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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.rxjava3.parallel;
import java.util.*;
import java.util.stream.*;
import org.reactivestreams.*;
import io.reactivex.rxjava3.annotations.*;
import io.reactivex.rxjava3.core.*;
import io.reactivex.rxjava3.exceptions.MissingBackpressureException;
import io.reactivex.rxjava3.functions.*;
import io.reactivex.rxjava3.internal.functions.*;
import io.reactivex.rxjava3.internal.jdk8.*;
import io.reactivex.rxjava3.internal.operators.parallel.*;
import io.reactivex.rxjava3.internal.subscriptions.EmptySubscription;
import io.reactivex.rxjava3.internal.util.*;
import io.reactivex.rxjava3.plugins.RxJavaPlugins;
/**
* Abstract base class for parallel publishing of events signaled to an array of {@link Subscriber}s.
*
* Use {@link #from(Publisher)} to start processing a regular {@link Publisher} in 'rails'.
* Use {@link #runOn(Scheduler)} to introduce where each 'rail' should run on thread-vise.
* Use {@link #sequential()} to merge the sources back into a single {@link Flowable}.
*
*
History: 2.0.5 - experimental; 2.1 - beta
* @param the value type
* @since 2.2
*/
public abstract class ParallelFlowable<@NonNull T> {
/**
* Subscribes an array of {@link Subscriber}s to this {@code ParallelFlowable} and triggers
* the execution chain for all 'rails'.
*
* - Backpressure:
* - The backpressure behavior/expectation is determined by the supplied {@code Subscriber}.
* - Scheduler:
* - {@code subscribe} does not operate by default on a particular {@link Scheduler}.
*
*
* @param subscribers the subscribers array to run in parallel, the number
* of items must be equal to the parallelism level of this {@code ParallelFlowable}
* @throws NullPointerException if {@code subscribers} is {@code null}
* @see #parallelism()
*/
@BackpressureSupport(BackpressureKind.SPECIAL)
@SchedulerSupport(SchedulerSupport.NONE)
public abstract void subscribe(@NonNull Subscriber[] subscribers);
/**
* Returns the number of expected parallel {@link Subscriber}s.
* @return the number of expected parallel {@code Subscriber}s
*/
@CheckReturnValue
public abstract int parallelism();
/**
* Validates the number of subscribers and returns {@code true} if their number
* matches the parallelism level of this {@code ParallelFlowable}.
*
* @param subscribers the array of {@link Subscriber}s
* @return {@code true} if the number of subscribers equals to the parallelism level
* @throws NullPointerException if {@code subscribers} is {@code null}
* @throws IllegalArgumentException if {@code subscribers.length} is different from {@link #parallelism()}
*/
protected final boolean validate(@NonNull Subscriber<@NonNull ?>[] subscribers) {
Objects.requireNonNull(subscribers, "subscribers is null");
int p = parallelism();
if (subscribers.length != p) {
Throwable iae = new IllegalArgumentException("parallelism = " + p + ", subscribers = " + subscribers.length);
for (Subscriber<@NonNull ?> s : subscribers) {
EmptySubscription.error(iae, s);
}
return false;
}
return true;
}
/**
* Take a {@link Publisher} and prepare to consume it on multiple 'rails' (number of CPUs)
* in a round-robin fashion.
*
* - Backpressure:
* - The operator honors the backpressure of the parallel rails and
* requests {@link Flowable#bufferSize} amount from the upstream, followed
* by 75% of that amount requested after every 75% received.
* - Scheduler:
* - {@code from} does not operate by default on a particular {@link Scheduler}.
*
* @param the value type
* @param source the source {@code Publisher}
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code source} is {@code null}
*/
@CheckReturnValue
@NonNull
@SchedulerSupport(SchedulerSupport.NONE)
@BackpressureSupport(BackpressureKind.FULL)
public static <@NonNull T> ParallelFlowable from(@NonNull Publisher source) {
return from(source, Runtime.getRuntime().availableProcessors(), Flowable.bufferSize());
}
/**
* Take a {@link Publisher} and prepare to consume it on parallelism number of 'rails' in a round-robin fashion.
*
* - Backpressure:
* - The operator honors the backpressure of the parallel rails and
* requests {@link Flowable#bufferSize} amount from the upstream, followed
* by 75% of that amount requested after every 75% received.
* - Scheduler:
* - {@code from} does not operate by default on a particular {@link Scheduler}.
*
* @param the value type
* @param source the source {@code Publisher}
* @param parallelism the number of parallel rails
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code source} is {@code null}
* @throws IllegalArgumentException if {@code parallelism} is non-positive
*/
@CheckReturnValue
@NonNull
@SchedulerSupport(SchedulerSupport.NONE)
@BackpressureSupport(BackpressureKind.FULL)
public static <@NonNull T> ParallelFlowable from(@NonNull Publisher source, int parallelism) {
return from(source, parallelism, Flowable.bufferSize());
}
/**
* Take a {@link 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 {@code Publisher}'s values.
*
* - Backpressure:
* - The operator honors the backpressure of the parallel rails and
* requests the {@code prefetch} amount from the upstream, followed
* by 75% of that amount requested after every 75% received.
* - Scheduler:
* - {@code from} does not operate by default on a particular {@link Scheduler}.
*
* @param the value type
* @param source the source {@code 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 {@code ParallelFlowable} instance
* @throws NullPointerException if {@code source} is {@code null}
* @throws IllegalArgumentException if {@code parallelism} or {@code prefetch} is non-positive
*/
@CheckReturnValue
@NonNull
@SchedulerSupport(SchedulerSupport.NONE)
@BackpressureSupport(BackpressureKind.FULL)
public static <@NonNull T> ParallelFlowable from(@NonNull Publisher source,
int parallelism, int prefetch) {
Objects.requireNonNull(source, "source is null");
ObjectHelper.verifyPositive(parallelism, "parallelism");
ObjectHelper.verifyPositive(prefetch, "prefetch");
return RxJavaPlugins.onAssembly(new ParallelFromPublisher<>(source, parallelism, prefetch));
}
/**
* Maps the source values on each 'rail' to another value.
*
* Note that the same {@code mapper} function may be called from multiple threads concurrently.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
* @param the output value type
* @param mapper the mapper function turning Ts into Rs.
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code mapper} is {@code null}
*/
@CheckReturnValue
@NonNull
@SchedulerSupport(SchedulerSupport.NONE)
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
public final <@NonNull R> ParallelFlowable map(@NonNull Function mapper) {
Objects.requireNonNull(mapper, "mapper is null");
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 {@code mapper} function may be called from multiple threads concurrently.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
* History: 2.0.8 - experimental
* @param the output value type
* @param mapper the mapper function turning Ts into Rs.
* @param errorHandler the enumeration that defines how to handle errors thrown
* from the {@code mapper} function
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code mapper} or {@code errorHandler} is {@code null}
* @since 2.2
*/
@CheckReturnValue
@NonNull
@SchedulerSupport(SchedulerSupport.NONE)
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
public final <@NonNull R> ParallelFlowable map(@NonNull Function mapper, @NonNull ParallelFailureHandling errorHandler) {
Objects.requireNonNull(mapper, "mapper is null");
Objects.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 {@code mapper} function may be called from multiple threads concurrently.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
* History: 2.0.8 - experimental
* @param the output value type
* @param mapper the mapper function turning Ts into Rs.
* @param errorHandler the function called with the current repeat count and
* failure {@link Throwable} and should return one of the {@link ParallelFailureHandling}
* enumeration values to indicate how to proceed.
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code mapper} or {@code errorHandler} is {@code null}
* @since 2.2
*/
@CheckReturnValue
@NonNull
@SchedulerSupport(SchedulerSupport.NONE)
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
public final <@NonNull R> ParallelFlowable map(@NonNull Function mapper, @NonNull BiFunction errorHandler) {
Objects.requireNonNull(mapper, "mapper is null");
Objects.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.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code filter} does not operate by default on a particular {@link Scheduler}.
*
* @param predicate the function returning {@code true} to keep a value or {@code false} to drop a value
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code predicate} is {@code null}
*/
@CheckReturnValue
@NonNull
@SchedulerSupport(SchedulerSupport.NONE)
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
public final ParallelFlowable filter(@NonNull Predicate predicate) {
Objects.requireNonNull(predicate, "predicate is null");
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.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code filter} does not operate by default on a particular {@link Scheduler}.
*
* History: 2.0.8 - experimental
* @param predicate the function returning {@code true} to keep a value or {@code false} to drop a value
* @param errorHandler the enumeration that defines how to handle errors thrown
* from the {@code predicate}
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code predicate} or {@code errorHandler} is {@code null}
* @since 2.2
*/
@CheckReturnValue
@NonNull
@SchedulerSupport(SchedulerSupport.NONE)
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
public final ParallelFlowable filter(@NonNull Predicate predicate, @NonNull ParallelFailureHandling errorHandler) {
Objects.requireNonNull(predicate, "predicate is null");
Objects.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.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
* History: 2.0.8 - experimental
* @param predicate the function returning {@code true} to keep a value or {@code false} to drop a value
* @param errorHandler the function called with the current repeat count and
* failure {@link Throwable} and should return one of the {@link ParallelFailureHandling}
* enumeration values to indicate how to proceed.
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code predicate} or {@code errorHandler} is {@code null}
* @since 2.2
*/
@CheckReturnValue
@NonNull
@SchedulerSupport(SchedulerSupport.NONE)
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
public final ParallelFlowable filter(@NonNull Predicate predicate, @NonNull BiFunction errorHandler) {
Objects.requireNonNull(predicate, "predicate is null");
Objects.requireNonNull(errorHandler, "errorHandler is null");
return RxJavaPlugins.onAssembly(new ParallelFilterTry<>(this, predicate, errorHandler));
}
/**
* Specifies where each 'rail' will observe its incoming values, specified via a {@link Scheduler}, with
* no work-stealing and default prefetch amount.
*
* This operator uses the default prefetch size returned by {@link Flowable#bufferSize()}.
*
* The operator will call {@link Scheduler#createWorker()} as many
* times as this {@code ParallelFlowable}'s parallelism level is.
*
* No assumptions are made about the {@code Scheduler}'s parallelism level,
* if the {@code Scheduler}'s parallelism level is lower than the {@code ParallelFlowable}'s,
* some rails may end up on the same thread/worker.
*
* This operator doesn't require the {@code Scheduler} to be trampolining as it
* does its own built-in trampolining logic.
*
* - Backpressure:
* - The operator honors the backpressure of the parallel rails and
* requests {@link Flowable#bufferSize} amount from the upstream, followed
* by 75% of that amount requested after every 75% received.
* - Scheduler:
* - {@code runOn} drains the upstream rails on the specified {@code Scheduler}'s
* {@link io.reactivex.rxjava3.core.Scheduler.Worker Worker}s.
*
*
* @param scheduler the scheduler to use
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code scheduler} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.CUSTOM)
public final ParallelFlowable runOn(@NonNull Scheduler scheduler) {
return runOn(scheduler, Flowable.bufferSize());
}
/**
* Specifies where each 'rail' will observe its incoming values, specified via a {@link Scheduler}, with
* possibly work-stealing and a given prefetch amount.
*
* This operator uses the default prefetch size returned by {@link Flowable#bufferSize()}.
*
* The operator will call {@link Scheduler#createWorker()} as many
* times as this {@code ParallelFlowable}'s parallelism level is.
*
* No assumptions are made about the {@code Scheduler}'s parallelism level,
* if the {@code Scheduler}'s parallelism level is lower than the {@code ParallelFlowable}'s,
* some rails may end up on the same thread/worker.
*
* This operator doesn't require the {@code Scheduler} to be trampolining as it
* does its own built-in trampolining logic.
*
* - Backpressure:
* - The operator honors the backpressure of the parallel rails and
* requests the {@code prefetch} amount from the upstream, followed
* by 75% of that amount requested after every 75% received.
* - Scheduler:
* - {@code runOn} drains the upstream rails on the specified {@code Scheduler}'s
* {@link io.reactivex.rxjava3.core.Scheduler.Worker Worker}s.
*
*
* @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 {@code ParallelFlowable} instance
* @throws NullPointerException if {@code scheduler} is {@code null}
* @throws IllegalArgumentException if {@code prefetch} is non-positive
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.CUSTOM)
public final ParallelFlowable runOn(@NonNull Scheduler scheduler, int prefetch) {
Objects.requireNonNull(scheduler, "scheduler is null");
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 one
* {@link Flowable} sequence.
*
* Note that the same reducer function may be called from multiple threads concurrently.
*
* - Backpressure:
* - The operator honors backpressure from the downstream and consumes
* the upstream rails in an unbounded manner (requesting {@link Long#MAX_VALUE}).
* - Scheduler:
* - {@code reduce} does not operate by default on a particular {@link Scheduler}.
*
* @param reducer the function to reduce two values into one.
* @return the new {@code Flowable} instance emitting the reduced value or empty if the current {@code ParallelFlowable} is empty
* @throws NullPointerException if {@code reducer} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.UNBOUNDED_IN)
@SchedulerSupport(SchedulerSupport.NONE)
public final Flowable reduce(@NonNull BiFunction reducer) {
Objects.requireNonNull(reducer, "reducer is null");
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 {@code initialSupplier} value.
*
* Note that the same mapper function may be called from multiple threads concurrently.
*
* - Backpressure:
* - The operator honors backpressure from the downstream rails and consumes
* the upstream rails in an unbounded manner (requesting {@link Long#MAX_VALUE}).
* - Scheduler:
* - {@code reduce} does not operate by default on a particular {@link Scheduler}.
*
* @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 {@code ParallelFlowable} instance
* @throws NullPointerException if {@code initialSupplier} or {@code reducer} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.UNBOUNDED_IN)
@SchedulerSupport(SchedulerSupport.NONE)
public final <@NonNull R> ParallelFlowable reduce(@NonNull Supplier initialSupplier, @NonNull BiFunction reducer) {
Objects.requireNonNull(initialSupplier, "initialSupplier is null");
Objects.requireNonNull(reducer, "reducer is null");
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 {@link Flowable} 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 from the downstream and
* requests {@link Flowable#bufferSize()} amount from each rail, then
* requests from each rail 75% of this amount after 75% received.
* - Scheduler:
* - {@code sequential} does not operate by default on a particular {@link Scheduler}.
*
* @return the new {@code Flowable} instance
* @see ParallelFlowable#sequential(int)
* @see ParallelFlowable#sequentialDelayError()
*/
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
@CheckReturnValue
@NonNull
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 {@link Flowable} sequence, running with a give prefetch value
* for the rails.
*
*
* - Backpressure:
* - The operator honors backpressure from the downstream and
* requests the {@code prefetch} amount from each rail, then
* requests from each rail 75% of this amount after 75% received.
* - 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 {@code Flowable} instance
* @throws IllegalArgumentException if {@code prefetch} is non-positive
* @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 {@link 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 from the downstream and
* requests {@link Flowable#bufferSize()} amount from each rail, then
* requests from each rail 75% of this amount after 75% received.
* - Scheduler:
* - {@code sequentialDelayError} does not operate by default on a particular {@link Scheduler}.
*
* History: 2.0.7 - experimental
* @return the new {@code 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 {@link Flowable} sequence, running with a give prefetch value
* for the rails and delaying errors from all rails till all terminate.
*
*
* - Backpressure:
* - The operator honors backpressure from the downstream and
* requests the {@code prefetch} amount from each rail, then
* requests from each rail 75% of this amount after 75% received.
* - 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 {@code Flowable} instance
* @throws IllegalArgumentException if {@code prefetch} is non-positive
* @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 {@code ParallelFlowable} and returns a {@link Flowable} that sequentially
* picks the smallest next value from the rails.
*
* This operator requires a finite source {@code ParallelFlowable}.
*
* - Backpressure:
* - The operator honors backpressure from the downstream and
* consumes the upstream rails in an unbounded manner (requesting {@link Long#MAX_VALUE}).
* - Scheduler:
* - {@code sorted} does not operate by default on a particular {@link Scheduler}.
*
*
* @param comparator the comparator to use
* @return the new {@code Flowable} instance
* @throws NullPointerException if {@code comparator} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.UNBOUNDED_IN)
@SchedulerSupport(SchedulerSupport.NONE)
public final Flowable sorted(@NonNull Comparator comparator) {
return sorted(comparator, 16);
}
/**
* Sorts the 'rails' of this {@code ParallelFlowable} and returns a {@link Flowable} that sequentially
* picks the smallest next value from the rails.
*
* This operator requires a finite source {@code ParallelFlowable}.
*
* - Backpressure:
* - The operator honors backpressure from the downstream and
* consumes the upstream rails in an unbounded manner (requesting {@link Long#MAX_VALUE}).
* - Scheduler:
* - {@code sorted} does not operate by default on a particular {@link Scheduler}.
*
*
* @param comparator the comparator to use
* @param capacityHint the expected number of total elements
* @return the new {@code Flowable} instance
* @throws NullPointerException if {@code comparator} is {@code null}
* @throws IllegalArgumentException if {@code capacityHint} is non-positive
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.UNBOUNDED_IN)
@SchedulerSupport(SchedulerSupport.NONE)
public final Flowable sorted(@NonNull Comparator comparator, int capacityHint) {
Objects.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 {@link List} as a {@link Flowable}.
*
* This operator requires a finite source {@code ParallelFlowable}.
*
* - Backpressure:
* - The operator honors backpressure from the downstream and
* consumes the upstream rails in an unbounded manner (requesting {@link Long#MAX_VALUE}).
* - Scheduler:
* - {@code toSortedList} does not operate by default on a particular {@link Scheduler}.
*
*
* @param comparator the comparator to compare elements
* @return the new {@code Flowable} instance
* @throws NullPointerException if {@code comparator} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.UNBOUNDED_IN)
@SchedulerSupport(SchedulerSupport.NONE)
public final Flowable> toSortedList(@NonNull Comparator comparator) {
return toSortedList(comparator, 16);
}
/**
* Sorts the 'rails' according to the comparator and returns a full sorted {@link List} as a {@link Flowable}.
*
* This operator requires a finite source {@code ParallelFlowable}.
*
* - Backpressure:
* - The operator honors backpressure from the downstream and
* consumes the upstream rails in an unbounded manner (requesting {@link Long#MAX_VALUE}).
* - Scheduler:
* - {@code toSortedList} does not operate by default on a particular {@link Scheduler}.
*
*
* @param comparator the comparator to compare elements
* @param capacityHint the expected number of total elements
* @return the new {@code Flowable} instance
* @throws NullPointerException if {@code comparator} is {@code null}
* @throws IllegalArgumentException if {@code capacityHint} is non-positive
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.UNBOUNDED_IN)
@SchedulerSupport(SchedulerSupport.NONE)
public final Flowable<@NonNull List> toSortedList(@NonNull Comparator comparator, int capacityHint) {
Objects.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'.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
*
* @param onNext the callback
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code onNext} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
@SchedulerSupport(SchedulerSupport.NONE)
public final ParallelFlowable doOnNext(@NonNull Consumer onNext) {
Objects.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.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
* History: 2.0.8 - experimental
* @param onNext the callback
* @param errorHandler the enumeration that defines how to handle errors thrown
* from the {@code onNext} consumer
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code onNext} or {@code errorHandler} is {@code null}
* @since 2.2
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
@SchedulerSupport(SchedulerSupport.NONE)
public final ParallelFlowable doOnNext(@NonNull Consumer onNext, @NonNull ParallelFailureHandling errorHandler) {
Objects.requireNonNull(onNext, "onNext is null");
Objects.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.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
* History: 2.0.8 - experimental
* @param onNext the callback
* @param errorHandler the function called with the current repeat count and
* failure {@link Throwable} and should return one of the {@link ParallelFailureHandling}
* enumeration values to indicate how to proceed.
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code onNext} or {@code errorHandler} is {@code null}
* @since 2.2
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
@SchedulerSupport(SchedulerSupport.NONE)
public final ParallelFlowable doOnNext(@NonNull Consumer onNext, @NonNull BiFunction errorHandler) {
Objects.requireNonNull(onNext, "onNext is null");
Objects.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.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
*
* @param onAfterNext the callback
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code onAfterNext} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
@SchedulerSupport(SchedulerSupport.NONE)
public final ParallelFlowable doAfterNext(@NonNull Consumer onAfterNext) {
Objects.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'.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
*
* @param onError the callback
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code onError} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
@SchedulerSupport(SchedulerSupport.NONE)
public final ParallelFlowable doOnError(@NonNull Consumer onError) {
Objects.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 {@link Action} when a 'rail' completes.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
*
* @param onComplete the callback
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code onComplete} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
@SchedulerSupport(SchedulerSupport.NONE)
public final ParallelFlowable doOnComplete(@NonNull Action onComplete) {
Objects.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 {@link Action} when a 'rail' completes or signals an error.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
*
* @param onAfterTerminate the callback
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code onAfterTerminate} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
@SchedulerSupport(SchedulerSupport.NONE)
public final ParallelFlowable doAfterTerminated(@NonNull Action onAfterTerminate) {
Objects.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 {@link Subscription} from its upstream.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
*
* @param onSubscribe the callback
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code onSubscribe} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
@SchedulerSupport(SchedulerSupport.NONE)
public final ParallelFlowable doOnSubscribe(@NonNull Consumer onSubscribe) {
Objects.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.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
*
* @param onRequest the callback
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code onRequest} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
@SchedulerSupport(SchedulerSupport.NONE)
public final ParallelFlowable doOnRequest(@NonNull LongConsumer onRequest) {
Objects.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 {@link Action} when a 'rail' receives a cancellation.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
*
* @param onCancel the callback
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code onCancel} is {@code null}
*/
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
@SchedulerSupport(SchedulerSupport.NONE)
@CheckReturnValue
@NonNull
public final ParallelFlowable doOnCancel(@NonNull Action onCancel) {
Objects.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 {@code collectionSupplier}
* and collected into with a collector action, emitting the collection at the end.
*
* - Backpressure:
* - The operator honors backpressure from the downstream rails and
* consumes the upstream rails in an unbounded manner (requesting {@link Long#MAX_VALUE}).
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
*
* @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 {@code ParallelFlowable} instance
* @throws NullPointerException if {@code collectionSupplier} or {@code collector} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.UNBOUNDED_IN)
@SchedulerSupport(SchedulerSupport.NONE)
public final <@NonNull C> ParallelFlowable collect(@NonNull Supplier collectionSupplier, @NonNull BiConsumer collector) {
Objects.requireNonNull(collectionSupplier, "collectionSupplier is null");
Objects.requireNonNull(collector, "collector is null");
return RxJavaPlugins.onAssembly(new ParallelCollect<>(this, collectionSupplier, collector));
}
/**
* Wraps multiple {@link Publisher}s into a {@code ParallelFlowable} which runs them
* in parallel and unordered.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
*
* @param the value type
* @param publishers the array of publishers
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code publishers} is {@code null}
* @throws IllegalArgumentException if {@code publishers} is an empty array
*/
@CheckReturnValue
@NonNull
@SafeVarargs
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
@SchedulerSupport(SchedulerSupport.NONE)
public static <@NonNull T> ParallelFlowable fromArray(@NonNull Publisher... publishers) {
Objects.requireNonNull(publishers, "publishers is null");
if (publishers.length == 0) {
throw new IllegalArgumentException("Zero publishers not supported");
}
return RxJavaPlugins.onAssembly(new ParallelFromArray<>(publishers));
}
/**
* Calls the specified converter function during assembly time and returns its resulting value.
*
* This allows fluent conversion to any other type.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by how the converter function composes over the upstream source.
* - Scheduler:
* - {@code to} does not operate by default on a particular {@link Scheduler}.
*
* History: 2.1.7 - experimental
* @param the resulting object type
* @param converter the function that receives the current {@code ParallelFlowable} instance and returns a value
* @return the converted value
* @throws NullPointerException if {@code converter} is {@code null}
* @since 2.2
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
@SchedulerSupport(SchedulerSupport.NONE)
public final <@NonNull R> R to(@NonNull ParallelFlowableConverter converter) {
return Objects.requireNonNull(converter, "converter is null").apply(this);
}
/**
* Allows composing operators, in assembly time, on top of this {@code ParallelFlowable}
* and returns another {@code ParallelFlowable} with composed features.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by how the converter function composes over the upstream source.
* - Scheduler:
* - {@code compose} does not operate by default on a particular {@link Scheduler}.
*
*
* @param the output value type
* @param composer the composer function from {@code ParallelFlowable} (this) to another {@code ParallelFlowable}
* @return the {@code ParallelFlowable} returned by the function
* @throws NullPointerException if {@code composer} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
@SchedulerSupport(SchedulerSupport.NONE)
public final <@NonNull U> ParallelFlowable compose(@NonNull ParallelTransformer composer) {
return RxJavaPlugins.onAssembly(Objects.requireNonNull(composer, "composer is null").apply(this));
}
/**
* Generates and flattens {@link Publisher}s on each 'rail'.
*
* The errors are not delayed and uses unbounded concurrency along with default inner prefetch.
*
* - Backpressure:
* - The operator honors backpressure from the downstream rails and
* requests {@link Flowable#bufferSize()} amount from each rail upfront
* and keeps requesting as many items per rail as many inner sources on
* that rail completed. The inner sources are requested {@link Flowable#bufferSize()}
* amount upfront, then 75% of this amount requested after 75% received.
* - Scheduler:
* - {@code flatMap} does not operate by default on a particular {@link Scheduler}.
*
*
* @param the result type
* @param mapper the function to map each rail's value into a {@code Publisher}
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code mapper} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
public final <@NonNull R> ParallelFlowable flatMap(@NonNull Function> mapper) {
return flatMap(mapper, false, Flowable.bufferSize(), Flowable.bufferSize());
}
/**
* Generates and flattens {@link Publisher}s on each 'rail', optionally delaying errors.
*
* It uses unbounded concurrency along with default inner prefetch.
*
* - Backpressure:
* - The operator honors backpressure from the downstream rails and
* requests {@link Flowable#bufferSize()} amount from each rail upfront
* and keeps requesting as many items per rail as many inner sources on
* that rail completed. The inner sources are requested {@link Flowable#bufferSize()}
* amount upfront, then 75% of this amount requested after 75% received.
*
* - Scheduler:
* - {@code flatMap} does not operate by default on a particular {@link Scheduler}.
*
*
* @param the result type
* @param mapper the function to map each rail's value into a {@code Publisher}
* @param delayError should the errors from the main and the inner sources delayed till everybody terminates?
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code mapper} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
public final <@NonNull R> ParallelFlowable flatMap(
@NonNull Function> mapper, boolean delayError) {
return flatMap(mapper, delayError, Flowable.bufferSize(), Flowable.bufferSize());
}
/**
* Generates and flattens {@link Publisher}s on each 'rail', optionally delaying errors
* and having a total number of simultaneous subscriptions to the inner {@code Publisher}s.
*
* It uses a default inner prefetch.
*
* - Backpressure:
* - The operator honors backpressure from the downstream rails and
* requests {@code maxConcurrency} amount from each rail upfront
* and keeps requesting as many items per rail as many inner sources on
* that rail completed. The inner sources are requested {@link Flowable#bufferSize()}
* amount upfront, then 75% of this amount requested after 75% received.
*
* - Scheduler:
* - {@code flatMap} does not operate by default on a particular {@link Scheduler}.
*
*
* @param the result type
* @param mapper the function to map each rail's value into a {@code 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 {@code Publisher}s
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code mapper} is {@code null}
* @throws IllegalArgumentException if {@code maxConcurrency} is non-positive
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
public final <@NonNull R> ParallelFlowable flatMap(
@NonNull Function> mapper, boolean delayError, int maxConcurrency) {
return flatMap(mapper, delayError, maxConcurrency, Flowable.bufferSize());
}
/**
* Generates and flattens {@link Publisher}s on each 'rail', optionally delaying errors,
* having a total number of simultaneous subscriptions to the inner {@code Publisher}s
* and using the given prefetch amount for the inner {@code Publisher}s.
*
* - Backpressure:
* - The operator honors backpressure from the downstream rails and
* requests {@code maxConcurrency} amount from each rail upfront
* and keeps requesting as many items per rail as many inner sources on
* that rail completed. The inner sources are requested the {@code prefetch}
* amount upfront, then 75% of this amount requested after 75% received.
*
* - Scheduler:
* - {@code flatMap} does not operate by default on a particular {@link Scheduler}.
*
*
* @param the result type
* @param mapper the function to map each rail's value into a {@code 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 {@code Publisher}s
* @param prefetch the number of items to prefetch from each inner {@code Publisher}
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code mapper} is {@code null}
* @throws IllegalArgumentException if {@code maxConcurrency} or {@code prefetch} is non-positive
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
public final <@NonNull R> ParallelFlowable flatMap(
@NonNull Function> mapper,
boolean delayError, int maxConcurrency, int prefetch) {
Objects.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 {@link Publisher}s on each 'rail', signalling errors immediately
* and generating 2 publishers upfront.
*
* - Backpressure:
* - The operator honors backpressure from the downstream rails and
* requests 2 from each rail upfront and keeps requesting 1 when the inner source complete.
* Requests for the inner sources are determined by the downstream rails'
* backpressure behavior.
* - Scheduler:
* - {@code concatMap} does not operate by default on a particular {@link Scheduler}.
*
*
* @param the result type
* @param mapper the function to map each rail's value into a {@code Publisher}
* source and the inner {@code Publisher}s (immediate, boundary, end)
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code mapper} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
public final <@NonNull R> ParallelFlowable concatMap(
@NonNull Function> mapper) {
return concatMap(mapper, 2);
}
/**
* Generates and concatenates {@link Publisher}s on each 'rail', signalling errors immediately
* and using the given prefetch amount for generating {@code Publisher}s upfront.
*
* - Backpressure:
* - The operator honors backpressure from the downstream rails and
* requests the {@code prefetch} amount from each rail upfront and keeps
* requesting 75% of this amount after 75% received and the inner sources completed.
* Requests for the inner sources are determined by the downstream rails'
* backpressure behavior.
* - Scheduler:
* - {@code concatMap} does not operate by default on a particular {@link Scheduler}.
*
*
* @param the result type
* @param mapper the function to map each rail's value into a {@code Publisher}
* @param prefetch the number of items to prefetch from each inner {@code Publisher}
* source and the inner {@code Publisher}s (immediate, boundary, end)
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code mapper} is {@code null}
* @throws IllegalArgumentException if {@code prefetch} is non-positive
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
public final <@NonNull R> ParallelFlowable concatMap(
@NonNull Function> mapper,
int prefetch) {
Objects.requireNonNull(mapper, "mapper is null");
ObjectHelper.verifyPositive(prefetch, "prefetch");
return RxJavaPlugins.onAssembly(new ParallelConcatMap<>(this, mapper, prefetch, ErrorMode.IMMEDIATE));
}
/**
* Generates and concatenates {@link Publisher}s on each 'rail', optionally delaying errors
* and generating 2 publishers upfront.
*
* - Backpressure:
* - The operator honors backpressure from the downstream rails and
* requests 2 from each rail upfront and keeps requesting 1 when the inner source complete.
* Requests for the inner sources are determined by the downstream rails'
* backpressure behavior.
* - Scheduler:
* - {@code concatMap} does not operate by default on a particular {@link Scheduler}.
*
*
* @param the result type
* @param mapper the function to map each rail's value into a {@code Publisher}
* @param tillTheEnd if {@code true}, all errors from the upstream and inner {@code Publisher}s are delayed
* till all of them terminate, if {@code false}, the error is emitted when an inner {@code Publisher} terminates.
* source and the inner {@code Publisher}s (immediate, boundary, end)
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code mapper} is {@code null}
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
public final <@NonNull R> ParallelFlowable concatMapDelayError(
@NonNull Function> mapper,
boolean tillTheEnd) {
return concatMapDelayError(mapper, 2, tillTheEnd);
}
/**
* Generates and concatenates {@link Publisher}s on each 'rail', optionally delaying errors
* and using the given prefetch amount for generating {@code Publisher}s upfront.
*
* - Backpressure:
* - The operator honors backpressure from the downstream rails and
* requests the {@code prefetch} amount from each rail upfront and keeps
* requesting 75% of this amount after 75% received and the inner sources completed.
* Requests for the inner sources are determined by the downstream rails'
* backpressure behavior.
* - Scheduler:
* - {@code concatMap} does not operate by default on a particular {@link Scheduler}.
*
*
* @param the result type
* @param mapper the function to map each rail's value into a {@code Publisher}
* @param prefetch the number of items to prefetch from each inner {@code Publisher}
* @param tillTheEnd if {@code true}, all errors from the upstream and inner {@code Publisher}s are delayed
* till all of them terminate, if {@code false}, the error is emitted when an inner {@code Publisher} terminates.
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code mapper} is {@code null}
* @throws IllegalArgumentException if {@code prefetch} is non-positive
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
public final <@NonNull R> ParallelFlowable concatMapDelayError(
@NonNull Function> mapper,
int prefetch, boolean tillTheEnd) {
Objects.requireNonNull(mapper, "mapper is null");
ObjectHelper.verifyPositive(prefetch, "prefetch");
return RxJavaPlugins.onAssembly(new ParallelConcatMap<>(
this, mapper, prefetch, tillTheEnd ? ErrorMode.END : ErrorMode.BOUNDARY));
}
/**
* Returns a {@code ParallelFlowable} that merges each item emitted by the source on each rail with the values in an
* {@link Iterable} corresponding to that item that is generated by a selector.
*
* 
*
* - Backpressure:
* - The operator honors backpressure from each downstream rail. The source {@code ParallelFlowable}s is
* expected to honor backpressure as well. If the source {@code ParallelFlowable} violates the rule, the operator will
* signal a {@link MissingBackpressureException}.
* - Scheduler:
* - {@code flatMapIterable} does not operate by default on a particular {@link Scheduler}.
*
*
* @param
* the type of item emitted by the resulting {@code Iterable}
* @param mapper
* a function that returns an {@code Iterable} sequence of values for when given an item emitted by the
* source {@code ParallelFlowable}
* @return the new {@code ParallelFlowable} instance
* @see ReactiveX operators documentation: FlatMap
* @see #flatMapStream(Function)
* @since 3.0.0
* @throws NullPointerException if {@code mapper} is {@code null}
*/
@CheckReturnValue
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
@NonNull
public final <@NonNull U> ParallelFlowable flatMapIterable(@NonNull Function> mapper) {
return flatMapIterable(mapper, Flowable.bufferSize());
}
/**
* Returns a {@code ParallelFlowable} that merges each item emitted by the source {@code ParallelFlowable} with the values in an
* {@link Iterable} corresponding to that item that is generated by a selector.
*
*
*
* - Backpressure:
* - The operator honors backpressure from each downstream rail. The source {@code ParallelFlowable}s is
* expected to honor backpressure as well. If the source {@code ParallelFlowable} violates the rule, the operator will
* signal a {@link MissingBackpressureException}.
* - Scheduler:
* - {@code flatMapIterable} does not operate by default on a particular {@link Scheduler}.
*
*
* @param
* the type of item emitted by the resulting {@code Iterable}
* @param mapper
* a function that returns an {@code Iterable} sequence of values for when given an item emitted by the
* source {@code ParallelFlowable}
* @param bufferSize
* the number of elements to prefetch from each upstream rail
* @return the new {@code ParallelFlowable} instance
* @see ReactiveX operators documentation: FlatMap
* @see #flatMapStream(Function, int)
* @since 3.0.0
* @throws NullPointerException if {@code mapper} is {@code null}
* @throws IllegalArgumentException if {@code bufferSize} is non-positive
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
public final <@NonNull U> ParallelFlowable flatMapIterable(@NonNull Function> mapper, int bufferSize) {
Objects.requireNonNull(mapper, "mapper is null");
ObjectHelper.verifyPositive(bufferSize, "bufferSize");
return RxJavaPlugins.onAssembly(new ParallelFlatMapIterable<>(this, mapper, bufferSize));
}
// -------------------------------------------------------------------------
// JDK 8 Support
// -------------------------------------------------------------------------
/**
* Maps the source values on each 'rail' to an optional and emits its value if any.
*
* Note that the same mapper function may be called from multiple threads concurrently.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
* @param the output value type
* @param mapper the mapper function turning Ts into optional of Rs.
* @return the new {@code ParallelFlowable} instance
* @since 3.0.0
* @throws NullPointerException if {@code mapper} is {@code null}
*/
@CheckReturnValue
@NonNull
@SchedulerSupport(SchedulerSupport.NONE)
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
public final <@NonNull R> ParallelFlowable mapOptional(@NonNull Function> mapper) {
Objects.requireNonNull(mapper, "mapper is null");
return RxJavaPlugins.onAssembly(new ParallelMapOptional<>(this, mapper));
}
/**
* Maps the source values on each 'rail' to an optional and emits its value if any and
* handles errors based on the given {@link ParallelFailureHandling} enumeration value.
*
* Note that the same mapper function may be called from multiple threads concurrently.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
* History: 2.0.8 - experimental
* @param the output value type
* @param mapper the mapper function turning Ts into optional of Rs.
* @param errorHandler the enumeration that defines how to handle errors thrown
* from the mapper function
* @return the new {@code ParallelFlowable} instance
* @since 3.0.0
* @throws NullPointerException if {@code mapper} or {@code errorHandler} is {@code null}
*/
@CheckReturnValue
@NonNull
@SchedulerSupport(SchedulerSupport.NONE)
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
public final <@NonNull R> ParallelFlowable mapOptional(@NonNull Function> mapper, @NonNull ParallelFailureHandling errorHandler) {
Objects.requireNonNull(mapper, "mapper is null");
Objects.requireNonNull(errorHandler, "errorHandler is null");
return RxJavaPlugins.onAssembly(new ParallelMapTryOptional<>(this, mapper, errorHandler));
}
/**
* Maps the source values on each 'rail' to an optional and emits its value if any 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.
*
* - Backpressure:
* - The operator is a pass-through for backpressure and the behavior
* is determined by the upstream and downstream rail behaviors.
* - Scheduler:
* - {@code map} does not operate by default on a particular {@link Scheduler}.
*
* History: 2.0.8 - experimental
* @param the output value type
* @param mapper the mapper function turning Ts into optional of Rs.
* @param errorHandler the function called with the current repeat count and
* failure {@link Throwable} and should return one of the {@link ParallelFailureHandling}
* enumeration values to indicate how to proceed.
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code mapper} or {@code errorHandler} is {@code null}
* @since 3.0.0
*/
@CheckReturnValue
@NonNull
@SchedulerSupport(SchedulerSupport.NONE)
@BackpressureSupport(BackpressureKind.PASS_THROUGH)
public final <@NonNull R> ParallelFlowable mapOptional(@NonNull Function> mapper, @NonNull BiFunction errorHandler) {
Objects.requireNonNull(mapper, "mapper is null");
Objects.requireNonNull(errorHandler, "errorHandler is null");
return RxJavaPlugins.onAssembly(new ParallelMapTryOptional<>(this, mapper, errorHandler));
}
/**
* Maps each upstream item on each rail into a {@link Stream} and emits the {@code Stream}'s items to the downstream in a sequential fashion.
*
* 
*
* Due to the blocking and sequential nature of Java {@code Stream}s, the streams are mapped and consumed in a sequential fashion
* without interleaving (unlike a more general {@link #flatMap(Function)}). Therefore, {@code flatMapStream} and
* {@code concatMapStream} are identical operators and are provided as aliases.
*
* The operator closes the {@code Stream} upon cancellation and when it terminates. The exceptions raised when
* closing a {@code Stream} are routed to the global error handler ({@link RxJavaPlugins#onError(Throwable)}.
* If a {@code Stream} should not be closed, turn it into an {@link Iterable} and use {@link #flatMapIterable(Function)}:
*
* source.flatMapIterable(v -> createStream(v)::iterator);
*
*
* Note that {@code Stream}s can be consumed only once; any subsequent attempt to consume a {@code Stream}
* will result in an {@link IllegalStateException}.
*
* Primitive streams are not supported and items have to be boxed manually (e.g., via {@link IntStream#boxed()}):
*
* source.flatMapStream(v -> IntStream.rangeClosed(v + 1, v + 10).boxed());
*
*
* {@code Stream} does not support concurrent usage so creating and/or consuming the same instance multiple times
* from multiple threads can lead to undefined behavior.
*
* - Backpressure:
* - The operator honors the downstream backpressure and consumes the inner stream only on demand. The operator
* prefetches {@link Flowable#bufferSize()} items of the upstream (then 75% of it after the 75% received)
* and caches them until they are ready to be mapped into {@code Stream}s
* after the current {@code Stream} has been consumed.
* - Scheduler:
* - {@code flatMapStream} does not operate by default on a particular {@link Scheduler}.
*
*
* @param the element type of the {@code Stream}s and the result
* @param mapper the function that receives an upstream item and should return a {@code Stream} whose elements
* will be emitted to the downstream
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code mapper} is {@code null}
* @see #flatMap(Function)
* @see #flatMapIterable(Function)
* @see #flatMapStream(Function, int)
* @since 3.0.0
*/
@CheckReturnValue
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
@NonNull
public final <@NonNull R> ParallelFlowable flatMapStream(@NonNull Function> mapper) {
return flatMapStream(mapper, Flowable.bufferSize());
}
/**
* Maps each upstream item of each rail into a {@link Stream} and emits the {@code Stream}'s items to the downstream in a sequential fashion.
*
* 
*
* Due to the blocking and sequential nature of Java {@code Stream}s, the streams are mapped and consumed in a sequential fashion
* without interleaving (unlike a more general {@link #flatMap(Function)}). Therefore, {@code flatMapStream} and
* {@code concatMapStream} are identical operators and are provided as aliases.
*
* The operator closes the {@code Stream} upon cancellation and when it terminates. The exceptions raised when
* closing a {@code Stream} are routed to the global error handler ({@link RxJavaPlugins#onError(Throwable)}.
* If a {@code Stream} should not be closed, turn it into an {@link Iterable} and use {@link #flatMapIterable(Function, int)}:
*
* source.flatMapIterable(v -> createStream(v)::iterator, 32);
*
*
* Note that {@code Stream}s can be consumed only once; any subsequent attempt to consume a {@code Stream}
* will result in an {@link IllegalStateException}.
*
* Primitive streams are not supported and items have to be boxed manually (e.g., via {@link IntStream#boxed()}):
*
* source.flatMapStream(v -> IntStream.rangeClosed(v + 1, v + 10).boxed(), 32);
*
*
* {@code Stream} does not support concurrent usage so creating and/or consuming the same instance multiple times
* from multiple threads can lead to undefined behavior.
*
* - Backpressure:
* - The operator honors the downstream backpressure and consumes the inner stream only on demand. The operator
* prefetches the given amount of upstream items and caches them until they are ready to be mapped into {@code Stream}s
* after the current {@code Stream} has been consumed.
* - Scheduler:
* - {@code flatMapStream} does not operate by default on a particular {@link Scheduler}.
*
*
* @param the element type of the {@code Stream}s and the result
* @param mapper the function that receives an upstream item and should return a {@code Stream} whose elements
* will be emitted to the downstream
* @param prefetch the number of upstream items to request upfront, then 75% of this amount after each 75% upstream items received
* @return the new {@code ParallelFlowable} instance
* @throws NullPointerException if {@code mapper} is {@code null}
* @throws IllegalArgumentException if {@code prefetch} is non-positive
* @see #flatMap(Function, boolean, int)
* @see #flatMapIterable(Function, int)
* @since 3.0.0
*/
@CheckReturnValue
@BackpressureSupport(BackpressureKind.FULL)
@SchedulerSupport(SchedulerSupport.NONE)
@NonNull
public final <@NonNull R> ParallelFlowable flatMapStream(@NonNull Function> mapper, int prefetch) {
Objects.requireNonNull(mapper, "mapper is null");
ObjectHelper.verifyPositive(prefetch, "prefetch");
return RxJavaPlugins.onAssembly(new ParallelFlatMapStream<>(this, mapper, prefetch));
}
/**
* Reduces all values within a 'rail' and across 'rails' with a callbacks
* of the given {@link Collector} into one {@link Flowable} containing a single value.
*
* Each parallel rail receives its own {@link Collector#accumulator()} and
* {@link Collector#combiner()}.
*
* - Backpressure:
* - The operator honors backpressure from the downstream and consumes
* the upstream rails in an unbounded manner (requesting {@link Long#MAX_VALUE}).
* - Scheduler:
* - {@code collect} does not operate by default on a particular {@link Scheduler}.
*
* @param the accumulator type
* @param the output value type
* @param collector the {@code Collector} instance
* @return the new {@code Flowable} instance emitting the collected value.
* @throws NullPointerException if {@code collector} is {@code null}
* @since 3.0.0
*/
@CheckReturnValue
@NonNull
@BackpressureSupport(BackpressureKind.UNBOUNDED_IN)
@SchedulerSupport(SchedulerSupport.NONE)
public final <@NonNull A, @NonNull R> Flowable collect(@NonNull Collector collector) {
Objects.requireNonNull(collector, "collector is null");
return RxJavaPlugins.onAssembly(new ParallelCollector<>(this, collector));
}
}