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/**
* Copyright (c) 2016-present, RxJava Contributors.
*
* Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in
* compliance with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software distributed under the License is
* distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See
* the License for the specific language governing permissions and limitations under the License.
*/
package io.reactivex.parallel;
import java.util.*;
import java.util.concurrent.Callable;
import io.reactivex.*;
import io.reactivex.annotations.*;
import io.reactivex.exceptions.Exceptions;
import io.reactivex.functions.*;
import io.reactivex.internal.functions.*;
import io.reactivex.internal.operators.parallel.*;
import io.reactivex.internal.subscriptions.EmptySubscription;
import io.reactivex.internal.util.*;
import io.reactivex.plugins.RxJavaPlugins;
import org.reactivestreams.*;
/**
* Abstract base class for Parallel publishers that take an array of Subscribers.
*
* Use {@code from()} to start processing a regular Publisher in 'rails'.
* Use {@code runOn()} to introduce where each 'rail' should run on thread-vise.
* Use {@code sequential()} to merge the sources back into a single Flowable.
*
*
History: 2.0.5 - experimental; 2.1 - beta
* @param the value type
* @since 2.2
*/
public abstract class ParallelFlowable {
/**
* Subscribes an array of Subscribers to this ParallelFlowable and triggers
* the execution chain for all 'rails'.
*
* @param subscribers the subscribers array to run in parallel, the number
* of items must be equal to the parallelism level of this ParallelFlowable
* @see #parallelism()
*/
public abstract void subscribe(@NonNull Subscriber[] subscribers);
/**
* Returns the number of expected parallel Subscribers.
* @return the number of expected parallel Subscribers
*/
public abstract int parallelism();
/**
* Validates the number of subscribers and returns true if their number
* matches the parallelism level of this ParallelFlowable.
*
* @param subscribers the array of Subscribers
* @return true if the number of subscribers equals to the parallelism level
*/
protected final boolean validate(@NonNull Subscriber[] subscribers) {
int p = parallelism();
if (subscribers.length != p) {
Throwable iae = new IllegalArgumentException("parallelism = " + p + ", subscribers = " + subscribers.length);
for (Subscriber s : subscribers) {
EmptySubscription.error(iae, s);
}
return false;
}
return true;
}
/**
* Take a Publisher and prepare to consume it on multiple 'rails' (number of CPUs)
* in a round-robin fashion.
* @param the value type
* @param source the source Publisher
* @return the ParallelFlowable instance
*/
@CheckReturnValue
public static ParallelFlowable from(@NonNull Publisher source) {
return from(source, Runtime.getRuntime().availableProcessors(), Flowable.bufferSize());
}
/**
* Take a Publisher and prepare to consume it on parallelism number of 'rails' in a round-robin fashion.
* @param the value type
* @param source the source Publisher
* @param parallelism the number of parallel rails
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
public static ParallelFlowable from(@NonNull Publisher source, int parallelism) {
return from(source, parallelism, Flowable.bufferSize());
}
/**
* Take a Publisher and prepare to consume it on parallelism number of 'rails' ,
* possibly ordered and round-robin fashion and use custom prefetch amount and queue
* for dealing with the source Publisher's values.
* @param the value type
* @param source the source Publisher
* @param parallelism the number of parallel rails
* @param prefetch the number of values to prefetch from the source
* the source until there is a rail ready to process it.
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public static ParallelFlowable from(@NonNull Publisher source,
int parallelism, int prefetch) {
ObjectHelper.requireNonNull(source, "source");
ObjectHelper.verifyPositive(parallelism, "parallelism");
ObjectHelper.verifyPositive(prefetch, "prefetch");
return RxJavaPlugins.onAssembly(new ParallelFromPublisher(source, parallelism, prefetch));
}
/**
* Calls the specified converter function during assembly time and returns its resulting value.
*
* This allows fluent conversion to any other type.
*
History: 2.1.7 - experimental
* @param the resulting object type
* @param converter the function that receives the current ParallelFlowable instance and returns a value
* @return the converted value
* @throws NullPointerException if converter is null
* @since 2.2
*/
@CheckReturnValue
@NonNull
public final R as(@NonNull ParallelFlowableConverter converter) {
return ObjectHelper.requireNonNull(converter, "converter is null").apply(this);
}
/**
* Maps the source values on each 'rail' to another value.
*
* Note that the same mapper function may be called from multiple threads concurrently.
* @param the output value type
* @param mapper the mapper function turning Ts into Us.
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable map(@NonNull Function mapper) {
ObjectHelper.requireNonNull(mapper, "mapper");
return RxJavaPlugins.onAssembly(new ParallelMap(this, mapper));
}
/**
* Maps the source values on each 'rail' to another value and
* handles errors based on the given {@link ParallelFailureHandling} enumeration value.
*
* Note that the same mapper function may be called from multiple threads concurrently.
*
History: 2.0.8 - experimental
* @param the output value type
* @param mapper the mapper function turning Ts into Us.
* @param errorHandler the enumeration that defines how to handle errors thrown
* from the mapper function
* @return the new ParallelFlowable instance
* @since 2.2
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable map(@NonNull Function mapper, @NonNull ParallelFailureHandling errorHandler) {
ObjectHelper.requireNonNull(mapper, "mapper");
ObjectHelper.requireNonNull(errorHandler, "errorHandler is null");
return RxJavaPlugins.onAssembly(new ParallelMapTry(this, mapper, errorHandler));
}
/**
* Maps the source values on each 'rail' to another value and
* handles errors based on the returned value by the handler function.
*
* Note that the same mapper function may be called from multiple threads concurrently.
*
History: 2.0.8 - experimental
* @param the output value type
* @param mapper the mapper function turning Ts into Us.
* @param errorHandler the function called with the current repeat count and
* failure Throwable and should return one of the {@link ParallelFailureHandling}
* enumeration values to indicate how to proceed.
* @return the new ParallelFlowable instance
* @since 2.2
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable map(@NonNull Function mapper, @NonNull BiFunction errorHandler) {
ObjectHelper.requireNonNull(mapper, "mapper");
ObjectHelper.requireNonNull(errorHandler, "errorHandler is null");
return RxJavaPlugins.onAssembly(new ParallelMapTry(this, mapper, errorHandler));
}
/**
* Filters the source values on each 'rail'.
*
* Note that the same predicate may be called from multiple threads concurrently.
* @param predicate the function returning true to keep a value or false to drop a value
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
public final ParallelFlowable filter(@NonNull Predicate predicate) {
ObjectHelper.requireNonNull(predicate, "predicate");
return RxJavaPlugins.onAssembly(new ParallelFilter(this, predicate));
}
/**
* Filters the source values on each 'rail' and
* handles errors based on the given {@link ParallelFailureHandling} enumeration value.
*
* Note that the same predicate may be called from multiple threads concurrently.
*
History: 2.0.8 - experimental
* @param predicate the function returning true to keep a value or false to drop a value
* @param errorHandler the enumeration that defines how to handle errors thrown
* from the predicate
* @return the new ParallelFlowable instance
* @since 2.2
*/
@CheckReturnValue
public final ParallelFlowable filter(@NonNull Predicate predicate, @NonNull ParallelFailureHandling errorHandler) {
ObjectHelper.requireNonNull(predicate, "predicate");
ObjectHelper.requireNonNull(errorHandler, "errorHandler is null");
return RxJavaPlugins.onAssembly(new ParallelFilterTry(this, predicate, errorHandler));
}
/**
* Filters the source values on each 'rail' and
* handles errors based on the returned value by the handler function.
*
* Note that the same predicate may be called from multiple threads concurrently.
*
History: 2.0.8 - experimental
* @param predicate the function returning true to keep a value or false to drop a value
* @param errorHandler the function called with the current repeat count and
* failure Throwable and should return one of the {@link ParallelFailureHandling}
* enumeration values to indicate how to proceed.
* @return the new ParallelFlowable instance
* @since 2.2
*/
@CheckReturnValue
public final ParallelFlowable filter(@NonNull Predicate predicate, @NonNull BiFunction errorHandler) {
ObjectHelper.requireNonNull(predicate, "predicate");
ObjectHelper.requireNonNull(errorHandler, "errorHandler is null");
return RxJavaPlugins.onAssembly(new ParallelFilterTry(this, predicate, errorHandler));
}
/**
* 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 {@code Flowable.bufferSize()}.
*
* The operator will call {@code Scheduler.createWorker()} as many
* times as this ParallelFlowable's parallelism level is.
*
* No assumptions are made about the Scheduler's parallelism level,
* if the Scheduler's parallelism level is lower than the ParallelFlowable'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.
*
* @param scheduler the scheduler to use
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable runOn(@NonNull Scheduler scheduler) {
return runOn(scheduler, Flowable.bufferSize());
}
/**
* 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 {@code Flowable.bufferSize()}.
*
* The operator will call {@code Scheduler.createWorker()} as many
* times as this ParallelFlowable's parallelism level is.
*
* No assumptions are made about the Scheduler's parallelism level,
* if the Scheduler's parallelism level is lower than the ParallelFlowable'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.
*
* @param scheduler the scheduler to use
* that rail's worker has run out of work.
* @param prefetch the number of values to request on each 'rail' from the source
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable runOn(@NonNull Scheduler scheduler, int prefetch) {
ObjectHelper.requireNonNull(scheduler, "scheduler");
ObjectHelper.verifyPositive(prefetch, "prefetch");
return RxJavaPlugins.onAssembly(new ParallelRunOn(this, scheduler, prefetch));
}
/**
* 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.
* @param reducer the function to reduce two values into one.
* @return the new Flowable instance emitting the reduced value or empty if the ParallelFlowable was empty
*/
@CheckReturnValue
@NonNull
public final Flowable reduce(@NonNull BiFunction reducer) {
ObjectHelper.requireNonNull(reducer, "reducer");
return RxJavaPlugins.onAssembly(new ParallelReduceFull(this, 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.
* @param the reduced output type
* @param initialSupplier the supplier for the initial value
* @param reducer the function to reduce a previous output of reduce (or the initial value supplied)
* with a current source value.
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable reduce(@NonNull Callable initialSupplier, @NonNull BiFunction reducer) {
ObjectHelper.requireNonNull(initialSupplier, "initialSupplier");
ObjectHelper.requireNonNull(reducer, "reducer");
return RxJavaPlugins.onAssembly(new ParallelReduce(this, initialSupplier, reducer));
}
/**
* 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 {@code Flowable.bufferSize()}.
* 
*
* - Backpressure:
* - The operator honors backpressure.
* - Scheduler:
* - {@code sequential} does not operate by default on a particular {@link Scheduler}.
*
* @return the new Flowable instance
* @see ParallelFlowable#sequential(int)
* @see ParallelFlowable#sequentialDelayError()
*/
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
@CheckReturnValue
public final Flowable sequential() {
return sequential(Flowable.bufferSize());
}
/**
* 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.
*
*
* - Backpressure:
* - The operator honors backpressure.
* - Scheduler:
* - {@code sequential} does not operate by default on a particular {@link Scheduler}.
*
* @param prefetch the prefetch amount to use for each rail
* @return the new Flowable instance
* @see ParallelFlowable#sequential()
* @see ParallelFlowable#sequentialDelayError(int)
*/
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
@CheckReturnValue
@NonNull
public final Flowable sequential(int prefetch) {
ObjectHelper.verifyPositive(prefetch, "prefetch");
return RxJavaPlugins.onAssembly(new ParallelJoin(this, prefetch, false));
}
/**
* Merges the values from each 'rail' in a round-robin or same-order fashion and
* exposes it as a regular Flowable sequence, running with a default prefetch value
* for the rails and delaying errors from all rails till all terminate.
*
* This operator uses the default prefetch size returned by {@code Flowable.bufferSize()}.
*
*
* - Backpressure:
* - The operator honors backpressure.
* - Scheduler:
* - {@code sequentialDelayError} does not operate by default on a particular {@link Scheduler}.
*
* History: 2.0.7 - experimental
* @return the new Flowable instance
* @see ParallelFlowable#sequentialDelayError(int)
* @see ParallelFlowable#sequential()
* @since 2.2
*/
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
@CheckReturnValue
@NonNull
public final Flowable sequentialDelayError() {
return sequentialDelayError(Flowable.bufferSize());
}
/**
* 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 and delaying errors from all rails till all terminate.
*
*
* - Backpressure:
* - The operator honors backpressure.
* - Scheduler:
* - {@code sequentialDelayError} does not operate by default on a particular {@link Scheduler}.
*
* History: 2.0.7 - experimental
* @param prefetch the prefetch amount to use for each rail
* @return the new Flowable instance
* @see ParallelFlowable#sequential()
* @see ParallelFlowable#sequentialDelayError()
* @since 2.2
*/
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
@CheckReturnValue
@NonNull
public final Flowable sequentialDelayError(int prefetch) {
ObjectHelper.verifyPositive(prefetch, "prefetch");
return RxJavaPlugins.onAssembly(new ParallelJoin(this, prefetch, true));
}
/**
* Sorts the 'rails' of this ParallelFlowable and returns a Publisher that sequentially
* picks the smallest next value from the rails.
*
* This operator requires a finite source ParallelFlowable.
*
* @param comparator the comparator to use
* @return the new Flowable instance
*/
@CheckReturnValue
@NonNull
public final Flowable sorted(@NonNull Comparator comparator) {
return sorted(comparator, 16);
}
/**
* Sorts the 'rails' of this ParallelFlowable and returns a Publisher that sequentially
* picks the smallest next value from the rails.
*
* This operator requires a finite source ParallelFlowable.
*
* @param comparator the comparator to use
* @param capacityHint the expected number of total elements
* @return the new Flowable instance
*/
@CheckReturnValue
@NonNull
public final Flowable sorted(@NonNull Comparator comparator, int capacityHint) {
ObjectHelper.requireNonNull(comparator, "comparator is null");
ObjectHelper.verifyPositive(capacityHint, "capacityHint");
int ch = capacityHint / parallelism() + 1;
ParallelFlowable> railReduced = reduce(Functions.createArrayList(ch), ListAddBiConsumer.instance());
ParallelFlowable> railSorted = railReduced.map(new SorterFunction(comparator));
return RxJavaPlugins.onAssembly(new ParallelSortedJoin(railSorted, comparator));
}
/**
* Sorts the 'rails' according to the comparator and returns a full sorted list as a Publisher.
*
* This operator requires a finite source ParallelFlowable.
*
* @param comparator the comparator to compare elements
* @return the new Flowable instance
*/
@CheckReturnValue
@NonNull
public final Flowable> toSortedList(@NonNull Comparator comparator) {
return toSortedList(comparator, 16);
}
/**
* Sorts the 'rails' according to the comparator and returns a full sorted list as a Publisher.
*
* This operator requires a finite source ParallelFlowable.
*
* @param comparator the comparator to compare elements
* @param capacityHint the expected number of total elements
* @return the new Flowable instance
*/
@CheckReturnValue
@NonNull
public final Flowable> toSortedList(@NonNull Comparator comparator, int capacityHint) {
ObjectHelper.requireNonNull(comparator, "comparator is null");
ObjectHelper.verifyPositive(capacityHint, "capacityHint");
int ch = capacityHint / parallelism() + 1;
ParallelFlowable> railReduced = reduce(Functions.createArrayList(ch), ListAddBiConsumer.instance());
ParallelFlowable> railSorted = railReduced.map(new SorterFunction(comparator));
Flowable> merged = railSorted.reduce(new MergerBiFunction(comparator));
return RxJavaPlugins.onAssembly(merged);
}
/**
* Call the specified consumer with the current element passing through any 'rail'.
*
* @param onNext the callback
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable doOnNext(@NonNull Consumer onNext) {
ObjectHelper.requireNonNull(onNext, "onNext is null");
return RxJavaPlugins.onAssembly(new ParallelPeek(this,
onNext,
Functions.emptyConsumer(),
Functions.emptyConsumer(),
Functions.EMPTY_ACTION,
Functions.EMPTY_ACTION,
Functions.emptyConsumer(),
Functions.EMPTY_LONG_CONSUMER,
Functions.EMPTY_ACTION
));
}
/**
* Call the specified consumer with the current element passing through any 'rail' and
* handles errors based on the given {@link ParallelFailureHandling} enumeration value.
* History: 2.0.8 - experimental
* @param onNext the callback
* @param errorHandler the enumeration that defines how to handle errors thrown
* from the onNext consumer
* @return the new ParallelFlowable instance
* @since 2.2
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable doOnNext(@NonNull Consumer onNext, @NonNull ParallelFailureHandling errorHandler) {
ObjectHelper.requireNonNull(onNext, "onNext is null");
ObjectHelper.requireNonNull(errorHandler, "errorHandler is null");
return RxJavaPlugins.onAssembly(new ParallelDoOnNextTry(this, onNext, errorHandler));
}
/**
* Call the specified consumer with the current element passing through any 'rail' and
* handles errors based on the returned value by the handler function.
* History: 2.0.8 - experimental
* @param onNext the callback
* @param errorHandler the function called with the current repeat count and
* failure Throwable and should return one of the {@link ParallelFailureHandling}
* enumeration values to indicate how to proceed.
* @return the new ParallelFlowable instance
* @since 2.2
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable doOnNext(@NonNull Consumer onNext, @NonNull BiFunction errorHandler) {
ObjectHelper.requireNonNull(onNext, "onNext is null");
ObjectHelper.requireNonNull(errorHandler, "errorHandler is null");
return RxJavaPlugins.onAssembly(new ParallelDoOnNextTry(this, onNext, errorHandler));
}
/**
* Call the specified consumer with the current element passing through any 'rail'
* after it has been delivered to downstream within the rail.
*
* @param onAfterNext the callback
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable doAfterNext(@NonNull Consumer onAfterNext) {
ObjectHelper.requireNonNull(onAfterNext, "onAfterNext is null");
return RxJavaPlugins.onAssembly(new ParallelPeek(this,
Functions.emptyConsumer(),
onAfterNext,
Functions.emptyConsumer(),
Functions.EMPTY_ACTION,
Functions.EMPTY_ACTION,
Functions.emptyConsumer(),
Functions.EMPTY_LONG_CONSUMER,
Functions.EMPTY_ACTION
));
}
/**
* Call the specified consumer with the exception passing through any 'rail'.
*
* @param onError the callback
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable doOnError(@NonNull Consumer onError) {
ObjectHelper.requireNonNull(onError, "onError is null");
return RxJavaPlugins.onAssembly(new ParallelPeek(this,
Functions.emptyConsumer(),
Functions.emptyConsumer(),
onError,
Functions.EMPTY_ACTION,
Functions.EMPTY_ACTION,
Functions.emptyConsumer(),
Functions.EMPTY_LONG_CONSUMER,
Functions.EMPTY_ACTION
));
}
/**
* Run the specified Action when a 'rail' completes.
*
* @param onComplete the callback
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable doOnComplete(@NonNull Action onComplete) {
ObjectHelper.requireNonNull(onComplete, "onComplete is null");
return RxJavaPlugins.onAssembly(new ParallelPeek(this,
Functions.emptyConsumer(),
Functions.emptyConsumer(),
Functions.emptyConsumer(),
onComplete,
Functions.EMPTY_ACTION,
Functions.emptyConsumer(),
Functions.EMPTY_LONG_CONSUMER,
Functions.EMPTY_ACTION
));
}
/**
* Run the specified Action when a 'rail' completes or signals an error.
*
* @param onAfterTerminate the callback
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable doAfterTerminated(@NonNull Action onAfterTerminate) {
ObjectHelper.requireNonNull(onAfterTerminate, "onAfterTerminate is null");
return RxJavaPlugins.onAssembly(new ParallelPeek(this,
Functions.emptyConsumer(),
Functions.emptyConsumer(),
Functions.emptyConsumer(),
Functions.EMPTY_ACTION,
onAfterTerminate,
Functions.emptyConsumer(),
Functions.EMPTY_LONG_CONSUMER,
Functions.EMPTY_ACTION
));
}
/**
* Call the specified callback when a 'rail' receives a Subscription from its upstream.
*
* @param onSubscribe the callback
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable doOnSubscribe(@NonNull Consumer onSubscribe) {
ObjectHelper.requireNonNull(onSubscribe, "onSubscribe is null");
return RxJavaPlugins.onAssembly(new ParallelPeek(this,
Functions.emptyConsumer(),
Functions.emptyConsumer(),
Functions.emptyConsumer(),
Functions.EMPTY_ACTION,
Functions.EMPTY_ACTION,
onSubscribe,
Functions.EMPTY_LONG_CONSUMER,
Functions.EMPTY_ACTION
));
}
/**
* Call the specified consumer with the request amount if any rail receives a request.
*
* @param onRequest the callback
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable doOnRequest(@NonNull LongConsumer onRequest) {
ObjectHelper.requireNonNull(onRequest, "onRequest is null");
return RxJavaPlugins.onAssembly(new ParallelPeek(this,
Functions.emptyConsumer(),
Functions.emptyConsumer(),
Functions.emptyConsumer(),
Functions.EMPTY_ACTION,
Functions.EMPTY_ACTION,
Functions.emptyConsumer(),
onRequest,
Functions.EMPTY_ACTION
));
}
/**
* Run the specified Action when a 'rail' receives a cancellation.
*
* @param onCancel the callback
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable doOnCancel(@NonNull Action onCancel) {
ObjectHelper.requireNonNull(onCancel, "onCancel is null");
return RxJavaPlugins.onAssembly(new ParallelPeek(this,
Functions.emptyConsumer(),
Functions.emptyConsumer(),
Functions.emptyConsumer(),
Functions.EMPTY_ACTION,
Functions.EMPTY_ACTION,
Functions.emptyConsumer(),
Functions.EMPTY_LONG_CONSUMER,
onCancel
));
}
/**
* 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.
*
* @param the collection type
* @param collectionSupplier the supplier of the collection in each rail
* @param collector the collector, taking the per-rail collection and the current item
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable collect(@NonNull Callable collectionSupplier, @NonNull BiConsumer collector) {
ObjectHelper.requireNonNull(collectionSupplier, "collectionSupplier is null");
ObjectHelper.requireNonNull(collector, "collector is null");
return RxJavaPlugins.onAssembly(new ParallelCollect(this, collectionSupplier, collector));
}
/**
* Wraps multiple Publishers into a ParallelFlowable which runs them
* in parallel and unordered.
*
* @param the value type
* @param publishers the array of publishers
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public static ParallelFlowable fromArray(@NonNull Publisher... publishers) {
if (publishers.length == 0) {
throw new IllegalArgumentException("Zero publishers not supported");
}
return RxJavaPlugins.onAssembly(new ParallelFromArray(publishers));
}
/**
* Perform a fluent transformation to a value via a converter function which
* receives this ParallelFlowable.
*
* @param the output value type
* @param converter the converter function from ParallelFlowable to some type
* @return the value returned by the converter function
*/
@CheckReturnValue
@NonNull
public final U to(@NonNull Function, U> converter) {
try {
return ObjectHelper.requireNonNull(converter, "converter is null").apply(this);
} catch (Throwable ex) {
Exceptions.throwIfFatal(ex);
throw ExceptionHelper.wrapOrThrow(ex);
}
}
/**
* Allows composing operators, in assembly time, on top of this ParallelFlowable
* and returns another ParallelFlowable with composed features.
*
* @param the output value type
* @param composer the composer function from ParallelFlowable (this) to another ParallelFlowable
* @return the ParallelFlowable returned by the function
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable compose(@NonNull ParallelTransformer composer) {
return RxJavaPlugins.onAssembly(ObjectHelper.requireNonNull(composer, "composer is null").apply(this));
}
/**
* Generates and flattens Publishers on each 'rail'.
*
* Errors are not delayed and uses unbounded concurrency along with default inner prefetch.
*
* @param the result type
* @param mapper the function to map each rail's value into a Publisher
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable flatMap(@NonNull Function> mapper) {
return flatMap(mapper, false, Integer.MAX_VALUE, Flowable.bufferSize());
}
/**
* Generates and flattens Publishers on each 'rail', optionally delaying errors.
*
* It uses unbounded concurrency along with default inner prefetch.
*
* @param the result type
* @param mapper the function to map each rail's value into a Publisher
* @param delayError should the errors from the main and the inner sources delayed till everybody terminates?
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable flatMap(
@NonNull Function> mapper, boolean delayError) {
return flatMap(mapper, delayError, Integer.MAX_VALUE, Flowable.bufferSize());
}
/**
* 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.
*
* @param the result type
* @param mapper the function to map each rail's value into a Publisher
* @param delayError should the errors from the main and the inner sources delayed till everybody terminates?
* @param maxConcurrency the maximum number of simultaneous subscriptions to the generated inner Publishers
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable flatMap(
@NonNull Function> mapper, boolean delayError, int maxConcurrency) {
return flatMap(mapper, delayError, maxConcurrency, Flowable.bufferSize());
}
/**
* 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.
*
* @param the result type
* @param mapper the function to map each rail's value into a Publisher
* @param delayError should the errors from the main and the inner sources delayed till everybody terminates?
* @param maxConcurrency the maximum number of simultaneous subscriptions to the generated inner Publishers
* @param prefetch the number of items to prefetch from each inner Publisher
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable flatMap(
@NonNull Function> mapper,
boolean delayError, int maxConcurrency, int prefetch) {
ObjectHelper.requireNonNull(mapper, "mapper is null");
ObjectHelper.verifyPositive(maxConcurrency, "maxConcurrency");
ObjectHelper.verifyPositive(prefetch, "prefetch");
return RxJavaPlugins.onAssembly(new ParallelFlatMap(this, mapper, delayError, maxConcurrency, prefetch));
}
/**
* Generates and concatenates Publishers on each 'rail', signalling errors immediately
* and generating 2 publishers upfront.
*
* @param the result type
* @param mapper the function to map each rail's value into a Publisher
* source and the inner Publishers (immediate, boundary, end)
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable concatMap(
@NonNull Function> mapper) {
return concatMap(mapper, 2);
}
/**
* Generates and concatenates Publishers on each 'rail', signalling errors immediately
* and using the given prefetch amount for generating Publishers upfront.
*
* @param the result type
* @param mapper the function to map each rail's value into a Publisher
* @param prefetch the number of items to prefetch from each inner Publisher
* source and the inner Publishers (immediate, boundary, end)
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable concatMap(
@NonNull Function> mapper,
int prefetch) {
ObjectHelper.requireNonNull(mapper, "mapper is null");
ObjectHelper.verifyPositive(prefetch, "prefetch");
return RxJavaPlugins.onAssembly(new ParallelConcatMap(this, mapper, prefetch, ErrorMode.IMMEDIATE));
}
/**
* Generates and concatenates Publishers on each 'rail', optionally delaying errors
* and generating 2 publishers upfront.
*
* @param the result type
* @param mapper the function to map each rail's value into a Publisher
* @param tillTheEnd if true all errors from the upstream and inner Publishers are delayed
* till all of them terminate, if false, the error is emitted when an inner Publisher terminates.
* source and the inner Publishers (immediate, boundary, end)
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable concatMapDelayError(
@NonNull Function> mapper,
boolean tillTheEnd) {
return concatMapDelayError(mapper, 2, tillTheEnd);
}
/**
* Generates and concatenates Publishers on each 'rail', optionally delaying errors
* and using the given prefetch amount for generating Publishers upfront.
*
* @param the result type
* @param mapper the function to map each rail's value into a Publisher
* @param prefetch the number of items to prefetch from each inner Publisher
* @param tillTheEnd if true all errors from the upstream and inner Publishers are delayed
* till all of them terminate, if false, the error is emitted when an inner Publisher terminates.
* @return the new ParallelFlowable instance
*/
@CheckReturnValue
@NonNull
public final ParallelFlowable concatMapDelayError(
@NonNull Function> mapper,
int prefetch, boolean tillTheEnd) {
ObjectHelper.requireNonNull(mapper, "mapper is null");
ObjectHelper.verifyPositive(prefetch, "prefetch");
return RxJavaPlugins.onAssembly(new ParallelConcatMap(
this, mapper, prefetch, tillTheEnd ? ErrorMode.END : ErrorMode.BOUNDARY));
}
}