reactor.core.publisher

Class ParallelFlux<T>

java.lang.Object

reactor.core.publisher.ParallelFlux<T>

Type Parameters:

T - the value type

All Implemented Interfaces:

Publisher<T>

public abstract class ParallelFlux<T>
extends Object
implements Publisher<T>

A ParallelFlux publishes to an array of Subscribers, in parallel 'rails' (or 'groups').

Use from() to start processing a regular Publisher in 'rails', which each cover a subset of the original Publisher's data. Flux.parallel() is a convenient shortcut to achieve that on a Flux. Use runOn() to introduce where each 'rail' should run on thread-vise. Use sequential() to merge the sources back into a single Flux or subscribe(Subscriber) if you simply want to subscribe to the merged sequence. Note that other variants like subscribe(Consumer) instead do multiple subscribes, one on each rail (which means that the lambdas should be as stateless and side-effect free as possible).

Constructor Summary

Constructors

Constructor and Description
ParallelFlux()

Method Summary

Modifier and Type	Method and Description
<U> U	as(Function<? super ParallelFlux<T>,U> converter) Perform a fluent transformation to a value via a converter function which receives this ParallelFlux.
ParallelFlux<T>	checkpoint() Activate assembly tracing for this particular ParallelFlux, in case of an error upstream of the checkpoint.
ParallelFlux<T>	checkpoint(String description) Activate assembly tracing for this particular ParallelFlux and give it a description that will be reflected in the assembly traceback, in case of an error upstream of the checkpoint.
<C> ParallelFlux<C>	collect(Supplier<? extends C> collectionSupplier, BiConsumer<? super C,? super T> collector) Collect the elements in each rail into a collection supplied via a collectionSupplier and collected into with a collector action, emitting the collection at the end.
Mono<List<T>>	collectSortedList(Comparator<? super T> comparator) Sorts the 'rails' according to the comparator and returns a full sorted list as a Publisher.
Mono<List<T>>	collectSortedList(Comparator<? super T> comparator, int capacityHint) Sorts the 'rails' according to the comparator and returns a full sorted list as a Publisher.
<U> ParallelFlux<U>	composeGroup(Function<? super GroupedFlux<Integer,T>,? extends Publisher<? extends U>> composer) Allows composing operators off the 'rails', as individual GroupedFlux instances keyed by the zero based rail's index.
<R> ParallelFlux<R>	concatMap(Function<? super T,? extends Publisher<? extends R>> mapper) Generates and concatenates Publishers on each 'rail', signalling errors immediately and generating 2 publishers upfront.
<R> ParallelFlux<R>	concatMap(Function<? super T,? extends Publisher<? extends R>> mapper, int prefetch) Generates and concatenates Publishers on each 'rail', signalling errors immediately and using the given prefetch amount for generating Publishers upfront.
<R> ParallelFlux<R>	concatMapDelayError(Function<? super T,? extends Publisher<? extends R>> mapper) Generates and concatenates Publishers on each 'rail', delaying errors and generating 2 publishers upfront.
ParallelFlux<T>	doAfterTerminate(Runnable afterTerminate) Run the specified runnable when a 'rail' completes or signals an error.
ParallelFlux<T>	doOnCancel(Runnable onCancel) Run the specified runnable when a 'rail' receives a cancellation.
ParallelFlux<T>	doOnComplete(Runnable onComplete) Run the specified runnable when a 'rail' completes.
ParallelFlux<T>	doOnEach(Consumer<? super Signal<T>> signalConsumer) Triggers side-effects when the ParallelFlux emits an item, fails with an error or completes successfully.
ParallelFlux<T>	doOnError(Consumer<? super Throwable> onError) Call the specified consumer with the exception passing through any 'rail'.
ParallelFlux<T>	doOnNext(Consumer<? super T> onNext) Call the specified consumer with the current element passing through any 'rail'.
ParallelFlux<T>	doOnRequest(LongConsumer onRequest) Call the specified consumer with the request amount if any rail receives a request.
ParallelFlux<T>	doOnSubscribe(Consumer<? super Subscription> onSubscribe) Call the specified callback when a 'rail' receives a Subscription from its upstream.
ParallelFlux<T>	doOnTerminate(Runnable onTerminate) Triggered when the ParallelFlux terminates, either by completing successfully or with an error.
ParallelFlux<T>	filter(Predicate<? super T> predicate) Filters the source values on each 'rail'.
<R> ParallelFlux<R>	flatMap(Function<? super T,? extends Publisher<? extends R>> mapper) Generates and flattens Publishers on each 'rail'.
<R> ParallelFlux<R>	flatMap(Function<? super T,? extends Publisher<? extends R>> mapper, boolean delayError) Generates and flattens Publishers on each 'rail', optionally delaying errors.
<R> ParallelFlux<R>	flatMap(Function<? super T,? extends Publisher<? extends R>> mapper, boolean delayError, int maxConcurrency) Generates and flattens Publishers on each 'rail', optionally delaying errors and having a total number of simultaneous subscriptions to the inner Publishers.
<R> ParallelFlux<R>	flatMap(Function<? super T,? extends Publisher<? extends R>> mapper, boolean delayError, int maxConcurrency, int prefetch) Generates and flattens Publishers on each 'rail', optionally delaying errors, having a total number of simultaneous subscriptions to the inner Publishers and using the given prefetch amount for the inner Publishers.
static <T> ParallelFlux<T>	from(Publisher<? extends T> source) Take a Publisher and prepare to consume it on multiple 'rails' (number of CPUs) in a round-robin fashion.
static <T> ParallelFlux<T>	from(Publisher<? extends T> source, int parallelism) Take a Publisher and prepare to consume it on parallelism number of 'rails' , possibly ordered and round-robin fashion.
static <T> ParallelFlux<T>	from(Publisher<? extends T> source, int parallelism, int prefetch, Supplier<Queue<T>> queueSupplier) Take a Publisher and prepare to consume it on parallelism number of 'rails' and round-robin fashion and use custom prefetch amount and queue for dealing with the source Publisher's values.
static <T> ParallelFlux<T>	from(Publisher<T>... publishers) Wraps multiple Publishers into a ParallelFlux which runs them in parallel and unordered.
long	getPrefetch() The prefetch configuration of the component
Flux<GroupedFlux<Integer,T>>	groups() Exposes the 'rails' as individual GroupedFlux instances, keyed by the rail index (zero based).
ParallelFlux<T>	hide() Hides the identities of this ParallelFlux and its Subscription as well.
boolean	isOrdered() Deprecated. This accessor was initially exposed to introspect the internal ordering scenario for parallel rails. In effect reactor 3.0 and 3.1 only offer non ordered merge at the end and therefore this should always returns false;
ParallelFlux<T>	log() Observe all Reactive Streams signals and use Logger support to handle trace implementation.
ParallelFlux<T>	log(String category) Observe all Reactive Streams signals and use Logger support to handle trace implementation.
ParallelFlux<T>	log(String category, Level level, boolean showOperatorLine, SignalType... options) Observe Reactive Streams signals matching the passed filter options and use Logger support to handle trace implementation.
ParallelFlux<T>	log(String category, Level level, SignalType... options) Observe Reactive Streams signals matching the passed filter options and use Logger support to handle trace implementation.
<U> ParallelFlux<U>	map(Function<? super T,? extends U> mapper) Maps the source values on each 'rail' to another value.
protected static <T> ParallelFlux<T>	onAssembly(ParallelFlux<T> source) Invoke Hooks pointcut given a ParallelFlux and returning an eventually new ParallelFlux
abstract int	parallelism() Returns the number of expected parallel Subscribers.
Mono<T>	reduce(BiFunction<T,T,T> reducer) Reduces all values within a 'rail' and across 'rails' with a reducer function into a single sequential value.
<R> ParallelFlux<R>	reduce(Supplier<R> initialSupplier, BiFunction<R,? super T,R> reducer) Reduces all values within a 'rail' to a single value (with a possibly different type) via a reducer function that is initialized on each rail from an initialSupplier value.
ParallelFlux<T>	runOn(Scheduler scheduler) Specifies where each 'rail' will observe its incoming values with no work-stealing and default prefetch amount.
ParallelFlux<T>	runOn(Scheduler scheduler, int prefetch) Specifies where each 'rail' will observe its incoming values with possibly work-stealing and a given prefetch amount.
Flux<T>	sequential() Merges the values from each 'rail' in a round-robin or same-order fashion and exposes it as a regular Publisher sequence, running with a default prefetch value for the rails.
Flux<T>	sequential(int prefetch) Merges the values from each 'rail' in a round-robin or same-order fashion and exposes it as a regular Publisher sequence, running with a give prefetch value for the rails.
Flux<T>	sorted(Comparator<? super T> comparator) Sorts the 'rails' of this ParallelFlux and returns a Publisher that sequentially picks the smallest next value from the rails.
Flux<T>	sorted(Comparator<? super T> comparator, int capacityHint) Sorts the 'rails' of this ParallelFlux and returns a Publisher that sequentially picks the smallest next value from the rails.
void	subscribe(Consumer<? super T> onNext) Subscribes to this ParallelFlux by providing an onNext callback and triggers the execution chain for all 'rails'.
void	subscribe(Consumer<? super T> onNext, Consumer<? super Throwable> onError) Subscribes to this ParallelFlux by providing an onNext and onError callback and triggers the execution chain for all 'rails'.
void	subscribe(Consumer<? super T> onNext, Consumer<? super Throwable> onError, Runnable onComplete) Subscribes to this ParallelFlux by providing an onNext, onError and onComplete callback and triggers the execution chain for all 'rails'.
void	subscribe(Consumer<? super T> onNext, Consumer<? super Throwable> onError, Runnable onComplete, Consumer<? super Subscription> onSubscribe) Subscribes to this ParallelFlux by providing an onNext, onError, onComplete and onSubscribe callback and triggers the execution chain for all 'rails'.
void	subscribe(Subscriber<? super T> s) Merge the rails into a sequential() Flux and subscribe to said Flux.
abstract void	subscribe(Subscriber<? super T>[] subscribers) Subscribes an array of Subscribers to this ParallelFlux and triggers the execution chain for all 'rails'.
<U> ParallelFlux<U>	transform(Function<? super ParallelFlux<T>,ParallelFlux<U>> composer) Allows composing operators, in assembly time, on top of this ParallelFlux and returns another ParallelFlux with composed features.
protected boolean	validate(Subscriber<?>[] subscribers) Validates the number of subscribers and returns true if their number matches the parallelism level of this ParallelFlux.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

ParallelFlux

public ParallelFlux()

Method Detail

from

public static <T> ParallelFlux<T> from(Publisher<? extends T> source)

Take a Publisher and prepare to consume it on multiple 'rails' (number of CPUs) in a round-robin fashion.

Type Parameters:

T - the value type

Parameters:

source - the source Publisher

Returns:

the ParallelFlux instance

from

public static <T> ParallelFlux<T> from(Publisher<? extends T> source,
                                       int parallelism)

Take a Publisher and prepare to consume it on parallelism number of 'rails' , possibly ordered and round-robin fashion.

Type Parameters:

T - the value type

Parameters:

source - the source Publisher

parallelism - the number of parallel rails

Returns:

the new ParallelFlux instance

from

public static <T> ParallelFlux<T> from(Publisher<? extends T> source,
                                       int parallelism,
                                       int prefetch,
                                       Supplier<Queue<T>> queueSupplier)

Take a Publisher and prepare to consume it on parallelism number of 'rails' and round-robin fashion and use custom prefetch amount and queue for dealing with the source Publisher's values.

Type Parameters:

T - the value type

Parameters:

source - the source Publisher

parallelism - the number of parallel rails

prefetch - the number of values to prefetch from the source

queueSupplier - the queue structure supplier to hold the prefetched values from the source until there is a rail ready to process it.

Returns:

the new ParallelFlux instance

from

@SafeVarargs
public static <T> ParallelFlux<T> from(Publisher<T>... publishers)

Wraps multiple Publishers into a ParallelFlux which runs them in parallel and unordered.

Type Parameters:

T - the value type

Parameters:

publishers - the array of publishers

Returns:

the new ParallelFlux instance

as

public final <U> U as(Function<? super ParallelFlux<T>,U> converter)

Perform a fluent transformation to a value via a converter function which receives this ParallelFlux.

Type Parameters:

U - the output value type

Parameters:

converter - the converter function from ParallelFlux to some type

Returns:

the value returned by the converter function

checkpoint

public final ParallelFlux<T> checkpoint()

Activate assembly tracing for this particular ParallelFlux, in case of an error upstream of the checkpoint.

It should be placed towards the end of the reactive chain, as errors triggered downstream of it cannot be observed and augmented with assembly trace.

Returns:

the assembly tracing ParallelFlux

checkpoint

public final ParallelFlux<T> checkpoint(String description)

Activate assembly tracing for this particular ParallelFlux and give it a description that will be reflected in the assembly traceback, in case of an error upstream of the checkpoint.

It should be placed towards the end of the reactive chain, as errors triggered downstream of it cannot be observed and augmented with assembly trace.

The description could for example be a meaningful name for the assembled flux or a wider correlation ID.

Parameters:

description - a description to include in the assembly traceback.

Returns:

the assembly tracing ParallelFlux

collect

public final <C> ParallelFlux<C> collect(Supplier<? extends C> collectionSupplier,
                                         BiConsumer<? super C,? super T> collector)

Collect the elements in each rail into a collection supplied via a collectionSupplier and collected into with a collector action, emitting the collection at the end.

Type Parameters:

C - the collection type

Parameters:

collectionSupplier - the supplier of the collection in each rail

collector - the collector, taking the per-rail collection and the current item

Returns:

the new ParallelFlux instance

collectSortedList

public final Mono<List<T>> collectSortedList(Comparator<? super T> comparator)

Sorts the 'rails' according to the comparator and returns a full sorted list as a Publisher.

This operator requires a finite source ParallelFlux.

Parameters:

comparator - the comparator to compare elements

Returns:

the new Flux instance

collectSortedList

public final Mono<List<T>> collectSortedList(Comparator<? super T> comparator,
                                             int capacityHint)

Sorts the 'rails' according to the comparator and returns a full sorted list as a Publisher.

This operator requires a finite source ParallelFlux.

Parameters:

comparator - the comparator to compare elements

capacityHint - the expected number of total elements

Returns:

the new Mono instance

concatMap

public final <R> ParallelFlux<R> concatMap(Function<? super T,? extends Publisher<? extends R>> mapper)

Generates and concatenates Publishers on each 'rail', signalling errors immediately and generating 2 publishers upfront.

Type Parameters:

R - the result type

Parameters:

mapper - the function to map each rail's value into a Publisher source and the inner Publishers (immediate, boundary, end)

Returns:

the new ParallelFlux instance

concatMap

public final <R> ParallelFlux<R> concatMap(Function<? super T,? extends Publisher<? extends R>> mapper,
                                           int prefetch)

Generates and concatenates Publishers on each 'rail', signalling errors immediately and using the given prefetch amount for generating Publishers upfront.

Type Parameters:

R - the result type

Parameters:

mapper - the function to map each rail's value into a Publisher

prefetch - the number of items to prefetch from each inner Publisher source and the inner Publishers (immediate, boundary, end)

Returns:

the new ParallelFlux instance

concatMapDelayError

public final <R> ParallelFlux<R> concatMapDelayError(Function<? super T,? extends Publisher<? extends R>> mapper)

Generates and concatenates Publishers on each 'rail', delaying errors and generating 2 publishers upfront.

Type Parameters:

R - the result type

Parameters:

mapper - the function to map each rail's value into a Publisher source and the inner Publishers (immediate, boundary, end)

Returns:

the new ParallelFlux instance

doAfterTerminate

public final ParallelFlux<T> doAfterTerminate(Runnable afterTerminate)

Run the specified runnable when a 'rail' completes or signals an error.

Parameters:

afterTerminate - the callback

Returns:

the new ParallelFlux instance

doOnCancel

public final ParallelFlux<T> doOnCancel(Runnable onCancel)

Run the specified runnable when a 'rail' receives a cancellation.

Parameters:

onCancel - the callback

Returns:

the new ParallelFlux instance

doOnComplete

public final ParallelFlux<T> doOnComplete(Runnable onComplete)

Run the specified runnable when a 'rail' completes.

Parameters:

onComplete - the callback

Returns:

the new ParallelFlux instance

doOnEach

public final ParallelFlux<T> doOnEach(Consumer<? super Signal<T>> signalConsumer)

Triggers side-effects when the ParallelFlux emits an item, fails with an error or completes successfully. All these events are represented as a Signal that is passed to the side-effect callback. Note that with ParallelFlux and the lambda-based subscribes or the array-based one, onError and onComplete will be invoked as many times as there are rails, resulting in as many corresponding Signal being seen in the callback.

Use of subscribe(Subscriber), which calls sequential(), might cancel some rails, resulting in less signals being observed. This is an advanced operator, typically used for monitoring of a ParallelFlux.

Parameters:

signalConsumer - the mandatory callback to call on Subscriber.onNext(Object), Subscriber.onError(Throwable) and Subscriber.onComplete()

Returns:

an observed ParallelFlux

See Also:

doOnNext(Consumer), doOnError(Consumer), doOnComplete(Runnable), subscribe(Subscriber[]), Signal

doOnError

public final ParallelFlux<T> doOnError(Consumer<? super Throwable> onError)

Call the specified consumer with the exception passing through any 'rail'.

Parameters:

onError - the callback

Returns:

the new ParallelFlux instance

doOnSubscribe

public final ParallelFlux<T> doOnSubscribe(Consumer<? super Subscription> onSubscribe)

Call the specified callback when a 'rail' receives a Subscription from its upstream.

Parameters:

onSubscribe - the callback

Returns:

the new ParallelFlux instance

doOnNext

public final ParallelFlux<T> doOnNext(Consumer<? super T> onNext)

Call the specified consumer with the current element passing through any 'rail'.

Parameters:

onNext - the callback

Returns:

the new ParallelFlux instance

doOnRequest

public final ParallelFlux<T> doOnRequest(LongConsumer onRequest)

Call the specified consumer with the request amount if any rail receives a request.

Parameters:

onRequest - the callback

Returns:

the new ParallelFlux instance

doOnTerminate

public final ParallelFlux<T> doOnTerminate(Runnable onTerminate)

Triggered when the ParallelFlux terminates, either by completing successfully or with an error.

Parameters:

onTerminate - the callback to call on Subscriber.onComplete() or Subscriber.onError(java.lang.Throwable)

Returns:

an observed ParallelFlux

filter

public final ParallelFlux<T> filter(Predicate<? super T> predicate)

Filters the source values on each 'rail'.

Note that the same predicate may be called from multiple threads concurrently.

Parameters:

predicate - the function returning true to keep a value or false to drop a value

Returns:

the new ParallelFlux instance

flatMap

public final <R> ParallelFlux<R> flatMap(Function<? super T,? extends Publisher<? extends R>> mapper)

Generates and flattens Publishers on each 'rail'.

Errors are not delayed and uses unbounded concurrency along with default inner prefetch.

Type Parameters:

R - the result type

Parameters:

mapper - the function to map each rail's value into a Publisher

Returns:

the new ParallelFlux instance

flatMap

public final <R> ParallelFlux<R> flatMap(Function<? super T,? extends Publisher<? extends R>> mapper,
                                         boolean delayError)

Generates and flattens Publishers on each 'rail', optionally delaying errors.

It uses unbounded concurrency along with default inner prefetch.

Type Parameters:

R - the result type

Parameters:

mapper - the function to map each rail's value into a Publisher

delayError - should the errors from the main and the inner sources delayed till everybody terminates?

Returns:

the new ParallelFlux instance

flatMap

public final <R> ParallelFlux<R> flatMap(Function<? super T,? extends Publisher<? extends R>> mapper,
                                         boolean delayError,
                                         int maxConcurrency)

Generates and flattens Publishers on each 'rail', optionally delaying errors and having a total number of simultaneous subscriptions to the inner Publishers.

It uses a default inner prefetch.

Type Parameters:

R - the result type

Parameters:

mapper - the function to map each rail's value into a Publisher

delayError - should the errors from the main and the inner sources delayed till everybody terminates?

maxConcurrency - the maximum number of simultaneous subscriptions to the generated inner Publishers

Returns:

the new ParallelFlux instance

flatMap

public final <R> ParallelFlux<R> flatMap(Function<? super T,? extends Publisher<? extends R>> mapper,
                                         boolean delayError,
                                         int maxConcurrency,
                                         int prefetch)

Generates and flattens Publishers on each 'rail', optionally delaying errors, having a total number of simultaneous subscriptions to the inner Publishers and using the given prefetch amount for the inner Publishers.

Type Parameters:

R - the result type

Parameters:

mapper - the function to map each rail's value into a Publisher

delayError - should the errors from the main and the inner sources delayed till everybody terminates?

maxConcurrency - the maximum number of simultaneous subscriptions to the generated inner Publishers

prefetch - the number of items to prefetch from each inner Publisher

Returns:

the new ParallelFlux instance

groups

public final Flux<GroupedFlux<Integer,T>> groups()

Exposes the 'rails' as individual GroupedFlux instances, keyed by the rail index (zero based).

Each group can be consumed only once; requests and cancellation compose through. Note that cancelling only one rail may result in undefined behavior.

Returns:

the new Flux instance

hide

public final ParallelFlux<T> hide()

Hides the identities of this ParallelFlux and its Subscription as well.

Returns:

a new ParallelFlux defeating any Publisher / Subscription feature-detection

isOrdered

@Deprecated
public boolean isOrdered()

Deprecated. This accessor was initially exposed to introspect the internal ordering scenario for parallel rails. In effect reactor 3.0 and 3.1 only offer non ordered merge at the end and therefore this should always returns false;

Returns true if the parallel sequence has to be ordered when joining back.

Returns:

true if the parallel sequence has to be ordered when joining back

log

public final ParallelFlux<T> log()

Observe all Reactive Streams signals and use Logger support to handle trace implementation. Default will use Level.INFO and java.util.logging. If SLF4J is available, it will be used instead.

The default log category will be "reactor.*", a generated operator suffix will complete, e.g. "reactor.Parallel.Map".

Returns:

a new unaltered ParallelFlux

log

public final ParallelFlux<T> log(String category)

Observe all Reactive Streams signals and use Logger support to handle trace implementation. Default will use Level.INFO and java.util.logging. If SLF4J is available, it will be used instead.

Parameters:

category - to be mapped into logger configuration (e.g. org.springframework .reactor). If category ends with "." like "reactor.", a generated operator suffix will complete, e.g. "reactor.Parallel.Map".

Returns:

a new unaltered ParallelFlux

log

public final ParallelFlux<T> log(String category,
                                 Level level,
                                 SignalType... options)

Observe Reactive Streams signals matching the passed filter options and use Logger support to handle trace implementation. Default will use the passed Level and java.util.logging. If SLF4J is available, it will be used instead.

Options allow fine grained filtering of the traced signal, for instance to only capture onNext and onError:

     ParallelFlux.log("category", Level.INFO, SignalType.ON_NEXT,
 SignalType.ON_ERROR)

 

Parameters:

category - to be mapped into logger configuration (e.g. org.springframework .reactor). If category ends with "." like "reactor.", a generated operator suffix will complete, e.g. "reactor.Parallel.Map".

level - the Level to enforce for this tracing ParallelFlux (only FINEST, FINE, INFO, WARNING and SEVERE are taken into account)

options - a vararg SignalType option to filter log messages

Returns:

a new unaltered ParallelFlux

log

public final ParallelFlux<T> log(String category,
                                 Level level,
                                 boolean showOperatorLine,
                                 SignalType... options)

Observe Reactive Streams signals matching the passed filter options and use Logger support to handle trace implementation. Default will use the passed Level and java.util.logging. If SLF4J is available, it will be used instead.

Options allow fine grained filtering of the traced signal, for instance to only capture onNext and onError:

     ParallelFlux.log("category", Level.INFO, SignalType.ON_NEXT,
 SignalType.ON_ERROR)

 

Parameters:

category - to be mapped into logger configuration (e.g. org.springframework .reactor). If category ends with "." like "reactor.", a generated operator suffix will complete, e.g. "reactor.ParallelFlux.Map".

level - the Level to enforce for this tracing ParallelFlux (only FINEST, FINE, INFO, WARNING and SEVERE are taken into account)

showOperatorLine - capture the current stack to display operator class/line number.

options - a vararg SignalType option to filter log messages

Returns:

a new unaltered ParallelFlux

map

public final <U> ParallelFlux<U> map(Function<? super T,? extends U> mapper)

Maps the source values on each 'rail' to another value.

Note that the same mapper function may be called from multiple threads concurrently.

Type Parameters:

U - the output value type

Parameters:

mapper - the mapper function turning Ts into Us.

Returns:

the new ParallelFlux instance

parallelism

public abstract int parallelism()

Returns the number of expected parallel Subscribers.

Returns:

the number of expected parallel Subscribers

reduce

public final Mono<T> reduce(BiFunction<T,T,T> reducer)

Reduces all values within a 'rail' and across 'rails' with a reducer function into a single sequential value.

Note that the same reducer function may be called from multiple threads concurrently.

Parameters:

reducer - the function to reduce two values into one.

Returns:

the new Mono instance emitting the reduced value or empty if the ParallelFlux was empty

reduce

public final <R> ParallelFlux<R> reduce(Supplier<R> initialSupplier,
                                        BiFunction<R,? super T,R> reducer)

Reduces all values within a 'rail' to a single value (with a possibly different type) via a reducer function that is initialized on each rail from an initialSupplier value.

Note that the same mapper function may be called from multiple threads concurrently.

Type Parameters:

R - the reduced output type

Parameters:

initialSupplier - the supplier for the initial value

reducer - the function to reduce a previous output of reduce (or the initial value supplied) with a current source value.

Returns:

the new ParallelFlux instance

runOn

public final ParallelFlux<T> runOn(Scheduler scheduler)

Specifies where each 'rail' will observe its incoming values with no work-stealing and default prefetch amount.

This operator uses the default prefetch size returned by QueueSupplier.SMALL_BUFFER_SIZE.

The operator will call Scheduler.createWorker() as many times as this ParallelFlux's parallelism level is.

No assumptions are made about the Scheduler's parallelism level, if the Scheduler's parallelism level is lower than the ParallelFlux's, some rails may end up on the same thread/worker.

This operator doesn't require the Scheduler to be trampolining as it does its own built-in trampolining logic.

Parameters:

scheduler - the scheduler to use

Returns:

the new ParallelFlux instance

runOn

public final ParallelFlux<T> runOn(Scheduler scheduler,
                                   int prefetch)

Specifies where each 'rail' will observe its incoming values with possibly work-stealing and a given prefetch amount.

This operator uses the default prefetch size returned by QueueSupplier.SMALL_BUFFER_SIZE.

The operator will call Scheduler.createWorker() as many times as this ParallelFlux's parallelism level is.

No assumptions are made about the Scheduler's parallelism level, if the Scheduler's parallelism level is lower than the ParallelFlux's, some rails may end up on the same thread/worker.

This operator doesn't require the Scheduler to be trampolining as it does its own built-in trampolining logic.

Parameters:

scheduler - the scheduler to use that rail's worker has run out of work.

prefetch - the number of values to request on each 'rail' from the source

Returns:

the new ParallelFlux instance

sequential

public final Flux<T> sequential()

Merges the values from each 'rail' in a round-robin or same-order fashion and exposes it as a regular Publisher sequence, running with a default prefetch value for the rails.

This operator uses the default prefetch size returned by QueueSupplier.SMALL_BUFFER_SIZE.

Returns:

the new Flux instance

See Also:

sequential(int)

sequential

public final Flux<T> sequential(int prefetch)

Merges the values from each 'rail' in a round-robin or same-order fashion and exposes it as a regular Publisher sequence, running with a give prefetch value for the rails.

Parameters:

prefetch - the prefetch amount to use for each rail

Returns:

the new Flux instance

sorted

public final Flux<T> sorted(Comparator<? super T> comparator)

Sorts the 'rails' of this ParallelFlux and returns a Publisher that sequentially picks the smallest next value from the rails.

This operator requires a finite source ParallelFlux.

Parameters:

comparator - the comparator to use

Returns:

the new Flux instance

sorted

public final Flux<T> sorted(Comparator<? super T> comparator,
                            int capacityHint)

Sorts the 'rails' of this ParallelFlux and returns a Publisher that sequentially picks the smallest next value from the rails.

This operator requires a finite source ParallelFlux.

Parameters:

comparator - the comparator to use

capacityHint - the expected number of total elements

Returns:

the new Flux instance

subscribe

public abstract void subscribe(Subscriber<? super T>[] subscribers)

Subscribes an array of Subscribers to this ParallelFlux and triggers the execution chain for all 'rails'.

Parameters:

subscribers - the subscribers array to run in parallel, the number of items must be equal to the parallelism level of this ParallelFlux

subscribe

public void subscribe(Consumer<? super T> onNext)

Subscribes to this ParallelFlux by providing an onNext callback and triggers the execution chain for all 'rails'.

Parameters:

onNext - consumer of onNext signals

subscribe

public void subscribe(Consumer<? super T> onNext,
                      Consumer<? super Throwable> onError)

Subscribes to this ParallelFlux by providing an onNext and onError callback and triggers the execution chain for all 'rails'.

Parameters:

onNext - consumer of onNext signals

onError - consumer of error signal

subscribe

public void subscribe(Consumer<? super T> onNext,
                      Consumer<? super Throwable> onError,
                      Runnable onComplete)

Subscribes to this ParallelFlux by providing an onNext, onError and onComplete callback and triggers the execution chain for all 'rails'.

Parameters:

onNext - consumer of onNext signals

onError - consumer of error signal

onComplete - callback on completion signal

subscribe

public void subscribe(Consumer<? super T> onNext,
                      Consumer<? super Throwable> onError,
                      Runnable onComplete,
                      Consumer<? super Subscription> onSubscribe)

Subscribes to this ParallelFlux by providing an onNext, onError, onComplete and onSubscribe callback and triggers the execution chain for all 'rails'.

Parameters:

onNext - consumer of onNext signals

onError - consumer of error signal

onComplete - callback on completion signal

onSubscribe - consumer of the subscription signal

transform

public final <U> ParallelFlux<U> transform(Function<? super ParallelFlux<T>,ParallelFlux<U>> composer)

Allows composing operators, in assembly time, on top of this ParallelFlux and returns another ParallelFlux with composed features.

Type Parameters:

U - the output value type

Parameters:

composer - the composer function from ParallelFlux (this) to another ParallelFlux

Returns:

the ParallelFlux returned by the function

composeGroup

public final <U> ParallelFlux<U> composeGroup(Function<? super GroupedFlux<Integer,T>,? extends Publisher<? extends U>> composer)

Allows composing operators off the 'rails', as individual GroupedFlux instances keyed by the zero based rail's index. The transformed groups are parallelized back once the transformation has been applied.

Note that like in groups(), requests and cancellation compose through, and cancelling only one rail may result in undefined behavior.

Type Parameters:

U - the type of the resulting parallelized flux

Parameters:

composer - the composition function to apply on each rail

Returns:

a ParallelFlux of the composed groups

validate

protected final boolean validate(Subscriber<?>[] subscribers)

Validates the number of subscribers and returns true if their number matches the parallelism level of this ParallelFlux.

Parameters:

subscribers - the array of Subscribers

Returns:

true if the number of subscribers equals to the parallelism level

getPrefetch

public long getPrefetch()

The prefetch configuration of the component

Returns:

the prefetch configuration of the component

subscribe

public final void subscribe(Subscriber<? super T> s)

Merge the rails into a sequential() Flux and subscribe to said Flux.

Specified by:

subscribe in interface Publisher<T>

Parameters:

s - the subscriber to use on sequential() Flux

onAssembly

protected static <T> ParallelFlux<T> onAssembly(ParallelFlux<T> source)

Invoke Hooks pointcut given a ParallelFlux and returning an eventually new ParallelFlux

Type Parameters:

T - the value type

Parameters:

source - the source to wrap

Returns:

the potentially wrapped source