on the given rate (cost/per). In other words the throttler always enforces the rate limit when maximumBurst parameter is given, but in certain cases (mostly due to limited scheduler resolution) it enforces a tighter bound than what was prescribed.
 '''Emits when''' upstream emits an element and configured time per each element elapsed
 '''Backpressures when''' downstream backpressures or the incoming rate is higher than the speed limit
 '''Completes when''' upstream completes
 '''Cancels when''' downstream cancels
 - 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 to cost/per. Cost is calculating for each element individually by calling calculateCost function. This operator works for streams when elements have different cost(length). Streams of ByteString for example.
 Throttle implements the token bucket model. There is a bucket with a given token capacity (burst size). Tokens drops into the bucket at a given rate and can be spared for later use up to bucket capacity to allow some burstiness. Whenever stream wants to send an element, it takes as many tokens from the bucket as element costs. If there isn't any, throttle waits until the bucket accumulates enough tokens. Elements that costs more than the allowed burst will be delayed proportionally to their cost minus available tokens, meeting the target rate. Bucket is full when stream just materialized and started.
 The burst size is calculated based on the given rate (cost/per) as 0.1 * rate, for example: - rate < 20/second => burst size 1 - rate 20/second => burst size 2 - rate 100/second => burst size 10 - rate 200/second => burst size 20
 The throttle mode is pekko.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 Akka 2.5.12.
 
 Sends elements downstream with speed limited to cost/per. Cost is calculating for each element individually by calling calculateCost function. This operator works for streams when elements have different cost(length). Streams of ByteString for example.
 Throttle implements the token bucket model. There is a bucket with a given token capacity (burst size or maximumBurst). Tokens drops into the bucket at a given rate and can be spared for later use up to bucket capacity to allow some burstiness. Whenever stream wants to send an element, it takes as many tokens from the bucket as element costs. If there isn't any, throttle waits until the bucket accumulates enough tokens. Elements that costs more than the allowed burst will be delayed proportionally to their cost minus available tokens, meeting the target rate. Bucket is full when stream just materialized and started.
 Parameter mode manages behavior when upstream is faster than throttle rate: - pekko.stream.ThrottleMode.Shaping makes pauses before emitting messages to meet throttle rate - pekko.stream.ThrottleMode.Enforcing fails with exception when upstream is faster than throttle rate. Enforcing cannot emit elements that cost more than the maximumBurst
 It is recommended to use non-zero burst sizes as they improve both performance and throttling precision by allowing the implementation to avoid using the scheduler when input rates fall below the enforced limit and to reduce most of the inaccuracy caused by the scheduler resolution (which is in the range of milliseconds).
 WARNING: Be aware that throttle is using scheduler to slow down the stream. This scheduler has minimal time of triggering next push. Consequently it will slow down the stream as it has minimal pause for emitting. This can happen in case burst is 0 and speed is higher than 30 events per second. You need to increase the maximumBurst if elements arrive with small interval (30 milliseconds or less). Use the overloaded throttle method without maximumBurst parameter to automatically calculate the maximumBurst based on the given rate (cost/per). In other words the throttler always enforces the rate limit when maximumBurst parameter is given, but in certain cases (mostly due to limited scheduler resolution) it enforces a tighter bound than what was prescribed.
 '''Emits when''' upstream emits an element and configured time per each element elapsed
 '''Backpressures when''' downstream backpressures or the incoming rate is higher than the speed limit
 '''Completes when''' upstream completes
 '''Cancels when''' downstream cancels
 - 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 to cost/per. Cost is calculating for each element individually by calling calculateCost function. This operator works for streams when elements have different cost(length). Streams of ByteString for example.
 Throttle implements the token bucket model. There is a bucket with a given token capacity (burst size or maximumBurst). Tokens drops into the bucket at a given rate and can be spared for later use up to bucket capacity to allow some burstiness. Whenever stream wants to send an element, it takes as many tokens from the bucket as element costs. If there isn't any, throttle waits until the bucket accumulates enough tokens. Elements that costs more than the allowed burst will be delayed proportionally to their cost minus available tokens, meeting the target rate. Bucket is full when stream just materialized and started.
 Parameter mode manages behavior when upstream is faster than throttle rate: - pekko.stream.ThrottleMode.Shaping makes pauses before emitting messages to meet throttle rate - pekko.stream.ThrottleMode.Enforcing fails with exception when upstream is faster than throttle rate. Enforcing cannot emit elements that cost more than the maximumBurst
 It is recommended to use non-zero burst sizes as they improve both performance and throttling precision by allowing the implementation to avoid using the scheduler when input rates fall below the enforced limit and to reduce most of the inaccuracy caused by the scheduler resolution (which is in the range of milliseconds).
 WARNING: Be aware that throttle is using scheduler to slow down the stream. This scheduler has minimal time of triggering next push. Consequently it will slow down the stream as it has minimal pause for emitting. This can happen in case burst is 0 and speed is higher than 30 events per second. You need to increase the maximumBurst if elements arrive with small interval (30 milliseconds or less). Use the overloaded throttle method without maximumBurst parameter to automatically calculate the maximumBurst based on the given rate (cost/per). In other words the throttler always enforces the rate limit when maximumBurst parameter is given, but in certain cases (mostly due to limited scheduler resolution) it enforces a tighter bound than what was prescribed.
 '''Emits when''' upstream emits an element and configured time per each element elapsed
 '''Backpressures when''' downstream backpressures or the incoming rate is higher than the speed limit
 '''Completes when''' upstream completes
 '''Cancels when''' downstream cancels
 - throttleEven
```
public SubFlow<In,Out,Mat> throttleEven(int elements,
 scala.concurrent.duration.FiniteDuration per,
 ThrottleMode mode)
```
 Deprecated.
 Use throttle without `maximumBurst` parameter instead. Since Akka 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 Akka 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 Akka 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 Akka 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 Akka 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 this Source to the given ones and seal the list of attributes. This means that further calls will not be able to remove these attributes, but instead add new ones. Note that this operation has no effect on an empty Flow (because the attributes apply only to the contained processing operators).
 - addAttributes
```
public SubFlow<In,Out,Mat> addAttributes(Attributes attr)
```
 Add the given attributes to this Source. Further calls to withAttributes will not remove these attributes. Note that this operation has no effect on an empty Flow (because the attributes apply only to the contained processing operators).
 - named
```
public SubFlow<In,Out,Mat> named(java.lang.String name)
```
 Add a name attribute to this Flow.
 - async
```
public SubFlow<In,Out,Mat> async()
```
 Put an asynchronous boundary around this SubFlow
 - 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 uses org.apache.pekko.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 uses org.apache.pekko.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
 - 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
 - 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 uses org.apache.pekko.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
 - 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
 - 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 uses org.apache.pekko.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
 - 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 general groupedWeightedWithin(long,org.apache.pekko.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 elements
 
 aggregate - update the aggregated elements, return true if ready to emit after update.
 
 harvest - this is invoked before emit within the current stage/operator
 
 emitOnTimer - decide whether the current aggregated elements can be emitted, the custom function is invoked on every interval

Class SubFlow<In,​Out,​Mat>

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

SubFlow

Method Detail

upcast

concatAllLazy

alsoToAll

asScala

mergeSubstreams

mergeSubstreamsWithParallelism

concatSubstreams

via

to

map

wireTap

mapConcat

statefulMap

statefulMapConcat

mapAsync

mapAsyncUnordered

filter

filterNot

collect

collectType

grouped

groupedWeighted

limit

limitWeighted

sliding

sliding$default$2

scan

scanAsync

fold

foldAsync

reduce

intersperse

intersperse

groupedWithin

groupedWithin

groupedWeightedWithin

groupedWeightedWithin

groupedWeightedWithin

delay

delay

delayWith

drop

dropWithin

dropWithin

takeWhile

takeWhile

dropWhile

recover

recoverWith

recoverWithRetries

mapError

mapError

take

takeWithin

takeWithin

conflateWithSeed

conflate

batch

batchWeighted

expand

extrapolate

extrapolate

buffer

prefixAndTail

flatMapPrefix

flatMapConcat

flatMapMerge

concat

concatLazy

concatAllLazy

prepend

prependLazy

orElse

Class SubFlow<In,Out,Mat>