8187443: Forest Consolidation: Move files to unified layout

Reviewed-by: darcy, ihse
This commit is contained in:
Erik Joelsson 2017-09-12 19:03:39 +02:00
parent 270fe13182
commit 3789983e89
56923 changed files with 3 additions and 15727 deletions

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/*
* Copyright (c) 2012, 2016, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Objects;
import java.util.Spliterator;
import java.util.function.IntFunction;
import java.util.function.Supplier;
/**
* Abstract base class for "pipeline" classes, which are the core
* implementations of the Stream interface and its primitive specializations.
* Manages construction and evaluation of stream pipelines.
*
* <p>An {@code AbstractPipeline} represents an initial portion of a stream
* pipeline, encapsulating a stream source and zero or more intermediate
* operations. The individual {@code AbstractPipeline} objects are often
* referred to as <em>stages</em>, where each stage describes either the stream
* source or an intermediate operation.
*
* <p>A concrete intermediate stage is generally built from an
* {@code AbstractPipeline}, a shape-specific pipeline class which extends it
* (e.g., {@code IntPipeline}) which is also abstract, and an operation-specific
* concrete class which extends that. {@code AbstractPipeline} contains most of
* the mechanics of evaluating the pipeline, and implements methods that will be
* used by the operation; the shape-specific classes add helper methods for
* dealing with collection of results into the appropriate shape-specific
* containers.
*
* <p>After chaining a new intermediate operation, or executing a terminal
* operation, the stream is considered to be consumed, and no more intermediate
* or terminal operations are permitted on this stream instance.
*
* @implNote
* <p>For sequential streams, and parallel streams without
* <a href="package-summary.html#StreamOps">stateful intermediate
* operations</a>, parallel streams, pipeline evaluation is done in a single
* pass that "jams" all the operations together. For parallel streams with
* stateful operations, execution is divided into segments, where each
* stateful operations marks the end of a segment, and each segment is
* evaluated separately and the result used as the input to the next
* segment. In all cases, the source data is not consumed until a terminal
* operation begins.
*
* @param <E_IN> type of input elements
* @param <E_OUT> type of output elements
* @param <S> type of the subclass implementing {@code BaseStream}
* @since 1.8
*/
abstract class AbstractPipeline<E_IN, E_OUT, S extends BaseStream<E_OUT, S>>
extends PipelineHelper<E_OUT> implements BaseStream<E_OUT, S> {
private static final String MSG_STREAM_LINKED = "stream has already been operated upon or closed";
private static final String MSG_CONSUMED = "source already consumed or closed";
/**
* Backlink to the head of the pipeline chain (self if this is the source
* stage).
*/
@SuppressWarnings("rawtypes")
private final AbstractPipeline sourceStage;
/**
* The "upstream" pipeline, or null if this is the source stage.
*/
@SuppressWarnings("rawtypes")
private final AbstractPipeline previousStage;
/**
* The operation flags for the intermediate operation represented by this
* pipeline object.
*/
protected final int sourceOrOpFlags;
/**
* The next stage in the pipeline, or null if this is the last stage.
* Effectively final at the point of linking to the next pipeline.
*/
@SuppressWarnings("rawtypes")
private AbstractPipeline nextStage;
/**
* The number of intermediate operations between this pipeline object
* and the stream source if sequential, or the previous stateful if parallel.
* Valid at the point of pipeline preparation for evaluation.
*/
private int depth;
/**
* The combined source and operation flags for the source and all operations
* up to and including the operation represented by this pipeline object.
* Valid at the point of pipeline preparation for evaluation.
*/
private int combinedFlags;
/**
* The source spliterator. Only valid for the head pipeline.
* Before the pipeline is consumed if non-null then {@code sourceSupplier}
* must be null. After the pipeline is consumed if non-null then is set to
* null.
*/
private Spliterator<?> sourceSpliterator;
/**
* The source supplier. Only valid for the head pipeline. Before the
* pipeline is consumed if non-null then {@code sourceSpliterator} must be
* null. After the pipeline is consumed if non-null then is set to null.
*/
private Supplier<? extends Spliterator<?>> sourceSupplier;
/**
* True if this pipeline has been linked or consumed
*/
private boolean linkedOrConsumed;
/**
* True if there are any stateful ops in the pipeline; only valid for the
* source stage.
*/
private boolean sourceAnyStateful;
private Runnable sourceCloseAction;
/**
* True if pipeline is parallel, otherwise the pipeline is sequential; only
* valid for the source stage.
*/
private boolean parallel;
/**
* Constructor for the head of a stream pipeline.
*
* @param source {@code Supplier<Spliterator>} describing the stream source
* @param sourceFlags The source flags for the stream source, described in
* {@link StreamOpFlag}
* @param parallel True if the pipeline is parallel
*/
AbstractPipeline(Supplier<? extends Spliterator<?>> source,
int sourceFlags, boolean parallel) {
this.previousStage = null;
this.sourceSupplier = source;
this.sourceStage = this;
this.sourceOrOpFlags = sourceFlags & StreamOpFlag.STREAM_MASK;
// The following is an optimization of:
// StreamOpFlag.combineOpFlags(sourceOrOpFlags, StreamOpFlag.INITIAL_OPS_VALUE);
this.combinedFlags = (~(sourceOrOpFlags << 1)) & StreamOpFlag.INITIAL_OPS_VALUE;
this.depth = 0;
this.parallel = parallel;
}
/**
* Constructor for the head of a stream pipeline.
*
* @param source {@code Spliterator} describing the stream source
* @param sourceFlags the source flags for the stream source, described in
* {@link StreamOpFlag}
* @param parallel {@code true} if the pipeline is parallel
*/
AbstractPipeline(Spliterator<?> source,
int sourceFlags, boolean parallel) {
this.previousStage = null;
this.sourceSpliterator = source;
this.sourceStage = this;
this.sourceOrOpFlags = sourceFlags & StreamOpFlag.STREAM_MASK;
// The following is an optimization of:
// StreamOpFlag.combineOpFlags(sourceOrOpFlags, StreamOpFlag.INITIAL_OPS_VALUE);
this.combinedFlags = (~(sourceOrOpFlags << 1)) & StreamOpFlag.INITIAL_OPS_VALUE;
this.depth = 0;
this.parallel = parallel;
}
/**
* Constructor for appending an intermediate operation stage onto an
* existing pipeline.
*
* @param previousStage the upstream pipeline stage
* @param opFlags the operation flags for the new stage, described in
* {@link StreamOpFlag}
*/
AbstractPipeline(AbstractPipeline<?, E_IN, ?> previousStage, int opFlags) {
if (previousStage.linkedOrConsumed)
throw new IllegalStateException(MSG_STREAM_LINKED);
previousStage.linkedOrConsumed = true;
previousStage.nextStage = this;
this.previousStage = previousStage;
this.sourceOrOpFlags = opFlags & StreamOpFlag.OP_MASK;
this.combinedFlags = StreamOpFlag.combineOpFlags(opFlags, previousStage.combinedFlags);
this.sourceStage = previousStage.sourceStage;
if (opIsStateful())
sourceStage.sourceAnyStateful = true;
this.depth = previousStage.depth + 1;
}
// Terminal evaluation methods
/**
* Evaluate the pipeline with a terminal operation to produce a result.
*
* @param <R> the type of result
* @param terminalOp the terminal operation to be applied to the pipeline.
* @return the result
*/
final <R> R evaluate(TerminalOp<E_OUT, R> terminalOp) {
assert getOutputShape() == terminalOp.inputShape();
if (linkedOrConsumed)
throw new IllegalStateException(MSG_STREAM_LINKED);
linkedOrConsumed = true;
return isParallel()
? terminalOp.evaluateParallel(this, sourceSpliterator(terminalOp.getOpFlags()))
: terminalOp.evaluateSequential(this, sourceSpliterator(terminalOp.getOpFlags()));
}
/**
* Collect the elements output from the pipeline stage.
*
* @param generator the array generator to be used to create array instances
* @return a flat array-backed Node that holds the collected output elements
*/
@SuppressWarnings("unchecked")
final Node<E_OUT> evaluateToArrayNode(IntFunction<E_OUT[]> generator) {
if (linkedOrConsumed)
throw new IllegalStateException(MSG_STREAM_LINKED);
linkedOrConsumed = true;
// If the last intermediate operation is stateful then
// evaluate directly to avoid an extra collection step
if (isParallel() && previousStage != null && opIsStateful()) {
// Set the depth of this, last, pipeline stage to zero to slice the
// pipeline such that this operation will not be included in the
// upstream slice and upstream operations will not be included
// in this slice
depth = 0;
return opEvaluateParallel(previousStage, previousStage.sourceSpliterator(0), generator);
}
else {
return evaluate(sourceSpliterator(0), true, generator);
}
}
/**
* Gets the source stage spliterator if this pipeline stage is the source
* stage. The pipeline is consumed after this method is called and
* returns successfully.
*
* @return the source stage spliterator
* @throws IllegalStateException if this pipeline stage is not the source
* stage.
*/
@SuppressWarnings("unchecked")
final Spliterator<E_OUT> sourceStageSpliterator() {
if (this != sourceStage)
throw new IllegalStateException();
if (linkedOrConsumed)
throw new IllegalStateException(MSG_STREAM_LINKED);
linkedOrConsumed = true;
if (sourceStage.sourceSpliterator != null) {
@SuppressWarnings("unchecked")
Spliterator<E_OUT> s = sourceStage.sourceSpliterator;
sourceStage.sourceSpliterator = null;
return s;
}
else if (sourceStage.sourceSupplier != null) {
@SuppressWarnings("unchecked")
Spliterator<E_OUT> s = (Spliterator<E_OUT>) sourceStage.sourceSupplier.get();
sourceStage.sourceSupplier = null;
return s;
}
else {
throw new IllegalStateException(MSG_CONSUMED);
}
}
// BaseStream
@Override
@SuppressWarnings("unchecked")
public final S sequential() {
sourceStage.parallel = false;
return (S) this;
}
@Override
@SuppressWarnings("unchecked")
public final S parallel() {
sourceStage.parallel = true;
return (S) this;
}
@Override
public void close() {
linkedOrConsumed = true;
sourceSupplier = null;
sourceSpliterator = null;
if (sourceStage.sourceCloseAction != null) {
Runnable closeAction = sourceStage.sourceCloseAction;
sourceStage.sourceCloseAction = null;
closeAction.run();
}
}
@Override
@SuppressWarnings("unchecked")
public S onClose(Runnable closeHandler) {
if (linkedOrConsumed)
throw new IllegalStateException(MSG_STREAM_LINKED);
Objects.requireNonNull(closeHandler);
Runnable existingHandler = sourceStage.sourceCloseAction;
sourceStage.sourceCloseAction =
(existingHandler == null)
? closeHandler
: Streams.composeWithExceptions(existingHandler, closeHandler);
return (S) this;
}
// Primitive specialization use co-variant overrides, hence is not final
@Override
@SuppressWarnings("unchecked")
public Spliterator<E_OUT> spliterator() {
if (linkedOrConsumed)
throw new IllegalStateException(MSG_STREAM_LINKED);
linkedOrConsumed = true;
if (this == sourceStage) {
if (sourceStage.sourceSpliterator != null) {
@SuppressWarnings("unchecked")
Spliterator<E_OUT> s = (Spliterator<E_OUT>) sourceStage.sourceSpliterator;
sourceStage.sourceSpliterator = null;
return s;
}
else if (sourceStage.sourceSupplier != null) {
@SuppressWarnings("unchecked")
Supplier<Spliterator<E_OUT>> s = (Supplier<Spliterator<E_OUT>>) sourceStage.sourceSupplier;
sourceStage.sourceSupplier = null;
return lazySpliterator(s);
}
else {
throw new IllegalStateException(MSG_CONSUMED);
}
}
else {
return wrap(this, () -> sourceSpliterator(0), isParallel());
}
}
@Override
public final boolean isParallel() {
return sourceStage.parallel;
}
/**
* Returns the composition of stream flags of the stream source and all
* intermediate operations.
*
* @return the composition of stream flags of the stream source and all
* intermediate operations
* @see StreamOpFlag
*/
final int getStreamFlags() {
return StreamOpFlag.toStreamFlags(combinedFlags);
}
/**
* Get the source spliterator for this pipeline stage. For a sequential or
* stateless parallel pipeline, this is the source spliterator. For a
* stateful parallel pipeline, this is a spliterator describing the results
* of all computations up to and including the most recent stateful
* operation.
*/
@SuppressWarnings("unchecked")
private Spliterator<?> sourceSpliterator(int terminalFlags) {
// Get the source spliterator of the pipeline
Spliterator<?> spliterator = null;
if (sourceStage.sourceSpliterator != null) {
spliterator = sourceStage.sourceSpliterator;
sourceStage.sourceSpliterator = null;
}
else if (sourceStage.sourceSupplier != null) {
spliterator = (Spliterator<?>) sourceStage.sourceSupplier.get();
sourceStage.sourceSupplier = null;
}
else {
throw new IllegalStateException(MSG_CONSUMED);
}
if (isParallel() && sourceStage.sourceAnyStateful) {
// Adapt the source spliterator, evaluating each stateful op
// in the pipeline up to and including this pipeline stage.
// The depth and flags of each pipeline stage are adjusted accordingly.
int depth = 1;
for (@SuppressWarnings("rawtypes") AbstractPipeline u = sourceStage, p = sourceStage.nextStage, e = this;
u != e;
u = p, p = p.nextStage) {
int thisOpFlags = p.sourceOrOpFlags;
if (p.opIsStateful()) {
depth = 0;
if (StreamOpFlag.SHORT_CIRCUIT.isKnown(thisOpFlags)) {
// Clear the short circuit flag for next pipeline stage
// This stage encapsulates short-circuiting, the next
// stage may not have any short-circuit operations, and
// if so spliterator.forEachRemaining should be used
// for traversal
thisOpFlags = thisOpFlags & ~StreamOpFlag.IS_SHORT_CIRCUIT;
}
spliterator = p.opEvaluateParallelLazy(u, spliterator);
// Inject or clear SIZED on the source pipeline stage
// based on the stage's spliterator
thisOpFlags = spliterator.hasCharacteristics(Spliterator.SIZED)
? (thisOpFlags & ~StreamOpFlag.NOT_SIZED) | StreamOpFlag.IS_SIZED
: (thisOpFlags & ~StreamOpFlag.IS_SIZED) | StreamOpFlag.NOT_SIZED;
}
p.depth = depth++;
p.combinedFlags = StreamOpFlag.combineOpFlags(thisOpFlags, u.combinedFlags);
}
}
if (terminalFlags != 0) {
// Apply flags from the terminal operation to last pipeline stage
combinedFlags = StreamOpFlag.combineOpFlags(terminalFlags, combinedFlags);
}
return spliterator;
}
// PipelineHelper
@Override
final StreamShape getSourceShape() {
@SuppressWarnings("rawtypes")
AbstractPipeline p = AbstractPipeline.this;
while (p.depth > 0) {
p = p.previousStage;
}
return p.getOutputShape();
}
@Override
final <P_IN> long exactOutputSizeIfKnown(Spliterator<P_IN> spliterator) {
return StreamOpFlag.SIZED.isKnown(getStreamAndOpFlags()) ? spliterator.getExactSizeIfKnown() : -1;
}
@Override
final <P_IN, S extends Sink<E_OUT>> S wrapAndCopyInto(S sink, Spliterator<P_IN> spliterator) {
copyInto(wrapSink(Objects.requireNonNull(sink)), spliterator);
return sink;
}
@Override
final <P_IN> void copyInto(Sink<P_IN> wrappedSink, Spliterator<P_IN> spliterator) {
Objects.requireNonNull(wrappedSink);
if (!StreamOpFlag.SHORT_CIRCUIT.isKnown(getStreamAndOpFlags())) {
wrappedSink.begin(spliterator.getExactSizeIfKnown());
spliterator.forEachRemaining(wrappedSink);
wrappedSink.end();
}
else {
copyIntoWithCancel(wrappedSink, spliterator);
}
}
@Override
@SuppressWarnings("unchecked")
final <P_IN> boolean copyIntoWithCancel(Sink<P_IN> wrappedSink, Spliterator<P_IN> spliterator) {
@SuppressWarnings({"rawtypes","unchecked"})
AbstractPipeline p = AbstractPipeline.this;
while (p.depth > 0) {
p = p.previousStage;
}
wrappedSink.begin(spliterator.getExactSizeIfKnown());
boolean cancelled = p.forEachWithCancel(spliterator, wrappedSink);
wrappedSink.end();
return cancelled;
}
@Override
final int getStreamAndOpFlags() {
return combinedFlags;
}
final boolean isOrdered() {
return StreamOpFlag.ORDERED.isKnown(combinedFlags);
}
@Override
@SuppressWarnings("unchecked")
final <P_IN> Sink<P_IN> wrapSink(Sink<E_OUT> sink) {
Objects.requireNonNull(sink);
for ( @SuppressWarnings("rawtypes") AbstractPipeline p=AbstractPipeline.this; p.depth > 0; p=p.previousStage) {
sink = p.opWrapSink(p.previousStage.combinedFlags, sink);
}
return (Sink<P_IN>) sink;
}
@Override
@SuppressWarnings("unchecked")
final <P_IN> Spliterator<E_OUT> wrapSpliterator(Spliterator<P_IN> sourceSpliterator) {
if (depth == 0) {
return (Spliterator<E_OUT>) sourceSpliterator;
}
else {
return wrap(this, () -> sourceSpliterator, isParallel());
}
}
@Override
@SuppressWarnings("unchecked")
final <P_IN> Node<E_OUT> evaluate(Spliterator<P_IN> spliterator,
boolean flatten,
IntFunction<E_OUT[]> generator) {
if (isParallel()) {
// @@@ Optimize if op of this pipeline stage is a stateful op
return evaluateToNode(this, spliterator, flatten, generator);
}
else {
Node.Builder<E_OUT> nb = makeNodeBuilder(
exactOutputSizeIfKnown(spliterator), generator);
return wrapAndCopyInto(nb, spliterator).build();
}
}
// Shape-specific abstract methods, implemented by XxxPipeline classes
/**
* Get the output shape of the pipeline. If the pipeline is the head,
* then it's output shape corresponds to the shape of the source.
* Otherwise, it's output shape corresponds to the output shape of the
* associated operation.
*
* @return the output shape
*/
abstract StreamShape getOutputShape();
/**
* Collect elements output from a pipeline into a Node that holds elements
* of this shape.
*
* @param helper the pipeline helper describing the pipeline stages
* @param spliterator the source spliterator
* @param flattenTree true if the returned node should be flattened
* @param generator the array generator
* @return a Node holding the output of the pipeline
*/
abstract <P_IN> Node<E_OUT> evaluateToNode(PipelineHelper<E_OUT> helper,
Spliterator<P_IN> spliterator,
boolean flattenTree,
IntFunction<E_OUT[]> generator);
/**
* Create a spliterator that wraps a source spliterator, compatible with
* this stream shape, and operations associated with a {@link
* PipelineHelper}.
*
* @param ph the pipeline helper describing the pipeline stages
* @param supplier the supplier of a spliterator
* @return a wrapping spliterator compatible with this shape
*/
abstract <P_IN> Spliterator<E_OUT> wrap(PipelineHelper<E_OUT> ph,
Supplier<Spliterator<P_IN>> supplier,
boolean isParallel);
/**
* Create a lazy spliterator that wraps and obtains the supplied the
* spliterator when a method is invoked on the lazy spliterator.
* @param supplier the supplier of a spliterator
*/
abstract Spliterator<E_OUT> lazySpliterator(Supplier<? extends Spliterator<E_OUT>> supplier);
/**
* Traverse the elements of a spliterator compatible with this stream shape,
* pushing those elements into a sink. If the sink requests cancellation,
* no further elements will be pulled or pushed.
*
* @param spliterator the spliterator to pull elements from
* @param sink the sink to push elements to
* @return true if the cancellation was requested
*/
abstract boolean forEachWithCancel(Spliterator<E_OUT> spliterator, Sink<E_OUT> sink);
/**
* Make a node builder compatible with this stream shape.
*
* @param exactSizeIfKnown if {@literal >=0}, then a node builder will be
* created that has a fixed capacity of at most sizeIfKnown elements. If
* {@literal < 0}, then the node builder has an unfixed capacity. A fixed
* capacity node builder will throw exceptions if an element is added after
* builder has reached capacity, or is built before the builder has reached
* capacity.
*
* @param generator the array generator to be used to create instances of a
* T[] array. For implementations supporting primitive nodes, this parameter
* may be ignored.
* @return a node builder
*/
@Override
abstract Node.Builder<E_OUT> makeNodeBuilder(long exactSizeIfKnown,
IntFunction<E_OUT[]> generator);
// Op-specific abstract methods, implemented by the operation class
/**
* Returns whether this operation is stateful or not. If it is stateful,
* then the method
* {@link #opEvaluateParallel(PipelineHelper, java.util.Spliterator, java.util.function.IntFunction)}
* must be overridden.
*
* @return {@code true} if this operation is stateful
*/
abstract boolean opIsStateful();
/**
* Accepts a {@code Sink} which will receive the results of this operation,
* and return a {@code Sink} which accepts elements of the input type of
* this operation and which performs the operation, passing the results to
* the provided {@code Sink}.
*
* @apiNote
* The implementation may use the {@code flags} parameter to optimize the
* sink wrapping. For example, if the input is already {@code DISTINCT},
* the implementation for the {@code Stream#distinct()} method could just
* return the sink it was passed.
*
* @param flags The combined stream and operation flags up to, but not
* including, this operation
* @param sink sink to which elements should be sent after processing
* @return a sink which accepts elements, perform the operation upon
* each element, and passes the results (if any) to the provided
* {@code Sink}.
*/
abstract Sink<E_IN> opWrapSink(int flags, Sink<E_OUT> sink);
/**
* Performs a parallel evaluation of the operation using the specified
* {@code PipelineHelper} which describes the upstream intermediate
* operations. Only called on stateful operations. If {@link
* #opIsStateful()} returns true then implementations must override the
* default implementation.
*
* @implSpec The default implementation always throw
* {@code UnsupportedOperationException}.
*
* @param helper the pipeline helper describing the pipeline stages
* @param spliterator the source {@code Spliterator}
* @param generator the array generator
* @return a {@code Node} describing the result of the evaluation
*/
<P_IN> Node<E_OUT> opEvaluateParallel(PipelineHelper<E_OUT> helper,
Spliterator<P_IN> spliterator,
IntFunction<E_OUT[]> generator) {
throw new UnsupportedOperationException("Parallel evaluation is not supported");
}
/**
* Returns a {@code Spliterator} describing a parallel evaluation of the
* operation, using the specified {@code PipelineHelper} which describes the
* upstream intermediate operations. Only called on stateful operations.
* It is not necessary (though acceptable) to do a full computation of the
* result here; it is preferable, if possible, to describe the result via a
* lazily evaluated spliterator.
*
* @implSpec The default implementation behaves as if:
* <pre>{@code
* return evaluateParallel(helper, i -> (E_OUT[]) new
* Object[i]).spliterator();
* }</pre>
* and is suitable for implementations that cannot do better than a full
* synchronous evaluation.
*
* @param helper the pipeline helper
* @param spliterator the source {@code Spliterator}
* @return a {@code Spliterator} describing the result of the evaluation
*/
@SuppressWarnings("unchecked")
<P_IN> Spliterator<E_OUT> opEvaluateParallelLazy(PipelineHelper<E_OUT> helper,
Spliterator<P_IN> spliterator) {
return opEvaluateParallel(helper, spliterator, i -> (E_OUT[]) new Object[i]).spliterator();
}
}

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/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Spliterator;
import java.util.concurrent.atomic.AtomicReference;
/**
* Abstract class for fork-join tasks used to implement short-circuiting
* stream ops, which can produce a result without processing all elements of the
* stream.
*
* @param <P_IN> type of input elements to the pipeline
* @param <P_OUT> type of output elements from the pipeline
* @param <R> type of intermediate result, may be different from operation
* result type
* @param <K> type of child and sibling tasks
* @since 1.8
*/
@SuppressWarnings("serial")
abstract class AbstractShortCircuitTask<P_IN, P_OUT, R,
K extends AbstractShortCircuitTask<P_IN, P_OUT, R, K>>
extends AbstractTask<P_IN, P_OUT, R, K> {
/**
* The result for this computation; this is shared among all tasks and set
* exactly once
*/
protected final AtomicReference<R> sharedResult;
/**
* Indicates whether this task has been canceled. Tasks may cancel other
* tasks in the computation under various conditions, such as in a
* find-first operation, a task that finds a value will cancel all tasks
* that are later in the encounter order.
*/
protected volatile boolean canceled;
/**
* Constructor for root tasks.
*
* @param helper the {@code PipelineHelper} describing the stream pipeline
* up to this operation
* @param spliterator the {@code Spliterator} describing the source for this
* pipeline
*/
protected AbstractShortCircuitTask(PipelineHelper<P_OUT> helper,
Spliterator<P_IN> spliterator) {
super(helper, spliterator);
sharedResult = new AtomicReference<>(null);
}
/**
* Constructor for non-root nodes.
*
* @param parent parent task in the computation tree
* @param spliterator the {@code Spliterator} for the portion of the
* computation tree described by this task
*/
protected AbstractShortCircuitTask(K parent,
Spliterator<P_IN> spliterator) {
super(parent, spliterator);
sharedResult = parent.sharedResult;
}
/**
* Returns the value indicating the computation completed with no task
* finding a short-circuitable result. For example, for a "find" operation,
* this might be null or an empty {@code Optional}.
*
* @return the result to return when no task finds a result
*/
protected abstract R getEmptyResult();
/**
* Overrides AbstractTask version to include checks for early
* exits while splitting or computing.
*/
@Override
public void compute() {
Spliterator<P_IN> rs = spliterator, ls;
long sizeEstimate = rs.estimateSize();
long sizeThreshold = getTargetSize(sizeEstimate);
boolean forkRight = false;
@SuppressWarnings("unchecked") K task = (K) this;
AtomicReference<R> sr = sharedResult;
R result;
while ((result = sr.get()) == null) {
if (task.taskCanceled()) {
result = task.getEmptyResult();
break;
}
if (sizeEstimate <= sizeThreshold || (ls = rs.trySplit()) == null) {
result = task.doLeaf();
break;
}
K leftChild, rightChild, taskToFork;
task.leftChild = leftChild = task.makeChild(ls);
task.rightChild = rightChild = task.makeChild(rs);
task.setPendingCount(1);
if (forkRight) {
forkRight = false;
rs = ls;
task = leftChild;
taskToFork = rightChild;
}
else {
forkRight = true;
task = rightChild;
taskToFork = leftChild;
}
taskToFork.fork();
sizeEstimate = rs.estimateSize();
}
task.setLocalResult(result);
task.tryComplete();
}
/**
* Declares that a globally valid result has been found. If another task has
* not already found the answer, the result is installed in
* {@code sharedResult}. The {@code compute()} method will check
* {@code sharedResult} before proceeding with computation, so this causes
* the computation to terminate early.
*
* @param result the result found
*/
protected void shortCircuit(R result) {
if (result != null)
sharedResult.compareAndSet(null, result);
}
/**
* Sets a local result for this task. If this task is the root, set the
* shared result instead (if not already set).
*
* @param localResult The result to set for this task
*/
@Override
protected void setLocalResult(R localResult) {
if (isRoot()) {
if (localResult != null)
sharedResult.compareAndSet(null, localResult);
}
else
super.setLocalResult(localResult);
}
/**
* Retrieves the local result for this task
*/
@Override
public R getRawResult() {
return getLocalResult();
}
/**
* Retrieves the local result for this task. If this task is the root,
* retrieves the shared result instead.
*/
@Override
public R getLocalResult() {
if (isRoot()) {
R answer = sharedResult.get();
return (answer == null) ? getEmptyResult() : answer;
}
else
return super.getLocalResult();
}
/**
* Mark this task as canceled
*/
protected void cancel() {
canceled = true;
}
/**
* Queries whether this task is canceled. A task is considered canceled if
* it or any of its parents have been canceled.
*
* @return {@code true} if this task or any parent is canceled.
*/
protected boolean taskCanceled() {
boolean cancel = canceled;
if (!cancel) {
for (K parent = getParent(); !cancel && parent != null; parent = parent.getParent())
cancel = parent.canceled;
}
return cancel;
}
/**
* Cancels all tasks which succeed this one in the encounter order. This
* includes canceling all the current task's right sibling, as well as the
* later right siblings of all its parents.
*/
protected void cancelLaterNodes() {
// Go up the tree, cancel right siblings of this node and all parents
for (@SuppressWarnings("unchecked") K parent = getParent(), node = (K) this;
parent != null;
node = parent, parent = parent.getParent()) {
// If node is a left child of parent, then has a right sibling
if (parent.leftChild == node) {
K rightSibling = parent.rightChild;
if (!rightSibling.canceled)
rightSibling.cancel();
}
}
}
}

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/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
/**
* Base class for a data structure for gathering elements into a buffer and then
* iterating them. Maintains an array of increasingly sized arrays, so there is
* no copying cost associated with growing the data structure.
* @since 1.8
*/
abstract class AbstractSpinedBuffer {
/**
* Minimum power-of-two for the first chunk.
*/
public static final int MIN_CHUNK_POWER = 4;
/**
* Minimum size for the first chunk.
*/
public static final int MIN_CHUNK_SIZE = 1 << MIN_CHUNK_POWER;
/**
* Max power-of-two for chunks.
*/
public static final int MAX_CHUNK_POWER = 30;
/**
* Minimum array size for array-of-chunks.
*/
public static final int MIN_SPINE_SIZE = 8;
/**
* log2 of the size of the first chunk.
*/
protected final int initialChunkPower;
/**
* Index of the *next* element to write; may point into, or just outside of,
* the current chunk.
*/
protected int elementIndex;
/**
* Index of the *current* chunk in the spine array, if the spine array is
* non-null.
*/
protected int spineIndex;
/**
* Count of elements in all prior chunks.
*/
protected long[] priorElementCount;
/**
* Construct with an initial capacity of 16.
*/
protected AbstractSpinedBuffer() {
this.initialChunkPower = MIN_CHUNK_POWER;
}
/**
* Construct with a specified initial capacity.
*
* @param initialCapacity The minimum expected number of elements
*/
protected AbstractSpinedBuffer(int initialCapacity) {
if (initialCapacity < 0)
throw new IllegalArgumentException("Illegal Capacity: "+ initialCapacity);
this.initialChunkPower = Math.max(MIN_CHUNK_POWER,
Integer.SIZE - Integer.numberOfLeadingZeros(initialCapacity - 1));
}
/**
* Is the buffer currently empty?
*/
public boolean isEmpty() {
return (spineIndex == 0) && (elementIndex == 0);
}
/**
* How many elements are currently in the buffer?
*/
public long count() {
return (spineIndex == 0)
? elementIndex
: priorElementCount[spineIndex] + elementIndex;
}
/**
* How big should the nth chunk be?
*/
protected int chunkSize(int n) {
int power = (n == 0 || n == 1)
? initialChunkPower
: Math.min(initialChunkPower + n - 1, AbstractSpinedBuffer.MAX_CHUNK_POWER);
return 1 << power;
}
/**
* Remove all data from the buffer
*/
public abstract void clear();
}

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/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Spliterator;
import java.util.concurrent.CountedCompleter;
import java.util.concurrent.ForkJoinPool;
/**
* Abstract base class for most fork-join tasks used to implement stream ops.
* Manages splitting logic, tracking of child tasks, and intermediate results.
* Each task is associated with a {@link Spliterator} that describes the portion
* of the input associated with the subtree rooted at this task.
* Tasks may be leaf nodes (which will traverse the elements of
* the {@code Spliterator}) or internal nodes (which split the
* {@code Spliterator} into multiple child tasks).
*
* @implNote
* <p>This class is based on {@link CountedCompleter}, a form of fork-join task
* where each task has a semaphore-like count of uncompleted children, and the
* task is implicitly completed and notified when its last child completes.
* Internal node tasks will likely override the {@code onCompletion} method from
* {@code CountedCompleter} to merge the results from child tasks into the
* current task's result.
*
* <p>Splitting and setting up the child task links is done by {@code compute()}
* for internal nodes. At {@code compute()} time for leaf nodes, it is
* guaranteed that the parent's child-related fields (including sibling links
* for the parent's children) will be set up for all children.
*
* <p>For example, a task that performs a reduce would override {@code doLeaf()}
* to perform a reduction on that leaf node's chunk using the
* {@code Spliterator}, and override {@code onCompletion()} to merge the results
* of the child tasks for internal nodes:
*
* <pre>{@code
* protected S doLeaf() {
* spliterator.forEach(...);
* return localReductionResult;
* }
*
* public void onCompletion(CountedCompleter caller) {
* if (!isLeaf()) {
* ReduceTask<P_IN, P_OUT, T, R> child = children;
* R result = child.getLocalResult();
* child = child.nextSibling;
* for (; child != null; child = child.nextSibling)
* result = combine(result, child.getLocalResult());
* setLocalResult(result);
* }
* }
* }</pre>
*
* <p>Serialization is not supported as there is no intention to serialize
* tasks managed by stream ops.
*
* @param <P_IN> Type of elements input to the pipeline
* @param <P_OUT> Type of elements output from the pipeline
* @param <R> Type of intermediate result, which may be different from operation
* result type
* @param <K> Type of parent, child and sibling tasks
* @since 1.8
*/
@SuppressWarnings("serial")
abstract class AbstractTask<P_IN, P_OUT, R,
K extends AbstractTask<P_IN, P_OUT, R, K>>
extends CountedCompleter<R> {
/**
* Default target factor of leaf tasks for parallel decomposition.
* To allow load balancing, we over-partition, currently to approximately
* four tasks per processor, which enables others to help out
* if leaf tasks are uneven or some processors are otherwise busy.
*/
static final int LEAF_TARGET = ForkJoinPool.getCommonPoolParallelism() << 2;
/** The pipeline helper, common to all tasks in a computation */
protected final PipelineHelper<P_OUT> helper;
/**
* The spliterator for the portion of the input associated with the subtree
* rooted at this task
*/
protected Spliterator<P_IN> spliterator;
/** Target leaf size, common to all tasks in a computation */
protected long targetSize; // may be lazily initialized
/**
* The left child.
* null if no children
* if non-null rightChild is non-null
*/
protected K leftChild;
/**
* The right child.
* null if no children
* if non-null leftChild is non-null
*/
protected K rightChild;
/** The result of this node, if completed */
private R localResult;
/**
* Constructor for root nodes.
*
* @param helper The {@code PipelineHelper} describing the stream pipeline
* up to this operation
* @param spliterator The {@code Spliterator} describing the source for this
* pipeline
*/
protected AbstractTask(PipelineHelper<P_OUT> helper,
Spliterator<P_IN> spliterator) {
super(null);
this.helper = helper;
this.spliterator = spliterator;
this.targetSize = 0L;
}
/**
* Constructor for non-root nodes.
*
* @param parent this node's parent task
* @param spliterator {@code Spliterator} describing the subtree rooted at
* this node, obtained by splitting the parent {@code Spliterator}
*/
protected AbstractTask(K parent,
Spliterator<P_IN> spliterator) {
super(parent);
this.spliterator = spliterator;
this.helper = parent.helper;
this.targetSize = parent.targetSize;
}
/**
* Constructs a new node of type T whose parent is the receiver; must call
* the AbstractTask(T, Spliterator) constructor with the receiver and the
* provided Spliterator.
*
* @param spliterator {@code Spliterator} describing the subtree rooted at
* this node, obtained by splitting the parent {@code Spliterator}
* @return newly constructed child node
*/
protected abstract K makeChild(Spliterator<P_IN> spliterator);
/**
* Computes the result associated with a leaf node. Will be called by
* {@code compute()} and the result passed to @{code setLocalResult()}
*
* @return the computed result of a leaf node
*/
protected abstract R doLeaf();
/**
* Returns a suggested target leaf size based on the initial size estimate.
*
* @return suggested target leaf size
*/
public static long suggestTargetSize(long sizeEstimate) {
long est = sizeEstimate / LEAF_TARGET;
return est > 0L ? est : 1L;
}
/**
* Returns the targetSize, initializing it via the supplied
* size estimate if not already initialized.
*/
protected final long getTargetSize(long sizeEstimate) {
long s;
return ((s = targetSize) != 0 ? s :
(targetSize = suggestTargetSize(sizeEstimate)));
}
/**
* Returns the local result, if any. Subclasses should use
* {@link #setLocalResult(Object)} and {@link #getLocalResult()} to manage
* results. This returns the local result so that calls from within the
* fork-join framework will return the correct result.
*
* @return local result for this node previously stored with
* {@link #setLocalResult}
*/
@Override
public R getRawResult() {
return localResult;
}
/**
* Does nothing; instead, subclasses should use
* {@link #setLocalResult(Object)}} to manage results.
*
* @param result must be null, or an exception is thrown (this is a safety
* tripwire to detect when {@code setRawResult()} is being used
* instead of {@code setLocalResult()}
*/
@Override
protected void setRawResult(R result) {
if (result != null)
throw new IllegalStateException();
}
/**
* Retrieves a result previously stored with {@link #setLocalResult}
*
* @return local result for this node previously stored with
* {@link #setLocalResult}
*/
protected R getLocalResult() {
return localResult;
}
/**
* Associates the result with the task, can be retrieved with
* {@link #getLocalResult}
*
* @param localResult local result for this node
*/
protected void setLocalResult(R localResult) {
this.localResult = localResult;
}
/**
* Indicates whether this task is a leaf node. (Only valid after
* {@link #compute} has been called on this node). If the node is not a
* leaf node, then children will be non-null and numChildren will be
* positive.
*
* @return {@code true} if this task is a leaf node
*/
protected boolean isLeaf() {
return leftChild == null;
}
/**
* Indicates whether this task is the root node
*
* @return {@code true} if this task is the root node.
*/
protected boolean isRoot() {
return getParent() == null;
}
/**
* Returns the parent of this task, or null if this task is the root
*
* @return the parent of this task, or null if this task is the root
*/
@SuppressWarnings("unchecked")
protected K getParent() {
return (K) getCompleter();
}
/**
* Decides whether or not to split a task further or compute it
* directly. If computing directly, calls {@code doLeaf} and pass
* the result to {@code setRawResult}. Otherwise splits off
* subtasks, forking one and continuing as the other.
*
* <p> The method is structured to conserve resources across a
* range of uses. The loop continues with one of the child tasks
* when split, to avoid deep recursion. To cope with spliterators
* that may be systematically biased toward left-heavy or
* right-heavy splits, we alternate which child is forked versus
* continued in the loop.
*/
@Override
public void compute() {
Spliterator<P_IN> rs = spliterator, ls; // right, left spliterators
long sizeEstimate = rs.estimateSize();
long sizeThreshold = getTargetSize(sizeEstimate);
boolean forkRight = false;
@SuppressWarnings("unchecked") K task = (K) this;
while (sizeEstimate > sizeThreshold && (ls = rs.trySplit()) != null) {
K leftChild, rightChild, taskToFork;
task.leftChild = leftChild = task.makeChild(ls);
task.rightChild = rightChild = task.makeChild(rs);
task.setPendingCount(1);
if (forkRight) {
forkRight = false;
rs = ls;
task = leftChild;
taskToFork = rightChild;
}
else {
forkRight = true;
task = rightChild;
taskToFork = leftChild;
}
taskToFork.fork();
sizeEstimate = rs.estimateSize();
}
task.setLocalResult(task.doLeaf());
task.tryComplete();
}
/**
* {@inheritDoc}
*
* @implNote
* Clears spliterator and children fields. Overriders MUST call
* {@code super.onCompletion} as the last thing they do if they want these
* cleared.
*/
@Override
public void onCompletion(CountedCompleter<?> caller) {
spliterator = null;
leftChild = rightChild = null;
}
/**
* Returns whether this node is a "leftmost" node -- whether the path from
* the root to this node involves only traversing leftmost child links. For
* a leaf node, this means it is the first leaf node in the encounter order.
*
* @return {@code true} if this node is a "leftmost" node
*/
protected boolean isLeftmostNode() {
@SuppressWarnings("unchecked")
K node = (K) this;
while (node != null) {
K parent = node.getParent();
if (parent != null && parent.leftChild != node)
return false;
node = parent;
}
return true;
}
}

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/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.nio.charset.Charset;
import java.nio.file.Files;
import java.nio.file.Path;
import java.util.Collection;
import java.util.Iterator;
import java.util.Spliterator;
import java.util.concurrent.ConcurrentHashMap;
import java.util.function.IntConsumer;
import java.util.function.Predicate;
/**
* Base interface for streams, which are sequences of elements supporting
* sequential and parallel aggregate operations. The following example
* illustrates an aggregate operation using the stream types {@link Stream}
* and {@link IntStream}, computing the sum of the weights of the red widgets:
*
* <pre>{@code
* int sum = widgets.stream()
* .filter(w -> w.getColor() == RED)
* .mapToInt(w -> w.getWeight())
* .sum();
* }</pre>
*
* See the class documentation for {@link Stream} and the package documentation
* for <a href="package-summary.html">java.util.stream</a> for additional
* specification of streams, stream operations, stream pipelines, and
* parallelism, which governs the behavior of all stream types.
*
* @param <T> the type of the stream elements
* @param <S> the type of the stream implementing {@code BaseStream}
* @since 1.8
* @see Stream
* @see IntStream
* @see LongStream
* @see DoubleStream
* @see <a href="package-summary.html">java.util.stream</a>
*/
public interface BaseStream<T, S extends BaseStream<T, S>>
extends AutoCloseable {
/**
* Returns an iterator for the elements of this stream.
*
* <p>This is a <a href="package-summary.html#StreamOps">terminal
* operation</a>.
*
* @return the element iterator for this stream
*/
Iterator<T> iterator();
/**
* Returns a spliterator for the elements of this stream.
*
* <p>This is a <a href="package-summary.html#StreamOps">terminal
* operation</a>.
*
* <p>
* The returned spliterator should report the set of characteristics derived
* from the stream pipeline (namely the characteristics derived from the
* stream source spliterator and the intermediate operations).
* Implementations may report a sub-set of those characteristics. For
* example, it may be too expensive to compute the entire set for some or
* all possible stream pipelines.
*
* @return the element spliterator for this stream
*/
Spliterator<T> spliterator();
/**
* Returns whether this stream, if a terminal operation were to be executed,
* would execute in parallel. Calling this method after invoking an
* terminal stream operation method may yield unpredictable results.
*
* @return {@code true} if this stream would execute in parallel if executed
*/
boolean isParallel();
/**
* Returns an equivalent stream that is sequential. May return
* itself, either because the stream was already sequential, or because
* the underlying stream state was modified to be sequential.
*
* <p>This is an <a href="package-summary.html#StreamOps">intermediate
* operation</a>.
*
* @return a sequential stream
*/
S sequential();
/**
* Returns an equivalent stream that is parallel. May return
* itself, either because the stream was already parallel, or because
* the underlying stream state was modified to be parallel.
*
* <p>This is an <a href="package-summary.html#StreamOps">intermediate
* operation</a>.
*
* @return a parallel stream
*/
S parallel();
/**
* Returns an equivalent stream that is
* <a href="package-summary.html#Ordering">unordered</a>. May return
* itself, either because the stream was already unordered, or because
* the underlying stream state was modified to be unordered.
*
* <p>This is an <a href="package-summary.html#StreamOps">intermediate
* operation</a>.
*
* @return an unordered stream
*/
S unordered();
/**
* Returns an equivalent stream with an additional close handler. Close
* handlers are run when the {@link #close()} method
* is called on the stream, and are executed in the order they were
* added. All close handlers are run, even if earlier close handlers throw
* exceptions. If any close handler throws an exception, the first
* exception thrown will be relayed to the caller of {@code close()}, with
* any remaining exceptions added to that exception as suppressed exceptions
* (unless one of the remaining exceptions is the same exception as the
* first exception, since an exception cannot suppress itself.) May
* return itself.
*
* <p>This is an <a href="package-summary.html#StreamOps">intermediate
* operation</a>.
*
* @param closeHandler A task to execute when the stream is closed
* @return a stream with a handler that is run if the stream is closed
*/
S onClose(Runnable closeHandler);
/**
* Closes this stream, causing all close handlers for this stream pipeline
* to be called.
*
* @see AutoCloseable#close()
*/
@Override
void close();
}

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/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Collections;
import java.util.EnumSet;
import java.util.Objects;
import java.util.Set;
import java.util.function.BiConsumer;
import java.util.function.BinaryOperator;
import java.util.function.Function;
import java.util.function.Supplier;
/**
* A <a href="package-summary.html#Reduction">mutable reduction operation</a> that
* accumulates input elements into a mutable result container, optionally transforming
* the accumulated result into a final representation after all input elements
* have been processed. Reduction operations can be performed either sequentially
* or in parallel.
*
* <p>Examples of mutable reduction operations include:
* accumulating elements into a {@code Collection}; concatenating
* strings using a {@code StringBuilder}; computing summary information about
* elements such as sum, min, max, or average; computing "pivot table" summaries
* such as "maximum valued transaction by seller", etc. The class {@link Collectors}
* provides implementations of many common mutable reductions.
*
* <p>A {@code Collector} is specified by four functions that work together to
* accumulate entries into a mutable result container, and optionally perform
* a final transform on the result. They are: <ul>
* <li>creation of a new result container ({@link #supplier()})</li>
* <li>incorporating a new data element into a result container ({@link #accumulator()})</li>
* <li>combining two result containers into one ({@link #combiner()})</li>
* <li>performing an optional final transform on the container ({@link #finisher()})</li>
* </ul>
*
* <p>Collectors also have a set of characteristics, such as
* {@link Characteristics#CONCURRENT}, that provide hints that can be used by a
* reduction implementation to provide better performance.
*
* <p>A sequential implementation of a reduction using a collector would
* create a single result container using the supplier function, and invoke the
* accumulator function once for each input element. A parallel implementation
* would partition the input, create a result container for each partition,
* accumulate the contents of each partition into a subresult for that partition,
* and then use the combiner function to merge the subresults into a combined
* result.
*
* <p>To ensure that sequential and parallel executions produce equivalent
* results, the collector functions must satisfy an <em>identity</em> and an
* <a href="package-summary.html#Associativity">associativity</a> constraints.
*
* <p>The identity constraint says that for any partially accumulated result,
* combining it with an empty result container must produce an equivalent
* result. That is, for a partially accumulated result {@code a} that is the
* result of any series of accumulator and combiner invocations, {@code a} must
* be equivalent to {@code combiner.apply(a, supplier.get())}.
*
* <p>The associativity constraint says that splitting the computation must
* produce an equivalent result. That is, for any input elements {@code t1}
* and {@code t2}, the results {@code r1} and {@code r2} in the computation
* below must be equivalent:
* <pre>{@code
* A a1 = supplier.get();
* accumulator.accept(a1, t1);
* accumulator.accept(a1, t2);
* R r1 = finisher.apply(a1); // result without splitting
*
* A a2 = supplier.get();
* accumulator.accept(a2, t1);
* A a3 = supplier.get();
* accumulator.accept(a3, t2);
* R r2 = finisher.apply(combiner.apply(a2, a3)); // result with splitting
* } </pre>
*
* <p>For collectors that do not have the {@code UNORDERED} characteristic,
* two accumulated results {@code a1} and {@code a2} are equivalent if
* {@code finisher.apply(a1).equals(finisher.apply(a2))}. For unordered
* collectors, equivalence is relaxed to allow for non-equality related to
* differences in order. (For example, an unordered collector that accumulated
* elements to a {@code List} would consider two lists equivalent if they
* contained the same elements, ignoring order.)
*
* <p>Libraries that implement reduction based on {@code Collector}, such as
* {@link Stream#collect(Collector)}, must adhere to the following constraints:
* <ul>
* <li>The first argument passed to the accumulator function, both
* arguments passed to the combiner function, and the argument passed to the
* finisher function must be the result of a previous invocation of the
* result supplier, accumulator, or combiner functions.</li>
* <li>The implementation should not do anything with the result of any of
* the result supplier, accumulator, or combiner functions other than to
* pass them again to the accumulator, combiner, or finisher functions,
* or return them to the caller of the reduction operation.</li>
* <li>If a result is passed to the combiner or finisher
* function, and the same object is not returned from that function, it is
* never used again.</li>
* <li>Once a result is passed to the combiner or finisher function, it
* is never passed to the accumulator function again.</li>
* <li>For non-concurrent collectors, any result returned from the result
* supplier, accumulator, or combiner functions must be serially
* thread-confined. This enables collection to occur in parallel without
* the {@code Collector} needing to implement any additional synchronization.
* The reduction implementation must manage that the input is properly
* partitioned, that partitions are processed in isolation, and combining
* happens only after accumulation is complete.</li>
* <li>For concurrent collectors, an implementation is free to (but not
* required to) implement reduction concurrently. A concurrent reduction
* is one where the accumulator function is called concurrently from
* multiple threads, using the same concurrently-modifiable result container,
* rather than keeping the result isolated during accumulation.
* A concurrent reduction should only be applied if the collector has the
* {@link Characteristics#UNORDERED} characteristics or if the
* originating data is unordered.</li>
* </ul>
*
* <p>In addition to the predefined implementations in {@link Collectors}, the
* static factory methods {@link #of(Supplier, BiConsumer, BinaryOperator, Characteristics...)}
* can be used to construct collectors. For example, you could create a collector
* that accumulates widgets into a {@code TreeSet} with:
*
* <pre>{@code
* Collector<Widget, ?, TreeSet<Widget>> intoSet =
* Collector.of(TreeSet::new, TreeSet::add,
* (left, right) -> { left.addAll(right); return left; });
* }</pre>
*
* (This behavior is also implemented by the predefined collector
* {@link Collectors#toCollection(Supplier)}).
*
* @apiNote
* Performing a reduction operation with a {@code Collector} should produce a
* result equivalent to:
* <pre>{@code
* R container = collector.supplier().get();
* for (T t : data)
* collector.accumulator().accept(container, t);
* return collector.finisher().apply(container);
* }</pre>
*
* <p>However, the library is free to partition the input, perform the reduction
* on the partitions, and then use the combiner function to combine the partial
* results to achieve a parallel reduction. (Depending on the specific reduction
* operation, this may perform better or worse, depending on the relative cost
* of the accumulator and combiner functions.)
*
* <p>Collectors are designed to be <em>composed</em>; many of the methods
* in {@link Collectors} are functions that take a collector and produce
* a new collector. For example, given the following collector that computes
* the sum of the salaries of a stream of employees:
*
* <pre>{@code
* Collector<Employee, ?, Integer> summingSalaries
* = Collectors.summingInt(Employee::getSalary))
* }</pre>
*
* If we wanted to create a collector to tabulate the sum of salaries by
* department, we could reuse the "sum of salaries" logic using
* {@link Collectors#groupingBy(Function, Collector)}:
*
* <pre>{@code
* Collector<Employee, ?, Map<Department, Integer>> summingSalariesByDept
* = Collectors.groupingBy(Employee::getDepartment, summingSalaries);
* }</pre>
*
* @see Stream#collect(Collector)
* @see Collectors
*
* @param <T> the type of input elements to the reduction operation
* @param <A> the mutable accumulation type of the reduction operation (often
* hidden as an implementation detail)
* @param <R> the result type of the reduction operation
* @since 1.8
*/
public interface Collector<T, A, R> {
/**
* A function that creates and returns a new mutable result container.
*
* @return a function which returns a new, mutable result container
*/
Supplier<A> supplier();
/**
* A function that folds a value into a mutable result container.
*
* @return a function which folds a value into a mutable result container
*/
BiConsumer<A, T> accumulator();
/**
* A function that accepts two partial results and merges them. The
* combiner function may fold state from one argument into the other and
* return that, or may return a new result container.
*
* @return a function which combines two partial results into a combined
* result
*/
BinaryOperator<A> combiner();
/**
* Perform the final transformation from the intermediate accumulation type
* {@code A} to the final result type {@code R}.
*
* <p>If the characteristic {@code IDENTITY_FINISH} is
* set, this function may be presumed to be an identity transform with an
* unchecked cast from {@code A} to {@code R}.
*
* @return a function which transforms the intermediate result to the final
* result
*/
Function<A, R> finisher();
/**
* Returns a {@code Set} of {@code Collector.Characteristics} indicating
* the characteristics of this Collector. This set should be immutable.
*
* @return an immutable set of collector characteristics
*/
Set<Characteristics> characteristics();
/**
* Returns a new {@code Collector} described by the given {@code supplier},
* {@code accumulator}, and {@code combiner} functions. The resulting
* {@code Collector} has the {@code Collector.Characteristics.IDENTITY_FINISH}
* characteristic.
*
* @param supplier The supplier function for the new collector
* @param accumulator The accumulator function for the new collector
* @param combiner The combiner function for the new collector
* @param characteristics The collector characteristics for the new
* collector
* @param <T> The type of input elements for the new collector
* @param <R> The type of intermediate accumulation result, and final result,
* for the new collector
* @throws NullPointerException if any argument is null
* @return the new {@code Collector}
*/
public static<T, R> Collector<T, R, R> of(Supplier<R> supplier,
BiConsumer<R, T> accumulator,
BinaryOperator<R> combiner,
Characteristics... characteristics) {
Objects.requireNonNull(supplier);
Objects.requireNonNull(accumulator);
Objects.requireNonNull(combiner);
Objects.requireNonNull(characteristics);
Set<Characteristics> cs = (characteristics.length == 0)
? Collectors.CH_ID
: Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.IDENTITY_FINISH,
characteristics));
return new Collectors.CollectorImpl<>(supplier, accumulator, combiner, cs);
}
/**
* Returns a new {@code Collector} described by the given {@code supplier},
* {@code accumulator}, {@code combiner}, and {@code finisher} functions.
*
* @param supplier The supplier function for the new collector
* @param accumulator The accumulator function for the new collector
* @param combiner The combiner function for the new collector
* @param finisher The finisher function for the new collector
* @param characteristics The collector characteristics for the new
* collector
* @param <T> The type of input elements for the new collector
* @param <A> The intermediate accumulation type of the new collector
* @param <R> The final result type of the new collector
* @throws NullPointerException if any argument is null
* @return the new {@code Collector}
*/
public static<T, A, R> Collector<T, A, R> of(Supplier<A> supplier,
BiConsumer<A, T> accumulator,
BinaryOperator<A> combiner,
Function<A, R> finisher,
Characteristics... characteristics) {
Objects.requireNonNull(supplier);
Objects.requireNonNull(accumulator);
Objects.requireNonNull(combiner);
Objects.requireNonNull(finisher);
Objects.requireNonNull(characteristics);
Set<Characteristics> cs = Collectors.CH_NOID;
if (characteristics.length > 0) {
cs = EnumSet.noneOf(Characteristics.class);
Collections.addAll(cs, characteristics);
cs = Collections.unmodifiableSet(cs);
}
return new Collectors.CollectorImpl<>(supplier, accumulator, combiner, finisher, cs);
}
/**
* Characteristics indicating properties of a {@code Collector}, which can
* be used to optimize reduction implementations.
*/
enum Characteristics {
/**
* Indicates that this collector is <em>concurrent</em>, meaning that
* the result container can support the accumulator function being
* called concurrently with the same result container from multiple
* threads.
*
* <p>If a {@code CONCURRENT} collector is not also {@code UNORDERED},
* then it should only be evaluated concurrently if applied to an
* unordered data source.
*/
CONCURRENT,
/**
* Indicates that the collection operation does not commit to preserving
* the encounter order of input elements. (This might be true if the
* result container has no intrinsic order, such as a {@link Set}.)
*/
UNORDERED,
/**
* Indicates that the finisher function is the identity function and
* can be elided. If set, it must be the case that an unchecked cast
* from A to R will succeed.
*/
IDENTITY_FINISH
}
}

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/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.HashSet;
import java.util.LinkedHashSet;
import java.util.Objects;
import java.util.Set;
import java.util.Spliterator;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicBoolean;
import java.util.function.IntFunction;
/**
* Factory methods for transforming streams into duplicate-free streams, using
* {@link Object#equals(Object)} to determine equality.
*
* @since 1.8
*/
final class DistinctOps {
private DistinctOps() { }
/**
* Appends a "distinct" operation to the provided stream, and returns the
* new stream.
*
* @param <T> the type of both input and output elements
* @param upstream a reference stream with element type T
* @return the new stream
*/
static <T> ReferencePipeline<T, T> makeRef(AbstractPipeline<?, T, ?> upstream) {
return new ReferencePipeline.StatefulOp<T, T>(upstream, StreamShape.REFERENCE,
StreamOpFlag.IS_DISTINCT | StreamOpFlag.NOT_SIZED) {
<P_IN> Node<T> reduce(PipelineHelper<T> helper, Spliterator<P_IN> spliterator) {
// If the stream is SORTED then it should also be ORDERED so the following will also
// preserve the sort order
TerminalOp<T, LinkedHashSet<T>> reduceOp
= ReduceOps.<T, LinkedHashSet<T>>makeRef(LinkedHashSet::new, LinkedHashSet::add,
LinkedHashSet::addAll);
return Nodes.node(reduceOp.evaluateParallel(helper, spliterator));
}
@Override
<P_IN> Node<T> opEvaluateParallel(PipelineHelper<T> helper,
Spliterator<P_IN> spliterator,
IntFunction<T[]> generator) {
if (StreamOpFlag.DISTINCT.isKnown(helper.getStreamAndOpFlags())) {
// No-op
return helper.evaluate(spliterator, false, generator);
}
else if (StreamOpFlag.ORDERED.isKnown(helper.getStreamAndOpFlags())) {
return reduce(helper, spliterator);
}
else {
// Holder of null state since ConcurrentHashMap does not support null values
AtomicBoolean seenNull = new AtomicBoolean(false);
ConcurrentHashMap<T, Boolean> map = new ConcurrentHashMap<>();
TerminalOp<T, Void> forEachOp = ForEachOps.makeRef(t -> {
if (t == null)
seenNull.set(true);
else
map.putIfAbsent(t, Boolean.TRUE);
}, false);
forEachOp.evaluateParallel(helper, spliterator);
// If null has been seen then copy the key set into a HashSet that supports null values
// and add null
Set<T> keys = map.keySet();
if (seenNull.get()) {
// TODO Implement a more efficient set-union view, rather than copying
keys = new HashSet<>(keys);
keys.add(null);
}
return Nodes.node(keys);
}
}
@Override
<P_IN> Spliterator<T> opEvaluateParallelLazy(PipelineHelper<T> helper, Spliterator<P_IN> spliterator) {
if (StreamOpFlag.DISTINCT.isKnown(helper.getStreamAndOpFlags())) {
// No-op
return helper.wrapSpliterator(spliterator);
}
else if (StreamOpFlag.ORDERED.isKnown(helper.getStreamAndOpFlags())) {
// Not lazy, barrier required to preserve order
return reduce(helper, spliterator).spliterator();
}
else {
// Lazy
return new StreamSpliterators.DistinctSpliterator<>(helper.wrapSpliterator(spliterator));
}
}
@Override
Sink<T> opWrapSink(int flags, Sink<T> sink) {
Objects.requireNonNull(sink);
if (StreamOpFlag.DISTINCT.isKnown(flags)) {
return sink;
} else if (StreamOpFlag.SORTED.isKnown(flags)) {
return new Sink.ChainedReference<T, T>(sink) {
boolean seenNull;
T lastSeen;
@Override
public void begin(long size) {
seenNull = false;
lastSeen = null;
downstream.begin(-1);
}
@Override
public void end() {
seenNull = false;
lastSeen = null;
downstream.end();
}
@Override
public void accept(T t) {
if (t == null) {
if (!seenNull) {
seenNull = true;
downstream.accept(lastSeen = null);
}
} else if (lastSeen == null || !t.equals(lastSeen)) {
downstream.accept(lastSeen = t);
}
}
};
} else {
return new Sink.ChainedReference<T, T>(sink) {
Set<T> seen;
@Override
public void begin(long size) {
seen = new HashSet<>();
downstream.begin(-1);
}
@Override
public void end() {
seen = null;
downstream.end();
}
@Override
public void accept(T t) {
if (!seen.contains(t)) {
seen.add(t);
downstream.accept(t);
}
}
};
}
}
};
}
}

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/*
* Copyright (c) 2013, 2016, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.DoubleSummaryStatistics;
import java.util.Objects;
import java.util.OptionalDouble;
import java.util.PrimitiveIterator;
import java.util.Spliterator;
import java.util.Spliterators;
import java.util.function.BiConsumer;
import java.util.function.BinaryOperator;
import java.util.function.DoubleBinaryOperator;
import java.util.function.DoubleConsumer;
import java.util.function.DoubleFunction;
import java.util.function.DoublePredicate;
import java.util.function.DoubleToIntFunction;
import java.util.function.DoubleToLongFunction;
import java.util.function.DoubleUnaryOperator;
import java.util.function.IntFunction;
import java.util.function.LongPredicate;
import java.util.function.ObjDoubleConsumer;
import java.util.function.Supplier;
/**
* Abstract base class for an intermediate pipeline stage or pipeline source
* stage implementing whose elements are of type {@code double}.
*
* @param <E_IN> type of elements in the upstream source
*
* @since 1.8
*/
abstract class DoublePipeline<E_IN>
extends AbstractPipeline<E_IN, Double, DoubleStream>
implements DoubleStream {
/**
* Constructor for the head of a stream pipeline.
*
* @param source {@code Supplier<Spliterator>} describing the stream source
* @param sourceFlags the source flags for the stream source, described in
* {@link StreamOpFlag}
*/
DoublePipeline(Supplier<? extends Spliterator<Double>> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
/**
* Constructor for the head of a stream pipeline.
*
* @param source {@code Spliterator} describing the stream source
* @param sourceFlags the source flags for the stream source, described in
* {@link StreamOpFlag}
*/
DoublePipeline(Spliterator<Double> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
/**
* Constructor for appending an intermediate operation onto an existing
* pipeline.
*
* @param upstream the upstream element source.
* @param opFlags the operation flags
*/
DoublePipeline(AbstractPipeline<?, E_IN, ?> upstream, int opFlags) {
super(upstream, opFlags);
}
/**
* Adapt a {@code Sink<Double> to a {@code DoubleConsumer}, ideally simply
* by casting.
*/
private static DoubleConsumer adapt(Sink<Double> sink) {
if (sink instanceof DoubleConsumer) {
return (DoubleConsumer) sink;
} else {
if (Tripwire.ENABLED)
Tripwire.trip(AbstractPipeline.class,
"using DoubleStream.adapt(Sink<Double> s)");
return sink::accept;
}
}
/**
* Adapt a {@code Spliterator<Double>} to a {@code Spliterator.OfDouble}.
*
* @implNote
* The implementation attempts to cast to a Spliterator.OfDouble, and throws
* an exception if this cast is not possible.
*/
private static Spliterator.OfDouble adapt(Spliterator<Double> s) {
if (s instanceof Spliterator.OfDouble) {
return (Spliterator.OfDouble) s;
} else {
if (Tripwire.ENABLED)
Tripwire.trip(AbstractPipeline.class,
"using DoubleStream.adapt(Spliterator<Double> s)");
throw new UnsupportedOperationException("DoubleStream.adapt(Spliterator<Double> s)");
}
}
// Shape-specific methods
@Override
final StreamShape getOutputShape() {
return StreamShape.DOUBLE_VALUE;
}
@Override
final <P_IN> Node<Double> evaluateToNode(PipelineHelper<Double> helper,
Spliterator<P_IN> spliterator,
boolean flattenTree,
IntFunction<Double[]> generator) {
return Nodes.collectDouble(helper, spliterator, flattenTree);
}
@Override
final <P_IN> Spliterator<Double> wrap(PipelineHelper<Double> ph,
Supplier<Spliterator<P_IN>> supplier,
boolean isParallel) {
return new StreamSpliterators.DoubleWrappingSpliterator<>(ph, supplier, isParallel);
}
@Override
@SuppressWarnings("unchecked")
final Spliterator.OfDouble lazySpliterator(Supplier<? extends Spliterator<Double>> supplier) {
return new StreamSpliterators.DelegatingSpliterator.OfDouble((Supplier<Spliterator.OfDouble>) supplier);
}
@Override
final boolean forEachWithCancel(Spliterator<Double> spliterator, Sink<Double> sink) {
Spliterator.OfDouble spl = adapt(spliterator);
DoubleConsumer adaptedSink = adapt(sink);
boolean cancelled;
do { } while (!(cancelled = sink.cancellationRequested()) && spl.tryAdvance(adaptedSink));
return cancelled;
}
@Override
final Node.Builder<Double> makeNodeBuilder(long exactSizeIfKnown, IntFunction<Double[]> generator) {
return Nodes.doubleBuilder(exactSizeIfKnown);
}
private <U> Stream<U> mapToObj(DoubleFunction<? extends U> mapper, int opFlags) {
return new ReferencePipeline.StatelessOp<Double, U>(this, StreamShape.DOUBLE_VALUE, opFlags) {
@Override
Sink<Double> opWrapSink(int flags, Sink<U> sink) {
return new Sink.ChainedDouble<U>(sink) {
@Override
public void accept(double t) {
downstream.accept(mapper.apply(t));
}
};
}
};
}
// DoubleStream
@Override
public final PrimitiveIterator.OfDouble iterator() {
return Spliterators.iterator(spliterator());
}
@Override
public final Spliterator.OfDouble spliterator() {
return adapt(super.spliterator());
}
// Stateless intermediate ops from DoubleStream
@Override
public final Stream<Double> boxed() {
return mapToObj(Double::valueOf, 0);
}
@Override
public final DoubleStream map(DoubleUnaryOperator mapper) {
Objects.requireNonNull(mapper);
return new StatelessOp<Double>(this, StreamShape.DOUBLE_VALUE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT) {
@Override
Sink<Double> opWrapSink(int flags, Sink<Double> sink) {
return new Sink.ChainedDouble<Double>(sink) {
@Override
public void accept(double t) {
downstream.accept(mapper.applyAsDouble(t));
}
};
}
};
}
@Override
public final <U> Stream<U> mapToObj(DoubleFunction<? extends U> mapper) {
Objects.requireNonNull(mapper);
return mapToObj(mapper, StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT);
}
@Override
public final IntStream mapToInt(DoubleToIntFunction mapper) {
Objects.requireNonNull(mapper);
return new IntPipeline.StatelessOp<Double>(this, StreamShape.DOUBLE_VALUE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT) {
@Override
Sink<Double> opWrapSink(int flags, Sink<Integer> sink) {
return new Sink.ChainedDouble<Integer>(sink) {
@Override
public void accept(double t) {
downstream.accept(mapper.applyAsInt(t));
}
};
}
};
}
@Override
public final LongStream mapToLong(DoubleToLongFunction mapper) {
Objects.requireNonNull(mapper);
return new LongPipeline.StatelessOp<Double>(this, StreamShape.DOUBLE_VALUE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT) {
@Override
Sink<Double> opWrapSink(int flags, Sink<Long> sink) {
return new Sink.ChainedDouble<Long>(sink) {
@Override
public void accept(double t) {
downstream.accept(mapper.applyAsLong(t));
}
};
}
};
}
@Override
public final DoubleStream flatMap(DoubleFunction<? extends DoubleStream> mapper) {
Objects.requireNonNull(mapper);
return new StatelessOp<Double>(this, StreamShape.DOUBLE_VALUE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT | StreamOpFlag.NOT_SIZED) {
@Override
Sink<Double> opWrapSink(int flags, Sink<Double> sink) {
return new Sink.ChainedDouble<Double>(sink) {
@Override
public void begin(long size) {
downstream.begin(-1);
}
@Override
public void accept(double t) {
try (DoubleStream result = mapper.apply(t)) {
// We can do better that this too; optimize for depth=0 case and just grab spliterator and forEach it
if (result != null)
result.sequential().forEach(i -> downstream.accept(i));
}
}
};
}
};
}
@Override
public DoubleStream unordered() {
if (!isOrdered())
return this;
return new StatelessOp<Double>(this, StreamShape.DOUBLE_VALUE, StreamOpFlag.NOT_ORDERED) {
@Override
Sink<Double> opWrapSink(int flags, Sink<Double> sink) {
return sink;
}
};
}
@Override
public final DoubleStream filter(DoublePredicate predicate) {
Objects.requireNonNull(predicate);
return new StatelessOp<Double>(this, StreamShape.DOUBLE_VALUE,
StreamOpFlag.NOT_SIZED) {
@Override
Sink<Double> opWrapSink(int flags, Sink<Double> sink) {
return new Sink.ChainedDouble<Double>(sink) {
@Override
public void begin(long size) {
downstream.begin(-1);
}
@Override
public void accept(double t) {
if (predicate.test(t))
downstream.accept(t);
}
};
}
};
}
@Override
public final DoubleStream peek(DoubleConsumer action) {
Objects.requireNonNull(action);
return new StatelessOp<Double>(this, StreamShape.DOUBLE_VALUE,
0) {
@Override
Sink<Double> opWrapSink(int flags, Sink<Double> sink) {
return new Sink.ChainedDouble<Double>(sink) {
@Override
public void accept(double t) {
action.accept(t);
downstream.accept(t);
}
};
}
};
}
// Stateful intermediate ops from DoubleStream
@Override
public final DoubleStream limit(long maxSize) {
if (maxSize < 0)
throw new IllegalArgumentException(Long.toString(maxSize));
return SliceOps.makeDouble(this, (long) 0, maxSize);
}
@Override
public final DoubleStream skip(long n) {
if (n < 0)
throw new IllegalArgumentException(Long.toString(n));
if (n == 0)
return this;
else {
long limit = -1;
return SliceOps.makeDouble(this, n, limit);
}
}
@Override
public final DoubleStream takeWhile(DoublePredicate predicate) {
return WhileOps.makeTakeWhileDouble(this, predicate);
}
@Override
public final DoubleStream dropWhile(DoublePredicate predicate) {
return WhileOps.makeDropWhileDouble(this, predicate);
}
@Override
public final DoubleStream sorted() {
return SortedOps.makeDouble(this);
}
@Override
public final DoubleStream distinct() {
// While functional and quick to implement, this approach is not very efficient.
// An efficient version requires a double-specific map/set implementation.
return boxed().distinct().mapToDouble(i -> (double) i);
}
// Terminal ops from DoubleStream
@Override
public void forEach(DoubleConsumer consumer) {
evaluate(ForEachOps.makeDouble(consumer, false));
}
@Override
public void forEachOrdered(DoubleConsumer consumer) {
evaluate(ForEachOps.makeDouble(consumer, true));
}
@Override
public final double sum() {
/*
* In the arrays allocated for the collect operation, index 0
* holds the high-order bits of the running sum, index 1 holds
* the low-order bits of the sum computed via compensated
* summation, and index 2 holds the simple sum used to compute
* the proper result if the stream contains infinite values of
* the same sign.
*/
double[] summation = collect(() -> new double[3],
(ll, d) -> {
Collectors.sumWithCompensation(ll, d);
ll[2] += d;
},
(ll, rr) -> {
Collectors.sumWithCompensation(ll, rr[0]);
Collectors.sumWithCompensation(ll, rr[1]);
ll[2] += rr[2];
});
return Collectors.computeFinalSum(summation);
}
@Override
public final OptionalDouble min() {
return reduce(Math::min);
}
@Override
public final OptionalDouble max() {
return reduce(Math::max);
}
/**
* {@inheritDoc}
*
* @implNote The {@code double} format can represent all
* consecutive integers in the range -2<sup>53</sup> to
* 2<sup>53</sup>. If the pipeline has more than 2<sup>53</sup>
* values, the divisor in the average computation will saturate at
* 2<sup>53</sup>, leading to additional numerical errors.
*/
@Override
public final OptionalDouble average() {
/*
* In the arrays allocated for the collect operation, index 0
* holds the high-order bits of the running sum, index 1 holds
* the low-order bits of the sum computed via compensated
* summation, index 2 holds the number of values seen, index 3
* holds the simple sum.
*/
double[] avg = collect(() -> new double[4],
(ll, d) -> {
ll[2]++;
Collectors.sumWithCompensation(ll, d);
ll[3] += d;
},
(ll, rr) -> {
Collectors.sumWithCompensation(ll, rr[0]);
Collectors.sumWithCompensation(ll, rr[1]);
ll[2] += rr[2];
ll[3] += rr[3];
});
return avg[2] > 0
? OptionalDouble.of(Collectors.computeFinalSum(avg) / avg[2])
: OptionalDouble.empty();
}
@Override
public final long count() {
return evaluate(ReduceOps.makeDoubleCounting());
}
@Override
public final DoubleSummaryStatistics summaryStatistics() {
return collect(DoubleSummaryStatistics::new, DoubleSummaryStatistics::accept,
DoubleSummaryStatistics::combine);
}
@Override
public final double reduce(double identity, DoubleBinaryOperator op) {
return evaluate(ReduceOps.makeDouble(identity, op));
}
@Override
public final OptionalDouble reduce(DoubleBinaryOperator op) {
return evaluate(ReduceOps.makeDouble(op));
}
@Override
public final <R> R collect(Supplier<R> supplier,
ObjDoubleConsumer<R> accumulator,
BiConsumer<R, R> combiner) {
Objects.requireNonNull(combiner);
BinaryOperator<R> operator = (left, right) -> {
combiner.accept(left, right);
return left;
};
return evaluate(ReduceOps.makeDouble(supplier, accumulator, operator));
}
@Override
public final boolean anyMatch(DoublePredicate predicate) {
return evaluate(MatchOps.makeDouble(predicate, MatchOps.MatchKind.ANY));
}
@Override
public final boolean allMatch(DoublePredicate predicate) {
return evaluate(MatchOps.makeDouble(predicate, MatchOps.MatchKind.ALL));
}
@Override
public final boolean noneMatch(DoublePredicate predicate) {
return evaluate(MatchOps.makeDouble(predicate, MatchOps.MatchKind.NONE));
}
@Override
public final OptionalDouble findFirst() {
return evaluate(FindOps.makeDouble(true));
}
@Override
public final OptionalDouble findAny() {
return evaluate(FindOps.makeDouble(false));
}
@Override
public final double[] toArray() {
return Nodes.flattenDouble((Node.OfDouble) evaluateToArrayNode(Double[]::new))
.asPrimitiveArray();
}
//
/**
* Source stage of a DoubleStream
*
* @param <E_IN> type of elements in the upstream source
*/
static class Head<E_IN> extends DoublePipeline<E_IN> {
/**
* Constructor for the source stage of a DoubleStream.
*
* @param source {@code Supplier<Spliterator>} describing the stream
* source
* @param sourceFlags the source flags for the stream source, described
* in {@link StreamOpFlag}
* @param parallel {@code true} if the pipeline is parallel
*/
Head(Supplier<? extends Spliterator<Double>> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
/**
* Constructor for the source stage of a DoubleStream.
*
* @param source {@code Spliterator} describing the stream source
* @param sourceFlags the source flags for the stream source, described
* in {@link StreamOpFlag}
* @param parallel {@code true} if the pipeline is parallel
*/
Head(Spliterator<Double> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
@Override
final boolean opIsStateful() {
throw new UnsupportedOperationException();
}
@Override
final Sink<E_IN> opWrapSink(int flags, Sink<Double> sink) {
throw new UnsupportedOperationException();
}
// Optimized sequential terminal operations for the head of the pipeline
@Override
public void forEach(DoubleConsumer consumer) {
if (!isParallel()) {
adapt(sourceStageSpliterator()).forEachRemaining(consumer);
}
else {
super.forEach(consumer);
}
}
@Override
public void forEachOrdered(DoubleConsumer consumer) {
if (!isParallel()) {
adapt(sourceStageSpliterator()).forEachRemaining(consumer);
}
else {
super.forEachOrdered(consumer);
}
}
}
/**
* Base class for a stateless intermediate stage of a DoubleStream.
*
* @param <E_IN> type of elements in the upstream source
* @since 1.8
*/
abstract static class StatelessOp<E_IN> extends DoublePipeline<E_IN> {
/**
* Construct a new DoubleStream by appending a stateless intermediate
* operation to an existing stream.
*
* @param upstream the upstream pipeline stage
* @param inputShape the stream shape for the upstream pipeline stage
* @param opFlags operation flags for the new stage
*/
StatelessOp(AbstractPipeline<?, E_IN, ?> upstream,
StreamShape inputShape,
int opFlags) {
super(upstream, opFlags);
assert upstream.getOutputShape() == inputShape;
}
@Override
final boolean opIsStateful() {
return false;
}
}
/**
* Base class for a stateful intermediate stage of a DoubleStream.
*
* @param <E_IN> type of elements in the upstream source
* @since 1.8
*/
abstract static class StatefulOp<E_IN> extends DoublePipeline<E_IN> {
/**
* Construct a new DoubleStream by appending a stateful intermediate
* operation to an existing stream.
*
* @param upstream the upstream pipeline stage
* @param inputShape the stream shape for the upstream pipeline stage
* @param opFlags operation flags for the new stage
*/
StatefulOp(AbstractPipeline<?, E_IN, ?> upstream,
StreamShape inputShape,
int opFlags) {
super(upstream, opFlags);
assert upstream.getOutputShape() == inputShape;
}
@Override
final boolean opIsStateful() {
return true;
}
@Override
abstract <P_IN> Node<Double> opEvaluateParallel(PipelineHelper<Double> helper,
Spliterator<P_IN> spliterator,
IntFunction<Double[]> generator);
}
}

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/*
* Copyright (c) 2012, 2016, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Optional;
import java.util.OptionalDouble;
import java.util.OptionalInt;
import java.util.OptionalLong;
import java.util.Spliterator;
import java.util.concurrent.CountedCompleter;
import java.util.function.Predicate;
import java.util.function.Supplier;
/**
* Factory for instances of a short-circuiting {@code TerminalOp} that searches
* for an element in a stream pipeline, and terminates when it finds one.
* Supported variants include find-first (find the first element in the
* encounter order) and find-any (find any element, may not be the first in
* encounter order.)
*
* @since 1.8
*/
final class FindOps {
private FindOps() { }
/**
* Constructs a {@code TerminalOp} for streams of objects.
*
* @param <T> the type of elements of the stream
* @param mustFindFirst whether the {@code TerminalOp} must produce the
* first element in the encounter order
* @return a {@code TerminalOp} implementing the find operation
*/
@SuppressWarnings("unchecked")
public static <T> TerminalOp<T, Optional<T>> makeRef(boolean mustFindFirst) {
return (TerminalOp<T, Optional<T>>)
(mustFindFirst ? FindSink.OfRef.OP_FIND_FIRST : FindSink.OfRef.OP_FIND_ANY);
}
/**
* Constructs a {@code TerminalOp} for streams of ints.
*
* @param mustFindFirst whether the {@code TerminalOp} must produce the
* first element in the encounter order
* @return a {@code TerminalOp} implementing the find operation
*/
public static TerminalOp<Integer, OptionalInt> makeInt(boolean mustFindFirst) {
return mustFindFirst ? FindSink.OfInt.OP_FIND_FIRST : FindSink.OfInt.OP_FIND_ANY;
}
/**
* Constructs a {@code TerminalOp} for streams of longs.
*
* @param mustFindFirst whether the {@code TerminalOp} must produce the
* first element in the encounter order
* @return a {@code TerminalOp} implementing the find operation
*/
public static TerminalOp<Long, OptionalLong> makeLong(boolean mustFindFirst) {
return mustFindFirst ? FindSink.OfLong.OP_FIND_FIRST : FindSink.OfLong.OP_FIND_ANY;
}
/**
* Constructs a {@code FindOp} for streams of doubles.
*
* @param mustFindFirst whether the {@code TerminalOp} must produce the
* first element in the encounter order
* @return a {@code TerminalOp} implementing the find operation
*/
public static TerminalOp<Double, OptionalDouble> makeDouble(boolean mustFindFirst) {
return mustFindFirst ? FindSink.OfDouble.OP_FIND_FIRST : FindSink.OfDouble.OP_FIND_ANY;
}
/**
* A short-circuiting {@code TerminalOp} that searches for an element in a
* stream pipeline, and terminates when it finds one. Implements both
* find-first (find the first element in the encounter order) and find-any
* (find any element, may not be the first in encounter order.)
*
* @param <T> the output type of the stream pipeline
* @param <O> the result type of the find operation, typically an optional
* type
*/
private static final class FindOp<T, O> implements TerminalOp<T, O> {
private final StreamShape shape;
final int opFlags;
final O emptyValue;
final Predicate<O> presentPredicate;
final Supplier<TerminalSink<T, O>> sinkSupplier;
/**
* Constructs a {@code FindOp}.
*
* @param mustFindFirst if true, must find the first element in
* encounter order, otherwise can find any element
* @param shape stream shape of elements to search
* @param emptyValue result value corresponding to "found nothing"
* @param presentPredicate {@code Predicate} on result value
* corresponding to "found something"
* @param sinkSupplier supplier for a {@code TerminalSink} implementing
* the matching functionality
*/
FindOp(boolean mustFindFirst,
StreamShape shape,
O emptyValue,
Predicate<O> presentPredicate,
Supplier<TerminalSink<T, O>> sinkSupplier) {
this.opFlags = StreamOpFlag.IS_SHORT_CIRCUIT | (mustFindFirst ? 0 : StreamOpFlag.NOT_ORDERED);
this.shape = shape;
this.emptyValue = emptyValue;
this.presentPredicate = presentPredicate;
this.sinkSupplier = sinkSupplier;
}
@Override
public int getOpFlags() {
return opFlags;
}
@Override
public StreamShape inputShape() {
return shape;
}
@Override
public <S> O evaluateSequential(PipelineHelper<T> helper,
Spliterator<S> spliterator) {
O result = helper.wrapAndCopyInto(sinkSupplier.get(), spliterator).get();
return result != null ? result : emptyValue;
}
@Override
public <P_IN> O evaluateParallel(PipelineHelper<T> helper,
Spliterator<P_IN> spliterator) {
// This takes into account the upstream ops flags and the terminal
// op flags and therefore takes into account findFirst or findAny
boolean mustFindFirst = StreamOpFlag.ORDERED.isKnown(helper.getStreamAndOpFlags());
return new FindTask<>(this, mustFindFirst, helper, spliterator).invoke();
}
}
/**
* Implementation of @{code TerminalSink} that implements the find
* functionality, requesting cancellation when something has been found
*
* @param <T> The type of input element
* @param <O> The result type, typically an optional type
*/
private abstract static class FindSink<T, O> implements TerminalSink<T, O> {
boolean hasValue;
T value;
FindSink() {} // Avoid creation of special accessor
@Override
public void accept(T value) {
if (!hasValue) {
hasValue = true;
this.value = value;
}
}
@Override
public boolean cancellationRequested() {
return hasValue;
}
/** Specialization of {@code FindSink} for reference streams */
static final class OfRef<T> extends FindSink<T, Optional<T>> {
@Override
public Optional<T> get() {
return hasValue ? Optional.of(value) : null;
}
static final TerminalOp<?, ?> OP_FIND_FIRST = new FindOp<>(true,
StreamShape.REFERENCE, Optional.empty(),
Optional::isPresent, FindSink.OfRef::new);
static final TerminalOp<?, ?> OP_FIND_ANY = new FindOp<>(false,
StreamShape.REFERENCE, Optional.empty(),
Optional::isPresent, FindSink.OfRef::new);
}
/** Specialization of {@code FindSink} for int streams */
static final class OfInt extends FindSink<Integer, OptionalInt>
implements Sink.OfInt {
@Override
public void accept(int value) {
// Boxing is OK here, since few values will actually flow into the sink
accept((Integer) value);
}
@Override
public OptionalInt get() {
return hasValue ? OptionalInt.of(value) : null;
}
static final TerminalOp<Integer, OptionalInt> OP_FIND_FIRST = new FindOp<>(true,
StreamShape.INT_VALUE, OptionalInt.empty(),
OptionalInt::isPresent, FindSink.OfInt::new);
static final TerminalOp<Integer, OptionalInt> OP_FIND_ANY = new FindOp<>(false,
StreamShape.INT_VALUE, OptionalInt.empty(),
OptionalInt::isPresent, FindSink.OfInt::new);
}
/** Specialization of {@code FindSink} for long streams */
static final class OfLong extends FindSink<Long, OptionalLong>
implements Sink.OfLong {
@Override
public void accept(long value) {
// Boxing is OK here, since few values will actually flow into the sink
accept((Long) value);
}
@Override
public OptionalLong get() {
return hasValue ? OptionalLong.of(value) : null;
}
static final TerminalOp<Long, OptionalLong> OP_FIND_FIRST = new FindOp<>(true,
StreamShape.LONG_VALUE, OptionalLong.empty(),
OptionalLong::isPresent, FindSink.OfLong::new);
static final TerminalOp<Long, OptionalLong> OP_FIND_ANY = new FindOp<>(false,
StreamShape.LONG_VALUE, OptionalLong.empty(),
OptionalLong::isPresent, FindSink.OfLong::new);
}
/** Specialization of {@code FindSink} for double streams */
static final class OfDouble extends FindSink<Double, OptionalDouble>
implements Sink.OfDouble {
@Override
public void accept(double value) {
// Boxing is OK here, since few values will actually flow into the sink
accept((Double) value);
}
@Override
public OptionalDouble get() {
return hasValue ? OptionalDouble.of(value) : null;
}
static final TerminalOp<Double, OptionalDouble> OP_FIND_FIRST = new FindOp<>(true,
StreamShape.DOUBLE_VALUE, OptionalDouble.empty(),
OptionalDouble::isPresent, FindSink.OfDouble::new);
static final TerminalOp<Double, OptionalDouble> OP_FIND_ANY = new FindOp<>(false,
StreamShape.DOUBLE_VALUE, OptionalDouble.empty(),
OptionalDouble::isPresent, FindSink.OfDouble::new);
}
}
/**
* {@code ForkJoinTask} implementing parallel short-circuiting search
* @param <P_IN> Input element type to the stream pipeline
* @param <P_OUT> Output element type from the stream pipeline
* @param <O> Result type from the find operation
*/
@SuppressWarnings("serial")
private static final class FindTask<P_IN, P_OUT, O>
extends AbstractShortCircuitTask<P_IN, P_OUT, O, FindTask<P_IN, P_OUT, O>> {
private final FindOp<P_OUT, O> op;
private final boolean mustFindFirst;
FindTask(FindOp<P_OUT, O> op,
boolean mustFindFirst,
PipelineHelper<P_OUT> helper,
Spliterator<P_IN> spliterator) {
super(helper, spliterator);
this.mustFindFirst = mustFindFirst;
this.op = op;
}
FindTask(FindTask<P_IN, P_OUT, O> parent, Spliterator<P_IN> spliterator) {
super(parent, spliterator);
this.mustFindFirst = parent.mustFindFirst;
this.op = parent.op;
}
@Override
protected FindTask<P_IN, P_OUT, O> makeChild(Spliterator<P_IN> spliterator) {
return new FindTask<>(this, spliterator);
}
@Override
protected O getEmptyResult() {
return op.emptyValue;
}
private void foundResult(O answer) {
if (isLeftmostNode())
shortCircuit(answer);
else
cancelLaterNodes();
}
@Override
protected O doLeaf() {
O result = helper.wrapAndCopyInto(op.sinkSupplier.get(), spliterator).get();
if (!mustFindFirst) {
if (result != null)
shortCircuit(result);
return null;
}
else {
if (result != null) {
foundResult(result);
return result;
}
else
return null;
}
}
@Override
public void onCompletion(CountedCompleter<?> caller) {
if (mustFindFirst) {
for (FindTask<P_IN, P_OUT, O> child = leftChild, p = null; child != p;
p = child, child = rightChild) {
O result = child.getLocalResult();
if (result != null && op.presentPredicate.test(result)) {
setLocalResult(result);
foundResult(result);
break;
}
}
}
super.onCompletion(caller);
}
}
}

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/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Objects;
import java.util.Spliterator;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.CountedCompleter;
import java.util.concurrent.ForkJoinTask;
import java.util.function.Consumer;
import java.util.function.DoubleConsumer;
import java.util.function.IntConsumer;
import java.util.function.IntFunction;
import java.util.function.LongConsumer;
/**
* Factory for creating instances of {@code TerminalOp} that perform an
* action for every element of a stream. Supported variants include unordered
* traversal (elements are provided to the {@code Consumer} as soon as they are
* available), and ordered traversal (elements are provided to the
* {@code Consumer} in encounter order.)
*
* <p>Elements are provided to the {@code Consumer} on whatever thread and
* whatever order they become available. For ordered traversals, it is
* guaranteed that processing an element <em>happens-before</em> processing
* subsequent elements in the encounter order.
*
* <p>Exceptions occurring as a result of sending an element to the
* {@code Consumer} will be relayed to the caller and traversal will be
* prematurely terminated.
*
* @since 1.8
*/
final class ForEachOps {
private ForEachOps() { }
/**
* Constructs a {@code TerminalOp} that perform an action for every element
* of a stream.
*
* @param action the {@code Consumer} that receives all elements of a
* stream
* @param ordered whether an ordered traversal is requested
* @param <T> the type of the stream elements
* @return the {@code TerminalOp} instance
*/
public static <T> TerminalOp<T, Void> makeRef(Consumer<? super T> action,
boolean ordered) {
Objects.requireNonNull(action);
return new ForEachOp.OfRef<>(action, ordered);
}
/**
* Constructs a {@code TerminalOp} that perform an action for every element
* of an {@code IntStream}.
*
* @param action the {@code IntConsumer} that receives all elements of a
* stream
* @param ordered whether an ordered traversal is requested
* @return the {@code TerminalOp} instance
*/
public static TerminalOp<Integer, Void> makeInt(IntConsumer action,
boolean ordered) {
Objects.requireNonNull(action);
return new ForEachOp.OfInt(action, ordered);
}
/**
* Constructs a {@code TerminalOp} that perform an action for every element
* of a {@code LongStream}.
*
* @param action the {@code LongConsumer} that receives all elements of a
* stream
* @param ordered whether an ordered traversal is requested
* @return the {@code TerminalOp} instance
*/
public static TerminalOp<Long, Void> makeLong(LongConsumer action,
boolean ordered) {
Objects.requireNonNull(action);
return new ForEachOp.OfLong(action, ordered);
}
/**
* Constructs a {@code TerminalOp} that perform an action for every element
* of a {@code DoubleStream}.
*
* @param action the {@code DoubleConsumer} that receives all elements of
* a stream
* @param ordered whether an ordered traversal is requested
* @return the {@code TerminalOp} instance
*/
public static TerminalOp<Double, Void> makeDouble(DoubleConsumer action,
boolean ordered) {
Objects.requireNonNull(action);
return new ForEachOp.OfDouble(action, ordered);
}
/**
* A {@code TerminalOp} that evaluates a stream pipeline and sends the
* output to itself as a {@code TerminalSink}. Elements will be sent in
* whatever thread they become available. If the traversal is unordered,
* they will be sent independent of the stream's encounter order.
*
* <p>This terminal operation is stateless. For parallel evaluation, each
* leaf instance of a {@code ForEachTask} will send elements to the same
* {@code TerminalSink} reference that is an instance of this class.
*
* @param <T> the output type of the stream pipeline
*/
abstract static class ForEachOp<T>
implements TerminalOp<T, Void>, TerminalSink<T, Void> {
private final boolean ordered;
protected ForEachOp(boolean ordered) {
this.ordered = ordered;
}
// TerminalOp
@Override
public int getOpFlags() {
return ordered ? 0 : StreamOpFlag.NOT_ORDERED;
}
@Override
public <S> Void evaluateSequential(PipelineHelper<T> helper,
Spliterator<S> spliterator) {
return helper.wrapAndCopyInto(this, spliterator).get();
}
@Override
public <S> Void evaluateParallel(PipelineHelper<T> helper,
Spliterator<S> spliterator) {
if (ordered)
new ForEachOrderedTask<>(helper, spliterator, this).invoke();
else
new ForEachTask<>(helper, spliterator, helper.wrapSink(this)).invoke();
return null;
}
// TerminalSink
@Override
public Void get() {
return null;
}
// Implementations
/** Implementation class for reference streams */
static final class OfRef<T> extends ForEachOp<T> {
final Consumer<? super T> consumer;
OfRef(Consumer<? super T> consumer, boolean ordered) {
super(ordered);
this.consumer = consumer;
}
@Override
public void accept(T t) {
consumer.accept(t);
}
}
/** Implementation class for {@code IntStream} */
static final class OfInt extends ForEachOp<Integer>
implements Sink.OfInt {
final IntConsumer consumer;
OfInt(IntConsumer consumer, boolean ordered) {
super(ordered);
this.consumer = consumer;
}
@Override
public StreamShape inputShape() {
return StreamShape.INT_VALUE;
}
@Override
public void accept(int t) {
consumer.accept(t);
}
}
/** Implementation class for {@code LongStream} */
static final class OfLong extends ForEachOp<Long>
implements Sink.OfLong {
final LongConsumer consumer;
OfLong(LongConsumer consumer, boolean ordered) {
super(ordered);
this.consumer = consumer;
}
@Override
public StreamShape inputShape() {
return StreamShape.LONG_VALUE;
}
@Override
public void accept(long t) {
consumer.accept(t);
}
}
/** Implementation class for {@code DoubleStream} */
static final class OfDouble extends ForEachOp<Double>
implements Sink.OfDouble {
final DoubleConsumer consumer;
OfDouble(DoubleConsumer consumer, boolean ordered) {
super(ordered);
this.consumer = consumer;
}
@Override
public StreamShape inputShape() {
return StreamShape.DOUBLE_VALUE;
}
@Override
public void accept(double t) {
consumer.accept(t);
}
}
}
/** A {@code ForkJoinTask} for performing a parallel for-each operation */
@SuppressWarnings("serial")
static final class ForEachTask<S, T> extends CountedCompleter<Void> {
private Spliterator<S> spliterator;
private final Sink<S> sink;
private final PipelineHelper<T> helper;
private long targetSize;
ForEachTask(PipelineHelper<T> helper,
Spliterator<S> spliterator,
Sink<S> sink) {
super(null);
this.sink = sink;
this.helper = helper;
this.spliterator = spliterator;
this.targetSize = 0L;
}
ForEachTask(ForEachTask<S, T> parent, Spliterator<S> spliterator) {
super(parent);
this.spliterator = spliterator;
this.sink = parent.sink;
this.targetSize = parent.targetSize;
this.helper = parent.helper;
}
// Similar to AbstractTask but doesn't need to track child tasks
public void compute() {
Spliterator<S> rightSplit = spliterator, leftSplit;
long sizeEstimate = rightSplit.estimateSize(), sizeThreshold;
if ((sizeThreshold = targetSize) == 0L)
targetSize = sizeThreshold = AbstractTask.suggestTargetSize(sizeEstimate);
boolean isShortCircuit = StreamOpFlag.SHORT_CIRCUIT.isKnown(helper.getStreamAndOpFlags());
boolean forkRight = false;
Sink<S> taskSink = sink;
ForEachTask<S, T> task = this;
while (!isShortCircuit || !taskSink.cancellationRequested()) {
if (sizeEstimate <= sizeThreshold ||
(leftSplit = rightSplit.trySplit()) == null) {
task.helper.copyInto(taskSink, rightSplit);
break;
}
ForEachTask<S, T> leftTask = new ForEachTask<>(task, leftSplit);
task.addToPendingCount(1);
ForEachTask<S, T> taskToFork;
if (forkRight) {
forkRight = false;
rightSplit = leftSplit;
taskToFork = task;
task = leftTask;
}
else {
forkRight = true;
taskToFork = leftTask;
}
taskToFork.fork();
sizeEstimate = rightSplit.estimateSize();
}
task.spliterator = null;
task.propagateCompletion();
}
}
/**
* A {@code ForkJoinTask} for performing a parallel for-each operation
* which visits the elements in encounter order
*/
@SuppressWarnings("serial")
static final class ForEachOrderedTask<S, T> extends CountedCompleter<Void> {
/*
* Our goal is to ensure that the elements associated with a task are
* processed according to an in-order traversal of the computation tree.
* We use completion counts for representing these dependencies, so that
* a task does not complete until all the tasks preceding it in this
* order complete. We use the "completion map" to associate the next
* task in this order for any left child. We increase the pending count
* of any node on the right side of such a mapping by one to indicate
* its dependency, and when a node on the left side of such a mapping
* completes, it decrements the pending count of its corresponding right
* side. As the computation tree is expanded by splitting, we must
* atomically update the mappings to maintain the invariant that the
* completion map maps left children to the next node in the in-order
* traversal.
*
* Take, for example, the following computation tree of tasks:
*
* a
* / \
* b c
* / \ / \
* d e f g
*
* The complete map will contain (not necessarily all at the same time)
* the following associations:
*
* d -> e
* b -> f
* f -> g
*
* Tasks e, f, g will have their pending counts increased by 1.
*
* The following relationships hold:
*
* - completion of d "happens-before" e;
* - completion of d and e "happens-before b;
* - completion of b "happens-before" f; and
* - completion of f "happens-before" g
*
* Thus overall the "happens-before" relationship holds for the
* reporting of elements, covered by tasks d, e, f and g, as specified
* by the forEachOrdered operation.
*/
private final PipelineHelper<T> helper;
private Spliterator<S> spliterator;
private final long targetSize;
private final ConcurrentHashMap<ForEachOrderedTask<S, T>, ForEachOrderedTask<S, T>> completionMap;
private final Sink<T> action;
private final ForEachOrderedTask<S, T> leftPredecessor;
private Node<T> node;
protected ForEachOrderedTask(PipelineHelper<T> helper,
Spliterator<S> spliterator,
Sink<T> action) {
super(null);
this.helper = helper;
this.spliterator = spliterator;
this.targetSize = AbstractTask.suggestTargetSize(spliterator.estimateSize());
// Size map to avoid concurrent re-sizes
this.completionMap = new ConcurrentHashMap<>(Math.max(16, AbstractTask.LEAF_TARGET << 1));
this.action = action;
this.leftPredecessor = null;
}
ForEachOrderedTask(ForEachOrderedTask<S, T> parent,
Spliterator<S> spliterator,
ForEachOrderedTask<S, T> leftPredecessor) {
super(parent);
this.helper = parent.helper;
this.spliterator = spliterator;
this.targetSize = parent.targetSize;
this.completionMap = parent.completionMap;
this.action = parent.action;
this.leftPredecessor = leftPredecessor;
}
@Override
public final void compute() {
doCompute(this);
}
private static <S, T> void doCompute(ForEachOrderedTask<S, T> task) {
Spliterator<S> rightSplit = task.spliterator, leftSplit;
long sizeThreshold = task.targetSize;
boolean forkRight = false;
while (rightSplit.estimateSize() > sizeThreshold &&
(leftSplit = rightSplit.trySplit()) != null) {
ForEachOrderedTask<S, T> leftChild =
new ForEachOrderedTask<>(task, leftSplit, task.leftPredecessor);
ForEachOrderedTask<S, T> rightChild =
new ForEachOrderedTask<>(task, rightSplit, leftChild);
// Fork the parent task
// Completion of the left and right children "happens-before"
// completion of the parent
task.addToPendingCount(1);
// Completion of the left child "happens-before" completion of
// the right child
rightChild.addToPendingCount(1);
task.completionMap.put(leftChild, rightChild);
// If task is not on the left spine
if (task.leftPredecessor != null) {
/*
* Completion of left-predecessor, or left subtree,
* "happens-before" completion of left-most leaf node of
* right subtree.
* The left child's pending count needs to be updated before
* it is associated in the completion map, otherwise the
* left child can complete prematurely and violate the
* "happens-before" constraint.
*/
leftChild.addToPendingCount(1);
// Update association of left-predecessor to left-most
// leaf node of right subtree
if (task.completionMap.replace(task.leftPredecessor, task, leftChild)) {
// If replaced, adjust the pending count of the parent
// to complete when its children complete
task.addToPendingCount(-1);
} else {
// Left-predecessor has already completed, parent's
// pending count is adjusted by left-predecessor;
// left child is ready to complete
leftChild.addToPendingCount(-1);
}
}
ForEachOrderedTask<S, T> taskToFork;
if (forkRight) {
forkRight = false;
rightSplit = leftSplit;
task = leftChild;
taskToFork = rightChild;
}
else {
forkRight = true;
task = rightChild;
taskToFork = leftChild;
}
taskToFork.fork();
}
/*
* Task's pending count is either 0 or 1. If 1 then the completion
* map will contain a value that is task, and two calls to
* tryComplete are required for completion, one below and one
* triggered by the completion of task's left-predecessor in
* onCompletion. Therefore there is no data race within the if
* block.
*/
if (task.getPendingCount() > 0) {
// Cannot complete just yet so buffer elements into a Node
// for use when completion occurs
@SuppressWarnings("unchecked")
IntFunction<T[]> generator = size -> (T[]) new Object[size];
Node.Builder<T> nb = task.helper.makeNodeBuilder(
task.helper.exactOutputSizeIfKnown(rightSplit),
generator);
task.node = task.helper.wrapAndCopyInto(nb, rightSplit).build();
task.spliterator = null;
}
task.tryComplete();
}
@Override
public void onCompletion(CountedCompleter<?> caller) {
if (node != null) {
// Dump buffered elements from this leaf into the sink
node.forEach(action);
node = null;
}
else if (spliterator != null) {
// Dump elements output from this leaf's pipeline into the sink
helper.wrapAndCopyInto(action, spliterator);
spliterator = null;
}
// The completion of this task *and* the dumping of elements
// "happens-before" completion of the associated left-most leaf task
// of right subtree (if any, which can be this task's right sibling)
//
ForEachOrderedTask<S, T> leftDescendant = completionMap.remove(this);
if (leftDescendant != null)
leftDescendant.tryComplete();
}
}
}

View file

@ -0,0 +1,647 @@
/*
* Copyright (c) 2012, 2016, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.IntSummaryStatistics;
import java.util.Objects;
import java.util.OptionalDouble;
import java.util.OptionalInt;
import java.util.PrimitiveIterator;
import java.util.Spliterator;
import java.util.Spliterators;
import java.util.function.BiConsumer;
import java.util.function.BinaryOperator;
import java.util.function.IntBinaryOperator;
import java.util.function.IntConsumer;
import java.util.function.IntFunction;
import java.util.function.IntPredicate;
import java.util.function.IntToDoubleFunction;
import java.util.function.IntToLongFunction;
import java.util.function.IntUnaryOperator;
import java.util.function.ObjIntConsumer;
import java.util.function.Supplier;
/**
* Abstract base class for an intermediate pipeline stage or pipeline source
* stage implementing whose elements are of type {@code int}.
*
* @param <E_IN> type of elements in the upstream source
* @since 1.8
*/
abstract class IntPipeline<E_IN>
extends AbstractPipeline<E_IN, Integer, IntStream>
implements IntStream {
/**
* Constructor for the head of a stream pipeline.
*
* @param source {@code Supplier<Spliterator>} describing the stream source
* @param sourceFlags The source flags for the stream source, described in
* {@link StreamOpFlag}
* @param parallel {@code true} if the pipeline is parallel
*/
IntPipeline(Supplier<? extends Spliterator<Integer>> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
/**
* Constructor for the head of a stream pipeline.
*
* @param source {@code Spliterator} describing the stream source
* @param sourceFlags The source flags for the stream source, described in
* {@link StreamOpFlag}
* @param parallel {@code true} if the pipeline is parallel
*/
IntPipeline(Spliterator<Integer> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
/**
* Constructor for appending an intermediate operation onto an existing
* pipeline.
*
* @param upstream the upstream element source
* @param opFlags the operation flags for the new operation
*/
IntPipeline(AbstractPipeline<?, E_IN, ?> upstream, int opFlags) {
super(upstream, opFlags);
}
/**
* Adapt a {@code Sink<Integer> to an {@code IntConsumer}, ideally simply
* by casting.
*/
private static IntConsumer adapt(Sink<Integer> sink) {
if (sink instanceof IntConsumer) {
return (IntConsumer) sink;
}
else {
if (Tripwire.ENABLED)
Tripwire.trip(AbstractPipeline.class,
"using IntStream.adapt(Sink<Integer> s)");
return sink::accept;
}
}
/**
* Adapt a {@code Spliterator<Integer>} to a {@code Spliterator.OfInt}.
*
* @implNote
* The implementation attempts to cast to a Spliterator.OfInt, and throws an
* exception if this cast is not possible.
*/
private static Spliterator.OfInt adapt(Spliterator<Integer> s) {
if (s instanceof Spliterator.OfInt) {
return (Spliterator.OfInt) s;
}
else {
if (Tripwire.ENABLED)
Tripwire.trip(AbstractPipeline.class,
"using IntStream.adapt(Spliterator<Integer> s)");
throw new UnsupportedOperationException("IntStream.adapt(Spliterator<Integer> s)");
}
}
// Shape-specific methods
@Override
final StreamShape getOutputShape() {
return StreamShape.INT_VALUE;
}
@Override
final <P_IN> Node<Integer> evaluateToNode(PipelineHelper<Integer> helper,
Spliterator<P_IN> spliterator,
boolean flattenTree,
IntFunction<Integer[]> generator) {
return Nodes.collectInt(helper, spliterator, flattenTree);
}
@Override
final <P_IN> Spliterator<Integer> wrap(PipelineHelper<Integer> ph,
Supplier<Spliterator<P_IN>> supplier,
boolean isParallel) {
return new StreamSpliterators.IntWrappingSpliterator<>(ph, supplier, isParallel);
}
@Override
@SuppressWarnings("unchecked")
final Spliterator.OfInt lazySpliterator(Supplier<? extends Spliterator<Integer>> supplier) {
return new StreamSpliterators.DelegatingSpliterator.OfInt((Supplier<Spliterator.OfInt>) supplier);
}
@Override
final boolean forEachWithCancel(Spliterator<Integer> spliterator, Sink<Integer> sink) {
Spliterator.OfInt spl = adapt(spliterator);
IntConsumer adaptedSink = adapt(sink);
boolean cancelled;
do { } while (!(cancelled = sink.cancellationRequested()) && spl.tryAdvance(adaptedSink));
return cancelled;
}
@Override
final Node.Builder<Integer> makeNodeBuilder(long exactSizeIfKnown,
IntFunction<Integer[]> generator) {
return Nodes.intBuilder(exactSizeIfKnown);
}
private <U> Stream<U> mapToObj(IntFunction<? extends U> mapper, int opFlags) {
return new ReferencePipeline.StatelessOp<Integer, U>(this, StreamShape.INT_VALUE, opFlags) {
@Override
Sink<Integer> opWrapSink(int flags, Sink<U> sink) {
return new Sink.ChainedInt<U>(sink) {
@Override
public void accept(int t) {
downstream.accept(mapper.apply(t));
}
};
}
};
}
// IntStream
@Override
public final PrimitiveIterator.OfInt iterator() {
return Spliterators.iterator(spliterator());
}
@Override
public final Spliterator.OfInt spliterator() {
return adapt(super.spliterator());
}
// Stateless intermediate ops from IntStream
@Override
public final LongStream asLongStream() {
return new LongPipeline.StatelessOp<Integer>(this, StreamShape.INT_VALUE, 0) {
@Override
Sink<Integer> opWrapSink(int flags, Sink<Long> sink) {
return new Sink.ChainedInt<Long>(sink) {
@Override
public void accept(int t) {
downstream.accept((long) t);
}
};
}
};
}
@Override
public final DoubleStream asDoubleStream() {
return new DoublePipeline.StatelessOp<Integer>(this, StreamShape.INT_VALUE, 0) {
@Override
Sink<Integer> opWrapSink(int flags, Sink<Double> sink) {
return new Sink.ChainedInt<Double>(sink) {
@Override
public void accept(int t) {
downstream.accept((double) t);
}
};
}
};
}
@Override
public final Stream<Integer> boxed() {
return mapToObj(Integer::valueOf, 0);
}
@Override
public final IntStream map(IntUnaryOperator mapper) {
Objects.requireNonNull(mapper);
return new StatelessOp<Integer>(this, StreamShape.INT_VALUE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT) {
@Override
Sink<Integer> opWrapSink(int flags, Sink<Integer> sink) {
return new Sink.ChainedInt<Integer>(sink) {
@Override
public void accept(int t) {
downstream.accept(mapper.applyAsInt(t));
}
};
}
};
}
@Override
public final <U> Stream<U> mapToObj(IntFunction<? extends U> mapper) {
Objects.requireNonNull(mapper);
return mapToObj(mapper, StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT);
}
@Override
public final LongStream mapToLong(IntToLongFunction mapper) {
Objects.requireNonNull(mapper);
return new LongPipeline.StatelessOp<Integer>(this, StreamShape.INT_VALUE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT) {
@Override
Sink<Integer> opWrapSink(int flags, Sink<Long> sink) {
return new Sink.ChainedInt<Long>(sink) {
@Override
public void accept(int t) {
downstream.accept(mapper.applyAsLong(t));
}
};
}
};
}
@Override
public final DoubleStream mapToDouble(IntToDoubleFunction mapper) {
Objects.requireNonNull(mapper);
return new DoublePipeline.StatelessOp<Integer>(this, StreamShape.INT_VALUE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT) {
@Override
Sink<Integer> opWrapSink(int flags, Sink<Double> sink) {
return new Sink.ChainedInt<Double>(sink) {
@Override
public void accept(int t) {
downstream.accept(mapper.applyAsDouble(t));
}
};
}
};
}
@Override
public final IntStream flatMap(IntFunction<? extends IntStream> mapper) {
Objects.requireNonNull(mapper);
return new StatelessOp<Integer>(this, StreamShape.INT_VALUE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT | StreamOpFlag.NOT_SIZED) {
@Override
Sink<Integer> opWrapSink(int flags, Sink<Integer> sink) {
return new Sink.ChainedInt<Integer>(sink) {
@Override
public void begin(long size) {
downstream.begin(-1);
}
@Override
public void accept(int t) {
try (IntStream result = mapper.apply(t)) {
// We can do better that this too; optimize for depth=0 case and just grab spliterator and forEach it
if (result != null)
result.sequential().forEach(i -> downstream.accept(i));
}
}
};
}
};
}
@Override
public IntStream unordered() {
if (!isOrdered())
return this;
return new StatelessOp<Integer>(this, StreamShape.INT_VALUE, StreamOpFlag.NOT_ORDERED) {
@Override
Sink<Integer> opWrapSink(int flags, Sink<Integer> sink) {
return sink;
}
};
}
@Override
public final IntStream filter(IntPredicate predicate) {
Objects.requireNonNull(predicate);
return new StatelessOp<Integer>(this, StreamShape.INT_VALUE,
StreamOpFlag.NOT_SIZED) {
@Override
Sink<Integer> opWrapSink(int flags, Sink<Integer> sink) {
return new Sink.ChainedInt<Integer>(sink) {
@Override
public void begin(long size) {
downstream.begin(-1);
}
@Override
public void accept(int t) {
if (predicate.test(t))
downstream.accept(t);
}
};
}
};
}
@Override
public final IntStream peek(IntConsumer action) {
Objects.requireNonNull(action);
return new StatelessOp<Integer>(this, StreamShape.INT_VALUE,
0) {
@Override
Sink<Integer> opWrapSink(int flags, Sink<Integer> sink) {
return new Sink.ChainedInt<Integer>(sink) {
@Override
public void accept(int t) {
action.accept(t);
downstream.accept(t);
}
};
}
};
}
// Stateful intermediate ops from IntStream
@Override
public final IntStream limit(long maxSize) {
if (maxSize < 0)
throw new IllegalArgumentException(Long.toString(maxSize));
return SliceOps.makeInt(this, 0, maxSize);
}
@Override
public final IntStream skip(long n) {
if (n < 0)
throw new IllegalArgumentException(Long.toString(n));
if (n == 0)
return this;
else
return SliceOps.makeInt(this, n, -1);
}
@Override
public final IntStream takeWhile(IntPredicate predicate) {
return WhileOps.makeTakeWhileInt(this, predicate);
}
@Override
public final IntStream dropWhile(IntPredicate predicate) {
return WhileOps.makeDropWhileInt(this, predicate);
}
@Override
public final IntStream sorted() {
return SortedOps.makeInt(this);
}
@Override
public final IntStream distinct() {
// While functional and quick to implement, this approach is not very efficient.
// An efficient version requires an int-specific map/set implementation.
return boxed().distinct().mapToInt(i -> i);
}
// Terminal ops from IntStream
@Override
public void forEach(IntConsumer action) {
evaluate(ForEachOps.makeInt(action, false));
}
@Override
public void forEachOrdered(IntConsumer action) {
evaluate(ForEachOps.makeInt(action, true));
}
@Override
public final int sum() {
return reduce(0, Integer::sum);
}
@Override
public final OptionalInt min() {
return reduce(Math::min);
}
@Override
public final OptionalInt max() {
return reduce(Math::max);
}
@Override
public final long count() {
return evaluate(ReduceOps.makeIntCounting());
}
@Override
public final OptionalDouble average() {
long[] avg = collect(() -> new long[2],
(ll, i) -> {
ll[0]++;
ll[1] += i;
},
(ll, rr) -> {
ll[0] += rr[0];
ll[1] += rr[1];
});
return avg[0] > 0
? OptionalDouble.of((double) avg[1] / avg[0])
: OptionalDouble.empty();
}
@Override
public final IntSummaryStatistics summaryStatistics() {
return collect(IntSummaryStatistics::new, IntSummaryStatistics::accept,
IntSummaryStatistics::combine);
}
@Override
public final int reduce(int identity, IntBinaryOperator op) {
return evaluate(ReduceOps.makeInt(identity, op));
}
@Override
public final OptionalInt reduce(IntBinaryOperator op) {
return evaluate(ReduceOps.makeInt(op));
}
@Override
public final <R> R collect(Supplier<R> supplier,
ObjIntConsumer<R> accumulator,
BiConsumer<R, R> combiner) {
Objects.requireNonNull(combiner);
BinaryOperator<R> operator = (left, right) -> {
combiner.accept(left, right);
return left;
};
return evaluate(ReduceOps.makeInt(supplier, accumulator, operator));
}
@Override
public final boolean anyMatch(IntPredicate predicate) {
return evaluate(MatchOps.makeInt(predicate, MatchOps.MatchKind.ANY));
}
@Override
public final boolean allMatch(IntPredicate predicate) {
return evaluate(MatchOps.makeInt(predicate, MatchOps.MatchKind.ALL));
}
@Override
public final boolean noneMatch(IntPredicate predicate) {
return evaluate(MatchOps.makeInt(predicate, MatchOps.MatchKind.NONE));
}
@Override
public final OptionalInt findFirst() {
return evaluate(FindOps.makeInt(true));
}
@Override
public final OptionalInt findAny() {
return evaluate(FindOps.makeInt(false));
}
@Override
public final int[] toArray() {
return Nodes.flattenInt((Node.OfInt) evaluateToArrayNode(Integer[]::new))
.asPrimitiveArray();
}
//
/**
* Source stage of an IntStream.
*
* @param <E_IN> type of elements in the upstream source
* @since 1.8
*/
static class Head<E_IN> extends IntPipeline<E_IN> {
/**
* Constructor for the source stage of an IntStream.
*
* @param source {@code Supplier<Spliterator>} describing the stream
* source
* @param sourceFlags the source flags for the stream source, described
* in {@link StreamOpFlag}
* @param parallel {@code true} if the pipeline is parallel
*/
Head(Supplier<? extends Spliterator<Integer>> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
/**
* Constructor for the source stage of an IntStream.
*
* @param source {@code Spliterator} describing the stream source
* @param sourceFlags the source flags for the stream source, described
* in {@link StreamOpFlag}
* @param parallel {@code true} if the pipeline is parallel
*/
Head(Spliterator<Integer> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
@Override
final boolean opIsStateful() {
throw new UnsupportedOperationException();
}
@Override
final Sink<E_IN> opWrapSink(int flags, Sink<Integer> sink) {
throw new UnsupportedOperationException();
}
// Optimized sequential terminal operations for the head of the pipeline
@Override
public void forEach(IntConsumer action) {
if (!isParallel()) {
adapt(sourceStageSpliterator()).forEachRemaining(action);
}
else {
super.forEach(action);
}
}
@Override
public void forEachOrdered(IntConsumer action) {
if (!isParallel()) {
adapt(sourceStageSpliterator()).forEachRemaining(action);
}
else {
super.forEachOrdered(action);
}
}
}
/**
* Base class for a stateless intermediate stage of an IntStream
*
* @param <E_IN> type of elements in the upstream source
* @since 1.8
*/
abstract static class StatelessOp<E_IN> extends IntPipeline<E_IN> {
/**
* Construct a new IntStream by appending a stateless intermediate
* operation to an existing stream.
* @param upstream The upstream pipeline stage
* @param inputShape The stream shape for the upstream pipeline stage
* @param opFlags Operation flags for the new stage
*/
StatelessOp(AbstractPipeline<?, E_IN, ?> upstream,
StreamShape inputShape,
int opFlags) {
super(upstream, opFlags);
assert upstream.getOutputShape() == inputShape;
}
@Override
final boolean opIsStateful() {
return false;
}
}
/**
* Base class for a stateful intermediate stage of an IntStream.
*
* @param <E_IN> type of elements in the upstream source
* @since 1.8
*/
abstract static class StatefulOp<E_IN> extends IntPipeline<E_IN> {
/**
* Construct a new IntStream by appending a stateful intermediate
* operation to an existing stream.
* @param upstream The upstream pipeline stage
* @param inputShape The stream shape for the upstream pipeline stage
* @param opFlags Operation flags for the new stage
*/
StatefulOp(AbstractPipeline<?, E_IN, ?> upstream,
StreamShape inputShape,
int opFlags) {
super(upstream, opFlags);
assert upstream.getOutputShape() == inputShape;
}
@Override
final boolean opIsStateful() {
return true;
}
@Override
abstract <P_IN> Node<Integer> opEvaluateParallel(PipelineHelper<Integer> helper,
Spliterator<P_IN> spliterator,
IntFunction<Integer[]> generator);
}
}

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/*
* Copyright (c) 2013, 2016, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.LongSummaryStatistics;
import java.util.Objects;
import java.util.OptionalDouble;
import java.util.OptionalLong;
import java.util.PrimitiveIterator;
import java.util.Spliterator;
import java.util.Spliterators;
import java.util.function.BiConsumer;
import java.util.function.BinaryOperator;
import java.util.function.IntFunction;
import java.util.function.LongBinaryOperator;
import java.util.function.LongConsumer;
import java.util.function.LongFunction;
import java.util.function.LongPredicate;
import java.util.function.LongToDoubleFunction;
import java.util.function.LongToIntFunction;
import java.util.function.LongUnaryOperator;
import java.util.function.ObjLongConsumer;
import java.util.function.Supplier;
/**
* Abstract base class for an intermediate pipeline stage or pipeline source
* stage implementing whose elements are of type {@code long}.
*
* @param <E_IN> type of elements in the upstream source
* @since 1.8
*/
abstract class LongPipeline<E_IN>
extends AbstractPipeline<E_IN, Long, LongStream>
implements LongStream {
/**
* Constructor for the head of a stream pipeline.
*
* @param source {@code Supplier<Spliterator>} describing the stream source
* @param sourceFlags the source flags for the stream source, described in
* {@link StreamOpFlag}
* @param parallel {@code true} if the pipeline is parallel
*/
LongPipeline(Supplier<? extends Spliterator<Long>> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
/**
* Constructor for the head of a stream pipeline.
*
* @param source {@code Spliterator} describing the stream source
* @param sourceFlags the source flags for the stream source, described in
* {@link StreamOpFlag}
* @param parallel {@code true} if the pipeline is parallel
*/
LongPipeline(Spliterator<Long> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
/**
* Constructor for appending an intermediate operation onto an existing pipeline.
*
* @param upstream the upstream element source.
* @param opFlags the operation flags
*/
LongPipeline(AbstractPipeline<?, E_IN, ?> upstream, int opFlags) {
super(upstream, opFlags);
}
/**
* Adapt a {@code Sink<Long> to an {@code LongConsumer}, ideally simply
* by casting.
*/
private static LongConsumer adapt(Sink<Long> sink) {
if (sink instanceof LongConsumer) {
return (LongConsumer) sink;
} else {
if (Tripwire.ENABLED)
Tripwire.trip(AbstractPipeline.class,
"using LongStream.adapt(Sink<Long> s)");
return sink::accept;
}
}
/**
* Adapt a {@code Spliterator<Long>} to a {@code Spliterator.OfLong}.
*
* @implNote
* The implementation attempts to cast to a Spliterator.OfLong, and throws
* an exception if this cast is not possible.
*/
private static Spliterator.OfLong adapt(Spliterator<Long> s) {
if (s instanceof Spliterator.OfLong) {
return (Spliterator.OfLong) s;
} else {
if (Tripwire.ENABLED)
Tripwire.trip(AbstractPipeline.class,
"using LongStream.adapt(Spliterator<Long> s)");
throw new UnsupportedOperationException("LongStream.adapt(Spliterator<Long> s)");
}
}
// Shape-specific methods
@Override
final StreamShape getOutputShape() {
return StreamShape.LONG_VALUE;
}
@Override
final <P_IN> Node<Long> evaluateToNode(PipelineHelper<Long> helper,
Spliterator<P_IN> spliterator,
boolean flattenTree,
IntFunction<Long[]> generator) {
return Nodes.collectLong(helper, spliterator, flattenTree);
}
@Override
final <P_IN> Spliterator<Long> wrap(PipelineHelper<Long> ph,
Supplier<Spliterator<P_IN>> supplier,
boolean isParallel) {
return new StreamSpliterators.LongWrappingSpliterator<>(ph, supplier, isParallel);
}
@Override
@SuppressWarnings("unchecked")
final Spliterator.OfLong lazySpliterator(Supplier<? extends Spliterator<Long>> supplier) {
return new StreamSpliterators.DelegatingSpliterator.OfLong((Supplier<Spliterator.OfLong>) supplier);
}
@Override
final boolean forEachWithCancel(Spliterator<Long> spliterator, Sink<Long> sink) {
Spliterator.OfLong spl = adapt(spliterator);
LongConsumer adaptedSink = adapt(sink);
boolean cancelled;
do { } while (!(cancelled = sink.cancellationRequested()) && spl.tryAdvance(adaptedSink));
return cancelled;
}
@Override
final Node.Builder<Long> makeNodeBuilder(long exactSizeIfKnown, IntFunction<Long[]> generator) {
return Nodes.longBuilder(exactSizeIfKnown);
}
private <U> Stream<U> mapToObj(LongFunction<? extends U> mapper, int opFlags) {
return new ReferencePipeline.StatelessOp<Long, U>(this, StreamShape.LONG_VALUE, opFlags) {
@Override
Sink<Long> opWrapSink(int flags, Sink<U> sink) {
return new Sink.ChainedLong<U>(sink) {
@Override
public void accept(long t) {
downstream.accept(mapper.apply(t));
}
};
}
};
}
// LongStream
@Override
public final PrimitiveIterator.OfLong iterator() {
return Spliterators.iterator(spliterator());
}
@Override
public final Spliterator.OfLong spliterator() {
return adapt(super.spliterator());
}
// Stateless intermediate ops from LongStream
@Override
public final DoubleStream asDoubleStream() {
return new DoublePipeline.StatelessOp<Long>(this, StreamShape.LONG_VALUE, StreamOpFlag.NOT_DISTINCT) {
@Override
Sink<Long> opWrapSink(int flags, Sink<Double> sink) {
return new Sink.ChainedLong<Double>(sink) {
@Override
public void accept(long t) {
downstream.accept((double) t);
}
};
}
};
}
@Override
public final Stream<Long> boxed() {
return mapToObj(Long::valueOf, 0);
}
@Override
public final LongStream map(LongUnaryOperator mapper) {
Objects.requireNonNull(mapper);
return new StatelessOp<Long>(this, StreamShape.LONG_VALUE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT) {
@Override
Sink<Long> opWrapSink(int flags, Sink<Long> sink) {
return new Sink.ChainedLong<Long>(sink) {
@Override
public void accept(long t) {
downstream.accept(mapper.applyAsLong(t));
}
};
}
};
}
@Override
public final <U> Stream<U> mapToObj(LongFunction<? extends U> mapper) {
Objects.requireNonNull(mapper);
return mapToObj(mapper, StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT);
}
@Override
public final IntStream mapToInt(LongToIntFunction mapper) {
Objects.requireNonNull(mapper);
return new IntPipeline.StatelessOp<Long>(this, StreamShape.LONG_VALUE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT) {
@Override
Sink<Long> opWrapSink(int flags, Sink<Integer> sink) {
return new Sink.ChainedLong<Integer>(sink) {
@Override
public void accept(long t) {
downstream.accept(mapper.applyAsInt(t));
}
};
}
};
}
@Override
public final DoubleStream mapToDouble(LongToDoubleFunction mapper) {
Objects.requireNonNull(mapper);
return new DoublePipeline.StatelessOp<Long>(this, StreamShape.LONG_VALUE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT) {
@Override
Sink<Long> opWrapSink(int flags, Sink<Double> sink) {
return new Sink.ChainedLong<Double>(sink) {
@Override
public void accept(long t) {
downstream.accept(mapper.applyAsDouble(t));
}
};
}
};
}
@Override
public final LongStream flatMap(LongFunction<? extends LongStream> mapper) {
Objects.requireNonNull(mapper);
return new StatelessOp<Long>(this, StreamShape.LONG_VALUE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT | StreamOpFlag.NOT_SIZED) {
@Override
Sink<Long> opWrapSink(int flags, Sink<Long> sink) {
return new Sink.ChainedLong<Long>(sink) {
@Override
public void begin(long size) {
downstream.begin(-1);
}
@Override
public void accept(long t) {
try (LongStream result = mapper.apply(t)) {
// We can do better that this too; optimize for depth=0 case and just grab spliterator and forEach it
if (result != null)
result.sequential().forEach(i -> downstream.accept(i));
}
}
};
}
};
}
@Override
public LongStream unordered() {
if (!isOrdered())
return this;
return new StatelessOp<Long>(this, StreamShape.LONG_VALUE, StreamOpFlag.NOT_ORDERED) {
@Override
Sink<Long> opWrapSink(int flags, Sink<Long> sink) {
return sink;
}
};
}
@Override
public final LongStream filter(LongPredicate predicate) {
Objects.requireNonNull(predicate);
return new StatelessOp<Long>(this, StreamShape.LONG_VALUE,
StreamOpFlag.NOT_SIZED) {
@Override
Sink<Long> opWrapSink(int flags, Sink<Long> sink) {
return new Sink.ChainedLong<Long>(sink) {
@Override
public void begin(long size) {
downstream.begin(-1);
}
@Override
public void accept(long t) {
if (predicate.test(t))
downstream.accept(t);
}
};
}
};
}
@Override
public final LongStream peek(LongConsumer action) {
Objects.requireNonNull(action);
return new StatelessOp<Long>(this, StreamShape.LONG_VALUE,
0) {
@Override
Sink<Long> opWrapSink(int flags, Sink<Long> sink) {
return new Sink.ChainedLong<Long>(sink) {
@Override
public void accept(long t) {
action.accept(t);
downstream.accept(t);
}
};
}
};
}
// Stateful intermediate ops from LongStream
@Override
public final LongStream limit(long maxSize) {
if (maxSize < 0)
throw new IllegalArgumentException(Long.toString(maxSize));
return SliceOps.makeLong(this, 0, maxSize);
}
@Override
public final LongStream skip(long n) {
if (n < 0)
throw new IllegalArgumentException(Long.toString(n));
if (n == 0)
return this;
else
return SliceOps.makeLong(this, n, -1);
}
@Override
public final LongStream takeWhile(LongPredicate predicate) {
return WhileOps.makeTakeWhileLong(this, predicate);
}
@Override
public final LongStream dropWhile(LongPredicate predicate) {
return WhileOps.makeDropWhileLong(this, predicate);
}
@Override
public final LongStream sorted() {
return SortedOps.makeLong(this);
}
@Override
public final LongStream distinct() {
// While functional and quick to implement, this approach is not very efficient.
// An efficient version requires a long-specific map/set implementation.
return boxed().distinct().mapToLong(i -> (long) i);
}
// Terminal ops from LongStream
@Override
public void forEach(LongConsumer action) {
evaluate(ForEachOps.makeLong(action, false));
}
@Override
public void forEachOrdered(LongConsumer action) {
evaluate(ForEachOps.makeLong(action, true));
}
@Override
public final long sum() {
// use better algorithm to compensate for intermediate overflow?
return reduce(0, Long::sum);
}
@Override
public final OptionalLong min() {
return reduce(Math::min);
}
@Override
public final OptionalLong max() {
return reduce(Math::max);
}
@Override
public final OptionalDouble average() {
long[] avg = collect(() -> new long[2],
(ll, i) -> {
ll[0]++;
ll[1] += i;
},
(ll, rr) -> {
ll[0] += rr[0];
ll[1] += rr[1];
});
return avg[0] > 0
? OptionalDouble.of((double) avg[1] / avg[0])
: OptionalDouble.empty();
}
@Override
public final long count() {
return evaluate(ReduceOps.makeLongCounting());
}
@Override
public final LongSummaryStatistics summaryStatistics() {
return collect(LongSummaryStatistics::new, LongSummaryStatistics::accept,
LongSummaryStatistics::combine);
}
@Override
public final long reduce(long identity, LongBinaryOperator op) {
return evaluate(ReduceOps.makeLong(identity, op));
}
@Override
public final OptionalLong reduce(LongBinaryOperator op) {
return evaluate(ReduceOps.makeLong(op));
}
@Override
public final <R> R collect(Supplier<R> supplier,
ObjLongConsumer<R> accumulator,
BiConsumer<R, R> combiner) {
Objects.requireNonNull(combiner);
BinaryOperator<R> operator = (left, right) -> {
combiner.accept(left, right);
return left;
};
return evaluate(ReduceOps.makeLong(supplier, accumulator, operator));
}
@Override
public final boolean anyMatch(LongPredicate predicate) {
return evaluate(MatchOps.makeLong(predicate, MatchOps.MatchKind.ANY));
}
@Override
public final boolean allMatch(LongPredicate predicate) {
return evaluate(MatchOps.makeLong(predicate, MatchOps.MatchKind.ALL));
}
@Override
public final boolean noneMatch(LongPredicate predicate) {
return evaluate(MatchOps.makeLong(predicate, MatchOps.MatchKind.NONE));
}
@Override
public final OptionalLong findFirst() {
return evaluate(FindOps.makeLong(true));
}
@Override
public final OptionalLong findAny() {
return evaluate(FindOps.makeLong(false));
}
@Override
public final long[] toArray() {
return Nodes.flattenLong((Node.OfLong) evaluateToArrayNode(Long[]::new))
.asPrimitiveArray();
}
//
/**
* Source stage of a LongPipeline.
*
* @param <E_IN> type of elements in the upstream source
* @since 1.8
*/
static class Head<E_IN> extends LongPipeline<E_IN> {
/**
* Constructor for the source stage of a LongStream.
*
* @param source {@code Supplier<Spliterator>} describing the stream
* source
* @param sourceFlags the source flags for the stream source, described
* in {@link StreamOpFlag}
* @param parallel {@code true} if the pipeline is parallel
*/
Head(Supplier<? extends Spliterator<Long>> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
/**
* Constructor for the source stage of a LongStream.
*
* @param source {@code Spliterator} describing the stream source
* @param sourceFlags the source flags for the stream source, described
* in {@link StreamOpFlag}
* @param parallel {@code true} if the pipeline is parallel
*/
Head(Spliterator<Long> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
@Override
final boolean opIsStateful() {
throw new UnsupportedOperationException();
}
@Override
final Sink<E_IN> opWrapSink(int flags, Sink<Long> sink) {
throw new UnsupportedOperationException();
}
// Optimized sequential terminal operations for the head of the pipeline
@Override
public void forEach(LongConsumer action) {
if (!isParallel()) {
adapt(sourceStageSpliterator()).forEachRemaining(action);
} else {
super.forEach(action);
}
}
@Override
public void forEachOrdered(LongConsumer action) {
if (!isParallel()) {
adapt(sourceStageSpliterator()).forEachRemaining(action);
} else {
super.forEachOrdered(action);
}
}
}
/** Base class for a stateless intermediate stage of a LongStream.
*
* @param <E_IN> type of elements in the upstream source
* @since 1.8
*/
abstract static class StatelessOp<E_IN> extends LongPipeline<E_IN> {
/**
* Construct a new LongStream by appending a stateless intermediate
* operation to an existing stream.
* @param upstream The upstream pipeline stage
* @param inputShape The stream shape for the upstream pipeline stage
* @param opFlags Operation flags for the new stage
*/
StatelessOp(AbstractPipeline<?, E_IN, ?> upstream,
StreamShape inputShape,
int opFlags) {
super(upstream, opFlags);
assert upstream.getOutputShape() == inputShape;
}
@Override
final boolean opIsStateful() {
return false;
}
}
/**
* Base class for a stateful intermediate stage of a LongStream.
*
* @param <E_IN> type of elements in the upstream source
* @since 1.8
*/
abstract static class StatefulOp<E_IN> extends LongPipeline<E_IN> {
/**
* Construct a new LongStream by appending a stateful intermediate
* operation to an existing stream.
* @param upstream The upstream pipeline stage
* @param inputShape The stream shape for the upstream pipeline stage
* @param opFlags Operation flags for the new stage
*/
StatefulOp(AbstractPipeline<?, E_IN, ?> upstream,
StreamShape inputShape,
int opFlags) {
super(upstream, opFlags);
assert upstream.getOutputShape() == inputShape;
}
@Override
final boolean opIsStateful() {
return true;
}
@Override
abstract <P_IN> Node<Long> opEvaluateParallel(PipelineHelper<Long> helper,
Spliterator<P_IN> spliterator,
IntFunction<Long[]> generator);
}
}

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/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Objects;
import java.util.Spliterator;
import java.util.function.DoublePredicate;
import java.util.function.IntPredicate;
import java.util.function.LongPredicate;
import java.util.function.Predicate;
import java.util.function.Supplier;
/**
* Factory for instances of a short-circuiting {@code TerminalOp} that implement
* quantified predicate matching on the elements of a stream. Supported variants
* include match-all, match-any, and match-none.
*
* @since 1.8
*/
final class MatchOps {
private MatchOps() { }
/**
* Enum describing quantified match options -- all match, any match, none
* match.
*/
enum MatchKind {
/** Do all elements match the predicate? */
ANY(true, true),
/** Do any elements match the predicate? */
ALL(false, false),
/** Do no elements match the predicate? */
NONE(true, false);
private final boolean stopOnPredicateMatches;
private final boolean shortCircuitResult;
private MatchKind(boolean stopOnPredicateMatches,
boolean shortCircuitResult) {
this.stopOnPredicateMatches = stopOnPredicateMatches;
this.shortCircuitResult = shortCircuitResult;
}
}
/**
* Constructs a quantified predicate matcher for a Stream.
*
* @param <T> the type of stream elements
* @param predicate the {@code Predicate} to apply to stream elements
* @param matchKind the kind of quantified match (all, any, none)
* @return a {@code TerminalOp} implementing the desired quantified match
* criteria
*/
public static <T> TerminalOp<T, Boolean> makeRef(Predicate<? super T> predicate,
MatchKind matchKind) {
Objects.requireNonNull(predicate);
Objects.requireNonNull(matchKind);
class MatchSink extends BooleanTerminalSink<T> {
MatchSink() {
super(matchKind);
}
@Override
public void accept(T t) {
if (!stop && predicate.test(t) == matchKind.stopOnPredicateMatches) {
stop = true;
value = matchKind.shortCircuitResult;
}
}
}
return new MatchOp<>(StreamShape.REFERENCE, matchKind, MatchSink::new);
}
/**
* Constructs a quantified predicate matcher for an {@code IntStream}.
*
* @param predicate the {@code Predicate} to apply to stream elements
* @param matchKind the kind of quantified match (all, any, none)
* @return a {@code TerminalOp} implementing the desired quantified match
* criteria
*/
public static TerminalOp<Integer, Boolean> makeInt(IntPredicate predicate,
MatchKind matchKind) {
Objects.requireNonNull(predicate);
Objects.requireNonNull(matchKind);
class MatchSink extends BooleanTerminalSink<Integer> implements Sink.OfInt {
MatchSink() {
super(matchKind);
}
@Override
public void accept(int t) {
if (!stop && predicate.test(t) == matchKind.stopOnPredicateMatches) {
stop = true;
value = matchKind.shortCircuitResult;
}
}
}
return new MatchOp<>(StreamShape.INT_VALUE, matchKind, MatchSink::new);
}
/**
* Constructs a quantified predicate matcher for a {@code LongStream}.
*
* @param predicate the {@code Predicate} to apply to stream elements
* @param matchKind the kind of quantified match (all, any, none)
* @return a {@code TerminalOp} implementing the desired quantified match
* criteria
*/
public static TerminalOp<Long, Boolean> makeLong(LongPredicate predicate,
MatchKind matchKind) {
Objects.requireNonNull(predicate);
Objects.requireNonNull(matchKind);
class MatchSink extends BooleanTerminalSink<Long> implements Sink.OfLong {
MatchSink() {
super(matchKind);
}
@Override
public void accept(long t) {
if (!stop && predicate.test(t) == matchKind.stopOnPredicateMatches) {
stop = true;
value = matchKind.shortCircuitResult;
}
}
}
return new MatchOp<>(StreamShape.LONG_VALUE, matchKind, MatchSink::new);
}
/**
* Constructs a quantified predicate matcher for a {@code DoubleStream}.
*
* @param predicate the {@code Predicate} to apply to stream elements
* @param matchKind the kind of quantified match (all, any, none)
* @return a {@code TerminalOp} implementing the desired quantified match
* criteria
*/
public static TerminalOp<Double, Boolean> makeDouble(DoublePredicate predicate,
MatchKind matchKind) {
Objects.requireNonNull(predicate);
Objects.requireNonNull(matchKind);
class MatchSink extends BooleanTerminalSink<Double> implements Sink.OfDouble {
MatchSink() {
super(matchKind);
}
@Override
public void accept(double t) {
if (!stop && predicate.test(t) == matchKind.stopOnPredicateMatches) {
stop = true;
value = matchKind.shortCircuitResult;
}
}
}
return new MatchOp<>(StreamShape.DOUBLE_VALUE, matchKind, MatchSink::new);
}
/**
* A short-circuiting {@code TerminalOp} that evaluates a predicate on the
* elements of a stream and determines whether all, any or none of those
* elements match the predicate.
*
* @param <T> the output type of the stream pipeline
*/
private static final class MatchOp<T> implements TerminalOp<T, Boolean> {
private final StreamShape inputShape;
final MatchKind matchKind;
final Supplier<BooleanTerminalSink<T>> sinkSupplier;
/**
* Constructs a {@code MatchOp}.
*
* @param shape the output shape of the stream pipeline
* @param matchKind the kind of quantified match (all, any, none)
* @param sinkSupplier {@code Supplier} for a {@code Sink} of the
* appropriate shape which implements the matching operation
*/
MatchOp(StreamShape shape,
MatchKind matchKind,
Supplier<BooleanTerminalSink<T>> sinkSupplier) {
this.inputShape = shape;
this.matchKind = matchKind;
this.sinkSupplier = sinkSupplier;
}
@Override
public int getOpFlags() {
return StreamOpFlag.IS_SHORT_CIRCUIT | StreamOpFlag.NOT_ORDERED;
}
@Override
public StreamShape inputShape() {
return inputShape;
}
@Override
public <S> Boolean evaluateSequential(PipelineHelper<T> helper,
Spliterator<S> spliterator) {
return helper.wrapAndCopyInto(sinkSupplier.get(), spliterator).getAndClearState();
}
@Override
public <S> Boolean evaluateParallel(PipelineHelper<T> helper,
Spliterator<S> spliterator) {
// Approach for parallel implementation:
// - Decompose as per usual
// - run match on leaf chunks, call result "b"
// - if b == matchKind.shortCircuitOn, complete early and return b
// - else if we complete normally, return !shortCircuitOn
return new MatchTask<>(this, helper, spliterator).invoke();
}
}
/**
* Boolean specific terminal sink to avoid the boxing costs when returning
* results. Subclasses implement the shape-specific functionality.
*
* @param <T> The output type of the stream pipeline
*/
private abstract static class BooleanTerminalSink<T> implements Sink<T> {
boolean stop;
boolean value;
BooleanTerminalSink(MatchKind matchKind) {
value = !matchKind.shortCircuitResult;
}
public boolean getAndClearState() {
return value;
}
@Override
public boolean cancellationRequested() {
return stop;
}
}
/**
* ForkJoinTask implementation to implement a parallel short-circuiting
* quantified match
*
* @param <P_IN> the type of source elements for the pipeline
* @param <P_OUT> the type of output elements for the pipeline
*/
@SuppressWarnings("serial")
private static final class MatchTask<P_IN, P_OUT>
extends AbstractShortCircuitTask<P_IN, P_OUT, Boolean, MatchTask<P_IN, P_OUT>> {
private final MatchOp<P_OUT> op;
/**
* Constructor for root node
*/
MatchTask(MatchOp<P_OUT> op, PipelineHelper<P_OUT> helper,
Spliterator<P_IN> spliterator) {
super(helper, spliterator);
this.op = op;
}
/**
* Constructor for non-root node
*/
MatchTask(MatchTask<P_IN, P_OUT> parent, Spliterator<P_IN> spliterator) {
super(parent, spliterator);
this.op = parent.op;
}
@Override
protected MatchTask<P_IN, P_OUT> makeChild(Spliterator<P_IN> spliterator) {
return new MatchTask<>(this, spliterator);
}
@Override
protected Boolean doLeaf() {
boolean b = helper.wrapAndCopyInto(op.sinkSupplier.get(), spliterator).getAndClearState();
if (b == op.matchKind.shortCircuitResult)
shortCircuit(b);
return null;
}
@Override
protected Boolean getEmptyResult() {
return !op.matchKind.shortCircuitResult;
}
}
}

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@ -0,0 +1,547 @@
/*
* Copyright (c) 2012, 2015, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Spliterator;
import java.util.function.Consumer;
import java.util.function.DoubleConsumer;
import java.util.function.IntConsumer;
import java.util.function.IntFunction;
import java.util.function.LongConsumer;
/**
* An immutable container for describing an ordered sequence of elements of some
* type {@code T}.
*
* <p>A {@code Node} contains a fixed number of elements, which can be accessed
* via the {@link #count}, {@link #spliterator}, {@link #forEach},
* {@link #asArray}, or {@link #copyInto} methods. A {@code Node} may have zero
* or more child {@code Node}s; if it has no children (accessed via
* {@link #getChildCount} and {@link #getChild(int)}, it is considered <em>flat
* </em> or a <em>leaf</em>; if it has children, it is considered an
* <em>internal</em> node. The size of an internal node is the sum of sizes of
* its children.
*
* @apiNote
* <p>A {@code Node} typically does not store the elements directly, but instead
* mediates access to one or more existing (effectively immutable) data
* structures such as a {@code Collection}, array, or a set of other
* {@code Node}s. Commonly {@code Node}s are formed into a tree whose shape
* corresponds to the computation tree that produced the elements that are
* contained in the leaf nodes. The use of {@code Node} within the stream
* framework is largely to avoid copying data unnecessarily during parallel
* operations.
*
* @param <T> the type of elements.
* @since 1.8
*/
interface Node<T> {
/**
* Returns a {@link Spliterator} describing the elements contained in this
* {@code Node}.
*
* @return a {@code Spliterator} describing the elements contained in this
* {@code Node}
*/
Spliterator<T> spliterator();
/**
* Traverses the elements of this node, and invoke the provided
* {@code Consumer} with each element. Elements are provided in encounter
* order if the source for the {@code Node} has a defined encounter order.
*
* @param consumer a {@code Consumer} that is to be invoked with each
* element in this {@code Node}
*/
void forEach(Consumer<? super T> consumer);
/**
* Returns the number of child nodes of this node.
*
* @implSpec The default implementation returns zero.
*
* @return the number of child nodes
*/
default int getChildCount() {
return 0;
}
/**
* Retrieves the child {@code Node} at a given index.
*
* @implSpec The default implementation always throws
* {@code IndexOutOfBoundsException}.
*
* @param i the index to the child node
* @return the child node
* @throws IndexOutOfBoundsException if the index is less than 0 or greater
* than or equal to the number of child nodes
*/
default Node<T> getChild(int i) {
throw new IndexOutOfBoundsException();
}
/**
* Return a node describing a subsequence of the elements of this node,
* starting at the given inclusive start offset and ending at the given
* exclusive end offset.
*
* @param from The (inclusive) starting offset of elements to include, must
* be in range 0..count().
* @param to The (exclusive) end offset of elements to include, must be
* in range 0..count().
* @param generator A function to be used to create a new array, if needed,
* for reference nodes.
* @return the truncated node
*/
default Node<T> truncate(long from, long to, IntFunction<T[]> generator) {
if (from == 0 && to == count())
return this;
Spliterator<T> spliterator = spliterator();
long size = to - from;
Node.Builder<T> nodeBuilder = Nodes.builder(size, generator);
nodeBuilder.begin(size);
for (int i = 0; i < from && spliterator.tryAdvance(e -> { }); i++) { }
if (to == count()) {
spliterator.forEachRemaining(nodeBuilder);
} else {
for (int i = 0; i < size && spliterator.tryAdvance(nodeBuilder); i++) { }
}
nodeBuilder.end();
return nodeBuilder.build();
}
/**
* Provides an array view of the contents of this node.
*
* <p>Depending on the underlying implementation, this may return a
* reference to an internal array rather than a copy. Since the returned
* array may be shared, the returned array should not be modified. The
* {@code generator} function may be consulted to create the array if a new
* array needs to be created.
*
* @param generator a factory function which takes an integer parameter and
* returns a new, empty array of that size and of the appropriate
* array type
* @return an array containing the contents of this {@code Node}
*/
T[] asArray(IntFunction<T[]> generator);
/**
* Copies the content of this {@code Node} into an array, starting at a
* given offset into the array. It is the caller's responsibility to ensure
* there is sufficient room in the array, otherwise unspecified behaviour
* will occur if the array length is less than the number of elements
* contained in this node.
*
* @param array the array into which to copy the contents of this
* {@code Node}
* @param offset the starting offset within the array
* @throws IndexOutOfBoundsException if copying would cause access of data
* outside array bounds
* @throws NullPointerException if {@code array} is {@code null}
*/
void copyInto(T[] array, int offset);
/**
* Gets the {@code StreamShape} associated with this {@code Node}.
*
* @implSpec The default in {@code Node} returns
* {@code StreamShape.REFERENCE}
*
* @return the stream shape associated with this node
*/
default StreamShape getShape() {
return StreamShape.REFERENCE;
}
/**
* Returns the number of elements contained in this node.
*
* @return the number of elements contained in this node
*/
long count();
/**
* A mutable builder for a {@code Node} that implements {@link Sink}, which
* builds a flat node containing the elements that have been pushed to it.
*/
interface Builder<T> extends Sink<T> {
/**
* Builds the node. Should be called after all elements have been
* pushed and signalled with an invocation of {@link Sink#end()}.
*
* @return the resulting {@code Node}
*/
Node<T> build();
/**
* Specialized @{code Node.Builder} for int elements
*/
interface OfInt extends Node.Builder<Integer>, Sink.OfInt {
@Override
Node.OfInt build();
}
/**
* Specialized @{code Node.Builder} for long elements
*/
interface OfLong extends Node.Builder<Long>, Sink.OfLong {
@Override
Node.OfLong build();
}
/**
* Specialized @{code Node.Builder} for double elements
*/
interface OfDouble extends Node.Builder<Double>, Sink.OfDouble {
@Override
Node.OfDouble build();
}
}
public interface OfPrimitive<T, T_CONS, T_ARR,
T_SPLITR extends Spliterator.OfPrimitive<T, T_CONS, T_SPLITR>,
T_NODE extends OfPrimitive<T, T_CONS, T_ARR, T_SPLITR, T_NODE>>
extends Node<T> {
/**
* {@inheritDoc}
*
* @return a {@link Spliterator.OfPrimitive} describing the elements of
* this node
*/
@Override
T_SPLITR spliterator();
/**
* Traverses the elements of this node, and invoke the provided
* {@code action} with each element.
*
* @param action a consumer that is to be invoked with each
* element in this {@code Node.OfPrimitive}
*/
@SuppressWarnings("overloads")
void forEach(T_CONS action);
@Override
default T_NODE getChild(int i) {
throw new IndexOutOfBoundsException();
}
T_NODE truncate(long from, long to, IntFunction<T[]> generator);
/**
* {@inheritDoc}
*
* @implSpec the default implementation invokes the generator to create
* an instance of a boxed primitive array with a length of
* {@link #count()} and then invokes {@link #copyInto(T[], int)} with
* that array at an offset of 0.
*/
@Override
default T[] asArray(IntFunction<T[]> generator) {
if (java.util.stream.Tripwire.ENABLED)
java.util.stream.Tripwire.trip(getClass(), "{0} calling Node.OfPrimitive.asArray");
long size = count();
if (size >= Nodes.MAX_ARRAY_SIZE)
throw new IllegalArgumentException(Nodes.BAD_SIZE);
T[] boxed = generator.apply((int) count());
copyInto(boxed, 0);
return boxed;
}
/**
* Views this node as a primitive array.
*
* <p>Depending on the underlying implementation this may return a
* reference to an internal array rather than a copy. It is the callers
* responsibility to decide if either this node or the array is utilized
* as the primary reference for the data.</p>
*
* @return an array containing the contents of this {@code Node}
*/
T_ARR asPrimitiveArray();
/**
* Creates a new primitive array.
*
* @param count the length of the primitive array.
* @return the new primitive array.
*/
T_ARR newArray(int count);
/**
* Copies the content of this {@code Node} into a primitive array,
* starting at a given offset into the array. It is the caller's
* responsibility to ensure there is sufficient room in the array.
*
* @param array the array into which to copy the contents of this
* {@code Node}
* @param offset the starting offset within the array
* @throws IndexOutOfBoundsException if copying would cause access of
* data outside array bounds
* @throws NullPointerException if {@code array} is {@code null}
*/
void copyInto(T_ARR array, int offset);
}
/**
* Specialized {@code Node} for int elements
*/
interface OfInt extends OfPrimitive<Integer, IntConsumer, int[], Spliterator.OfInt, OfInt> {
/**
* {@inheritDoc}
*
* @param consumer a {@code Consumer} that is to be invoked with each
* element in this {@code Node}. If this is an
* {@code IntConsumer}, it is cast to {@code IntConsumer} so the
* elements may be processed without boxing.
*/
@Override
default void forEach(Consumer<? super Integer> consumer) {
if (consumer instanceof IntConsumer) {
forEach((IntConsumer) consumer);
}
else {
if (Tripwire.ENABLED)
Tripwire.trip(getClass(), "{0} calling Node.OfInt.forEachRemaining(Consumer)");
spliterator().forEachRemaining(consumer);
}
}
/**
* {@inheritDoc}
*
* @implSpec the default implementation invokes {@link #asPrimitiveArray()} to
* obtain an int[] array then and copies the elements from that int[]
* array into the boxed Integer[] array. This is not efficient and it
* is recommended to invoke {@link #copyInto(Object, int)}.
*/
@Override
default void copyInto(Integer[] boxed, int offset) {
if (Tripwire.ENABLED)
Tripwire.trip(getClass(), "{0} calling Node.OfInt.copyInto(Integer[], int)");
int[] array = asPrimitiveArray();
for (int i = 0; i < array.length; i++) {
boxed[offset + i] = array[i];
}
}
@Override
default Node.OfInt truncate(long from, long to, IntFunction<Integer[]> generator) {
if (from == 0 && to == count())
return this;
long size = to - from;
Spliterator.OfInt spliterator = spliterator();
Node.Builder.OfInt nodeBuilder = Nodes.intBuilder(size);
nodeBuilder.begin(size);
for (int i = 0; i < from && spliterator.tryAdvance((IntConsumer) e -> { }); i++) { }
if (to == count()) {
spliterator.forEachRemaining((IntConsumer) nodeBuilder);
} else {
for (int i = 0; i < size && spliterator.tryAdvance((IntConsumer) nodeBuilder); i++) { }
}
nodeBuilder.end();
return nodeBuilder.build();
}
@Override
default int[] newArray(int count) {
return new int[count];
}
/**
* {@inheritDoc}
* @implSpec The default in {@code Node.OfInt} returns
* {@code StreamShape.INT_VALUE}
*/
default StreamShape getShape() {
return StreamShape.INT_VALUE;
}
}
/**
* Specialized {@code Node} for long elements
*/
interface OfLong extends OfPrimitive<Long, LongConsumer, long[], Spliterator.OfLong, OfLong> {
/**
* {@inheritDoc}
*
* @param consumer A {@code Consumer} that is to be invoked with each
* element in this {@code Node}. If this is an
* {@code LongConsumer}, it is cast to {@code LongConsumer} so
* the elements may be processed without boxing.
*/
@Override
default void forEach(Consumer<? super Long> consumer) {
if (consumer instanceof LongConsumer) {
forEach((LongConsumer) consumer);
}
else {
if (Tripwire.ENABLED)
Tripwire.trip(getClass(), "{0} calling Node.OfLong.forEachRemaining(Consumer)");
spliterator().forEachRemaining(consumer);
}
}
/**
* {@inheritDoc}
*
* @implSpec the default implementation invokes {@link #asPrimitiveArray()}
* to obtain a long[] array then and copies the elements from that
* long[] array into the boxed Long[] array. This is not efficient and
* it is recommended to invoke {@link #copyInto(Object, int)}.
*/
@Override
default void copyInto(Long[] boxed, int offset) {
if (Tripwire.ENABLED)
Tripwire.trip(getClass(), "{0} calling Node.OfInt.copyInto(Long[], int)");
long[] array = asPrimitiveArray();
for (int i = 0; i < array.length; i++) {
boxed[offset + i] = array[i];
}
}
@Override
default Node.OfLong truncate(long from, long to, IntFunction<Long[]> generator) {
if (from == 0 && to == count())
return this;
long size = to - from;
Spliterator.OfLong spliterator = spliterator();
Node.Builder.OfLong nodeBuilder = Nodes.longBuilder(size);
nodeBuilder.begin(size);
for (int i = 0; i < from && spliterator.tryAdvance((LongConsumer) e -> { }); i++) { }
if (to == count()) {
spliterator.forEachRemaining((LongConsumer) nodeBuilder);
} else {
for (int i = 0; i < size && spliterator.tryAdvance((LongConsumer) nodeBuilder); i++) { }
}
nodeBuilder.end();
return nodeBuilder.build();
}
@Override
default long[] newArray(int count) {
return new long[count];
}
/**
* {@inheritDoc}
* @implSpec The default in {@code Node.OfLong} returns
* {@code StreamShape.LONG_VALUE}
*/
default StreamShape getShape() {
return StreamShape.LONG_VALUE;
}
}
/**
* Specialized {@code Node} for double elements
*/
interface OfDouble extends OfPrimitive<Double, DoubleConsumer, double[], Spliterator.OfDouble, OfDouble> {
/**
* {@inheritDoc}
*
* @param consumer A {@code Consumer} that is to be invoked with each
* element in this {@code Node}. If this is an
* {@code DoubleConsumer}, it is cast to {@code DoubleConsumer}
* so the elements may be processed without boxing.
*/
@Override
default void forEach(Consumer<? super Double> consumer) {
if (consumer instanceof DoubleConsumer) {
forEach((DoubleConsumer) consumer);
}
else {
if (Tripwire.ENABLED)
Tripwire.trip(getClass(), "{0} calling Node.OfLong.forEachRemaining(Consumer)");
spliterator().forEachRemaining(consumer);
}
}
//
/**
* {@inheritDoc}
*
* @implSpec the default implementation invokes {@link #asPrimitiveArray()}
* to obtain a double[] array then and copies the elements from that
* double[] array into the boxed Double[] array. This is not efficient
* and it is recommended to invoke {@link #copyInto(Object, int)}.
*/
@Override
default void copyInto(Double[] boxed, int offset) {
if (Tripwire.ENABLED)
Tripwire.trip(getClass(), "{0} calling Node.OfDouble.copyInto(Double[], int)");
double[] array = asPrimitiveArray();
for (int i = 0; i < array.length; i++) {
boxed[offset + i] = array[i];
}
}
@Override
default Node.OfDouble truncate(long from, long to, IntFunction<Double[]> generator) {
if (from == 0 && to == count())
return this;
long size = to - from;
Spliterator.OfDouble spliterator = spliterator();
Node.Builder.OfDouble nodeBuilder = Nodes.doubleBuilder(size);
nodeBuilder.begin(size);
for (int i = 0; i < from && spliterator.tryAdvance((DoubleConsumer) e -> { }); i++) { }
if (to == count()) {
spliterator.forEachRemaining((DoubleConsumer) nodeBuilder);
} else {
for (int i = 0; i < size && spliterator.tryAdvance((DoubleConsumer) nodeBuilder); i++) { }
}
nodeBuilder.end();
return nodeBuilder.build();
}
@Override
default double[] newArray(int count) {
return new double[count];
}
/**
* {@inheritDoc}
*
* @implSpec The default in {@code Node.OfDouble} returns
* {@code StreamShape.DOUBLE_VALUE}
*/
default StreamShape getShape() {
return StreamShape.DOUBLE_VALUE;
}
}
}

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/*
* Copyright (c) 2012, 2015, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Spliterator;
import java.util.function.IntFunction;
/**
* Helper class for executing <a href="package-summary.html#StreamOps">
* stream pipelines</a>, capturing all of the information about a stream
* pipeline (output shape, intermediate operations, stream flags, parallelism,
* etc) in one place.
*
* <p>
* A {@code PipelineHelper} describes the initial segment of a stream pipeline,
* including its source, intermediate operations, and may additionally
* incorporate information about the terminal (or stateful) operation which
* follows the last intermediate operation described by this
* {@code PipelineHelper}. The {@code PipelineHelper} is passed to the
* {@link TerminalOp#evaluateParallel(PipelineHelper, java.util.Spliterator)},
* {@link TerminalOp#evaluateSequential(PipelineHelper, java.util.Spliterator)},
* and {@link AbstractPipeline#opEvaluateParallel(PipelineHelper, java.util.Spliterator,
* java.util.function.IntFunction)}, methods, which can use the
* {@code PipelineHelper} to access information about the pipeline such as
* head shape, stream flags, and size, and use the helper methods
* such as {@link #wrapAndCopyInto(Sink, Spliterator)},
* {@link #copyInto(Sink, Spliterator)}, and {@link #wrapSink(Sink)} to execute
* pipeline operations.
*
* @param <P_OUT> type of output elements from the pipeline
* @since 1.8
*/
abstract class PipelineHelper<P_OUT> {
/**
* Gets the stream shape for the source of the pipeline segment.
*
* @return the stream shape for the source of the pipeline segment.
*/
abstract StreamShape getSourceShape();
/**
* Gets the combined stream and operation flags for the output of the described
* pipeline. This will incorporate stream flags from the stream source, all
* the intermediate operations and the terminal operation.
*
* @return the combined stream and operation flags
* @see StreamOpFlag
*/
abstract int getStreamAndOpFlags();
/**
* Returns the exact output size of the portion of the output resulting from
* applying the pipeline stages described by this {@code PipelineHelper} to
* the portion of the input described by the provided
* {@code Spliterator}, if known. If not known or known infinite, will
* return {@code -1}.
*
* @apiNote
* The exact output size is known if the {@code Spliterator} has the
* {@code SIZED} characteristic, and the operation flags
* {@link StreamOpFlag#SIZED} is known on the combined stream and operation
* flags.
*
* @param spliterator the spliterator describing the relevant portion of the
* source data
* @return the exact size if known, or -1 if infinite or unknown
*/
abstract<P_IN> long exactOutputSizeIfKnown(Spliterator<P_IN> spliterator);
/**
* Applies the pipeline stages described by this {@code PipelineHelper} to
* the provided {@code Spliterator} and send the results to the provided
* {@code Sink}.
*
* @implSpec
* The implementation behaves as if:
* <pre>{@code
* copyInto(wrapSink(sink), spliterator);
* }</pre>
*
* @param sink the {@code Sink} to receive the results
* @param spliterator the spliterator describing the source input to process
*/
abstract<P_IN, S extends Sink<P_OUT>> S wrapAndCopyInto(S sink, Spliterator<P_IN> spliterator);
/**
* Pushes elements obtained from the {@code Spliterator} into the provided
* {@code Sink}. If the stream pipeline is known to have short-circuiting
* stages in it (see {@link StreamOpFlag#SHORT_CIRCUIT}), the
* {@link Sink#cancellationRequested()} is checked after each
* element, stopping if cancellation is requested.
*
* @implSpec
* This method conforms to the {@code Sink} protocol of calling
* {@code Sink.begin} before pushing elements, via {@code Sink.accept}, and
* calling {@code Sink.end} after all elements have been pushed.
*
* @param wrappedSink the destination {@code Sink}
* @param spliterator the source {@code Spliterator}
*/
abstract<P_IN> void copyInto(Sink<P_IN> wrappedSink, Spliterator<P_IN> spliterator);
/**
* Pushes elements obtained from the {@code Spliterator} into the provided
* {@code Sink}, checking {@link Sink#cancellationRequested()} after each
* element, and stopping if cancellation is requested.
*
* @implSpec
* This method conforms to the {@code Sink} protocol of calling
* {@code Sink.begin} before pushing elements, via {@code Sink.accept}, and
* calling {@code Sink.end} after all elements have been pushed or if
* cancellation is requested.
*
* @param wrappedSink the destination {@code Sink}
* @param spliterator the source {@code Spliterator}
* @return true if the cancellation was requested
*/
abstract <P_IN> boolean copyIntoWithCancel(Sink<P_IN> wrappedSink, Spliterator<P_IN> spliterator);
/**
* Takes a {@code Sink} that accepts elements of the output type of the
* {@code PipelineHelper}, and wrap it with a {@code Sink} that accepts
* elements of the input type and implements all the intermediate operations
* described by this {@code PipelineHelper}, delivering the result into the
* provided {@code Sink}.
*
* @param sink the {@code Sink} to receive the results
* @return a {@code Sink} that implements the pipeline stages and sends
* results to the provided {@code Sink}
*/
abstract<P_IN> Sink<P_IN> wrapSink(Sink<P_OUT> sink);
/**
*
* @param spliterator
* @param <P_IN>
* @return
*/
abstract<P_IN> Spliterator<P_OUT> wrapSpliterator(Spliterator<P_IN> spliterator);
/**
* Constructs a @{link Node.Builder} compatible with the output shape of
* this {@code PipelineHelper}.
*
* @param exactSizeIfKnown if >=0 then a builder will be created that has a
* fixed capacity of exactly sizeIfKnown elements; if < 0 then the
* builder has variable capacity. A fixed capacity builder will fail
* if an element is added after the builder has reached capacity.
* @param generator a factory function for array instances
* @return a {@code Node.Builder} compatible with the output shape of this
* {@code PipelineHelper}
*/
abstract Node.Builder<P_OUT> makeNodeBuilder(long exactSizeIfKnown,
IntFunction<P_OUT[]> generator);
/**
* Collects all output elements resulting from applying the pipeline stages
* to the source {@code Spliterator} into a {@code Node}.
*
* @implNote
* If the pipeline has no intermediate operations and the source is backed
* by a {@code Node} then that {@code Node} will be returned (or flattened
* and then returned). This reduces copying for a pipeline consisting of a
* stateful operation followed by a terminal operation that returns an
* array, such as:
* <pre>{@code
* stream.sorted().toArray();
* }</pre>
*
* @param spliterator the source {@code Spliterator}
* @param flatten if true and the pipeline is a parallel pipeline then the
* {@code Node} returned will contain no children, otherwise the
* {@code Node} may represent the root in a tree that reflects the
* shape of the computation tree.
* @param generator a factory function for array instances
* @return the {@code Node} containing all output elements
*/
abstract<P_IN> Node<P_OUT> evaluate(Spliterator<P_IN> spliterator,
boolean flatten,
IntFunction<P_OUT[]> generator);
}

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/*
* Copyright (c) 2012, 2015, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Objects;
import java.util.Optional;
import java.util.OptionalDouble;
import java.util.OptionalInt;
import java.util.OptionalLong;
import java.util.Spliterator;
import java.util.concurrent.CountedCompleter;
import java.util.function.BiConsumer;
import java.util.function.BiFunction;
import java.util.function.BinaryOperator;
import java.util.function.DoubleBinaryOperator;
import java.util.function.IntBinaryOperator;
import java.util.function.LongBinaryOperator;
import java.util.function.ObjDoubleConsumer;
import java.util.function.ObjIntConsumer;
import java.util.function.ObjLongConsumer;
import java.util.function.Supplier;
/**
* Factory for creating instances of {@code TerminalOp} that implement
* reductions.
*
* @since 1.8
*/
final class ReduceOps {
private ReduceOps() { }
/**
* Constructs a {@code TerminalOp} that implements a functional reduce on
* reference values.
*
* @param <T> the type of the input elements
* @param <U> the type of the result
* @param seed the identity element for the reduction
* @param reducer the accumulating function that incorporates an additional
* input element into the result
* @param combiner the combining function that combines two intermediate
* results
* @return a {@code TerminalOp} implementing the reduction
*/
public static <T, U> TerminalOp<T, U>
makeRef(U seed, BiFunction<U, ? super T, U> reducer, BinaryOperator<U> combiner) {
Objects.requireNonNull(reducer);
Objects.requireNonNull(combiner);
class ReducingSink extends Box<U> implements AccumulatingSink<T, U, ReducingSink> {
@Override
public void begin(long size) {
state = seed;
}
@Override
public void accept(T t) {
state = reducer.apply(state, t);
}
@Override
public void combine(ReducingSink other) {
state = combiner.apply(state, other.state);
}
}
return new ReduceOp<T, U, ReducingSink>(StreamShape.REFERENCE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
};
}
/**
* Constructs a {@code TerminalOp} that implements a functional reduce on
* reference values producing an optional reference result.
*
* @param <T> The type of the input elements, and the type of the result
* @param operator The reducing function
* @return A {@code TerminalOp} implementing the reduction
*/
public static <T> TerminalOp<T, Optional<T>>
makeRef(BinaryOperator<T> operator) {
Objects.requireNonNull(operator);
class ReducingSink
implements AccumulatingSink<T, Optional<T>, ReducingSink> {
private boolean empty;
private T state;
public void begin(long size) {
empty = true;
state = null;
}
@Override
public void accept(T t) {
if (empty) {
empty = false;
state = t;
} else {
state = operator.apply(state, t);
}
}
@Override
public Optional<T> get() {
return empty ? Optional.empty() : Optional.of(state);
}
@Override
public void combine(ReducingSink other) {
if (!other.empty)
accept(other.state);
}
}
return new ReduceOp<T, Optional<T>, ReducingSink>(StreamShape.REFERENCE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
};
}
/**
* Constructs a {@code TerminalOp} that implements a mutable reduce on
* reference values.
*
* @param <T> the type of the input elements
* @param <I> the type of the intermediate reduction result
* @param collector a {@code Collector} defining the reduction
* @return a {@code ReduceOp} implementing the reduction
*/
public static <T, I> TerminalOp<T, I>
makeRef(Collector<? super T, I, ?> collector) {
Supplier<I> supplier = Objects.requireNonNull(collector).supplier();
BiConsumer<I, ? super T> accumulator = collector.accumulator();
BinaryOperator<I> combiner = collector.combiner();
class ReducingSink extends Box<I>
implements AccumulatingSink<T, I, ReducingSink> {
@Override
public void begin(long size) {
state = supplier.get();
}
@Override
public void accept(T t) {
accumulator.accept(state, t);
}
@Override
public void combine(ReducingSink other) {
state = combiner.apply(state, other.state);
}
}
return new ReduceOp<T, I, ReducingSink>(StreamShape.REFERENCE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
@Override
public int getOpFlags() {
return collector.characteristics().contains(Collector.Characteristics.UNORDERED)
? StreamOpFlag.NOT_ORDERED
: 0;
}
};
}
/**
* Constructs a {@code TerminalOp} that implements a mutable reduce on
* reference values.
*
* @param <T> the type of the input elements
* @param <R> the type of the result
* @param seedFactory a factory to produce a new base accumulator
* @param accumulator a function to incorporate an element into an
* accumulator
* @param reducer a function to combine an accumulator into another
* @return a {@code TerminalOp} implementing the reduction
*/
public static <T, R> TerminalOp<T, R>
makeRef(Supplier<R> seedFactory,
BiConsumer<R, ? super T> accumulator,
BiConsumer<R,R> reducer) {
Objects.requireNonNull(seedFactory);
Objects.requireNonNull(accumulator);
Objects.requireNonNull(reducer);
class ReducingSink extends Box<R>
implements AccumulatingSink<T, R, ReducingSink> {
@Override
public void begin(long size) {
state = seedFactory.get();
}
@Override
public void accept(T t) {
accumulator.accept(state, t);
}
@Override
public void combine(ReducingSink other) {
reducer.accept(state, other.state);
}
}
return new ReduceOp<T, R, ReducingSink>(StreamShape.REFERENCE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
};
}
/**
* Constructs a {@code TerminalOp} that counts the number of stream
* elements. If the size of the pipeline is known then count is the size
* and there is no need to evaluate the pipeline. If the size of the
* pipeline is non known then count is produced, via reduction, using a
* {@link CountingSink}.
*
* @param <T> the type of the input elements
* @return a {@code TerminalOp} implementing the counting
*/
public static <T> TerminalOp<T, Long>
makeRefCounting() {
return new ReduceOp<T, Long, CountingSink<T>>(StreamShape.REFERENCE) {
@Override
public CountingSink<T> makeSink() { return new CountingSink.OfRef<>(); }
@Override
public <P_IN> Long evaluateSequential(PipelineHelper<T> helper,
Spliterator<P_IN> spliterator) {
if (StreamOpFlag.SIZED.isKnown(helper.getStreamAndOpFlags()))
return spliterator.getExactSizeIfKnown();
return super.evaluateSequential(helper, spliterator);
}
@Override
public <P_IN> Long evaluateParallel(PipelineHelper<T> helper,
Spliterator<P_IN> spliterator) {
if (StreamOpFlag.SIZED.isKnown(helper.getStreamAndOpFlags()))
return spliterator.getExactSizeIfKnown();
return super.evaluateParallel(helper, spliterator);
}
@Override
public int getOpFlags() {
return StreamOpFlag.NOT_ORDERED;
}
};
}
/**
* Constructs a {@code TerminalOp} that implements a functional reduce on
* {@code int} values.
*
* @param identity the identity for the combining function
* @param operator the combining function
* @return a {@code TerminalOp} implementing the reduction
*/
public static TerminalOp<Integer, Integer>
makeInt(int identity, IntBinaryOperator operator) {
Objects.requireNonNull(operator);
class ReducingSink
implements AccumulatingSink<Integer, Integer, ReducingSink>, Sink.OfInt {
private int state;
@Override
public void begin(long size) {
state = identity;
}
@Override
public void accept(int t) {
state = operator.applyAsInt(state, t);
}
@Override
public Integer get() {
return state;
}
@Override
public void combine(ReducingSink other) {
accept(other.state);
}
}
return new ReduceOp<Integer, Integer, ReducingSink>(StreamShape.INT_VALUE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
};
}
/**
* Constructs a {@code TerminalOp} that implements a functional reduce on
* {@code int} values, producing an optional integer result.
*
* @param operator the combining function
* @return a {@code TerminalOp} implementing the reduction
*/
public static TerminalOp<Integer, OptionalInt>
makeInt(IntBinaryOperator operator) {
Objects.requireNonNull(operator);
class ReducingSink
implements AccumulatingSink<Integer, OptionalInt, ReducingSink>, Sink.OfInt {
private boolean empty;
private int state;
public void begin(long size) {
empty = true;
state = 0;
}
@Override
public void accept(int t) {
if (empty) {
empty = false;
state = t;
}
else {
state = operator.applyAsInt(state, t);
}
}
@Override
public OptionalInt get() {
return empty ? OptionalInt.empty() : OptionalInt.of(state);
}
@Override
public void combine(ReducingSink other) {
if (!other.empty)
accept(other.state);
}
}
return new ReduceOp<Integer, OptionalInt, ReducingSink>(StreamShape.INT_VALUE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
};
}
/**
* Constructs a {@code TerminalOp} that implements a mutable reduce on
* {@code int} values.
*
* @param <R> The type of the result
* @param supplier a factory to produce a new accumulator of the result type
* @param accumulator a function to incorporate an int into an
* accumulator
* @param combiner a function to combine an accumulator into another
* @return A {@code ReduceOp} implementing the reduction
*/
public static <R> TerminalOp<Integer, R>
makeInt(Supplier<R> supplier,
ObjIntConsumer<R> accumulator,
BinaryOperator<R> combiner) {
Objects.requireNonNull(supplier);
Objects.requireNonNull(accumulator);
Objects.requireNonNull(combiner);
class ReducingSink extends Box<R>
implements AccumulatingSink<Integer, R, ReducingSink>, Sink.OfInt {
@Override
public void begin(long size) {
state = supplier.get();
}
@Override
public void accept(int t) {
accumulator.accept(state, t);
}
@Override
public void combine(ReducingSink other) {
state = combiner.apply(state, other.state);
}
}
return new ReduceOp<Integer, R, ReducingSink>(StreamShape.INT_VALUE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
};
}
/**
* Constructs a {@code TerminalOp} that counts the number of stream
* elements. If the size of the pipeline is known then count is the size
* and there is no need to evaluate the pipeline. If the size of the
* pipeline is non known then count is produced, via reduction, using a
* {@link CountingSink}.
*
* @return a {@code TerminalOp} implementing the counting
*/
public static TerminalOp<Integer, Long>
makeIntCounting() {
return new ReduceOp<Integer, Long, CountingSink<Integer>>(StreamShape.INT_VALUE) {
@Override
public CountingSink<Integer> makeSink() { return new CountingSink.OfInt(); }
@Override
public <P_IN> Long evaluateSequential(PipelineHelper<Integer> helper,
Spliterator<P_IN> spliterator) {
if (StreamOpFlag.SIZED.isKnown(helper.getStreamAndOpFlags()))
return spliterator.getExactSizeIfKnown();
return super.evaluateSequential(helper, spliterator);
}
@Override
public <P_IN> Long evaluateParallel(PipelineHelper<Integer> helper,
Spliterator<P_IN> spliterator) {
if (StreamOpFlag.SIZED.isKnown(helper.getStreamAndOpFlags()))
return spliterator.getExactSizeIfKnown();
return super.evaluateParallel(helper, spliterator);
}
@Override
public int getOpFlags() {
return StreamOpFlag.NOT_ORDERED;
}
};
}
/**
* Constructs a {@code TerminalOp} that implements a functional reduce on
* {@code long} values.
*
* @param identity the identity for the combining function
* @param operator the combining function
* @return a {@code TerminalOp} implementing the reduction
*/
public static TerminalOp<Long, Long>
makeLong(long identity, LongBinaryOperator operator) {
Objects.requireNonNull(operator);
class ReducingSink
implements AccumulatingSink<Long, Long, ReducingSink>, Sink.OfLong {
private long state;
@Override
public void begin(long size) {
state = identity;
}
@Override
public void accept(long t) {
state = operator.applyAsLong(state, t);
}
@Override
public Long get() {
return state;
}
@Override
public void combine(ReducingSink other) {
accept(other.state);
}
}
return new ReduceOp<Long, Long, ReducingSink>(StreamShape.LONG_VALUE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
};
}
/**
* Constructs a {@code TerminalOp} that implements a functional reduce on
* {@code long} values, producing an optional long result.
*
* @param operator the combining function
* @return a {@code TerminalOp} implementing the reduction
*/
public static TerminalOp<Long, OptionalLong>
makeLong(LongBinaryOperator operator) {
Objects.requireNonNull(operator);
class ReducingSink
implements AccumulatingSink<Long, OptionalLong, ReducingSink>, Sink.OfLong {
private boolean empty;
private long state;
public void begin(long size) {
empty = true;
state = 0;
}
@Override
public void accept(long t) {
if (empty) {
empty = false;
state = t;
}
else {
state = operator.applyAsLong(state, t);
}
}
@Override
public OptionalLong get() {
return empty ? OptionalLong.empty() : OptionalLong.of(state);
}
@Override
public void combine(ReducingSink other) {
if (!other.empty)
accept(other.state);
}
}
return new ReduceOp<Long, OptionalLong, ReducingSink>(StreamShape.LONG_VALUE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
};
}
/**
* Constructs a {@code TerminalOp} that implements a mutable reduce on
* {@code long} values.
*
* @param <R> the type of the result
* @param supplier a factory to produce a new accumulator of the result type
* @param accumulator a function to incorporate an int into an
* accumulator
* @param combiner a function to combine an accumulator into another
* @return a {@code TerminalOp} implementing the reduction
*/
public static <R> TerminalOp<Long, R>
makeLong(Supplier<R> supplier,
ObjLongConsumer<R> accumulator,
BinaryOperator<R> combiner) {
Objects.requireNonNull(supplier);
Objects.requireNonNull(accumulator);
Objects.requireNonNull(combiner);
class ReducingSink extends Box<R>
implements AccumulatingSink<Long, R, ReducingSink>, Sink.OfLong {
@Override
public void begin(long size) {
state = supplier.get();
}
@Override
public void accept(long t) {
accumulator.accept(state, t);
}
@Override
public void combine(ReducingSink other) {
state = combiner.apply(state, other.state);
}
}
return new ReduceOp<Long, R, ReducingSink>(StreamShape.LONG_VALUE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
};
}
/**
* Constructs a {@code TerminalOp} that counts the number of stream
* elements. If the size of the pipeline is known then count is the size
* and there is no need to evaluate the pipeline. If the size of the
* pipeline is non known then count is produced, via reduction, using a
* {@link CountingSink}.
*
* @return a {@code TerminalOp} implementing the counting
*/
public static TerminalOp<Long, Long>
makeLongCounting() {
return new ReduceOp<Long, Long, CountingSink<Long>>(StreamShape.LONG_VALUE) {
@Override
public CountingSink<Long> makeSink() { return new CountingSink.OfLong(); }
@Override
public <P_IN> Long evaluateSequential(PipelineHelper<Long> helper,
Spliterator<P_IN> spliterator) {
if (StreamOpFlag.SIZED.isKnown(helper.getStreamAndOpFlags()))
return spliterator.getExactSizeIfKnown();
return super.evaluateSequential(helper, spliterator);
}
@Override
public <P_IN> Long evaluateParallel(PipelineHelper<Long> helper,
Spliterator<P_IN> spliterator) {
if (StreamOpFlag.SIZED.isKnown(helper.getStreamAndOpFlags()))
return spliterator.getExactSizeIfKnown();
return super.evaluateParallel(helper, spliterator);
}
@Override
public int getOpFlags() {
return StreamOpFlag.NOT_ORDERED;
}
};
}
/**
* Constructs a {@code TerminalOp} that implements a functional reduce on
* {@code double} values.
*
* @param identity the identity for the combining function
* @param operator the combining function
* @return a {@code TerminalOp} implementing the reduction
*/
public static TerminalOp<Double, Double>
makeDouble(double identity, DoubleBinaryOperator operator) {
Objects.requireNonNull(operator);
class ReducingSink
implements AccumulatingSink<Double, Double, ReducingSink>, Sink.OfDouble {
private double state;
@Override
public void begin(long size) {
state = identity;
}
@Override
public void accept(double t) {
state = operator.applyAsDouble(state, t);
}
@Override
public Double get() {
return state;
}
@Override
public void combine(ReducingSink other) {
accept(other.state);
}
}
return new ReduceOp<Double, Double, ReducingSink>(StreamShape.DOUBLE_VALUE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
};
}
/**
* Constructs a {@code TerminalOp} that implements a functional reduce on
* {@code double} values, producing an optional double result.
*
* @param operator the combining function
* @return a {@code TerminalOp} implementing the reduction
*/
public static TerminalOp<Double, OptionalDouble>
makeDouble(DoubleBinaryOperator operator) {
Objects.requireNonNull(operator);
class ReducingSink
implements AccumulatingSink<Double, OptionalDouble, ReducingSink>, Sink.OfDouble {
private boolean empty;
private double state;
public void begin(long size) {
empty = true;
state = 0;
}
@Override
public void accept(double t) {
if (empty) {
empty = false;
state = t;
}
else {
state = operator.applyAsDouble(state, t);
}
}
@Override
public OptionalDouble get() {
return empty ? OptionalDouble.empty() : OptionalDouble.of(state);
}
@Override
public void combine(ReducingSink other) {
if (!other.empty)
accept(other.state);
}
}
return new ReduceOp<Double, OptionalDouble, ReducingSink>(StreamShape.DOUBLE_VALUE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
};
}
/**
* Constructs a {@code TerminalOp} that implements a mutable reduce on
* {@code double} values.
*
* @param <R> the type of the result
* @param supplier a factory to produce a new accumulator of the result type
* @param accumulator a function to incorporate an int into an
* accumulator
* @param combiner a function to combine an accumulator into another
* @return a {@code TerminalOp} implementing the reduction
*/
public static <R> TerminalOp<Double, R>
makeDouble(Supplier<R> supplier,
ObjDoubleConsumer<R> accumulator,
BinaryOperator<R> combiner) {
Objects.requireNonNull(supplier);
Objects.requireNonNull(accumulator);
Objects.requireNonNull(combiner);
class ReducingSink extends Box<R>
implements AccumulatingSink<Double, R, ReducingSink>, Sink.OfDouble {
@Override
public void begin(long size) {
state = supplier.get();
}
@Override
public void accept(double t) {
accumulator.accept(state, t);
}
@Override
public void combine(ReducingSink other) {
state = combiner.apply(state, other.state);
}
}
return new ReduceOp<Double, R, ReducingSink>(StreamShape.DOUBLE_VALUE) {
@Override
public ReducingSink makeSink() {
return new ReducingSink();
}
};
}
/**
* Constructs a {@code TerminalOp} that counts the number of stream
* elements. If the size of the pipeline is known then count is the size
* and there is no need to evaluate the pipeline. If the size of the
* pipeline is non known then count is produced, via reduction, using a
* {@link CountingSink}.
*
* @return a {@code TerminalOp} implementing the counting
*/
public static TerminalOp<Double, Long>
makeDoubleCounting() {
return new ReduceOp<Double, Long, CountingSink<Double>>(StreamShape.DOUBLE_VALUE) {
@Override
public CountingSink<Double> makeSink() { return new CountingSink.OfDouble(); }
@Override
public <P_IN> Long evaluateSequential(PipelineHelper<Double> helper,
Spliterator<P_IN> spliterator) {
if (StreamOpFlag.SIZED.isKnown(helper.getStreamAndOpFlags()))
return spliterator.getExactSizeIfKnown();
return super.evaluateSequential(helper, spliterator);
}
@Override
public <P_IN> Long evaluateParallel(PipelineHelper<Double> helper,
Spliterator<P_IN> spliterator) {
if (StreamOpFlag.SIZED.isKnown(helper.getStreamAndOpFlags()))
return spliterator.getExactSizeIfKnown();
return super.evaluateParallel(helper, spliterator);
}
@Override
public int getOpFlags() {
return StreamOpFlag.NOT_ORDERED;
}
};
}
/**
* A sink that counts elements
*/
abstract static class CountingSink<T>
extends Box<Long>
implements AccumulatingSink<T, Long, CountingSink<T>> {
long count;
@Override
public void begin(long size) {
count = 0L;
}
@Override
public Long get() {
return count;
}
@Override
public void combine(CountingSink<T> other) {
count += other.count;
}
static final class OfRef<T> extends CountingSink<T> {
@Override
public void accept(T t) {
count++;
}
}
static final class OfInt extends CountingSink<Integer> implements Sink.OfInt {
@Override
public void accept(int t) {
count++;
}
}
static final class OfLong extends CountingSink<Long> implements Sink.OfLong {
@Override
public void accept(long t) {
count++;
}
}
static final class OfDouble extends CountingSink<Double> implements Sink.OfDouble {
@Override
public void accept(double t) {
count++;
}
}
}
/**
* A type of {@code TerminalSink} that implements an associative reducing
* operation on elements of type {@code T} and producing a result of type
* {@code R}.
*
* @param <T> the type of input element to the combining operation
* @param <R> the result type
* @param <K> the type of the {@code AccumulatingSink}.
*/
private interface AccumulatingSink<T, R, K extends AccumulatingSink<T, R, K>>
extends TerminalSink<T, R> {
void combine(K other);
}
/**
* State box for a single state element, used as a base class for
* {@code AccumulatingSink} instances
*
* @param <U> The type of the state element
*/
private abstract static class Box<U> {
U state;
Box() {} // Avoid creation of special accessor
public U get() {
return state;
}
}
/**
* A {@code TerminalOp} that evaluates a stream pipeline and sends the
* output into an {@code AccumulatingSink}, which performs a reduce
* operation. The {@code AccumulatingSink} must represent an associative
* reducing operation.
*
* @param <T> the output type of the stream pipeline
* @param <R> the result type of the reducing operation
* @param <S> the type of the {@code AccumulatingSink}
*/
private abstract static class ReduceOp<T, R, S extends AccumulatingSink<T, R, S>>
implements TerminalOp<T, R> {
private final StreamShape inputShape;
/**
* Create a {@code ReduceOp} of the specified stream shape which uses
* the specified {@code Supplier} to create accumulating sinks.
*
* @param shape The shape of the stream pipeline
*/
ReduceOp(StreamShape shape) {
inputShape = shape;
}
public abstract S makeSink();
@Override
public StreamShape inputShape() {
return inputShape;
}
@Override
public <P_IN> R evaluateSequential(PipelineHelper<T> helper,
Spliterator<P_IN> spliterator) {
return helper.wrapAndCopyInto(makeSink(), spliterator).get();
}
@Override
public <P_IN> R evaluateParallel(PipelineHelper<T> helper,
Spliterator<P_IN> spliterator) {
return new ReduceTask<>(this, helper, spliterator).invoke().get();
}
}
/**
* A {@code ForkJoinTask} for performing a parallel reduce operation.
*/
@SuppressWarnings("serial")
private static final class ReduceTask<P_IN, P_OUT, R,
S extends AccumulatingSink<P_OUT, R, S>>
extends AbstractTask<P_IN, P_OUT, S, ReduceTask<P_IN, P_OUT, R, S>> {
private final ReduceOp<P_OUT, R, S> op;
ReduceTask(ReduceOp<P_OUT, R, S> op,
PipelineHelper<P_OUT> helper,
Spliterator<P_IN> spliterator) {
super(helper, spliterator);
this.op = op;
}
ReduceTask(ReduceTask<P_IN, P_OUT, R, S> parent,
Spliterator<P_IN> spliterator) {
super(parent, spliterator);
this.op = parent.op;
}
@Override
protected ReduceTask<P_IN, P_OUT, R, S> makeChild(Spliterator<P_IN> spliterator) {
return new ReduceTask<>(this, spliterator);
}
@Override
protected S doLeaf() {
return helper.wrapAndCopyInto(op.makeSink(), spliterator);
}
@Override
public void onCompletion(CountedCompleter<?> caller) {
if (!isLeaf()) {
S leftResult = leftChild.getLocalResult();
leftResult.combine(rightChild.getLocalResult());
setLocalResult(leftResult);
}
// GC spliterator, left and right child
super.onCompletion(caller);
}
}
}

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@ -0,0 +1,672 @@
/*
* Copyright (c) 2012, 2015, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Comparator;
import java.util.Iterator;
import java.util.Objects;
import java.util.Optional;
import java.util.Spliterator;
import java.util.Spliterators;
import java.util.function.BiConsumer;
import java.util.function.BiFunction;
import java.util.function.BinaryOperator;
import java.util.function.Consumer;
import java.util.function.DoubleConsumer;
import java.util.function.Function;
import java.util.function.IntConsumer;
import java.util.function.IntFunction;
import java.util.function.LongConsumer;
import java.util.function.Predicate;
import java.util.function.Supplier;
import java.util.function.ToDoubleFunction;
import java.util.function.ToIntFunction;
import java.util.function.ToLongFunction;
/**
* Abstract base class for an intermediate pipeline stage or pipeline source
* stage implementing whose elements are of type {@code U}.
*
* @param <P_IN> type of elements in the upstream source
* @param <P_OUT> type of elements in produced by this stage
*
* @since 1.8
*/
abstract class ReferencePipeline<P_IN, P_OUT>
extends AbstractPipeline<P_IN, P_OUT, Stream<P_OUT>>
implements Stream<P_OUT> {
/**
* Constructor for the head of a stream pipeline.
*
* @param source {@code Supplier<Spliterator>} describing the stream source
* @param sourceFlags the source flags for the stream source, described in
* {@link StreamOpFlag}
* @param parallel {@code true} if the pipeline is parallel
*/
ReferencePipeline(Supplier<? extends Spliterator<?>> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
/**
* Constructor for the head of a stream pipeline.
*
* @param source {@code Spliterator} describing the stream source
* @param sourceFlags The source flags for the stream source, described in
* {@link StreamOpFlag}
* @param parallel {@code true} if the pipeline is parallel
*/
ReferencePipeline(Spliterator<?> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
/**
* Constructor for appending an intermediate operation onto an existing
* pipeline.
*
* @param upstream the upstream element source.
*/
ReferencePipeline(AbstractPipeline<?, P_IN, ?> upstream, int opFlags) {
super(upstream, opFlags);
}
// Shape-specific methods
@Override
final StreamShape getOutputShape() {
return StreamShape.REFERENCE;
}
@Override
final <P_IN> Node<P_OUT> evaluateToNode(PipelineHelper<P_OUT> helper,
Spliterator<P_IN> spliterator,
boolean flattenTree,
IntFunction<P_OUT[]> generator) {
return Nodes.collect(helper, spliterator, flattenTree, generator);
}
@Override
final <P_IN> Spliterator<P_OUT> wrap(PipelineHelper<P_OUT> ph,
Supplier<Spliterator<P_IN>> supplier,
boolean isParallel) {
return new StreamSpliterators.WrappingSpliterator<>(ph, supplier, isParallel);
}
@Override
final Spliterator<P_OUT> lazySpliterator(Supplier<? extends Spliterator<P_OUT>> supplier) {
return new StreamSpliterators.DelegatingSpliterator<>(supplier);
}
@Override
final boolean forEachWithCancel(Spliterator<P_OUT> spliterator, Sink<P_OUT> sink) {
boolean cancelled;
do { } while (!(cancelled = sink.cancellationRequested()) && spliterator.tryAdvance(sink));
return cancelled;
}
@Override
final Node.Builder<P_OUT> makeNodeBuilder(long exactSizeIfKnown, IntFunction<P_OUT[]> generator) {
return Nodes.builder(exactSizeIfKnown, generator);
}
// BaseStream
@Override
public final Iterator<P_OUT> iterator() {
return Spliterators.iterator(spliterator());
}
// Stream
// Stateless intermediate operations from Stream
@Override
public Stream<P_OUT> unordered() {
if (!isOrdered())
return this;
return new StatelessOp<P_OUT, P_OUT>(this, StreamShape.REFERENCE, StreamOpFlag.NOT_ORDERED) {
@Override
Sink<P_OUT> opWrapSink(int flags, Sink<P_OUT> sink) {
return sink;
}
};
}
@Override
public final Stream<P_OUT> filter(Predicate<? super P_OUT> predicate) {
Objects.requireNonNull(predicate);
return new StatelessOp<P_OUT, P_OUT>(this, StreamShape.REFERENCE,
StreamOpFlag.NOT_SIZED) {
@Override
Sink<P_OUT> opWrapSink(int flags, Sink<P_OUT> sink) {
return new Sink.ChainedReference<P_OUT, P_OUT>(sink) {
@Override
public void begin(long size) {
downstream.begin(-1);
}
@Override
public void accept(P_OUT u) {
if (predicate.test(u))
downstream.accept(u);
}
};
}
};
}
@Override
@SuppressWarnings("unchecked")
public final <R> Stream<R> map(Function<? super P_OUT, ? extends R> mapper) {
Objects.requireNonNull(mapper);
return new StatelessOp<P_OUT, R>(this, StreamShape.REFERENCE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT) {
@Override
Sink<P_OUT> opWrapSink(int flags, Sink<R> sink) {
return new Sink.ChainedReference<P_OUT, R>(sink) {
@Override
public void accept(P_OUT u) {
downstream.accept(mapper.apply(u));
}
};
}
};
}
@Override
public final IntStream mapToInt(ToIntFunction<? super P_OUT> mapper) {
Objects.requireNonNull(mapper);
return new IntPipeline.StatelessOp<P_OUT>(this, StreamShape.REFERENCE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT) {
@Override
Sink<P_OUT> opWrapSink(int flags, Sink<Integer> sink) {
return new Sink.ChainedReference<P_OUT, Integer>(sink) {
@Override
public void accept(P_OUT u) {
downstream.accept(mapper.applyAsInt(u));
}
};
}
};
}
@Override
public final LongStream mapToLong(ToLongFunction<? super P_OUT> mapper) {
Objects.requireNonNull(mapper);
return new LongPipeline.StatelessOp<P_OUT>(this, StreamShape.REFERENCE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT) {
@Override
Sink<P_OUT> opWrapSink(int flags, Sink<Long> sink) {
return new Sink.ChainedReference<P_OUT, Long>(sink) {
@Override
public void accept(P_OUT u) {
downstream.accept(mapper.applyAsLong(u));
}
};
}
};
}
@Override
public final DoubleStream mapToDouble(ToDoubleFunction<? super P_OUT> mapper) {
Objects.requireNonNull(mapper);
return new DoublePipeline.StatelessOp<P_OUT>(this, StreamShape.REFERENCE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT) {
@Override
Sink<P_OUT> opWrapSink(int flags, Sink<Double> sink) {
return new Sink.ChainedReference<P_OUT, Double>(sink) {
@Override
public void accept(P_OUT u) {
downstream.accept(mapper.applyAsDouble(u));
}
};
}
};
}
@Override
public final <R> Stream<R> flatMap(Function<? super P_OUT, ? extends Stream<? extends R>> mapper) {
Objects.requireNonNull(mapper);
// We can do better than this, by polling cancellationRequested when stream is infinite
return new StatelessOp<P_OUT, R>(this, StreamShape.REFERENCE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT | StreamOpFlag.NOT_SIZED) {
@Override
Sink<P_OUT> opWrapSink(int flags, Sink<R> sink) {
return new Sink.ChainedReference<P_OUT, R>(sink) {
@Override
public void begin(long size) {
downstream.begin(-1);
}
@Override
public void accept(P_OUT u) {
try (Stream<? extends R> result = mapper.apply(u)) {
// We can do better that this too; optimize for depth=0 case and just grab spliterator and forEach it
if (result != null)
result.sequential().forEach(downstream);
}
}
};
}
};
}
@Override
public final IntStream flatMapToInt(Function<? super P_OUT, ? extends IntStream> mapper) {
Objects.requireNonNull(mapper);
// We can do better than this, by polling cancellationRequested when stream is infinite
return new IntPipeline.StatelessOp<P_OUT>(this, StreamShape.REFERENCE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT | StreamOpFlag.NOT_SIZED) {
@Override
Sink<P_OUT> opWrapSink(int flags, Sink<Integer> sink) {
return new Sink.ChainedReference<P_OUT, Integer>(sink) {
IntConsumer downstreamAsInt = downstream::accept;
@Override
public void begin(long size) {
downstream.begin(-1);
}
@Override
public void accept(P_OUT u) {
try (IntStream result = mapper.apply(u)) {
// We can do better that this too; optimize for depth=0 case and just grab spliterator and forEach it
if (result != null)
result.sequential().forEach(downstreamAsInt);
}
}
};
}
};
}
@Override
public final DoubleStream flatMapToDouble(Function<? super P_OUT, ? extends DoubleStream> mapper) {
Objects.requireNonNull(mapper);
// We can do better than this, by polling cancellationRequested when stream is infinite
return new DoublePipeline.StatelessOp<P_OUT>(this, StreamShape.REFERENCE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT | StreamOpFlag.NOT_SIZED) {
@Override
Sink<P_OUT> opWrapSink(int flags, Sink<Double> sink) {
return new Sink.ChainedReference<P_OUT, Double>(sink) {
DoubleConsumer downstreamAsDouble = downstream::accept;
@Override
public void begin(long size) {
downstream.begin(-1);
}
@Override
public void accept(P_OUT u) {
try (DoubleStream result = mapper.apply(u)) {
// We can do better that this too; optimize for depth=0 case and just grab spliterator and forEach it
if (result != null)
result.sequential().forEach(downstreamAsDouble);
}
}
};
}
};
}
@Override
public final LongStream flatMapToLong(Function<? super P_OUT, ? extends LongStream> mapper) {
Objects.requireNonNull(mapper);
// We can do better than this, by polling cancellationRequested when stream is infinite
return new LongPipeline.StatelessOp<P_OUT>(this, StreamShape.REFERENCE,
StreamOpFlag.NOT_SORTED | StreamOpFlag.NOT_DISTINCT | StreamOpFlag.NOT_SIZED) {
@Override
Sink<P_OUT> opWrapSink(int flags, Sink<Long> sink) {
return new Sink.ChainedReference<P_OUT, Long>(sink) {
LongConsumer downstreamAsLong = downstream::accept;
@Override
public void begin(long size) {
downstream.begin(-1);
}
@Override
public void accept(P_OUT u) {
try (LongStream result = mapper.apply(u)) {
// We can do better that this too; optimize for depth=0 case and just grab spliterator and forEach it
if (result != null)
result.sequential().forEach(downstreamAsLong);
}
}
};
}
};
}
@Override
public final Stream<P_OUT> peek(Consumer<? super P_OUT> action) {
Objects.requireNonNull(action);
return new StatelessOp<P_OUT, P_OUT>(this, StreamShape.REFERENCE,
0) {
@Override
Sink<P_OUT> opWrapSink(int flags, Sink<P_OUT> sink) {
return new Sink.ChainedReference<P_OUT, P_OUT>(sink) {
@Override
public void accept(P_OUT u) {
action.accept(u);
downstream.accept(u);
}
};
}
};
}
// Stateful intermediate operations from Stream
@Override
public final Stream<P_OUT> distinct() {
return DistinctOps.makeRef(this);
}
@Override
public final Stream<P_OUT> sorted() {
return SortedOps.makeRef(this);
}
@Override
public final Stream<P_OUT> sorted(Comparator<? super P_OUT> comparator) {
return SortedOps.makeRef(this, comparator);
}
@Override
public final Stream<P_OUT> limit(long maxSize) {
if (maxSize < 0)
throw new IllegalArgumentException(Long.toString(maxSize));
return SliceOps.makeRef(this, 0, maxSize);
}
@Override
public final Stream<P_OUT> skip(long n) {
if (n < 0)
throw new IllegalArgumentException(Long.toString(n));
if (n == 0)
return this;
else
return SliceOps.makeRef(this, n, -1);
}
@Override
public final Stream<P_OUT> takeWhile(Predicate<? super P_OUT> predicate) {
return WhileOps.makeTakeWhileRef(this, predicate);
}
@Override
public final Stream<P_OUT> dropWhile(Predicate<? super P_OUT> predicate) {
return WhileOps.makeDropWhileRef(this, predicate);
}
// Terminal operations from Stream
@Override
public void forEach(Consumer<? super P_OUT> action) {
evaluate(ForEachOps.makeRef(action, false));
}
@Override
public void forEachOrdered(Consumer<? super P_OUT> action) {
evaluate(ForEachOps.makeRef(action, true));
}
@Override
@SuppressWarnings("unchecked")
public final <A> A[] toArray(IntFunction<A[]> generator) {
// Since A has no relation to U (not possible to declare that A is an upper bound of U)
// there will be no static type checking.
// Therefore use a raw type and assume A == U rather than propagating the separation of A and U
// throughout the code-base.
// The runtime type of U is never checked for equality with the component type of the runtime type of A[].
// Runtime checking will be performed when an element is stored in A[], thus if A is not a
// super type of U an ArrayStoreException will be thrown.
@SuppressWarnings("rawtypes")
IntFunction rawGenerator = (IntFunction) generator;
return (A[]) Nodes.flatten(evaluateToArrayNode(rawGenerator), rawGenerator)
.asArray(rawGenerator);
}
@Override
public final Object[] toArray() {
return toArray(Object[]::new);
}
@Override
public final boolean anyMatch(Predicate<? super P_OUT> predicate) {
return evaluate(MatchOps.makeRef(predicate, MatchOps.MatchKind.ANY));
}
@Override
public final boolean allMatch(Predicate<? super P_OUT> predicate) {
return evaluate(MatchOps.makeRef(predicate, MatchOps.MatchKind.ALL));
}
@Override
public final boolean noneMatch(Predicate<? super P_OUT> predicate) {
return evaluate(MatchOps.makeRef(predicate, MatchOps.MatchKind.NONE));
}
@Override
public final Optional<P_OUT> findFirst() {
return evaluate(FindOps.makeRef(true));
}
@Override
public final Optional<P_OUT> findAny() {
return evaluate(FindOps.makeRef(false));
}
@Override
public final P_OUT reduce(final P_OUT identity, final BinaryOperator<P_OUT> accumulator) {
return evaluate(ReduceOps.makeRef(identity, accumulator, accumulator));
}
@Override
public final Optional<P_OUT> reduce(BinaryOperator<P_OUT> accumulator) {
return evaluate(ReduceOps.makeRef(accumulator));
}
@Override
public final <R> R reduce(R identity, BiFunction<R, ? super P_OUT, R> accumulator, BinaryOperator<R> combiner) {
return evaluate(ReduceOps.makeRef(identity, accumulator, combiner));
}
@Override
@SuppressWarnings("unchecked")
public final <R, A> R collect(Collector<? super P_OUT, A, R> collector) {
A container;
if (isParallel()
&& (collector.characteristics().contains(Collector.Characteristics.CONCURRENT))
&& (!isOrdered() || collector.characteristics().contains(Collector.Characteristics.UNORDERED))) {
container = collector.supplier().get();
BiConsumer<A, ? super P_OUT> accumulator = collector.accumulator();
forEach(u -> accumulator.accept(container, u));
}
else {
container = evaluate(ReduceOps.makeRef(collector));
}
return collector.characteristics().contains(Collector.Characteristics.IDENTITY_FINISH)
? (R) container
: collector.finisher().apply(container);
}
@Override
public final <R> R collect(Supplier<R> supplier,
BiConsumer<R, ? super P_OUT> accumulator,
BiConsumer<R, R> combiner) {
return evaluate(ReduceOps.makeRef(supplier, accumulator, combiner));
}
@Override
public final Optional<P_OUT> max(Comparator<? super P_OUT> comparator) {
return reduce(BinaryOperator.maxBy(comparator));
}
@Override
public final Optional<P_OUT> min(Comparator<? super P_OUT> comparator) {
return reduce(BinaryOperator.minBy(comparator));
}
@Override
public final long count() {
return evaluate(ReduceOps.makeRefCounting());
}
//
/**
* Source stage of a ReferencePipeline.
*
* @param <E_IN> type of elements in the upstream source
* @param <E_OUT> type of elements in produced by this stage
* @since 1.8
*/
static class Head<E_IN, E_OUT> extends ReferencePipeline<E_IN, E_OUT> {
/**
* Constructor for the source stage of a Stream.
*
* @param source {@code Supplier<Spliterator>} describing the stream
* source
* @param sourceFlags the source flags for the stream source, described
* in {@link StreamOpFlag}
*/
Head(Supplier<? extends Spliterator<?>> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
/**
* Constructor for the source stage of a Stream.
*
* @param source {@code Spliterator} describing the stream source
* @param sourceFlags the source flags for the stream source, described
* in {@link StreamOpFlag}
*/
Head(Spliterator<?> source,
int sourceFlags, boolean parallel) {
super(source, sourceFlags, parallel);
}
@Override
final boolean opIsStateful() {
throw new UnsupportedOperationException();
}
@Override
final Sink<E_IN> opWrapSink(int flags, Sink<E_OUT> sink) {
throw new UnsupportedOperationException();
}
// Optimized sequential terminal operations for the head of the pipeline
@Override
public void forEach(Consumer<? super E_OUT> action) {
if (!isParallel()) {
sourceStageSpliterator().forEachRemaining(action);
}
else {
super.forEach(action);
}
}
@Override
public void forEachOrdered(Consumer<? super E_OUT> action) {
if (!isParallel()) {
sourceStageSpliterator().forEachRemaining(action);
}
else {
super.forEachOrdered(action);
}
}
}
/**
* Base class for a stateless intermediate stage of a Stream.
*
* @param <E_IN> type of elements in the upstream source
* @param <E_OUT> type of elements in produced by this stage
* @since 1.8
*/
abstract static class StatelessOp<E_IN, E_OUT>
extends ReferencePipeline<E_IN, E_OUT> {
/**
* Construct a new Stream by appending a stateless intermediate
* operation to an existing stream.
*
* @param upstream The upstream pipeline stage
* @param inputShape The stream shape for the upstream pipeline stage
* @param opFlags Operation flags for the new stage
*/
StatelessOp(AbstractPipeline<?, E_IN, ?> upstream,
StreamShape inputShape,
int opFlags) {
super(upstream, opFlags);
assert upstream.getOutputShape() == inputShape;
}
@Override
final boolean opIsStateful() {
return false;
}
}
/**
* Base class for a stateful intermediate stage of a Stream.
*
* @param <E_IN> type of elements in the upstream source
* @param <E_OUT> type of elements in produced by this stage
* @since 1.8
*/
abstract static class StatefulOp<E_IN, E_OUT>
extends ReferencePipeline<E_IN, E_OUT> {
/**
* Construct a new Stream by appending a stateful intermediate operation
* to an existing stream.
* @param upstream The upstream pipeline stage
* @param inputShape The stream shape for the upstream pipeline stage
* @param opFlags Operation flags for the new stage
*/
StatefulOp(AbstractPipeline<?, E_IN, ?> upstream,
StreamShape inputShape,
int opFlags) {
super(upstream, opFlags);
assert upstream.getOutputShape() == inputShape;
}
@Override
final boolean opIsStateful() {
return true;
}
@Override
abstract <P_IN> Node<E_OUT> opEvaluateParallel(PipelineHelper<E_OUT> helper,
Spliterator<P_IN> spliterator,
IntFunction<E_OUT[]> generator);
}
}

View file

@ -0,0 +1,362 @@
/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Objects;
import java.util.function.Consumer;
import java.util.function.DoubleConsumer;
import java.util.function.IntConsumer;
import java.util.function.LongConsumer;
/**
* An extension of {@link Consumer} used to conduct values through the stages of
* a stream pipeline, with additional methods to manage size information,
* control flow, etc. Before calling the {@code accept()} method on a
* {@code Sink} for the first time, you must first call the {@code begin()}
* method to inform it that data is coming (optionally informing the sink how
* much data is coming), and after all data has been sent, you must call the
* {@code end()} method. After calling {@code end()}, you should not call
* {@code accept()} without again calling {@code begin()}. {@code Sink} also
* offers a mechanism by which the sink can cooperatively signal that it does
* not wish to receive any more data (the {@code cancellationRequested()}
* method), which a source can poll before sending more data to the
* {@code Sink}.
*
* <p>A sink may be in one of two states: an initial state and an active state.
* It starts out in the initial state; the {@code begin()} method transitions
* it to the active state, and the {@code end()} method transitions it back into
* the initial state, where it can be re-used. Data-accepting methods (such as
* {@code accept()} are only valid in the active state.
*
* @apiNote
* A stream pipeline consists of a source, zero or more intermediate stages
* (such as filtering or mapping), and a terminal stage, such as reduction or
* for-each. For concreteness, consider the pipeline:
*
* <pre>{@code
* int longestStringLengthStartingWithA
* = strings.stream()
* .filter(s -> s.startsWith("A"))
* .mapToInt(String::length)
* .max();
* }</pre>
*
* <p>Here, we have three stages, filtering, mapping, and reducing. The
* filtering stage consumes strings and emits a subset of those strings; the
* mapping stage consumes strings and emits ints; the reduction stage consumes
* those ints and computes the maximal value.
*
* <p>A {@code Sink} instance is used to represent each stage of this pipeline,
* whether the stage accepts objects, ints, longs, or doubles. Sink has entry
* points for {@code accept(Object)}, {@code accept(int)}, etc, so that we do
* not need a specialized interface for each primitive specialization. (It
* might be called a "kitchen sink" for this omnivorous tendency.) The entry
* point to the pipeline is the {@code Sink} for the filtering stage, which
* sends some elements "downstream" -- into the {@code Sink} for the mapping
* stage, which in turn sends integral values downstream into the {@code Sink}
* for the reduction stage. The {@code Sink} implementations associated with a
* given stage is expected to know the data type for the next stage, and call
* the correct {@code accept} method on its downstream {@code Sink}. Similarly,
* each stage must implement the correct {@code accept} method corresponding to
* the data type it accepts.
*
* <p>The specialized subtypes such as {@link Sink.OfInt} override
* {@code accept(Object)} to call the appropriate primitive specialization of
* {@code accept}, implement the appropriate primitive specialization of
* {@code Consumer}, and re-abstract the appropriate primitive specialization of
* {@code accept}.
*
* <p>The chaining subtypes such as {@link ChainedInt} not only implement
* {@code Sink.OfInt}, but also maintain a {@code downstream} field which
* represents the downstream {@code Sink}, and implement the methods
* {@code begin()}, {@code end()}, and {@code cancellationRequested()} to
* delegate to the downstream {@code Sink}. Most implementations of
* intermediate operations will use these chaining wrappers. For example, the
* mapping stage in the above example would look like:
*
* <pre>{@code
* IntSink is = new Sink.ChainedReference<U>(sink) {
* public void accept(U u) {
* downstream.accept(mapper.applyAsInt(u));
* }
* };
* }</pre>
*
* <p>Here, we implement {@code Sink.ChainedReference<U>}, meaning that we expect
* to receive elements of type {@code U} as input, and pass the downstream sink
* to the constructor. Because the next stage expects to receive integers, we
* must call the {@code accept(int)} method when emitting values to the downstream.
* The {@code accept()} method applies the mapping function from {@code U} to
* {@code int} and passes the resulting value to the downstream {@code Sink}.
*
* @param <T> type of elements for value streams
* @since 1.8
*/
interface Sink<T> extends Consumer<T> {
/**
* Resets the sink state to receive a fresh data set. This must be called
* before sending any data to the sink. After calling {@link #end()},
* you may call this method to reset the sink for another calculation.
* @param size The exact size of the data to be pushed downstream, if
* known or {@code -1} if unknown or infinite.
*
* <p>Prior to this call, the sink must be in the initial state, and after
* this call it is in the active state.
*/
default void begin(long size) {}
/**
* Indicates that all elements have been pushed. If the {@code Sink} is
* stateful, it should send any stored state downstream at this time, and
* should clear any accumulated state (and associated resources).
*
* <p>Prior to this call, the sink must be in the active state, and after
* this call it is returned to the initial state.
*/
default void end() {}
/**
* Indicates that this {@code Sink} does not wish to receive any more data.
*
* @implSpec The default implementation always returns false.
*
* @return true if cancellation is requested
*/
default boolean cancellationRequested() {
return false;
}
/**
* Accepts an int value.
*
* @implSpec The default implementation throws IllegalStateException.
*
* @throws IllegalStateException if this sink does not accept int values
*/
default void accept(int value) {
throw new IllegalStateException("called wrong accept method");
}
/**
* Accepts a long value.
*
* @implSpec The default implementation throws IllegalStateException.
*
* @throws IllegalStateException if this sink does not accept long values
*/
default void accept(long value) {
throw new IllegalStateException("called wrong accept method");
}
/**
* Accepts a double value.
*
* @implSpec The default implementation throws IllegalStateException.
*
* @throws IllegalStateException if this sink does not accept double values
*/
default void accept(double value) {
throw new IllegalStateException("called wrong accept method");
}
/**
* {@code Sink} that implements {@code Sink<Integer>}, re-abstracts
* {@code accept(int)}, and wires {@code accept(Integer)} to bridge to
* {@code accept(int)}.
*/
interface OfInt extends Sink<Integer>, IntConsumer {
@Override
void accept(int value);
@Override
default void accept(Integer i) {
if (Tripwire.ENABLED)
Tripwire.trip(getClass(), "{0} calling Sink.OfInt.accept(Integer)");
accept(i.intValue());
}
}
/**
* {@code Sink} that implements {@code Sink<Long>}, re-abstracts
* {@code accept(long)}, and wires {@code accept(Long)} to bridge to
* {@code accept(long)}.
*/
interface OfLong extends Sink<Long>, LongConsumer {
@Override
void accept(long value);
@Override
default void accept(Long i) {
if (Tripwire.ENABLED)
Tripwire.trip(getClass(), "{0} calling Sink.OfLong.accept(Long)");
accept(i.longValue());
}
}
/**
* {@code Sink} that implements {@code Sink<Double>}, re-abstracts
* {@code accept(double)}, and wires {@code accept(Double)} to bridge to
* {@code accept(double)}.
*/
interface OfDouble extends Sink<Double>, DoubleConsumer {
@Override
void accept(double value);
@Override
default void accept(Double i) {
if (Tripwire.ENABLED)
Tripwire.trip(getClass(), "{0} calling Sink.OfDouble.accept(Double)");
accept(i.doubleValue());
}
}
/**
* Abstract {@code Sink} implementation for creating chains of
* sinks. The {@code begin}, {@code end}, and
* {@code cancellationRequested} methods are wired to chain to the
* downstream {@code Sink}. This implementation takes a downstream
* {@code Sink} of unknown input shape and produces a {@code Sink<T>}. The
* implementation of the {@code accept()} method must call the correct
* {@code accept()} method on the downstream {@code Sink}.
*/
abstract static class ChainedReference<T, E_OUT> implements Sink<T> {
protected final Sink<? super E_OUT> downstream;
public ChainedReference(Sink<? super E_OUT> downstream) {
this.downstream = Objects.requireNonNull(downstream);
}
@Override
public void begin(long size) {
downstream.begin(size);
}
@Override
public void end() {
downstream.end();
}
@Override
public boolean cancellationRequested() {
return downstream.cancellationRequested();
}
}
/**
* Abstract {@code Sink} implementation designed for creating chains of
* sinks. The {@code begin}, {@code end}, and
* {@code cancellationRequested} methods are wired to chain to the
* downstream {@code Sink}. This implementation takes a downstream
* {@code Sink} of unknown input shape and produces a {@code Sink.OfInt}.
* The implementation of the {@code accept()} method must call the correct
* {@code accept()} method on the downstream {@code Sink}.
*/
abstract static class ChainedInt<E_OUT> implements Sink.OfInt {
protected final Sink<? super E_OUT> downstream;
public ChainedInt(Sink<? super E_OUT> downstream) {
this.downstream = Objects.requireNonNull(downstream);
}
@Override
public void begin(long size) {
downstream.begin(size);
}
@Override
public void end() {
downstream.end();
}
@Override
public boolean cancellationRequested() {
return downstream.cancellationRequested();
}
}
/**
* Abstract {@code Sink} implementation designed for creating chains of
* sinks. The {@code begin}, {@code end}, and
* {@code cancellationRequested} methods are wired to chain to the
* downstream {@code Sink}. This implementation takes a downstream
* {@code Sink} of unknown input shape and produces a {@code Sink.OfLong}.
* The implementation of the {@code accept()} method must call the correct
* {@code accept()} method on the downstream {@code Sink}.
*/
abstract static class ChainedLong<E_OUT> implements Sink.OfLong {
protected final Sink<? super E_OUT> downstream;
public ChainedLong(Sink<? super E_OUT> downstream) {
this.downstream = Objects.requireNonNull(downstream);
}
@Override
public void begin(long size) {
downstream.begin(size);
}
@Override
public void end() {
downstream.end();
}
@Override
public boolean cancellationRequested() {
return downstream.cancellationRequested();
}
}
/**
* Abstract {@code Sink} implementation designed for creating chains of
* sinks. The {@code begin}, {@code end}, and
* {@code cancellationRequested} methods are wired to chain to the
* downstream {@code Sink}. This implementation takes a downstream
* {@code Sink} of unknown input shape and produces a {@code Sink.OfDouble}.
* The implementation of the {@code accept()} method must call the correct
* {@code accept()} method on the downstream {@code Sink}.
*/
abstract static class ChainedDouble<E_OUT> implements Sink.OfDouble {
protected final Sink<? super E_OUT> downstream;
public ChainedDouble(Sink<? super E_OUT> downstream) {
this.downstream = Objects.requireNonNull(downstream);
}
@Override
public void begin(long size) {
downstream.begin(size);
}
@Override
public void end() {
downstream.end();
}
@Override
public boolean cancellationRequested() {
return downstream.cancellationRequested();
}
}
}

View file

@ -0,0 +1,717 @@
/*
* Copyright (c) 2012, 2016, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Spliterator;
import java.util.concurrent.CountedCompleter;
import java.util.function.IntFunction;
/**
* Factory for instances of a short-circuiting stateful intermediate operations
* that produce subsequences of their input stream.
*
* @since 1.8
*/
final class SliceOps {
// No instances
private SliceOps() { }
/**
* Calculates the sliced size given the current size, number of elements
* skip, and the number of elements to limit.
*
* @param size the current size
* @param skip the number of elements to skip, assumed to be >= 0
* @param limit the number of elements to limit, assumed to be >= 0, with
* a value of {@code Long.MAX_VALUE} if there is no limit
* @return the sliced size
*/
private static long calcSize(long size, long skip, long limit) {
return size >= 0 ? Math.max(-1, Math.min(size - skip, limit)) : -1;
}
/**
* Calculates the slice fence, which is one past the index of the slice
* range
* @param skip the number of elements to skip, assumed to be >= 0
* @param limit the number of elements to limit, assumed to be >= 0, with
* a value of {@code Long.MAX_VALUE} if there is no limit
* @return the slice fence.
*/
private static long calcSliceFence(long skip, long limit) {
long sliceFence = limit >= 0 ? skip + limit : Long.MAX_VALUE;
// Check for overflow
return (sliceFence >= 0) ? sliceFence : Long.MAX_VALUE;
}
/**
* Creates a slice spliterator given a stream shape governing the
* spliterator type. Requires that the underlying Spliterator
* be SUBSIZED.
*/
@SuppressWarnings("unchecked")
private static <P_IN> Spliterator<P_IN> sliceSpliterator(StreamShape shape,
Spliterator<P_IN> s,
long skip, long limit) {
assert s.hasCharacteristics(Spliterator.SUBSIZED);
long sliceFence = calcSliceFence(skip, limit);
switch (shape) {
case REFERENCE:
return new StreamSpliterators
.SliceSpliterator.OfRef<>(s, skip, sliceFence);
case INT_VALUE:
return (Spliterator<P_IN>) new StreamSpliterators
.SliceSpliterator.OfInt((Spliterator.OfInt) s, skip, sliceFence);
case LONG_VALUE:
return (Spliterator<P_IN>) new StreamSpliterators
.SliceSpliterator.OfLong((Spliterator.OfLong) s, skip, sliceFence);
case DOUBLE_VALUE:
return (Spliterator<P_IN>) new StreamSpliterators
.SliceSpliterator.OfDouble((Spliterator.OfDouble) s, skip, sliceFence);
default:
throw new IllegalStateException("Unknown shape " + shape);
}
}
/**
* Appends a "slice" operation to the provided stream. The slice operation
* may be may be skip-only, limit-only, or skip-and-limit.
*
* @param <T> the type of both input and output elements
* @param upstream a reference stream with element type T
* @param skip the number of elements to skip. Must be >= 0.
* @param limit the maximum size of the resulting stream, or -1 if no limit
* is to be imposed
*/
public static <T> Stream<T> makeRef(AbstractPipeline<?, T, ?> upstream,
long skip, long limit) {
if (skip < 0)
throw new IllegalArgumentException("Skip must be non-negative: " + skip);
return new ReferencePipeline.StatefulOp<T, T>(upstream, StreamShape.REFERENCE,
flags(limit)) {
Spliterator<T> unorderedSkipLimitSpliterator(Spliterator<T> s,
long skip, long limit, long sizeIfKnown) {
if (skip <= sizeIfKnown) {
// Use just the limit if the number of elements
// to skip is <= the known pipeline size
limit = limit >= 0 ? Math.min(limit, sizeIfKnown - skip) : sizeIfKnown - skip;
skip = 0;
}
return new StreamSpliterators.UnorderedSliceSpliterator.OfRef<>(s, skip, limit);
}
@Override
<P_IN> Spliterator<T> opEvaluateParallelLazy(PipelineHelper<T> helper, Spliterator<P_IN> spliterator) {
long size = helper.exactOutputSizeIfKnown(spliterator);
if (size > 0 && spliterator.hasCharacteristics(Spliterator.SUBSIZED)) {
return new StreamSpliterators.SliceSpliterator.OfRef<>(
helper.wrapSpliterator(spliterator),
skip,
calcSliceFence(skip, limit));
} else if (!StreamOpFlag.ORDERED.isKnown(helper.getStreamAndOpFlags())) {
return unorderedSkipLimitSpliterator(
helper.wrapSpliterator(spliterator),
skip, limit, size);
}
else {
// @@@ OOMEs will occur for LongStream.range(0, Long.MAX_VALUE).filter(i -> true).limit(n)
// when n * parallelismLevel is sufficiently large.
// Need to adjust the target size of splitting for the
// SliceTask from say (size / k) to say min(size / k, 1 << 14)
// This will limit the size of the buffers created at the leaf nodes
// cancellation will be more aggressive cancelling later tasks
// if the target slice size has been reached from a given task,
// cancellation should also clear local results if any
return new SliceTask<>(this, helper, spliterator, Nodes.castingArray(), skip, limit).
invoke().spliterator();
}
}
@Override
<P_IN> Node<T> opEvaluateParallel(PipelineHelper<T> helper,
Spliterator<P_IN> spliterator,
IntFunction<T[]> generator) {
long size = helper.exactOutputSizeIfKnown(spliterator);
if (size > 0 && spliterator.hasCharacteristics(Spliterator.SUBSIZED)) {
// Because the pipeline is SIZED the slice spliterator
// can be created from the source, this requires matching
// to shape of the source, and is potentially more efficient
// than creating the slice spliterator from the pipeline
// wrapping spliterator
Spliterator<P_IN> s = sliceSpliterator(helper.getSourceShape(), spliterator, skip, limit);
return Nodes.collect(helper, s, true, generator);
} else if (!StreamOpFlag.ORDERED.isKnown(helper.getStreamAndOpFlags())) {
Spliterator<T> s = unorderedSkipLimitSpliterator(
helper.wrapSpliterator(spliterator),
skip, limit, size);
// Collect using this pipeline, which is empty and therefore
// can be used with the pipeline wrapping spliterator
// Note that we cannot create a slice spliterator from
// the source spliterator if the pipeline is not SIZED
return Nodes.collect(this, s, true, generator);
}
else {
return new SliceTask<>(this, helper, spliterator, generator, skip, limit).
invoke();
}
}
@Override
Sink<T> opWrapSink(int flags, Sink<T> sink) {
return new Sink.ChainedReference<T, T>(sink) {
long n = skip;
long m = limit >= 0 ? limit : Long.MAX_VALUE;
@Override
public void begin(long size) {
downstream.begin(calcSize(size, skip, m));
}
@Override
public void accept(T t) {
if (n == 0) {
if (m > 0) {
m--;
downstream.accept(t);
}
}
else {
n--;
}
}
@Override
public boolean cancellationRequested() {
return m == 0 || downstream.cancellationRequested();
}
};
}
};
}
/**
* Appends a "slice" operation to the provided IntStream. The slice
* operation may be may be skip-only, limit-only, or skip-and-limit.
*
* @param upstream An IntStream
* @param skip The number of elements to skip. Must be >= 0.
* @param limit The maximum size of the resulting stream, or -1 if no limit
* is to be imposed
*/
public static IntStream makeInt(AbstractPipeline<?, Integer, ?> upstream,
long skip, long limit) {
if (skip < 0)
throw new IllegalArgumentException("Skip must be non-negative: " + skip);
return new IntPipeline.StatefulOp<Integer>(upstream, StreamShape.INT_VALUE,
flags(limit)) {
Spliterator.OfInt unorderedSkipLimitSpliterator(
Spliterator.OfInt s, long skip, long limit, long sizeIfKnown) {
if (skip <= sizeIfKnown) {
// Use just the limit if the number of elements
// to skip is <= the known pipeline size
limit = limit >= 0 ? Math.min(limit, sizeIfKnown - skip) : sizeIfKnown - skip;
skip = 0;
}
return new StreamSpliterators.UnorderedSliceSpliterator.OfInt(s, skip, limit);
}
@Override
<P_IN> Spliterator<Integer> opEvaluateParallelLazy(PipelineHelper<Integer> helper,
Spliterator<P_IN> spliterator) {
long size = helper.exactOutputSizeIfKnown(spliterator);
if (size > 0 && spliterator.hasCharacteristics(Spliterator.SUBSIZED)) {
return new StreamSpliterators.SliceSpliterator.OfInt(
(Spliterator.OfInt) helper.wrapSpliterator(spliterator),
skip,
calcSliceFence(skip, limit));
} else if (!StreamOpFlag.ORDERED.isKnown(helper.getStreamAndOpFlags())) {
return unorderedSkipLimitSpliterator(
(Spliterator.OfInt) helper.wrapSpliterator(spliterator),
skip, limit, size);
}
else {
return new SliceTask<>(this, helper, spliterator, Integer[]::new, skip, limit).
invoke().spliterator();
}
}
@Override
<P_IN> Node<Integer> opEvaluateParallel(PipelineHelper<Integer> helper,
Spliterator<P_IN> spliterator,
IntFunction<Integer[]> generator) {
long size = helper.exactOutputSizeIfKnown(spliterator);
if (size > 0 && spliterator.hasCharacteristics(Spliterator.SUBSIZED)) {
// Because the pipeline is SIZED the slice spliterator
// can be created from the source, this requires matching
// to shape of the source, and is potentially more efficient
// than creating the slice spliterator from the pipeline
// wrapping spliterator
Spliterator<P_IN> s = sliceSpliterator(helper.getSourceShape(), spliterator, skip, limit);
return Nodes.collectInt(helper, s, true);
} else if (!StreamOpFlag.ORDERED.isKnown(helper.getStreamAndOpFlags())) {
Spliterator.OfInt s = unorderedSkipLimitSpliterator(
(Spliterator.OfInt) helper.wrapSpliterator(spliterator),
skip, limit, size);
// Collect using this pipeline, which is empty and therefore
// can be used with the pipeline wrapping spliterator
// Note that we cannot create a slice spliterator from
// the source spliterator if the pipeline is not SIZED
return Nodes.collectInt(this, s, true);
}
else {
return new SliceTask<>(this, helper, spliterator, generator, skip, limit).
invoke();
}
}
@Override
Sink<Integer> opWrapSink(int flags, Sink<Integer> sink) {
return new Sink.ChainedInt<Integer>(sink) {
long n = skip;
long m = limit >= 0 ? limit : Long.MAX_VALUE;
@Override
public void begin(long size) {
downstream.begin(calcSize(size, skip, m));
}
@Override
public void accept(int t) {
if (n == 0) {
if (m > 0) {
m--;
downstream.accept(t);
}
}
else {
n--;
}
}
@Override
public boolean cancellationRequested() {
return m == 0 || downstream.cancellationRequested();
}
};
}
};
}
/**
* Appends a "slice" operation to the provided LongStream. The slice
* operation may be may be skip-only, limit-only, or skip-and-limit.
*
* @param upstream A LongStream
* @param skip The number of elements to skip. Must be >= 0.
* @param limit The maximum size of the resulting stream, or -1 if no limit
* is to be imposed
*/
public static LongStream makeLong(AbstractPipeline<?, Long, ?> upstream,
long skip, long limit) {
if (skip < 0)
throw new IllegalArgumentException("Skip must be non-negative: " + skip);
return new LongPipeline.StatefulOp<Long>(upstream, StreamShape.LONG_VALUE,
flags(limit)) {
Spliterator.OfLong unorderedSkipLimitSpliterator(
Spliterator.OfLong s, long skip, long limit, long sizeIfKnown) {
if (skip <= sizeIfKnown) {
// Use just the limit if the number of elements
// to skip is <= the known pipeline size
limit = limit >= 0 ? Math.min(limit, sizeIfKnown - skip) : sizeIfKnown - skip;
skip = 0;
}
return new StreamSpliterators.UnorderedSliceSpliterator.OfLong(s, skip, limit);
}
@Override
<P_IN> Spliterator<Long> opEvaluateParallelLazy(PipelineHelper<Long> helper,
Spliterator<P_IN> spliterator) {
long size = helper.exactOutputSizeIfKnown(spliterator);
if (size > 0 && spliterator.hasCharacteristics(Spliterator.SUBSIZED)) {
return new StreamSpliterators.SliceSpliterator.OfLong(
(Spliterator.OfLong) helper.wrapSpliterator(spliterator),
skip,
calcSliceFence(skip, limit));
} else if (!StreamOpFlag.ORDERED.isKnown(helper.getStreamAndOpFlags())) {
return unorderedSkipLimitSpliterator(
(Spliterator.OfLong) helper.wrapSpliterator(spliterator),
skip, limit, size);
}
else {
return new SliceTask<>(this, helper, spliterator, Long[]::new, skip, limit).
invoke().spliterator();
}
}
@Override
<P_IN> Node<Long> opEvaluateParallel(PipelineHelper<Long> helper,
Spliterator<P_IN> spliterator,
IntFunction<Long[]> generator) {
long size = helper.exactOutputSizeIfKnown(spliterator);
if (size > 0 && spliterator.hasCharacteristics(Spliterator.SUBSIZED)) {
// Because the pipeline is SIZED the slice spliterator
// can be created from the source, this requires matching
// to shape of the source, and is potentially more efficient
// than creating the slice spliterator from the pipeline
// wrapping spliterator
Spliterator<P_IN> s = sliceSpliterator(helper.getSourceShape(), spliterator, skip, limit);
return Nodes.collectLong(helper, s, true);
} else if (!StreamOpFlag.ORDERED.isKnown(helper.getStreamAndOpFlags())) {
Spliterator.OfLong s = unorderedSkipLimitSpliterator(
(Spliterator.OfLong) helper.wrapSpliterator(spliterator),
skip, limit, size);
// Collect using this pipeline, which is empty and therefore
// can be used with the pipeline wrapping spliterator
// Note that we cannot create a slice spliterator from
// the source spliterator if the pipeline is not SIZED
return Nodes.collectLong(this, s, true);
}
else {
return new SliceTask<>(this, helper, spliterator, generator, skip, limit).
invoke();
}
}
@Override
Sink<Long> opWrapSink(int flags, Sink<Long> sink) {
return new Sink.ChainedLong<Long>(sink) {
long n = skip;
long m = limit >= 0 ? limit : Long.MAX_VALUE;
@Override
public void begin(long size) {
downstream.begin(calcSize(size, skip, m));
}
@Override
public void accept(long t) {
if (n == 0) {
if (m > 0) {
m--;
downstream.accept(t);
}
}
else {
n--;
}
}
@Override
public boolean cancellationRequested() {
return m == 0 || downstream.cancellationRequested();
}
};
}
};
}
/**
* Appends a "slice" operation to the provided DoubleStream. The slice
* operation may be may be skip-only, limit-only, or skip-and-limit.
*
* @param upstream A DoubleStream
* @param skip The number of elements to skip. Must be >= 0.
* @param limit The maximum size of the resulting stream, or -1 if no limit
* is to be imposed
*/
public static DoubleStream makeDouble(AbstractPipeline<?, Double, ?> upstream,
long skip, long limit) {
if (skip < 0)
throw new IllegalArgumentException("Skip must be non-negative: " + skip);
return new DoublePipeline.StatefulOp<Double>(upstream, StreamShape.DOUBLE_VALUE,
flags(limit)) {
Spliterator.OfDouble unorderedSkipLimitSpliterator(
Spliterator.OfDouble s, long skip, long limit, long sizeIfKnown) {
if (skip <= sizeIfKnown) {
// Use just the limit if the number of elements
// to skip is <= the known pipeline size
limit = limit >= 0 ? Math.min(limit, sizeIfKnown - skip) : sizeIfKnown - skip;
skip = 0;
}
return new StreamSpliterators.UnorderedSliceSpliterator.OfDouble(s, skip, limit);
}
@Override
<P_IN> Spliterator<Double> opEvaluateParallelLazy(PipelineHelper<Double> helper,
Spliterator<P_IN> spliterator) {
long size = helper.exactOutputSizeIfKnown(spliterator);
if (size > 0 && spliterator.hasCharacteristics(Spliterator.SUBSIZED)) {
return new StreamSpliterators.SliceSpliterator.OfDouble(
(Spliterator.OfDouble) helper.wrapSpliterator(spliterator),
skip,
calcSliceFence(skip, limit));
} else if (!StreamOpFlag.ORDERED.isKnown(helper.getStreamAndOpFlags())) {
return unorderedSkipLimitSpliterator(
(Spliterator.OfDouble) helper.wrapSpliterator(spliterator),
skip, limit, size);
}
else {
return new SliceTask<>(this, helper, spliterator, Double[]::new, skip, limit).
invoke().spliterator();
}
}
@Override
<P_IN> Node<Double> opEvaluateParallel(PipelineHelper<Double> helper,
Spliterator<P_IN> spliterator,
IntFunction<Double[]> generator) {
long size = helper.exactOutputSizeIfKnown(spliterator);
if (size > 0 && spliterator.hasCharacteristics(Spliterator.SUBSIZED)) {
// Because the pipeline is SIZED the slice spliterator
// can be created from the source, this requires matching
// to shape of the source, and is potentially more efficient
// than creating the slice spliterator from the pipeline
// wrapping spliterator
Spliterator<P_IN> s = sliceSpliterator(helper.getSourceShape(), spliterator, skip, limit);
return Nodes.collectDouble(helper, s, true);
} else if (!StreamOpFlag.ORDERED.isKnown(helper.getStreamAndOpFlags())) {
Spliterator.OfDouble s = unorderedSkipLimitSpliterator(
(Spliterator.OfDouble) helper.wrapSpliterator(spliterator),
skip, limit, size);
// Collect using this pipeline, which is empty and therefore
// can be used with the pipeline wrapping spliterator
// Note that we cannot create a slice spliterator from
// the source spliterator if the pipeline is not SIZED
return Nodes.collectDouble(this, s, true);
}
else {
return new SliceTask<>(this, helper, spliterator, generator, skip, limit).
invoke();
}
}
@Override
Sink<Double> opWrapSink(int flags, Sink<Double> sink) {
return new Sink.ChainedDouble<Double>(sink) {
long n = skip;
long m = limit >= 0 ? limit : Long.MAX_VALUE;
@Override
public void begin(long size) {
downstream.begin(calcSize(size, skip, m));
}
@Override
public void accept(double t) {
if (n == 0) {
if (m > 0) {
m--;
downstream.accept(t);
}
}
else {
n--;
}
}
@Override
public boolean cancellationRequested() {
return m == 0 || downstream.cancellationRequested();
}
};
}
};
}
private static int flags(long limit) {
return StreamOpFlag.NOT_SIZED | ((limit != -1) ? StreamOpFlag.IS_SHORT_CIRCUIT : 0);
}
/**
* {@code ForkJoinTask} implementing slice computation.
*
* @param <P_IN> Input element type to the stream pipeline
* @param <P_OUT> Output element type from the stream pipeline
*/
@SuppressWarnings("serial")
private static final class SliceTask<P_IN, P_OUT>
extends AbstractShortCircuitTask<P_IN, P_OUT, Node<P_OUT>, SliceTask<P_IN, P_OUT>> {
private final AbstractPipeline<P_OUT, P_OUT, ?> op;
private final IntFunction<P_OUT[]> generator;
private final long targetOffset, targetSize;
private long thisNodeSize;
private volatile boolean completed;
SliceTask(AbstractPipeline<P_OUT, P_OUT, ?> op,
PipelineHelper<P_OUT> helper,
Spliterator<P_IN> spliterator,
IntFunction<P_OUT[]> generator,
long offset, long size) {
super(helper, spliterator);
this.op = op;
this.generator = generator;
this.targetOffset = offset;
this.targetSize = size;
}
SliceTask(SliceTask<P_IN, P_OUT> parent, Spliterator<P_IN> spliterator) {
super(parent, spliterator);
this.op = parent.op;
this.generator = parent.generator;
this.targetOffset = parent.targetOffset;
this.targetSize = parent.targetSize;
}
@Override
protected SliceTask<P_IN, P_OUT> makeChild(Spliterator<P_IN> spliterator) {
return new SliceTask<>(this, spliterator);
}
@Override
protected final Node<P_OUT> getEmptyResult() {
return Nodes.emptyNode(op.getOutputShape());
}
@Override
protected final Node<P_OUT> doLeaf() {
if (isRoot()) {
long sizeIfKnown = StreamOpFlag.SIZED.isPreserved(op.sourceOrOpFlags)
? op.exactOutputSizeIfKnown(spliterator)
: -1;
final Node.Builder<P_OUT> nb = op.makeNodeBuilder(sizeIfKnown, generator);
Sink<P_OUT> opSink = op.opWrapSink(helper.getStreamAndOpFlags(), nb);
helper.copyIntoWithCancel(helper.wrapSink(opSink), spliterator);
// There is no need to truncate since the op performs the
// skipping and limiting of elements
return nb.build();
}
else {
final Node.Builder<P_OUT> nb = op.makeNodeBuilder(-1, generator);
if (targetOffset == 0) { // limit only
Sink<P_OUT> opSink = op.opWrapSink(helper.getStreamAndOpFlags(), nb);
helper.copyIntoWithCancel(helper.wrapSink(opSink), spliterator);
}
else {
helper.wrapAndCopyInto(nb, spliterator);
}
Node<P_OUT> node = nb.build();
thisNodeSize = node.count();
completed = true;
spliterator = null;
return node;
}
}
@Override
public final void onCompletion(CountedCompleter<?> caller) {
if (!isLeaf()) {
Node<P_OUT> result;
thisNodeSize = leftChild.thisNodeSize + rightChild.thisNodeSize;
if (canceled) {
thisNodeSize = 0;
result = getEmptyResult();
}
else if (thisNodeSize == 0)
result = getEmptyResult();
else if (leftChild.thisNodeSize == 0)
result = rightChild.getLocalResult();
else {
result = Nodes.conc(op.getOutputShape(),
leftChild.getLocalResult(), rightChild.getLocalResult());
}
setLocalResult(isRoot() ? doTruncate(result) : result);
completed = true;
}
if (targetSize >= 0
&& !isRoot()
&& isLeftCompleted(targetOffset + targetSize))
cancelLaterNodes();
super.onCompletion(caller);
}
@Override
protected void cancel() {
super.cancel();
if (completed)
setLocalResult(getEmptyResult());
}
private Node<P_OUT> doTruncate(Node<P_OUT> input) {
long to = targetSize >= 0 ? Math.min(input.count(), targetOffset + targetSize) : thisNodeSize;
return input.truncate(targetOffset, to, generator);
}
/**
* Determine if the number of completed elements in this node and nodes
* to the left of this node is greater than or equal to the target size.
*
* @param target the target size
* @return true if the number of elements is greater than or equal to
* the target size, otherwise false.
*/
private boolean isLeftCompleted(long target) {
long size = completed ? thisNodeSize : completedSize(target);
if (size >= target)
return true;
for (SliceTask<P_IN, P_OUT> parent = getParent(), node = this;
parent != null;
node = parent, parent = parent.getParent()) {
if (node == parent.rightChild) {
SliceTask<P_IN, P_OUT> left = parent.leftChild;
if (left != null) {
size += left.completedSize(target);
if (size >= target)
return true;
}
}
}
return size >= target;
}
/**
* Compute the number of completed elements in this node.
* <p>
* Computation terminates if all nodes have been processed or the
* number of completed elements is greater than or equal to the target
* size.
*
* @param target the target size
* @return the number of completed elements
*/
private long completedSize(long target) {
if (completed)
return thisNodeSize;
else {
SliceTask<P_IN, P_OUT> left = leftChild;
SliceTask<P_IN, P_OUT> right = rightChild;
if (left == null || right == null) {
// must be completed
return thisNodeSize;
}
else {
long leftSize = left.completedSize(target);
return (leftSize >= target) ? leftSize : leftSize + right.completedSize(target);
}
}
}
}
}

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@ -0,0 +1,701 @@
/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Comparator;
import java.util.Objects;
import java.util.Spliterator;
import java.util.function.IntFunction;
/**
* Factory methods for transforming streams into sorted streams.
*
* @since 1.8
*/
final class SortedOps {
private SortedOps() { }
/**
* Appends a "sorted" operation to the provided stream.
*
* @param <T> the type of both input and output elements
* @param upstream a reference stream with element type T
*/
static <T> Stream<T> makeRef(AbstractPipeline<?, T, ?> upstream) {
return new OfRef<>(upstream);
}
/**
* Appends a "sorted" operation to the provided stream.
*
* @param <T> the type of both input and output elements
* @param upstream a reference stream with element type T
* @param comparator the comparator to order elements by
*/
static <T> Stream<T> makeRef(AbstractPipeline<?, T, ?> upstream,
Comparator<? super T> comparator) {
return new OfRef<>(upstream, comparator);
}
/**
* Appends a "sorted" operation to the provided stream.
*
* @param <T> the type of both input and output elements
* @param upstream a reference stream with element type T
*/
static <T> IntStream makeInt(AbstractPipeline<?, Integer, ?> upstream) {
return new OfInt(upstream);
}
/**
* Appends a "sorted" operation to the provided stream.
*
* @param <T> the type of both input and output elements
* @param upstream a reference stream with element type T
*/
static <T> LongStream makeLong(AbstractPipeline<?, Long, ?> upstream) {
return new OfLong(upstream);
}
/**
* Appends a "sorted" operation to the provided stream.
*
* @param <T> the type of both input and output elements
* @param upstream a reference stream with element type T
*/
static <T> DoubleStream makeDouble(AbstractPipeline<?, Double, ?> upstream) {
return new OfDouble(upstream);
}
/**
* Specialized subtype for sorting reference streams
*/
private static final class OfRef<T> extends ReferencePipeline.StatefulOp<T, T> {
/**
* Comparator used for sorting
*/
private final boolean isNaturalSort;
private final Comparator<? super T> comparator;
/**
* Sort using natural order of {@literal <T>} which must be
* {@code Comparable}.
*/
OfRef(AbstractPipeline<?, T, ?> upstream) {
super(upstream, StreamShape.REFERENCE,
StreamOpFlag.IS_ORDERED | StreamOpFlag.IS_SORTED);
this.isNaturalSort = true;
// Will throw CCE when we try to sort if T is not Comparable
@SuppressWarnings("unchecked")
Comparator<? super T> comp = (Comparator<? super T>) Comparator.naturalOrder();
this.comparator = comp;
}
/**
* Sort using the provided comparator.
*
* @param comparator The comparator to be used to evaluate ordering.
*/
OfRef(AbstractPipeline<?, T, ?> upstream, Comparator<? super T> comparator) {
super(upstream, StreamShape.REFERENCE,
StreamOpFlag.IS_ORDERED | StreamOpFlag.NOT_SORTED);
this.isNaturalSort = false;
this.comparator = Objects.requireNonNull(comparator);
}
@Override
public Sink<T> opWrapSink(int flags, Sink<T> sink) {
Objects.requireNonNull(sink);
// If the input is already naturally sorted and this operation
// also naturally sorted then this is a no-op
if (StreamOpFlag.SORTED.isKnown(flags) && isNaturalSort)
return sink;
else if (StreamOpFlag.SIZED.isKnown(flags))
return new SizedRefSortingSink<>(sink, comparator);
else
return new RefSortingSink<>(sink, comparator);
}
@Override
public <P_IN> Node<T> opEvaluateParallel(PipelineHelper<T> helper,
Spliterator<P_IN> spliterator,
IntFunction<T[]> generator) {
// If the input is already naturally sorted and this operation
// naturally sorts then collect the output
if (StreamOpFlag.SORTED.isKnown(helper.getStreamAndOpFlags()) && isNaturalSort) {
return helper.evaluate(spliterator, false, generator);
}
else {
// @@@ Weak two-pass parallel implementation; parallel collect, parallel sort
T[] flattenedData = helper.evaluate(spliterator, true, generator).asArray(generator);
Arrays.parallelSort(flattenedData, comparator);
return Nodes.node(flattenedData);
}
}
}
/**
* Specialized subtype for sorting int streams.
*/
private static final class OfInt extends IntPipeline.StatefulOp<Integer> {
OfInt(AbstractPipeline<?, Integer, ?> upstream) {
super(upstream, StreamShape.INT_VALUE,
StreamOpFlag.IS_ORDERED | StreamOpFlag.IS_SORTED);
}
@Override
public Sink<Integer> opWrapSink(int flags, Sink<Integer> sink) {
Objects.requireNonNull(sink);
if (StreamOpFlag.SORTED.isKnown(flags))
return sink;
else if (StreamOpFlag.SIZED.isKnown(flags))
return new SizedIntSortingSink(sink);
else
return new IntSortingSink(sink);
}
@Override
public <P_IN> Node<Integer> opEvaluateParallel(PipelineHelper<Integer> helper,
Spliterator<P_IN> spliterator,
IntFunction<Integer[]> generator) {
if (StreamOpFlag.SORTED.isKnown(helper.getStreamAndOpFlags())) {
return helper.evaluate(spliterator, false, generator);
}
else {
Node.OfInt n = (Node.OfInt) helper.evaluate(spliterator, true, generator);
int[] content = n.asPrimitiveArray();
Arrays.parallelSort(content);
return Nodes.node(content);
}
}
}
/**
* Specialized subtype for sorting long streams.
*/
private static final class OfLong extends LongPipeline.StatefulOp<Long> {
OfLong(AbstractPipeline<?, Long, ?> upstream) {
super(upstream, StreamShape.LONG_VALUE,
StreamOpFlag.IS_ORDERED | StreamOpFlag.IS_SORTED);
}
@Override
public Sink<Long> opWrapSink(int flags, Sink<Long> sink) {
Objects.requireNonNull(sink);
if (StreamOpFlag.SORTED.isKnown(flags))
return sink;
else if (StreamOpFlag.SIZED.isKnown(flags))
return new SizedLongSortingSink(sink);
else
return new LongSortingSink(sink);
}
@Override
public <P_IN> Node<Long> opEvaluateParallel(PipelineHelper<Long> helper,
Spliterator<P_IN> spliterator,
IntFunction<Long[]> generator) {
if (StreamOpFlag.SORTED.isKnown(helper.getStreamAndOpFlags())) {
return helper.evaluate(spliterator, false, generator);
}
else {
Node.OfLong n = (Node.OfLong) helper.evaluate(spliterator, true, generator);
long[] content = n.asPrimitiveArray();
Arrays.parallelSort(content);
return Nodes.node(content);
}
}
}
/**
* Specialized subtype for sorting double streams.
*/
private static final class OfDouble extends DoublePipeline.StatefulOp<Double> {
OfDouble(AbstractPipeline<?, Double, ?> upstream) {
super(upstream, StreamShape.DOUBLE_VALUE,
StreamOpFlag.IS_ORDERED | StreamOpFlag.IS_SORTED);
}
@Override
public Sink<Double> opWrapSink(int flags, Sink<Double> sink) {
Objects.requireNonNull(sink);
if (StreamOpFlag.SORTED.isKnown(flags))
return sink;
else if (StreamOpFlag.SIZED.isKnown(flags))
return new SizedDoubleSortingSink(sink);
else
return new DoubleSortingSink(sink);
}
@Override
public <P_IN> Node<Double> opEvaluateParallel(PipelineHelper<Double> helper,
Spliterator<P_IN> spliterator,
IntFunction<Double[]> generator) {
if (StreamOpFlag.SORTED.isKnown(helper.getStreamAndOpFlags())) {
return helper.evaluate(spliterator, false, generator);
}
else {
Node.OfDouble n = (Node.OfDouble) helper.evaluate(spliterator, true, generator);
double[] content = n.asPrimitiveArray();
Arrays.parallelSort(content);
return Nodes.node(content);
}
}
}
/**
* Abstract {@link Sink} for implementing sort on reference streams.
*
* <p>
* Note: documentation below applies to reference and all primitive sinks.
* <p>
* Sorting sinks first accept all elements, buffering then into an array
* or a re-sizable data structure, if the size of the pipeline is known or
* unknown respectively. At the end of the sink protocol those elements are
* sorted and then pushed downstream.
* This class records if {@link #cancellationRequested} is called. If so it
* can be inferred that the source pushing source elements into the pipeline
* knows that the pipeline is short-circuiting. In such cases sub-classes
* pushing elements downstream will preserve the short-circuiting protocol
* by calling {@code downstream.cancellationRequested()} and checking the
* result is {@code false} before an element is pushed.
* <p>
* Note that the above behaviour is an optimization for sorting with
* sequential streams. It is not an error that more elements, than strictly
* required to produce a result, may flow through the pipeline. This can
* occur, in general (not restricted to just sorting), for short-circuiting
* parallel pipelines.
*/
private abstract static class AbstractRefSortingSink<T> extends Sink.ChainedReference<T, T> {
protected final Comparator<? super T> comparator;
// @@@ could be a lazy final value, if/when support is added
protected boolean cancellationWasRequested;
AbstractRefSortingSink(Sink<? super T> downstream, Comparator<? super T> comparator) {
super(downstream);
this.comparator = comparator;
}
/**
* Records is cancellation is requested so short-circuiting behaviour
* can be preserved when the sorted elements are pushed downstream.
*
* @return false, as this sink never short-circuits.
*/
@Override
public final boolean cancellationRequested() {
cancellationWasRequested = true;
return false;
}
}
/**
* {@link Sink} for implementing sort on SIZED reference streams.
*/
private static final class SizedRefSortingSink<T> extends AbstractRefSortingSink<T> {
private T[] array;
private int offset;
SizedRefSortingSink(Sink<? super T> sink, Comparator<? super T> comparator) {
super(sink, comparator);
}
@Override
@SuppressWarnings("unchecked")
public void begin(long size) {
if (size >= Nodes.MAX_ARRAY_SIZE)
throw new IllegalArgumentException(Nodes.BAD_SIZE);
array = (T[]) new Object[(int) size];
}
@Override
public void end() {
Arrays.sort(array, 0, offset, comparator);
downstream.begin(offset);
if (!cancellationWasRequested) {
for (int i = 0; i < offset; i++)
downstream.accept(array[i]);
}
else {
for (int i = 0; i < offset && !downstream.cancellationRequested(); i++)
downstream.accept(array[i]);
}
downstream.end();
array = null;
}
@Override
public void accept(T t) {
array[offset++] = t;
}
}
/**
* {@link Sink} for implementing sort on reference streams.
*/
private static final class RefSortingSink<T> extends AbstractRefSortingSink<T> {
private ArrayList<T> list;
RefSortingSink(Sink<? super T> sink, Comparator<? super T> comparator) {
super(sink, comparator);
}
@Override
public void begin(long size) {
if (size >= Nodes.MAX_ARRAY_SIZE)
throw new IllegalArgumentException(Nodes.BAD_SIZE);
list = (size >= 0) ? new ArrayList<>((int) size) : new ArrayList<>();
}
@Override
public void end() {
list.sort(comparator);
downstream.begin(list.size());
if (!cancellationWasRequested) {
list.forEach(downstream::accept);
}
else {
for (T t : list) {
if (downstream.cancellationRequested()) break;
downstream.accept(t);
}
}
downstream.end();
list = null;
}
@Override
public void accept(T t) {
list.add(t);
}
}
/**
* Abstract {@link Sink} for implementing sort on int streams.
*/
private abstract static class AbstractIntSortingSink extends Sink.ChainedInt<Integer> {
protected boolean cancellationWasRequested;
AbstractIntSortingSink(Sink<? super Integer> downstream) {
super(downstream);
}
@Override
public final boolean cancellationRequested() {
cancellationWasRequested = true;
return false;
}
}
/**
* {@link Sink} for implementing sort on SIZED int streams.
*/
private static final class SizedIntSortingSink extends AbstractIntSortingSink {
private int[] array;
private int offset;
SizedIntSortingSink(Sink<? super Integer> downstream) {
super(downstream);
}
@Override
public void begin(long size) {
if (size >= Nodes.MAX_ARRAY_SIZE)
throw new IllegalArgumentException(Nodes.BAD_SIZE);
array = new int[(int) size];
}
@Override
public void end() {
Arrays.sort(array, 0, offset);
downstream.begin(offset);
if (!cancellationWasRequested) {
for (int i = 0; i < offset; i++)
downstream.accept(array[i]);
}
else {
for (int i = 0; i < offset && !downstream.cancellationRequested(); i++)
downstream.accept(array[i]);
}
downstream.end();
array = null;
}
@Override
public void accept(int t) {
array[offset++] = t;
}
}
/**
* {@link Sink} for implementing sort on int streams.
*/
private static final class IntSortingSink extends AbstractIntSortingSink {
private SpinedBuffer.OfInt b;
IntSortingSink(Sink<? super Integer> sink) {
super(sink);
}
@Override
public void begin(long size) {
if (size >= Nodes.MAX_ARRAY_SIZE)
throw new IllegalArgumentException(Nodes.BAD_SIZE);
b = (size > 0) ? new SpinedBuffer.OfInt((int) size) : new SpinedBuffer.OfInt();
}
@Override
public void end() {
int[] ints = b.asPrimitiveArray();
Arrays.sort(ints);
downstream.begin(ints.length);
if (!cancellationWasRequested) {
for (int anInt : ints)
downstream.accept(anInt);
}
else {
for (int anInt : ints) {
if (downstream.cancellationRequested()) break;
downstream.accept(anInt);
}
}
downstream.end();
}
@Override
public void accept(int t) {
b.accept(t);
}
}
/**
* Abstract {@link Sink} for implementing sort on long streams.
*/
private abstract static class AbstractLongSortingSink extends Sink.ChainedLong<Long> {
protected boolean cancellationWasRequested;
AbstractLongSortingSink(Sink<? super Long> downstream) {
super(downstream);
}
@Override
public final boolean cancellationRequested() {
cancellationWasRequested = true;
return false;
}
}
/**
* {@link Sink} for implementing sort on SIZED long streams.
*/
private static final class SizedLongSortingSink extends AbstractLongSortingSink {
private long[] array;
private int offset;
SizedLongSortingSink(Sink<? super Long> downstream) {
super(downstream);
}
@Override
public void begin(long size) {
if (size >= Nodes.MAX_ARRAY_SIZE)
throw new IllegalArgumentException(Nodes.BAD_SIZE);
array = new long[(int) size];
}
@Override
public void end() {
Arrays.sort(array, 0, offset);
downstream.begin(offset);
if (!cancellationWasRequested) {
for (int i = 0; i < offset; i++)
downstream.accept(array[i]);
}
else {
for (int i = 0; i < offset && !downstream.cancellationRequested(); i++)
downstream.accept(array[i]);
}
downstream.end();
array = null;
}
@Override
public void accept(long t) {
array[offset++] = t;
}
}
/**
* {@link Sink} for implementing sort on long streams.
*/
private static final class LongSortingSink extends AbstractLongSortingSink {
private SpinedBuffer.OfLong b;
LongSortingSink(Sink<? super Long> sink) {
super(sink);
}
@Override
public void begin(long size) {
if (size >= Nodes.MAX_ARRAY_SIZE)
throw new IllegalArgumentException(Nodes.BAD_SIZE);
b = (size > 0) ? new SpinedBuffer.OfLong((int) size) : new SpinedBuffer.OfLong();
}
@Override
public void end() {
long[] longs = b.asPrimitiveArray();
Arrays.sort(longs);
downstream.begin(longs.length);
if (!cancellationWasRequested) {
for (long aLong : longs)
downstream.accept(aLong);
}
else {
for (long aLong : longs) {
if (downstream.cancellationRequested()) break;
downstream.accept(aLong);
}
}
downstream.end();
}
@Override
public void accept(long t) {
b.accept(t);
}
}
/**
* Abstract {@link Sink} for implementing sort on long streams.
*/
private abstract static class AbstractDoubleSortingSink extends Sink.ChainedDouble<Double> {
protected boolean cancellationWasRequested;
AbstractDoubleSortingSink(Sink<? super Double> downstream) {
super(downstream);
}
@Override
public final boolean cancellationRequested() {
cancellationWasRequested = true;
return false;
}
}
/**
* {@link Sink} for implementing sort on SIZED double streams.
*/
private static final class SizedDoubleSortingSink extends AbstractDoubleSortingSink {
private double[] array;
private int offset;
SizedDoubleSortingSink(Sink<? super Double> downstream) {
super(downstream);
}
@Override
public void begin(long size) {
if (size >= Nodes.MAX_ARRAY_SIZE)
throw new IllegalArgumentException(Nodes.BAD_SIZE);
array = new double[(int) size];
}
@Override
public void end() {
Arrays.sort(array, 0, offset);
downstream.begin(offset);
if (!cancellationWasRequested) {
for (int i = 0; i < offset; i++)
downstream.accept(array[i]);
}
else {
for (int i = 0; i < offset && !downstream.cancellationRequested(); i++)
downstream.accept(array[i]);
}
downstream.end();
array = null;
}
@Override
public void accept(double t) {
array[offset++] = t;
}
}
/**
* {@link Sink} for implementing sort on double streams.
*/
private static final class DoubleSortingSink extends AbstractDoubleSortingSink {
private SpinedBuffer.OfDouble b;
DoubleSortingSink(Sink<? super Double> sink) {
super(sink);
}
@Override
public void begin(long size) {
if (size >= Nodes.MAX_ARRAY_SIZE)
throw new IllegalArgumentException(Nodes.BAD_SIZE);
b = (size > 0) ? new SpinedBuffer.OfDouble((int) size) : new SpinedBuffer.OfDouble();
}
@Override
public void end() {
double[] doubles = b.asPrimitiveArray();
Arrays.sort(doubles);
downstream.begin(doubles.length);
if (!cancellationWasRequested) {
for (double aDouble : doubles)
downstream.accept(aDouble);
}
else {
for (double aDouble : doubles) {
if (downstream.cancellationRequested()) break;
downstream.accept(aDouble);
}
}
downstream.end();
}
@Override
public void accept(double t) {
b.accept(t);
}
}
}

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/*
* Copyright (c) 2012, 2017, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.EnumMap;
import java.util.Map;
import java.util.Spliterator;
/**
* Flags corresponding to characteristics of streams and operations. Flags are
* utilized by the stream framework to control, specialize or optimize
* computation.
*
* <p>
* Stream flags may be used to describe characteristics of several different
* entities associated with streams: stream sources, intermediate operations,
* and terminal operations. Not all stream flags are meaningful for all
* entities; the following table summarizes which flags are meaningful in what
* contexts:
*
* <div>
* <table class="borderless">
* <caption>Type Characteristics</caption>
* <thead class="tableSubHeadingColor">
* <tr>
* <th colspan="2">&nbsp;</th>
* <th>{@code DISTINCT}</th>
* <th>{@code SORTED}</th>
* <th>{@code ORDERED}</th>
* <th>{@code SIZED}</th>
* <th>{@code SHORT_CIRCUIT}</th>
* </tr>
* </thead>
* <tbody>
* <tr>
* <th colspan="2" class="tableSubHeadingColor">Stream source</th>
* <td>Y</td>
* <td>Y</td>
* <td>Y</td>
* <td>Y</td>
* <td>N</td>
* </tr>
* <tr>
* <th colspan="2" class="tableSubHeadingColor">Intermediate operation</th>
* <td>PCI</td>
* <td>PCI</td>
* <td>PCI</td>
* <td>PC</td>
* <td>PI</td>
* </tr>
* <tr>
* <th colspan="2" class="tableSubHeadingColor">Terminal operation</th>
* <td>N</td>
* <td>N</td>
* <td>PC</td>
* <td>N</td>
* <td>PI</td>
* </tr>
* </tbody>
* <tfoot>
* <tr>
* <th class="tableSubHeadingColor" colspan="2">Legend</th>
* <th colspan="6" rowspan="7">&nbsp;</th>
* </tr>
* <tr>
* <th class="tableSubHeadingColor">Flag</th>
* <th class="tableSubHeadingColor">Meaning</th>
* <th colspan="6"></th>
* </tr>
* <tr><td>Y</td><td>Allowed</td></tr>
* <tr><td>N</td><td>Invalid</td></tr>
* <tr><td>P</td><td>Preserves</td></tr>
* <tr><td>C</td><td>Clears</td></tr>
* <tr><td>I</td><td>Injects</td></tr>
* </tfoot>
* </table>
* </div>
*
* <p>In the above table, "PCI" means "may preserve, clear, or inject"; "PC"
* means "may preserve or clear", "PI" means "may preserve or inject", and "N"
* means "not valid".
*
* <p>Stream flags are represented by unioned bit sets, so that a single word
* may describe all the characteristics of a given stream entity, and that, for
* example, the flags for a stream source can be efficiently combined with the
* flags for later operations on that stream.
*
* <p>The bit masks {@link #STREAM_MASK}, {@link #OP_MASK}, and
* {@link #TERMINAL_OP_MASK} can be ANDed with a bit set of stream flags to
* produce a mask containing only the valid flags for that entity type.
*
* <p>When describing a stream source, one only need describe what
* characteristics that stream has; when describing a stream operation, one need
* describe whether the operation preserves, injects, or clears that
* characteristic. Accordingly, two bits are used for each flag, so as to allow
* representing not only the presence of a characteristic, but how an
* operation modifies that characteristic. There are two common forms in which
* flag bits are combined into an {@code int} bit set. <em>Stream flags</em>
* are a unioned bit set constructed by ORing the enum characteristic values of
* {@link #set()} (or, more commonly, ORing the corresponding static named
* constants prefixed with {@code IS_}). <em>Operation flags</em> are a unioned
* bit set constructed by ORing the enum characteristic values of {@link #set()}
* or {@link #clear()} (to inject, or clear, respectively, the corresponding
* flag), or more commonly ORing the corresponding named constants prefixed with
* {@code IS_} or {@code NOT_}. Flags that are not marked with {@code IS_} or
* {@code NOT_} are implicitly treated as preserved. Care must be taken when
* combining bitsets that the correct combining operations are applied in the
* correct order.
*
* <p>
* With the exception of {@link #SHORT_CIRCUIT}, stream characteristics can be
* derived from the equivalent {@link java.util.Spliterator} characteristics:
* {@link java.util.Spliterator#DISTINCT}, {@link java.util.Spliterator#SORTED},
* {@link java.util.Spliterator#ORDERED}, and
* {@link java.util.Spliterator#SIZED}. A spliterator characteristics bit set
* can be converted to stream flags using the method
* {@link #fromCharacteristics(java.util.Spliterator)} and converted back using
* {@link #toCharacteristics(int)}. (The bit set
* {@link #SPLITERATOR_CHARACTERISTICS_MASK} is used to AND with a bit set to
* produce a valid spliterator characteristics bit set that can be converted to
* stream flags.)
*
* <p>
* The source of a stream encapsulates a spliterator. The characteristics of
* that source spliterator when transformed to stream flags will be a proper
* subset of stream flags of that stream.
* For example:
* <pre> {@code
* Spliterator s = ...;
* Stream stream = Streams.stream(s);
* flagsFromSplitr = fromCharacteristics(s.characteristics());
* assert(flagsFromSplitr & stream.getStreamFlags() == flagsFromSplitr);
* }</pre>
*
* <p>
* An intermediate operation, performed on an input stream to create a new
* output stream, may preserve, clear or inject stream or operation
* characteristics. Similarly, a terminal operation, performed on an input
* stream to produce an output result may preserve, clear or inject stream or
* operation characteristics. Preservation means that if that characteristic
* is present on the input, then it is also present on the output. Clearing
* means that the characteristic is not present on the output regardless of the
* input. Injection means that the characteristic is present on the output
* regardless of the input. If a characteristic is not cleared or injected then
* it is implicitly preserved.
*
* <p>
* A pipeline consists of a stream source encapsulating a spliterator, one or
* more intermediate operations, and finally a terminal operation that produces
* a result. At each stage of the pipeline, a combined stream and operation
* flags can be calculated, using {@link #combineOpFlags(int, int)}. Such flags
* ensure that preservation, clearing and injecting information is retained at
* each stage.
*
* The combined stream and operation flags for the source stage of the pipeline
* is calculated as follows:
* <pre> {@code
* int flagsForSourceStage = combineOpFlags(sourceFlags, INITIAL_OPS_VALUE);
* }</pre>
*
* The combined stream and operation flags of each subsequent intermediate
* operation stage in the pipeline is calculated as follows:
* <pre> {@code
* int flagsForThisStage = combineOpFlags(flagsForPreviousStage, thisOpFlags);
* }</pre>
*
* Finally the flags output from the last intermediate operation of the pipeline
* are combined with the operation flags of the terminal operation to produce
* the flags output from the pipeline.
*
* <p>Those flags can then be used to apply optimizations. For example, if
* {@code SIZED.isKnown(flags)} returns true then the stream size remains
* constant throughout the pipeline, this information can be utilized to
* pre-allocate data structures and combined with
* {@link java.util.Spliterator#SUBSIZED} that information can be utilized to
* perform concurrent in-place updates into a shared array.
*
* For specific details see the {@link AbstractPipeline} constructors.
*
* @since 1.8
*/
enum StreamOpFlag {
/*
* Each characteristic takes up 2 bits in a bit set to accommodate
* preserving, clearing and setting/injecting information.
*
* This applies to stream flags, intermediate/terminal operation flags, and
* combined stream and operation flags. Even though the former only requires
* 1 bit of information per characteristic, is it more efficient when
* combining flags to align set and inject bits.
*
* Characteristics belong to certain types, see the Type enum. Bit masks for
* the types are constructed as per the following table:
*
* DISTINCT SORTED ORDERED SIZED SHORT_CIRCUIT
* SPLITERATOR 01 01 01 01 00
* STREAM 01 01 01 01 00
* OP 11 11 11 10 01
* TERMINAL_OP 00 00 10 00 01
* UPSTREAM_TERMINAL_OP 00 00 10 00 00
*
* 01 = set/inject
* 10 = clear
* 11 = preserve
*
* Construction of the columns is performed using a simple builder for
* non-zero values.
*/
// The following flags correspond to characteristics on Spliterator
// and the values MUST be equal.
//
/**
* Characteristic value signifying that, for each pair of
* encountered elements in a stream {@code x, y}, {@code !x.equals(y)}.
* <p>
* A stream may have this value or an intermediate operation can preserve,
* clear or inject this value.
*/
// 0, 0x00000001
// Matches Spliterator.DISTINCT
DISTINCT(0,
set(Type.SPLITERATOR).set(Type.STREAM).setAndClear(Type.OP)),
/**
* Characteristic value signifying that encounter order follows a natural
* sort order of comparable elements.
* <p>
* A stream can have this value or an intermediate operation can preserve,
* clear or inject this value.
* <p>
* Note: The {@link java.util.Spliterator#SORTED} characteristic can define
* a sort order with an associated non-null comparator. Augmenting flag
* state with addition properties such that those properties can be passed
* to operations requires some disruptive changes for a singular use-case.
* Furthermore, comparing comparators for equality beyond that of identity
* is likely to be unreliable. Therefore the {@code SORTED} characteristic
* for a defined non-natural sort order is not mapped internally to the
* {@code SORTED} flag.
*/
// 1, 0x00000004
// Matches Spliterator.SORTED
SORTED(1,
set(Type.SPLITERATOR).set(Type.STREAM).setAndClear(Type.OP)),
/**
* Characteristic value signifying that an encounter order is
* defined for stream elements.
* <p>
* A stream can have this value, an intermediate operation can preserve,
* clear or inject this value, or a terminal operation can preserve or clear
* this value.
*/
// 2, 0x00000010
// Matches Spliterator.ORDERED
ORDERED(2,
set(Type.SPLITERATOR).set(Type.STREAM).setAndClear(Type.OP).clear(Type.TERMINAL_OP)
.clear(Type.UPSTREAM_TERMINAL_OP)),
/**
* Characteristic value signifying that size of the stream
* is of a known finite size that is equal to the known finite
* size of the source spliterator input to the first stream
* in the pipeline.
* <p>
* A stream can have this value or an intermediate operation can preserve or
* clear this value.
*/
// 3, 0x00000040
// Matches Spliterator.SIZED
SIZED(3,
set(Type.SPLITERATOR).set(Type.STREAM).clear(Type.OP)),
// The following Spliterator characteristics are not currently used but a
// gap in the bit set is deliberately retained to enable corresponding
// stream flags if//when required without modification to other flag values.
//
// 4, 0x00000100 NONNULL(4, ...
// 5, 0x00000400 IMMUTABLE(5, ...
// 6, 0x00001000 CONCURRENT(6, ...
// 7, 0x00004000 SUBSIZED(7, ...
// The following 4 flags are currently undefined and a free for any further
// spliterator characteristics.
//
// 8, 0x00010000
// 9, 0x00040000
// 10, 0x00100000
// 11, 0x00400000
// The following flags are specific to streams and operations
//
/**
* Characteristic value signifying that an operation may short-circuit the
* stream.
* <p>
* An intermediate operation can preserve or inject this value,
* or a terminal operation can preserve or inject this value.
*/
// 12, 0x01000000
SHORT_CIRCUIT(12,
set(Type.OP).set(Type.TERMINAL_OP));
// The following 2 flags are currently undefined and a free for any further
// stream flags if/when required
//
// 13, 0x04000000
// 14, 0x10000000
// 15, 0x40000000
/**
* Type of a flag
*/
enum Type {
/**
* The flag is associated with spliterator characteristics.
*/
SPLITERATOR,
/**
* The flag is associated with stream flags.
*/
STREAM,
/**
* The flag is associated with intermediate operation flags.
*/
OP,
/**
* The flag is associated with terminal operation flags.
*/
TERMINAL_OP,
/**
* The flag is associated with terminal operation flags that are
* propagated upstream across the last stateful operation boundary
*/
UPSTREAM_TERMINAL_OP
}
/**
* The bit pattern for setting/injecting a flag.
*/
private static final int SET_BITS = 0b01;
/**
* The bit pattern for clearing a flag.
*/
private static final int CLEAR_BITS = 0b10;
/**
* The bit pattern for preserving a flag.
*/
private static final int PRESERVE_BITS = 0b11;
private static MaskBuilder set(Type t) {
return new MaskBuilder(new EnumMap<>(Type.class)).set(t);
}
private static class MaskBuilder {
final Map<Type, Integer> map;
MaskBuilder(Map<Type, Integer> map) {
this.map = map;
}
MaskBuilder mask(Type t, Integer i) {
map.put(t, i);
return this;
}
MaskBuilder set(Type t) {
return mask(t, SET_BITS);
}
MaskBuilder clear(Type t) {
return mask(t, CLEAR_BITS);
}
MaskBuilder setAndClear(Type t) {
return mask(t, PRESERVE_BITS);
}
Map<Type, Integer> build() {
for (Type t : Type.values()) {
map.putIfAbsent(t, 0b00);
}
return map;
}
}
/**
* The mask table for a flag, this is used to determine if a flag
* corresponds to a certain flag type and for creating mask constants.
*/
private final Map<Type, Integer> maskTable;
/**
* The bit position in the bit mask.
*/
private final int bitPosition;
/**
* The set 2 bit set offset at the bit position.
*/
private final int set;
/**
* The clear 2 bit set offset at the bit position.
*/
private final int clear;
/**
* The preserve 2 bit set offset at the bit position.
*/
private final int preserve;
private StreamOpFlag(int position, MaskBuilder maskBuilder) {
this.maskTable = maskBuilder.build();
// Two bits per flag
position *= 2;
this.bitPosition = position;
this.set = SET_BITS << position;
this.clear = CLEAR_BITS << position;
this.preserve = PRESERVE_BITS << position;
}
/**
* Gets the bitmap associated with setting this characteristic.
*
* @return the bitmap for setting this characteristic
*/
int set() {
return set;
}
/**
* Gets the bitmap associated with clearing this characteristic.
*
* @return the bitmap for clearing this characteristic
*/
int clear() {
return clear;
}
/**
* Determines if this flag is a stream-based flag.
*
* @return true if a stream-based flag, otherwise false.
*/
boolean isStreamFlag() {
return maskTable.get(Type.STREAM) > 0;
}
/**
* Checks if this flag is set on stream flags, injected on operation flags,
* and injected on combined stream and operation flags.
*
* @param flags the stream flags, operation flags, or combined stream and
* operation flags
* @return true if this flag is known, otherwise false.
*/
boolean isKnown(int flags) {
return (flags & preserve) == set;
}
/**
* Checks if this flag is cleared on operation flags or combined stream and
* operation flags.
*
* @param flags the operation flags or combined stream and operations flags.
* @return true if this flag is preserved, otherwise false.
*/
boolean isCleared(int flags) {
return (flags & preserve) == clear;
}
/**
* Checks if this flag is preserved on combined stream and operation flags.
*
* @param flags the combined stream and operations flags.
* @return true if this flag is preserved, otherwise false.
*/
boolean isPreserved(int flags) {
return (flags & preserve) == preserve;
}
/**
* Determines if this flag can be set for a flag type.
*
* @param t the flag type.
* @return true if this flag can be set for the flag type, otherwise false.
*/
boolean canSet(Type t) {
return (maskTable.get(t) & SET_BITS) > 0;
}
/**
* The bit mask for spliterator characteristics
*/
static final int SPLITERATOR_CHARACTERISTICS_MASK = createMask(Type.SPLITERATOR);
/**
* The bit mask for source stream flags.
*/
static final int STREAM_MASK = createMask(Type.STREAM);
/**
* The bit mask for intermediate operation flags.
*/
static final int OP_MASK = createMask(Type.OP);
/**
* The bit mask for terminal operation flags.
*/
static final int TERMINAL_OP_MASK = createMask(Type.TERMINAL_OP);
/**
* The bit mask for upstream terminal operation flags.
*/
static final int UPSTREAM_TERMINAL_OP_MASK = createMask(Type.UPSTREAM_TERMINAL_OP);
private static int createMask(Type t) {
int mask = 0;
for (StreamOpFlag flag : StreamOpFlag.values()) {
mask |= flag.maskTable.get(t) << flag.bitPosition;
}
return mask;
}
/**
* Complete flag mask.
*/
private static final int FLAG_MASK = createFlagMask();
private static int createFlagMask() {
int mask = 0;
for (StreamOpFlag flag : StreamOpFlag.values()) {
mask |= flag.preserve;
}
return mask;
}
/**
* Flag mask for stream flags that are set.
*/
private static final int FLAG_MASK_IS = STREAM_MASK;
/**
* Flag mask for stream flags that are cleared.
*/
private static final int FLAG_MASK_NOT = STREAM_MASK << 1;
/**
* The initial value to be combined with the stream flags of the first
* stream in the pipeline.
*/
static final int INITIAL_OPS_VALUE = FLAG_MASK_IS | FLAG_MASK_NOT;
/**
* The bit value to set or inject {@link #DISTINCT}.
*/
static final int IS_DISTINCT = DISTINCT.set;
/**
* The bit value to clear {@link #DISTINCT}.
*/
static final int NOT_DISTINCT = DISTINCT.clear;
/**
* The bit value to set or inject {@link #SORTED}.
*/
static final int IS_SORTED = SORTED.set;
/**
* The bit value to clear {@link #SORTED}.
*/
static final int NOT_SORTED = SORTED.clear;
/**
* The bit value to set or inject {@link #ORDERED}.
*/
static final int IS_ORDERED = ORDERED.set;
/**
* The bit value to clear {@link #ORDERED}.
*/
static final int NOT_ORDERED = ORDERED.clear;
/**
* The bit value to set {@link #SIZED}.
*/
static final int IS_SIZED = SIZED.set;
/**
* The bit value to clear {@link #SIZED}.
*/
static final int NOT_SIZED = SIZED.clear;
/**
* The bit value to inject {@link #SHORT_CIRCUIT}.
*/
static final int IS_SHORT_CIRCUIT = SHORT_CIRCUIT.set;
private static int getMask(int flags) {
return (flags == 0)
? FLAG_MASK
: ~(flags | ((FLAG_MASK_IS & flags) << 1) | ((FLAG_MASK_NOT & flags) >> 1));
}
/**
* Combines stream or operation flags with previously combined stream and
* operation flags to produce updated combined stream and operation flags.
* <p>
* A flag set on stream flags or injected on operation flags,
* and injected combined stream and operation flags,
* will be injected on the updated combined stream and operation flags.
*
* <p>
* A flag set on stream flags or injected on operation flags,
* and cleared on the combined stream and operation flags,
* will be cleared on the updated combined stream and operation flags.
*
* <p>
* A flag set on the stream flags or injected on operation flags,
* and preserved on the combined stream and operation flags,
* will be injected on the updated combined stream and operation flags.
*
* <p>
* A flag not set on the stream flags or cleared/preserved on operation
* flags, and injected on the combined stream and operation flags,
* will be injected on the updated combined stream and operation flags.
*
* <p>
* A flag not set on the stream flags or cleared/preserved on operation
* flags, and cleared on the combined stream and operation flags,
* will be cleared on the updated combined stream and operation flags.
*
* <p>
* A flag not set on the stream flags,
* and preserved on the combined stream and operation flags
* will be preserved on the updated combined stream and operation flags.
*
* <p>
* A flag cleared on operation flags,
* and preserved on the combined stream and operation flags
* will be cleared on the updated combined stream and operation flags.
*
* <p>
* A flag preserved on operation flags,
* and preserved on the combined stream and operation flags
* will be preserved on the updated combined stream and operation flags.
*
* @param newStreamOrOpFlags the stream or operation flags.
* @param prevCombOpFlags previously combined stream and operation flags.
* The value {#link INITIAL_OPS_VALUE} must be used as the seed value.
* @return the updated combined stream and operation flags.
*/
static int combineOpFlags(int newStreamOrOpFlags, int prevCombOpFlags) {
// 0x01 or 0x10 nibbles are transformed to 0x11
// 0x00 nibbles remain unchanged
// Then all the bits are flipped
// Then the result is logically or'ed with the operation flags.
return (prevCombOpFlags & StreamOpFlag.getMask(newStreamOrOpFlags)) | newStreamOrOpFlags;
}
/**
* Converts combined stream and operation flags to stream flags.
*
* <p>Each flag injected on the combined stream and operation flags will be
* set on the stream flags.
*
* @param combOpFlags the combined stream and operation flags.
* @return the stream flags.
*/
static int toStreamFlags(int combOpFlags) {
// By flipping the nibbles 0x11 become 0x00 and 0x01 become 0x10
// Shift left 1 to restore set flags and mask off anything other than the set flags
return ((~combOpFlags) >> 1) & FLAG_MASK_IS & combOpFlags;
}
/**
* Converts stream flags to a spliterator characteristic bit set.
*
* @param streamFlags the stream flags.
* @return the spliterator characteristic bit set.
*/
static int toCharacteristics(int streamFlags) {
return streamFlags & SPLITERATOR_CHARACTERISTICS_MASK;
}
/**
* Converts a spliterator characteristic bit set to stream flags.
*
* @implSpec
* If the spliterator is naturally {@code SORTED} (the associated
* {@code Comparator} is {@code null}) then the characteristic is converted
* to the {@link #SORTED} flag, otherwise the characteristic is not
* converted.
*
* @param spliterator the spliterator from which to obtain characteristic
* bit set.
* @return the stream flags.
*/
static int fromCharacteristics(Spliterator<?> spliterator) {
int characteristics = spliterator.characteristics();
if ((characteristics & Spliterator.SORTED) != 0 && spliterator.getComparator() != null) {
// Do not propagate the SORTED characteristic if it does not correspond
// to a natural sort order
return characteristics & SPLITERATOR_CHARACTERISTICS_MASK & ~Spliterator.SORTED;
}
else {
return characteristics & SPLITERATOR_CHARACTERISTICS_MASK;
}
}
/**
* Converts a spliterator characteristic bit set to stream flags.
*
* @param characteristics the spliterator characteristic bit set.
* @return the stream flags.
*/
static int fromCharacteristics(int characteristics) {
return characteristics & SPLITERATOR_CHARACTERISTICS_MASK;
}
}

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@ -0,0 +1,70 @@
/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
/**
* An enum describing the known shape specializations for stream abstractions.
* Each will correspond to a specific subinterface of {@link BaseStream}
* (e.g., {@code REFERENCE} corresponds to {@code Stream}, {@code INT_VALUE}
* corresponds to {@code IntStream}). Each may also correspond to
* specializations of value-handling abstractions such as {@code Spliterator},
* {@code Consumer}, etc.
*
* @apiNote
* This enum is used by implementations to determine compatibility between
* streams and operations (i.e., if the output shape of a stream is compatible
* with the input shape of the next operation).
*
* <p>Some APIs require you to specify both a generic type and a stream shape
* for input or output elements, such as {@link TerminalOp} which has both
* generic type parameters for its input types, and a getter for the
* input shape. When representing primitive streams in this way, the
* generic type parameter should correspond to the wrapper type for that
* primitive type.
*
* @since 1.8
*/
enum StreamShape {
/**
* The shape specialization corresponding to {@code Stream} and elements
* that are object references.
*/
REFERENCE,
/**
* The shape specialization corresponding to {@code IntStream} and elements
* that are {@code int} values.
*/
INT_VALUE,
/**
* The shape specialization corresponding to {@code LongStream} and elements
* that are {@code long} values.
*/
LONG_VALUE,
/**
* The shape specialization corresponding to {@code DoubleStream} and
* elements that are {@code double} values.
*/
DOUBLE_VALUE
}

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/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Objects;
import java.util.Spliterator;
import java.util.function.Supplier;
/**
* Low-level utility methods for creating and manipulating streams.
*
* <p>This class is mostly for library writers presenting stream views
* of data structures; most static stream methods intended for end users are in
* the various {@code Stream} classes.
*
* @since 1.8
*/
public final class StreamSupport {
// Suppresses default constructor, ensuring non-instantiability.
private StreamSupport() {}
/**
* Creates a new sequential or parallel {@code Stream} from a
* {@code Spliterator}.
*
* <p>The spliterator is only traversed, split, or queried for estimated
* size after the terminal operation of the stream pipeline commences.
*
* <p>It is strongly recommended the spliterator report a characteristic of
* {@code IMMUTABLE} or {@code CONCURRENT}, or be
* <a href="../Spliterator.html#binding">late-binding</a>. Otherwise,
* {@link #stream(java.util.function.Supplier, int, boolean)} should be used
* to reduce the scope of potential interference with the source. See
* <a href="package-summary.html#NonInterference">Non-Interference</a> for
* more details.
*
* @param <T> the type of stream elements
* @param spliterator a {@code Spliterator} describing the stream elements
* @param parallel if {@code true} then the returned stream is a parallel
* stream; if {@code false} the returned stream is a sequential
* stream.
* @return a new sequential or parallel {@code Stream}
*/
public static <T> Stream<T> stream(Spliterator<T> spliterator, boolean parallel) {
Objects.requireNonNull(spliterator);
return new ReferencePipeline.Head<>(spliterator,
StreamOpFlag.fromCharacteristics(spliterator),
parallel);
}
/**
* Creates a new sequential or parallel {@code Stream} from a
* {@code Supplier} of {@code Spliterator}.
*
* <p>The {@link Supplier#get()} method will be invoked on the supplier no
* more than once, and only after the terminal operation of the stream pipeline
* commences.
*
* <p>For spliterators that report a characteristic of {@code IMMUTABLE}
* or {@code CONCURRENT}, or that are
* <a href="../Spliterator.html#binding">late-binding</a>, it is likely
* more efficient to use {@link #stream(java.util.Spliterator, boolean)}
* instead.
* <p>The use of a {@code Supplier} in this form provides a level of
* indirection that reduces the scope of potential interference with the
* source. Since the supplier is only invoked after the terminal operation
* commences, any modifications to the source up to the start of the
* terminal operation are reflected in the stream result. See
* <a href="package-summary.html#NonInterference">Non-Interference</a> for
* more details.
*
* @param <T> the type of stream elements
* @param supplier a {@code Supplier} of a {@code Spliterator}
* @param characteristics Spliterator characteristics of the supplied
* {@code Spliterator}. The characteristics must be equal to
* {@code supplier.get().characteristics()}, otherwise undefined
* behavior may occur when terminal operation commences.
* @param parallel if {@code true} then the returned stream is a parallel
* stream; if {@code false} the returned stream is a sequential
* stream.
* @return a new sequential or parallel {@code Stream}
* @see #stream(java.util.Spliterator, boolean)
*/
public static <T> Stream<T> stream(Supplier<? extends Spliterator<T>> supplier,
int characteristics,
boolean parallel) {
Objects.requireNonNull(supplier);
return new ReferencePipeline.Head<>(supplier,
StreamOpFlag.fromCharacteristics(characteristics),
parallel);
}
/**
* Creates a new sequential or parallel {@code IntStream} from a
* {@code Spliterator.OfInt}.
*
* <p>The spliterator is only traversed, split, or queried for estimated size
* after the terminal operation of the stream pipeline commences.
*
* <p>It is strongly recommended the spliterator report a characteristic of
* {@code IMMUTABLE} or {@code CONCURRENT}, or be
* <a href="../Spliterator.html#binding">late-binding</a>. Otherwise,
* {@link #intStream(java.util.function.Supplier, int, boolean)} should be
* used to reduce the scope of potential interference with the source. See
* <a href="package-summary.html#NonInterference">Non-Interference</a> for
* more details.
*
* @param spliterator a {@code Spliterator.OfInt} describing the stream elements
* @param parallel if {@code true} then the returned stream is a parallel
* stream; if {@code false} the returned stream is a sequential
* stream.
* @return a new sequential or parallel {@code IntStream}
*/
public static IntStream intStream(Spliterator.OfInt spliterator, boolean parallel) {
return new IntPipeline.Head<>(spliterator,
StreamOpFlag.fromCharacteristics(spliterator),
parallel);
}
/**
* Creates a new sequential or parallel {@code IntStream} from a
* {@code Supplier} of {@code Spliterator.OfInt}.
*
* <p>The {@link Supplier#get()} method will be invoked on the supplier no
* more than once, and only after the terminal operation of the stream pipeline
* commences.
*
* <p>For spliterators that report a characteristic of {@code IMMUTABLE}
* or {@code CONCURRENT}, or that are
* <a href="../Spliterator.html#binding">late-binding</a>, it is likely
* more efficient to use {@link #intStream(java.util.Spliterator.OfInt, boolean)}
* instead.
* <p>The use of a {@code Supplier} in this form provides a level of
* indirection that reduces the scope of potential interference with the
* source. Since the supplier is only invoked after the terminal operation
* commences, any modifications to the source up to the start of the
* terminal operation are reflected in the stream result. See
* <a href="package-summary.html#NonInterference">Non-Interference</a> for
* more details.
*
* @param supplier a {@code Supplier} of a {@code Spliterator.OfInt}
* @param characteristics Spliterator characteristics of the supplied
* {@code Spliterator.OfInt}. The characteristics must be equal to
* {@code supplier.get().characteristics()}, otherwise undefined
* behavior may occur when terminal operation commences.
* @param parallel if {@code true} then the returned stream is a parallel
* stream; if {@code false} the returned stream is a sequential
* stream.
* @return a new sequential or parallel {@code IntStream}
* @see #intStream(java.util.Spliterator.OfInt, boolean)
*/
public static IntStream intStream(Supplier<? extends Spliterator.OfInt> supplier,
int characteristics,
boolean parallel) {
return new IntPipeline.Head<>(supplier,
StreamOpFlag.fromCharacteristics(characteristics),
parallel);
}
/**
* Creates a new sequential or parallel {@code LongStream} from a
* {@code Spliterator.OfLong}.
*
* <p>The spliterator is only traversed, split, or queried for estimated
* size after the terminal operation of the stream pipeline commences.
*
* <p>It is strongly recommended the spliterator report a characteristic of
* {@code IMMUTABLE} or {@code CONCURRENT}, or be
* <a href="../Spliterator.html#binding">late-binding</a>. Otherwise,
* {@link #longStream(java.util.function.Supplier, int, boolean)} should be
* used to reduce the scope of potential interference with the source. See
* <a href="package-summary.html#NonInterference">Non-Interference</a> for
* more details.
*
* @param spliterator a {@code Spliterator.OfLong} describing the stream elements
* @param parallel if {@code true} then the returned stream is a parallel
* stream; if {@code false} the returned stream is a sequential
* stream.
* @return a new sequential or parallel {@code LongStream}
*/
public static LongStream longStream(Spliterator.OfLong spliterator,
boolean parallel) {
return new LongPipeline.Head<>(spliterator,
StreamOpFlag.fromCharacteristics(spliterator),
parallel);
}
/**
* Creates a new sequential or parallel {@code LongStream} from a
* {@code Supplier} of {@code Spliterator.OfLong}.
*
* <p>The {@link Supplier#get()} method will be invoked on the supplier no
* more than once, and only after the terminal operation of the stream pipeline
* commences.
*
* <p>For spliterators that report a characteristic of {@code IMMUTABLE}
* or {@code CONCURRENT}, or that are
* <a href="../Spliterator.html#binding">late-binding</a>, it is likely
* more efficient to use {@link #longStream(java.util.Spliterator.OfLong, boolean)}
* instead.
* <p>The use of a {@code Supplier} in this form provides a level of
* indirection that reduces the scope of potential interference with the
* source. Since the supplier is only invoked after the terminal operation
* commences, any modifications to the source up to the start of the
* terminal operation are reflected in the stream result. See
* <a href="package-summary.html#NonInterference">Non-Interference</a> for
* more details.
*
* @param supplier a {@code Supplier} of a {@code Spliterator.OfLong}
* @param characteristics Spliterator characteristics of the supplied
* {@code Spliterator.OfLong}. The characteristics must be equal to
* {@code supplier.get().characteristics()}, otherwise undefined
* behavior may occur when terminal operation commences.
* @param parallel if {@code true} then the returned stream is a parallel
* stream; if {@code false} the returned stream is a sequential
* stream.
* @return a new sequential or parallel {@code LongStream}
* @see #longStream(java.util.Spliterator.OfLong, boolean)
*/
public static LongStream longStream(Supplier<? extends Spliterator.OfLong> supplier,
int characteristics,
boolean parallel) {
return new LongPipeline.Head<>(supplier,
StreamOpFlag.fromCharacteristics(characteristics),
parallel);
}
/**
* Creates a new sequential or parallel {@code DoubleStream} from a
* {@code Spliterator.OfDouble}.
*
* <p>The spliterator is only traversed, split, or queried for estimated size
* after the terminal operation of the stream pipeline commences.
*
* <p>It is strongly recommended the spliterator report a characteristic of
* {@code IMMUTABLE} or {@code CONCURRENT}, or be
* <a href="../Spliterator.html#binding">late-binding</a>. Otherwise,
* {@link #doubleStream(java.util.function.Supplier, int, boolean)} should
* be used to reduce the scope of potential interference with the source. See
* <a href="package-summary.html#NonInterference">Non-Interference</a> for
* more details.
*
* @param spliterator A {@code Spliterator.OfDouble} describing the stream elements
* @param parallel if {@code true} then the returned stream is a parallel
* stream; if {@code false} the returned stream is a sequential
* stream.
* @return a new sequential or parallel {@code DoubleStream}
*/
public static DoubleStream doubleStream(Spliterator.OfDouble spliterator,
boolean parallel) {
return new DoublePipeline.Head<>(spliterator,
StreamOpFlag.fromCharacteristics(spliterator),
parallel);
}
/**
* Creates a new sequential or parallel {@code DoubleStream} from a
* {@code Supplier} of {@code Spliterator.OfDouble}.
*
* <p>The {@link Supplier#get()} method will be invoked on the supplier no
* more than once, and only after the terminal operation of the stream pipeline
* commences.
*
* <p>For spliterators that report a characteristic of {@code IMMUTABLE}
* or {@code CONCURRENT}, or that are
* <a href="../Spliterator.html#binding">late-binding</a>, it is likely
* more efficient to use {@link #doubleStream(java.util.Spliterator.OfDouble, boolean)}
* instead.
* <p>The use of a {@code Supplier} in this form provides a level of
* indirection that reduces the scope of potential interference with the
* source. Since the supplier is only invoked after the terminal operation
* commences, any modifications to the source up to the start of the
* terminal operation are reflected in the stream result. See
* <a href="package-summary.html#NonInterference">Non-Interference</a> for
* more details.
*
* @param supplier A {@code Supplier} of a {@code Spliterator.OfDouble}
* @param characteristics Spliterator characteristics of the supplied
* {@code Spliterator.OfDouble}. The characteristics must be equal to
* {@code supplier.get().characteristics()}, otherwise undefined
* behavior may occur when terminal operation commences.
* @param parallel if {@code true} then the returned stream is a parallel
* stream; if {@code false} the returned stream is a sequential
* stream.
* @return a new sequential or parallel {@code DoubleStream}
* @see #doubleStream(java.util.Spliterator.OfDouble, boolean)
*/
public static DoubleStream doubleStream(Supplier<? extends Spliterator.OfDouble> supplier,
int characteristics,
boolean parallel) {
return new DoublePipeline.Head<>(supplier,
StreamOpFlag.fromCharacteristics(characteristics),
parallel);
}
}

View file

@ -0,0 +1,888 @@
/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Comparator;
import java.util.Objects;
import java.util.Spliterator;
import java.util.function.Consumer;
import java.util.function.DoubleConsumer;
import java.util.function.IntConsumer;
import java.util.function.LongConsumer;
import jdk.internal.HotSpotIntrinsicCandidate;
/**
* Utility methods for operating on and creating streams.
*
* <p>Unless otherwise stated, streams are created as sequential streams. A
* sequential stream can be transformed into a parallel stream by calling the
* {@code parallel()} method on the created stream.
*
* @since 1.8
*/
final class Streams {
private Streams() {
throw new Error("no instances");
}
/**
* An {@code int} range spliterator.
*/
static final class RangeIntSpliterator implements Spliterator.OfInt {
// Can never be greater that upTo, this avoids overflow if upper bound
// is Integer.MAX_VALUE
// All elements are traversed if from == upTo & last == 0
private int from;
private final int upTo;
// 1 if the range is closed and the last element has not been traversed
// Otherwise, 0 if the range is open, or is a closed range and all
// elements have been traversed
private int last;
RangeIntSpliterator(int from, int upTo, boolean closed) {
this(from, upTo, closed ? 1 : 0);
}
private RangeIntSpliterator(int from, int upTo, int last) {
this.from = from;
this.upTo = upTo;
this.last = last;
}
@Override
public boolean tryAdvance(IntConsumer consumer) {
Objects.requireNonNull(consumer);
final int i = from;
if (i < upTo) {
from++;
consumer.accept(i);
return true;
}
else if (last > 0) {
last = 0;
consumer.accept(i);
return true;
}
return false;
}
@Override
@HotSpotIntrinsicCandidate
public void forEachRemaining(IntConsumer consumer) {
Objects.requireNonNull(consumer);
int i = from;
final int hUpTo = upTo;
int hLast = last;
from = upTo;
last = 0;
while (i < hUpTo) {
consumer.accept(i++);
}
if (hLast > 0) {
// Last element of closed range
consumer.accept(i);
}
}
@Override
public long estimateSize() {
// Ensure ranges of size > Integer.MAX_VALUE report the correct size
return ((long) upTo) - from + last;
}
@Override
public int characteristics() {
return Spliterator.ORDERED | Spliterator.SIZED | Spliterator.SUBSIZED |
Spliterator.IMMUTABLE | Spliterator.NONNULL |
Spliterator.DISTINCT | Spliterator.SORTED;
}
@Override
public Comparator<? super Integer> getComparator() {
return null;
}
@Override
public Spliterator.OfInt trySplit() {
long size = estimateSize();
return size <= 1
? null
// Left split always has a half-open range
: new RangeIntSpliterator(from, from = from + splitPoint(size), 0);
}
/**
* The spliterator size below which the spliterator will be split
* at the mid-point to produce balanced splits. Above this size the
* spliterator will be split at a ratio of
* 1:(RIGHT_BALANCED_SPLIT_RATIO - 1)
* to produce right-balanced splits.
*
* <p>Such splitting ensures that for very large ranges that the left
* side of the range will more likely be processed at a lower-depth
* than a balanced tree at the expense of a higher-depth for the right
* side of the range.
*
* <p>This is optimized for cases such as IntStream.range(0, Integer.MAX_VALUE)
* that is likely to be augmented with a limit operation that limits the
* number of elements to a count lower than this threshold.
*/
private static final int BALANCED_SPLIT_THRESHOLD = 1 << 24;
/**
* The split ratio of the left and right split when the spliterator
* size is above BALANCED_SPLIT_THRESHOLD.
*/
private static final int RIGHT_BALANCED_SPLIT_RATIO = 1 << 3;
private int splitPoint(long size) {
int d = (size < BALANCED_SPLIT_THRESHOLD) ? 2 : RIGHT_BALANCED_SPLIT_RATIO;
// Cast to int is safe since:
// 2 <= size < 2^32
// 2 <= d <= 8
return (int) (size / d);
}
}
/**
* A {@code long} range spliterator.
*
* This implementation cannot be used for ranges whose size is greater
* than Long.MAX_VALUE
*/
static final class RangeLongSpliterator implements Spliterator.OfLong {
// Can never be greater that upTo, this avoids overflow if upper bound
// is Long.MAX_VALUE
// All elements are traversed if from == upTo & last == 0
private long from;
private final long upTo;
// 1 if the range is closed and the last element has not been traversed
// Otherwise, 0 if the range is open, or is a closed range and all
// elements have been traversed
private int last;
RangeLongSpliterator(long from, long upTo, boolean closed) {
this(from, upTo, closed ? 1 : 0);
}
private RangeLongSpliterator(long from, long upTo, int last) {
assert upTo - from + last > 0;
this.from = from;
this.upTo = upTo;
this.last = last;
}
@Override
public boolean tryAdvance(LongConsumer consumer) {
Objects.requireNonNull(consumer);
final long i = from;
if (i < upTo) {
from++;
consumer.accept(i);
return true;
}
else if (last > 0) {
last = 0;
consumer.accept(i);
return true;
}
return false;
}
@Override
public void forEachRemaining(LongConsumer consumer) {
Objects.requireNonNull(consumer);
long i = from;
final long hUpTo = upTo;
int hLast = last;
from = upTo;
last = 0;
while (i < hUpTo) {
consumer.accept(i++);
}
if (hLast > 0) {
// Last element of closed range
consumer.accept(i);
}
}
@Override
public long estimateSize() {
return upTo - from + last;
}
@Override
public int characteristics() {
return Spliterator.ORDERED | Spliterator.SIZED | Spliterator.SUBSIZED |
Spliterator.IMMUTABLE | Spliterator.NONNULL |
Spliterator.DISTINCT | Spliterator.SORTED;
}
@Override
public Comparator<? super Long> getComparator() {
return null;
}
@Override
public Spliterator.OfLong trySplit() {
long size = estimateSize();
return size <= 1
? null
// Left split always has a half-open range
: new RangeLongSpliterator(from, from = from + splitPoint(size), 0);
}
/**
* The spliterator size below which the spliterator will be split
* at the mid-point to produce balanced splits. Above this size the
* spliterator will be split at a ratio of
* 1:(RIGHT_BALANCED_SPLIT_RATIO - 1)
* to produce right-balanced splits.
*
* <p>Such splitting ensures that for very large ranges that the left
* side of the range will more likely be processed at a lower-depth
* than a balanced tree at the expense of a higher-depth for the right
* side of the range.
*
* <p>This is optimized for cases such as LongStream.range(0, Long.MAX_VALUE)
* that is likely to be augmented with a limit operation that limits the
* number of elements to a count lower than this threshold.
*/
private static final long BALANCED_SPLIT_THRESHOLD = 1 << 24;
/**
* The split ratio of the left and right split when the spliterator
* size is above BALANCED_SPLIT_THRESHOLD.
*/
private static final long RIGHT_BALANCED_SPLIT_RATIO = 1 << 3;
private long splitPoint(long size) {
long d = (size < BALANCED_SPLIT_THRESHOLD) ? 2 : RIGHT_BALANCED_SPLIT_RATIO;
// 2 <= size <= Long.MAX_VALUE
return size / d;
}
}
private abstract static class AbstractStreamBuilderImpl<T, S extends Spliterator<T>> implements Spliterator<T> {
// >= 0 when building, < 0 when built
// -1 == no elements
// -2 == one element, held by first
// -3 == two or more elements, held by buffer
int count;
// Spliterator implementation for 0 or 1 element
// count == -1 for no elements
// count == -2 for one element held by first
@Override
public S trySplit() {
return null;
}
@Override
public long estimateSize() {
return -count - 1;
}
@Override
public int characteristics() {
return Spliterator.SIZED | Spliterator.SUBSIZED |
Spliterator.ORDERED | Spliterator.IMMUTABLE;
}
}
static final class StreamBuilderImpl<T>
extends AbstractStreamBuilderImpl<T, Spliterator<T>>
implements Stream.Builder<T> {
// The first element in the stream
// valid if count == 1
T first;
// The first and subsequent elements in the stream
// non-null if count == 2
SpinedBuffer<T> buffer;
/**
* Constructor for building a stream of 0 or more elements.
*/
StreamBuilderImpl() { }
/**
* Constructor for a singleton stream.
*
* @param t the single element
*/
StreamBuilderImpl(T t) {
first = t;
count = -2;
}
// StreamBuilder implementation
@Override
public void accept(T t) {
if (count == 0) {
first = t;
count++;
}
else if (count > 0) {
if (buffer == null) {
buffer = new SpinedBuffer<>();
buffer.accept(first);
count++;
}
buffer.accept(t);
}
else {
throw new IllegalStateException();
}
}
public Stream.Builder<T> add(T t) {
accept(t);
return this;
}
@Override
public Stream<T> build() {
int c = count;
if (c >= 0) {
// Switch count to negative value signalling the builder is built
count = -count - 1;
// Use this spliterator if 0 or 1 elements, otherwise use
// the spliterator of the spined buffer
return (c < 2) ? StreamSupport.stream(this, false) : StreamSupport.stream(buffer.spliterator(), false);
}
throw new IllegalStateException();
}
// Spliterator implementation for 0 or 1 element
// count == -1 for no elements
// count == -2 for one element held by first
@Override
public boolean tryAdvance(Consumer<? super T> action) {
Objects.requireNonNull(action);
if (count == -2) {
action.accept(first);
count = -1;
return true;
}
else {
return false;
}
}
@Override
public void forEachRemaining(Consumer<? super T> action) {
Objects.requireNonNull(action);
if (count == -2) {
action.accept(first);
count = -1;
}
}
}
static final class IntStreamBuilderImpl
extends AbstractStreamBuilderImpl<Integer, Spliterator.OfInt>
implements IntStream.Builder, Spliterator.OfInt {
// The first element in the stream
// valid if count == 1
int first;
// The first and subsequent elements in the stream
// non-null if count == 2
SpinedBuffer.OfInt buffer;
/**
* Constructor for building a stream of 0 or more elements.
*/
IntStreamBuilderImpl() { }
/**
* Constructor for a singleton stream.
*
* @param t the single element
*/
IntStreamBuilderImpl(int t) {
first = t;
count = -2;
}
// StreamBuilder implementation
@Override
public void accept(int t) {
if (count == 0) {
first = t;
count++;
}
else if (count > 0) {
if (buffer == null) {
buffer = new SpinedBuffer.OfInt();
buffer.accept(first);
count++;
}
buffer.accept(t);
}
else {
throw new IllegalStateException();
}
}
@Override
public IntStream build() {
int c = count;
if (c >= 0) {
// Switch count to negative value signalling the builder is built
count = -count - 1;
// Use this spliterator if 0 or 1 elements, otherwise use
// the spliterator of the spined buffer
return (c < 2) ? StreamSupport.intStream(this, false) : StreamSupport.intStream(buffer.spliterator(), false);
}
throw new IllegalStateException();
}
// Spliterator implementation for 0 or 1 element
// count == -1 for no elements
// count == -2 for one element held by first
@Override
public boolean tryAdvance(IntConsumer action) {
Objects.requireNonNull(action);
if (count == -2) {
action.accept(first);
count = -1;
return true;
}
else {
return false;
}
}
@Override
public void forEachRemaining(IntConsumer action) {
Objects.requireNonNull(action);
if (count == -2) {
action.accept(first);
count = -1;
}
}
}
static final class LongStreamBuilderImpl
extends AbstractStreamBuilderImpl<Long, Spliterator.OfLong>
implements LongStream.Builder, Spliterator.OfLong {
// The first element in the stream
// valid if count == 1
long first;
// The first and subsequent elements in the stream
// non-null if count == 2
SpinedBuffer.OfLong buffer;
/**
* Constructor for building a stream of 0 or more elements.
*/
LongStreamBuilderImpl() { }
/**
* Constructor for a singleton stream.
*
* @param t the single element
*/
LongStreamBuilderImpl(long t) {
first = t;
count = -2;
}
// StreamBuilder implementation
@Override
public void accept(long t) {
if (count == 0) {
first = t;
count++;
}
else if (count > 0) {
if (buffer == null) {
buffer = new SpinedBuffer.OfLong();
buffer.accept(first);
count++;
}
buffer.accept(t);
}
else {
throw new IllegalStateException();
}
}
@Override
public LongStream build() {
int c = count;
if (c >= 0) {
// Switch count to negative value signalling the builder is built
count = -count - 1;
// Use this spliterator if 0 or 1 elements, otherwise use
// the spliterator of the spined buffer
return (c < 2) ? StreamSupport.longStream(this, false) : StreamSupport.longStream(buffer.spliterator(), false);
}
throw new IllegalStateException();
}
// Spliterator implementation for 0 or 1 element
// count == -1 for no elements
// count == -2 for one element held by first
@Override
public boolean tryAdvance(LongConsumer action) {
Objects.requireNonNull(action);
if (count == -2) {
action.accept(first);
count = -1;
return true;
}
else {
return false;
}
}
@Override
public void forEachRemaining(LongConsumer action) {
Objects.requireNonNull(action);
if (count == -2) {
action.accept(first);
count = -1;
}
}
}
static final class DoubleStreamBuilderImpl
extends AbstractStreamBuilderImpl<Double, Spliterator.OfDouble>
implements DoubleStream.Builder, Spliterator.OfDouble {
// The first element in the stream
// valid if count == 1
double first;
// The first and subsequent elements in the stream
// non-null if count == 2
SpinedBuffer.OfDouble buffer;
/**
* Constructor for building a stream of 0 or more elements.
*/
DoubleStreamBuilderImpl() { }
/**
* Constructor for a singleton stream.
*
* @param t the single element
*/
DoubleStreamBuilderImpl(double t) {
first = t;
count = -2;
}
// StreamBuilder implementation
@Override
public void accept(double t) {
if (count == 0) {
first = t;
count++;
}
else if (count > 0) {
if (buffer == null) {
buffer = new SpinedBuffer.OfDouble();
buffer.accept(first);
count++;
}
buffer.accept(t);
}
else {
throw new IllegalStateException();
}
}
@Override
public DoubleStream build() {
int c = count;
if (c >= 0) {
// Switch count to negative value signalling the builder is built
count = -count - 1;
// Use this spliterator if 0 or 1 elements, otherwise use
// the spliterator of the spined buffer
return (c < 2) ? StreamSupport.doubleStream(this, false) : StreamSupport.doubleStream(buffer.spliterator(), false);
}
throw new IllegalStateException();
}
// Spliterator implementation for 0 or 1 element
// count == -1 for no elements
// count == -2 for one element held by first
@Override
public boolean tryAdvance(DoubleConsumer action) {
Objects.requireNonNull(action);
if (count == -2) {
action.accept(first);
count = -1;
return true;
}
else {
return false;
}
}
@Override
public void forEachRemaining(DoubleConsumer action) {
Objects.requireNonNull(action);
if (count == -2) {
action.accept(first);
count = -1;
}
}
}
abstract static class ConcatSpliterator<T, T_SPLITR extends Spliterator<T>>
implements Spliterator<T> {
protected final T_SPLITR aSpliterator;
protected final T_SPLITR bSpliterator;
// True when no split has occurred, otherwise false
boolean beforeSplit;
// Never read after splitting
final boolean unsized;
public ConcatSpliterator(T_SPLITR aSpliterator, T_SPLITR bSpliterator) {
this.aSpliterator = aSpliterator;
this.bSpliterator = bSpliterator;
beforeSplit = true;
// The spliterator is known to be unsized before splitting if the
// sum of the estimates overflows.
unsized = aSpliterator.estimateSize() + bSpliterator.estimateSize() < 0;
}
@Override
public T_SPLITR trySplit() {
@SuppressWarnings("unchecked")
T_SPLITR ret = beforeSplit ? aSpliterator : (T_SPLITR) bSpliterator.trySplit();
beforeSplit = false;
return ret;
}
@Override
public boolean tryAdvance(Consumer<? super T> consumer) {
boolean hasNext;
if (beforeSplit) {
hasNext = aSpliterator.tryAdvance(consumer);
if (!hasNext) {
beforeSplit = false;
hasNext = bSpliterator.tryAdvance(consumer);
}
}
else
hasNext = bSpliterator.tryAdvance(consumer);
return hasNext;
}
@Override
public void forEachRemaining(Consumer<? super T> consumer) {
if (beforeSplit)
aSpliterator.forEachRemaining(consumer);
bSpliterator.forEachRemaining(consumer);
}
@Override
public long estimateSize() {
if (beforeSplit) {
// If one or both estimates are Long.MAX_VALUE then the sum
// will either be Long.MAX_VALUE or overflow to a negative value
long size = aSpliterator.estimateSize() + bSpliterator.estimateSize();
return (size >= 0) ? size : Long.MAX_VALUE;
}
else {
return bSpliterator.estimateSize();
}
}
@Override
public int characteristics() {
if (beforeSplit) {
// Concatenation loses DISTINCT and SORTED characteristics
return aSpliterator.characteristics() & bSpliterator.characteristics()
& ~(Spliterator.DISTINCT | Spliterator.SORTED
| (unsized ? Spliterator.SIZED | Spliterator.SUBSIZED : 0));
}
else {
return bSpliterator.characteristics();
}
}
@Override
public Comparator<? super T> getComparator() {
if (beforeSplit)
throw new IllegalStateException();
return bSpliterator.getComparator();
}
static class OfRef<T> extends ConcatSpliterator<T, Spliterator<T>> {
OfRef(Spliterator<T> aSpliterator, Spliterator<T> bSpliterator) {
super(aSpliterator, bSpliterator);
}
}
private abstract static class OfPrimitive<T, T_CONS, T_SPLITR extends Spliterator.OfPrimitive<T, T_CONS, T_SPLITR>>
extends ConcatSpliterator<T, T_SPLITR>
implements Spliterator.OfPrimitive<T, T_CONS, T_SPLITR> {
private OfPrimitive(T_SPLITR aSpliterator, T_SPLITR bSpliterator) {
super(aSpliterator, bSpliterator);
}
@Override
public boolean tryAdvance(T_CONS action) {
boolean hasNext;
if (beforeSplit) {
hasNext = aSpliterator.tryAdvance(action);
if (!hasNext) {
beforeSplit = false;
hasNext = bSpliterator.tryAdvance(action);
}
}
else
hasNext = bSpliterator.tryAdvance(action);
return hasNext;
}
@Override
public void forEachRemaining(T_CONS action) {
if (beforeSplit)
aSpliterator.forEachRemaining(action);
bSpliterator.forEachRemaining(action);
}
}
static class OfInt
extends ConcatSpliterator.OfPrimitive<Integer, IntConsumer, Spliterator.OfInt>
implements Spliterator.OfInt {
OfInt(Spliterator.OfInt aSpliterator, Spliterator.OfInt bSpliterator) {
super(aSpliterator, bSpliterator);
}
}
static class OfLong
extends ConcatSpliterator.OfPrimitive<Long, LongConsumer, Spliterator.OfLong>
implements Spliterator.OfLong {
OfLong(Spliterator.OfLong aSpliterator, Spliterator.OfLong bSpliterator) {
super(aSpliterator, bSpliterator);
}
}
static class OfDouble
extends ConcatSpliterator.OfPrimitive<Double, DoubleConsumer, Spliterator.OfDouble>
implements Spliterator.OfDouble {
OfDouble(Spliterator.OfDouble aSpliterator, Spliterator.OfDouble bSpliterator) {
super(aSpliterator, bSpliterator);
}
}
}
/**
* Given two Runnables, return a Runnable that executes both in sequence,
* even if the first throws an exception, and if both throw exceptions, add
* any exceptions thrown by the second as suppressed exceptions of the first.
*/
static Runnable composeWithExceptions(Runnable a, Runnable b) {
return new Runnable() {
@Override
public void run() {
try {
a.run();
}
catch (Throwable e1) {
try {
b.run();
}
catch (Throwable e2) {
try {
e1.addSuppressed(e2);
} catch (Throwable ignore) {}
}
throw e1;
}
b.run();
}
};
}
/**
* Given two streams, return a Runnable that
* executes both of their {@link BaseStream#close} methods in sequence,
* even if the first throws an exception, and if both throw exceptions, add
* any exceptions thrown by the second as suppressed exceptions of the first.
*/
static Runnable composedClose(BaseStream<?, ?> a, BaseStream<?, ?> b) {
return new Runnable() {
@Override
public void run() {
try {
a.close();
}
catch (Throwable e1) {
try {
b.close();
}
catch (Throwable e2) {
try {
e1.addSuppressed(e2);
} catch (Throwable ignore) {}
}
throw e1;
}
b.close();
}
};
}
}

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/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.Spliterator;
/**
* An operation in a stream pipeline that takes a stream as input and produces
* a result or side-effect. A {@code TerminalOp} has an input type and stream
* shape, and a result type. A {@code TerminalOp} also has a set of
* <em>operation flags</em> that describes how the operation processes elements
* of the stream (such as short-circuiting or respecting encounter order; see
* {@link StreamOpFlag}).
*
* <p>A {@code TerminalOp} must provide a sequential and parallel implementation
* of the operation relative to a given stream source and set of intermediate
* operations.
*
* @param <E_IN> the type of input elements
* @param <R> the type of the result
* @since 1.8
*/
interface TerminalOp<E_IN, R> {
/**
* Gets the shape of the input type of this operation.
*
* @implSpec The default returns {@code StreamShape.REFERENCE}.
*
* @return StreamShape of the input type of this operation
*/
default StreamShape inputShape() { return StreamShape.REFERENCE; }
/**
* Gets the stream flags of the operation. Terminal operations may set a
* limited subset of the stream flags defined in {@link StreamOpFlag}, and
* these flags are combined with the previously combined stream and
* intermediate operation flags for the pipeline.
*
* @implSpec The default implementation returns zero.
*
* @return the stream flags for this operation
* @see StreamOpFlag
*/
default int getOpFlags() { return 0; }
/**
* Performs a parallel evaluation of the operation using the specified
* {@code PipelineHelper}, which describes the upstream intermediate
* operations.
*
* @implSpec The default performs a sequential evaluation of the operation
* using the specified {@code PipelineHelper}.
*
* @param helper the pipeline helper
* @param spliterator the source spliterator
* @return the result of the evaluation
*/
default <P_IN> R evaluateParallel(PipelineHelper<E_IN> helper,
Spliterator<P_IN> spliterator) {
if (Tripwire.ENABLED)
Tripwire.trip(getClass(), "{0} triggering TerminalOp.evaluateParallel serial default");
return evaluateSequential(helper, spliterator);
}
/**
* Performs a sequential evaluation of the operation using the specified
* {@code PipelineHelper}, which describes the upstream intermediate
* operations.
*
* @param helper the pipeline helper
* @param spliterator the source spliterator
* @return the result of the evaluation
*/
<P_IN> R evaluateSequential(PipelineHelper<E_IN> helper,
Spliterator<P_IN> spliterator);
}

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/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.util.function.Supplier;
/**
* A {@link Sink} which accumulates state as elements are accepted, and allows
* a result to be retrieved after the computation is finished.
*
* @param <T> the type of elements to be accepted
* @param <R> the type of the result
*
* @since 1.8
*/
interface TerminalSink<T, R> extends Sink<T>, Supplier<R> { }

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/*
* Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
package java.util.stream;
import java.security.AccessController;
import java.security.PrivilegedAction;
import sun.util.logging.PlatformLogger;
/**
* Utility class for detecting inadvertent uses of boxing in
* {@code java.util.stream} classes. The detection is turned on or off based on
* whether the system property {@code org.openjdk.java.util.stream.tripwire} is
* considered {@code true} according to {@link Boolean#getBoolean(String)}.
* This should normally be turned off for production use.
*
* @apiNote
* Typical usage would be for boxing code to do:
* <pre>{@code
* if (Tripwire.ENABLED)
* Tripwire.trip(getClass(), "{0} calling Sink.OfInt.accept(Integer)");
* }</pre>
*
* @since 1.8
*/
final class Tripwire {
private static final String TRIPWIRE_PROPERTY = "org.openjdk.java.util.stream.tripwire";
/** Should debugging checks be enabled? */
static final boolean ENABLED = AccessController.doPrivileged(
(PrivilegedAction<Boolean>) () -> Boolean.getBoolean(TRIPWIRE_PROPERTY));
private Tripwire() { }
/**
* Produces a log warning, using {@code PlatformLogger.getLogger(className)},
* using the supplied message. The class name of {@code trippingClass} will
* be used as the first parameter to the message.
*
* @param trippingClass Name of the class generating the message
* @param msg A message format string of the type expected by
* {@link PlatformLogger}
*/
static void trip(Class<?> trippingClass, String msg) {
PlatformLogger.getLogger(trippingClass.getName()).warning(msg, trippingClass.getName());
}
}

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/*
* Copyright (c) 2012, 2017, Oracle and/or its affiliates. All rights reserved.
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* This code is free software; you can redistribute it and/or modify it
* under the terms of the GNU General Public License version 2 only, as
* published by the Free Software Foundation. Oracle designates this
* particular file as subject to the "Classpath" exception as provided
* by Oracle in the LICENSE file that accompanied this code.
*
* This code is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
* version 2 for more details (a copy is included in the LICENSE file that
* accompanied this code).
*
* You should have received a copy of the GNU General Public License version
* 2 along with this work; if not, write to the Free Software Foundation,
* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
* or visit www.oracle.com if you need additional information or have any
* questions.
*/
/**
* Classes to support functional-style operations on streams of elements, such
* as map-reduce transformations on collections. For example:
*
* <pre>{@code
* int sum = widgets.stream()
* .filter(b -> b.getColor() == RED)
* .mapToInt(b -> b.getWeight())
* .sum();
* }</pre>
*
* <p>Here we use {@code widgets}, a {@code Collection<Widget>},
* as a source for a stream, and then perform a filter-map-reduce on the stream
* to obtain the sum of the weights of the red widgets. (Summation is an
* example of a <a href="package-summary.html#Reduction">reduction</a>
* operation.)
*
* <p>The key abstraction introduced in this package is <em>stream</em>. The
* classes {@link java.util.stream.Stream}, {@link java.util.stream.IntStream},
* {@link java.util.stream.LongStream}, and {@link java.util.stream.DoubleStream}
* are streams over objects and the primitive {@code int}, {@code long} and
* {@code double} types. Streams differ from collections in several ways:
*
* <ul>
* <li>No storage. A stream is not a data structure that stores elements;
* instead, it conveys elements from a source such as a data structure,
* an array, a generator function, or an I/O channel, through a pipeline of
* computational operations.</li>
* <li>Functional in nature. An operation on a stream produces a result,
* but does not modify its source. For example, filtering a {@code Stream}
* obtained from a collection produces a new {@code Stream} without the
* filtered elements, rather than removing elements from the source
* collection.</li>
* <li>Laziness-seeking. Many stream operations, such as filtering, mapping,
* or duplicate removal, can be implemented lazily, exposing opportunities
* for optimization. For example, "find the first {@code String} with
* three consecutive vowels" need not examine all the input strings.
* Stream operations are divided into intermediate ({@code Stream}-producing)
* operations and terminal (value- or side-effect-producing) operations.
* Intermediate operations are always lazy.</li>
* <li>Possibly unbounded. While collections have a finite size, streams
* need not. Short-circuiting operations such as {@code limit(n)} or
* {@code findFirst()} can allow computations on infinite streams to
* complete in finite time.</li>
* <li>Consumable. The elements of a stream are only visited once during
* the life of a stream. Like an {@link java.util.Iterator}, a new stream
* must be generated to revisit the same elements of the source.
* </li>
* </ul>
*
* Streams can be obtained in a number of ways. Some examples include:
* <ul>
* <li>From a {@link java.util.Collection} via the {@code stream()} and
* {@code parallelStream()} methods;</li>
* <li>From an array via {@link java.util.Arrays#stream(Object[])};</li>
* <li>From static factory methods on the stream classes, such as
* {@link java.util.stream.Stream#of(Object[])},
* {@link java.util.stream.IntStream#range(int, int)}
* or {@link java.util.stream.Stream#iterate(Object, UnaryOperator)};</li>
* <li>The lines of a file can be obtained from {@link java.io.BufferedReader#lines()};</li>
* <li>Streams of file paths can be obtained from methods in {@link java.nio.file.Files};</li>
* <li>Streams of random numbers can be obtained from {@link java.util.Random#ints()};</li>
* <li>Numerous other stream-bearing methods in the JDK, including
* {@link java.util.BitSet#stream()},
* {@link java.util.regex.Pattern#splitAsStream(java.lang.CharSequence)},
* and {@link java.util.jar.JarFile#stream()}.</li>
* </ul>
*
* <p>Additional stream sources can be provided by third-party libraries using
* <a href="package-summary.html#StreamSources">these techniques</a>.
*
* <h2><a id="StreamOps">Stream operations and pipelines</a></h2>
*
* <p>Stream operations are divided into <em>intermediate</em> and
* <em>terminal</em> operations, and are combined to form <em>stream
* pipelines</em>. A stream pipeline consists of a source (such as a
* {@code Collection}, an array, a generator function, or an I/O channel);
* followed by zero or more intermediate operations such as
* {@code Stream.filter} or {@code Stream.map}; and a terminal operation such
* as {@code Stream.forEach} or {@code Stream.reduce}.
*
* <p>Intermediate operations return a new stream. They are always
* <em>lazy</em>; executing an intermediate operation such as
* {@code filter()} does not actually perform any filtering, but instead
* creates a new stream that, when traversed, contains the elements of
* the initial stream that match the given predicate. Traversal
* of the pipeline source does not begin until the terminal operation of the
* pipeline is executed.
*
* <p>Terminal operations, such as {@code Stream.forEach} or
* {@code IntStream.sum}, may traverse the stream to produce a result or a
* side-effect. After the terminal operation is performed, the stream pipeline
* is considered consumed, and can no longer be used; if you need to traverse
* the same data source again, you must return to the data source to get a new
* stream. In almost all cases, terminal operations are <em>eager</em>,
* completing their traversal of the data source and processing of the pipeline
* before returning. Only the terminal operations {@code iterator()} and
* {@code spliterator()} are not; these are provided as an "escape hatch" to enable
* arbitrary client-controlled pipeline traversals in the event that the
* existing operations are not sufficient to the task.
*
* <p> Processing streams lazily allows for significant efficiencies; in a
* pipeline such as the filter-map-sum example above, filtering, mapping, and
* summing can be fused into a single pass on the data, with minimal
* intermediate state. Laziness also allows avoiding examining all the data
* when it is not necessary; for operations such as "find the first string
* longer than 1000 characters", it is only necessary to examine just enough
* strings to find one that has the desired characteristics without examining
* all of the strings available from the source. (This behavior becomes even
* more important when the input stream is infinite and not merely large.)
*
* <p>Intermediate operations are further divided into <em>stateless</em>
* and <em>stateful</em> operations. Stateless operations, such as {@code filter}
* and {@code map}, retain no state from previously seen element when processing
* a new element -- each element can be processed
* independently of operations on other elements. Stateful operations, such as
* {@code distinct} and {@code sorted}, may incorporate state from previously
* seen elements when processing new elements.
*
* <p>Stateful operations may need to process the entire input
* before producing a result. For example, one cannot produce any results from
* sorting a stream until one has seen all elements of the stream. As a result,
* under parallel computation, some pipelines containing stateful intermediate
* operations may require multiple passes on the data or may need to buffer
* significant data. Pipelines containing exclusively stateless intermediate
* operations can be processed in a single pass, whether sequential or parallel,
* with minimal data buffering.
*
* <p>Further, some operations are deemed <em>short-circuiting</em> operations.
* An intermediate operation is short-circuiting if, when presented with
* infinite input, it may produce a finite stream as a result. A terminal
* operation is short-circuiting if, when presented with infinite input, it may
* terminate in finite time. Having a short-circuiting operation in the pipeline
* is a necessary, but not sufficient, condition for the processing of an infinite
* stream to terminate normally in finite time.
*
* <h3><a id="Parallelism">Parallelism</a></h3>
*
* <p>Processing elements with an explicit {@code for-}loop is inherently serial.
* Streams facilitate parallel execution by reframing the computation as a pipeline of
* aggregate operations, rather than as imperative operations on each individual
* element. All streams operations can execute either in serial or in parallel.
* The stream implementations in the JDK create serial streams unless parallelism is
* explicitly requested. For example, {@code Collection} has methods
* {@link java.util.Collection#stream} and {@link java.util.Collection#parallelStream},
* which produce sequential and parallel streams respectively; other
* stream-bearing methods such as {@link java.util.stream.IntStream#range(int, int)}
* produce sequential streams but these streams can be efficiently parallelized by
* invoking their {@link java.util.stream.BaseStream#parallel()} method.
* To execute the prior "sum of weights of widgets" query in parallel, we would
* do:
*
* <pre>{@code
* int sumOfWeights = widgets.}<code><b>parallelStream()</b></code>{@code
* .filter(b -> b.getColor() == RED)
* .mapToInt(b -> b.getWeight())
* .sum();
* }</pre>
*
* <p>The only difference between the serial and parallel versions of this
* example is the creation of the initial stream, using "{@code parallelStream()}"
* instead of "{@code stream()}". The stream pipeline is executed sequentially or
* in parallel depending on the mode of the stream on which the terminal operation
* is invoked. The sequential or parallel mode of a stream can be determined with the
* {@link java.util.stream.BaseStream#isParallel()} method, and the
* stream's mode can be modified with the
* {@link java.util.stream.BaseStream#sequential()} and
* {@link java.util.stream.BaseStream#parallel()} operations.
* The most recent sequential or parallel mode setting applies to the
* execution of the entire stream pipeline.
*
* <p>Except for operations identified as explicitly nondeterministic, such
* as {@code findAny()}, whether a stream executes sequentially or in parallel
* should not change the result of the computation.
*
* <p>Most stream operations accept parameters that describe user-specified
* behavior, which are often lambda expressions. To preserve correct behavior,
* these <em>behavioral parameters</em> must be <em>non-interfering</em>, and in
* most cases must be <em>stateless</em>. Such parameters are always instances
* of a <a href="../function/package-summary.html">functional interface</a> such
* as {@link java.util.function.Function}, and are often lambda expressions or
* method references.
*
* <h3><a id="NonInterference">Non-interference</a></h3>
*
* Streams enable you to execute possibly-parallel aggregate operations over a
* variety of data sources, including even non-thread-safe collections such as
* {@code ArrayList}. This is possible only if we can prevent
* <em>interference</em> with the data source during the execution of a stream
* pipeline. Except for the escape-hatch operations {@code iterator()} and
* {@code spliterator()}, execution begins when the terminal operation is
* invoked, and ends when the terminal operation completes. For most data
* sources, preventing interference means ensuring that the data source is
* <em>not modified at all</em> during the execution of the stream pipeline.
* The notable exception to this are streams whose sources are concurrent
* collections, which are specifically designed to handle concurrent modification.
* Concurrent stream sources are those whose {@code Spliterator} reports the
* {@code CONCURRENT} characteristic.
*
* <p>Accordingly, behavioral parameters in stream pipelines whose source might
* not be concurrent should never modify the stream's data source.
* A behavioral parameter is said to <em>interfere</em> with a non-concurrent
* data source if it modifies, or causes to be
* modified, the stream's data source. The need for non-interference applies
* to all pipelines, not just parallel ones. Unless the stream source is
* concurrent, modifying a stream's data source during execution of a stream
* pipeline can cause exceptions, incorrect answers, or nonconformant behavior.
*
* For well-behaved stream sources, the source can be modified before the
* terminal operation commences and those modifications will be reflected in
* the covered elements. For example, consider the following code:
*
* <pre>{@code
* List<String> l = new ArrayList(Arrays.asList("one", "two"));
* Stream<String> sl = l.stream();
* l.add("three");
* String s = sl.collect(joining(" "));
* }</pre>
*
* First a list is created consisting of two strings: "one"; and "two". Then a
* stream is created from that list. Next the list is modified by adding a third
* string: "three". Finally the elements of the stream are collected and joined
* together. Since the list was modified before the terminal {@code collect}
* operation commenced the result will be a string of "one two three". All the
* streams returned from JDK collections, and most other JDK classes,
* are well-behaved in this manner; for streams generated by other libraries, see
* <a href="package-summary.html#StreamSources">Low-level stream
* construction</a> for requirements for building well-behaved streams.
*
* <h3><a id="Statelessness">Stateless behaviors</a></h3>
*
* Stream pipeline results may be nondeterministic or incorrect if the behavioral
* parameters to the stream operations are <em>stateful</em>. A stateful lambda
* (or other object implementing the appropriate functional interface) is one
* whose result depends on any state which might change during the execution
* of the stream pipeline. An example of a stateful lambda is the parameter
* to {@code map()} in:
*
* <pre>{@code
* Set<Integer> seen = Collections.synchronizedSet(new HashSet<>());
* stream.parallel().map(e -> { if (seen.add(e)) return 0; else return e; })...
* }</pre>
*
* Here, if the mapping operation is performed in parallel, the results for the
* same input could vary from run to run, due to thread scheduling differences,
* whereas, with a stateless lambda expression the results would always be the
* same.
*
* <p>Note also that attempting to access mutable state from behavioral parameters
* presents you with a bad choice with respect to safety and performance; if
* you do not synchronize access to that state, you have a data race and
* therefore your code is broken, but if you do synchronize access to that
* state, you risk having contention undermine the parallelism you are seeking
* to benefit from. The best approach is to avoid stateful behavioral
* parameters to stream operations entirely; there is usually a way to
* restructure the stream pipeline to avoid statefulness.
*
* <h3><a id="SideEffects">Side-effects</a></h3>
*
* Side-effects in behavioral parameters to stream operations are, in general,
* discouraged, as they can often lead to unwitting violations of the
* statelessness requirement, as well as other thread-safety hazards.
*
* <p>If the behavioral parameters do have side-effects, unless explicitly
* stated, there are no guarantees as to:
* <ul>
* <li>the <a href="../concurrent/package-summary.html#MemoryVisibility">
* <i>visibility</i></a> of those side-effects to other threads;</li>
* <li>that different operations on the "same" element within the same stream
* pipeline are executed in the same thread; and</li>
* <li>that behavioral parameters are always invoked, since a stream
* implementation is free to elide operations (or entire stages) from a
* stream pipeline if it can prove that it would not affect the result of the
* computation.
* </li>
* </ul>
* <p>The ordering of side-effects may be surprising. Even when a pipeline is
* constrained to produce a <em>result</em> that is consistent with the
* encounter order of the stream source (for example,
* {@code IntStream.range(0,5).parallel().map(x -> x*2).toArray()}
* must produce {@code [0, 2, 4, 6, 8]}), no guarantees are made as to the order
* in which the mapper function is applied to individual elements, or in what
* thread any behavioral parameter is executed for a given element.
*
* <p>The eliding of side-effects may also be surprising. With the exception of
* terminal operations {@link java.util.stream.Stream#forEach forEach} and
* {@link java.util.stream.Stream#forEachOrdered forEachOrdered}, side-effects
* of behavioral parameters may not always be executed when the stream
* implementation can optimize away the execution of behavioral parameters
* without affecting the result of the computation. (For a specific example
* see the API note documented on the {@link java.util.stream.Stream#count count}
* operation.)
*
* <p>Many computations where one might be tempted to use side effects can be more
* safely and efficiently expressed without side-effects, such as using
* <a href="package-summary.html#Reduction">reduction</a> instead of mutable
* accumulators. However, side-effects such as using {@code println()} for debugging
* purposes are usually harmless. A small number of stream operations, such as
* {@code forEach()} and {@code peek()}, can operate only via side-effects;
* these should be used with care.
*
* <p>As an example of how to transform a stream pipeline that inappropriately
* uses side-effects to one that does not, the following code searches a stream
* of strings for those matching a given regular expression, and puts the
* matches in a list.
*
* <pre>{@code
* ArrayList<String> results = new ArrayList<>();
* stream.filter(s -> pattern.matcher(s).matches())
* .forEach(s -> results.add(s)); // Unnecessary use of side-effects!
* }</pre>
*
* This code unnecessarily uses side-effects. If executed in parallel, the
* non-thread-safety of {@code ArrayList} would cause incorrect results, and
* adding needed synchronization would cause contention, undermining the
* benefit of parallelism. Furthermore, using side-effects here is completely
* unnecessary; the {@code forEach()} can simply be replaced with a reduction
* operation that is safer, more efficient, and more amenable to
* parallelization:
*
* <pre>{@code
* List<String>results =
* stream.filter(s -> pattern.matcher(s).matches())
* .collect(Collectors.toList()); // No side-effects!
* }</pre>
*
* <h3><a id="Ordering">Ordering</a></h3>
*
* <p>Streams may or may not have a defined <em>encounter order</em>. Whether
* or not a stream has an encounter order depends on the source and the
* intermediate operations. Certain stream sources (such as {@code List} or
* arrays) are intrinsically ordered, whereas others (such as {@code HashSet})
* are not. Some intermediate operations, such as {@code sorted()}, may impose
* an encounter order on an otherwise unordered stream, and others may render an
* ordered stream unordered, such as {@link java.util.stream.BaseStream#unordered()}.
* Further, some terminal operations may ignore encounter order, such as
* {@code forEach()}.
*
* <p>If a stream is ordered, most operations are constrained to operate on the
* elements in their encounter order; if the source of a stream is a {@code List}
* containing {@code [1, 2, 3]}, then the result of executing {@code map(x -> x*2)}
* must be {@code [2, 4, 6]}. However, if the source has no defined encounter
* order, then any permutation of the values {@code [2, 4, 6]} would be a valid
* result.
*
* <p>For sequential streams, the presence or absence of an encounter order does
* not affect performance, only determinism. If a stream is ordered, repeated
* execution of identical stream pipelines on an identical source will produce
* an identical result; if it is not ordered, repeated execution might produce
* different results.
*
* <p>For parallel streams, relaxing the ordering constraint can sometimes enable
* more efficient execution. Certain aggregate operations,
* such as filtering duplicates ({@code distinct()}) or grouped reductions
* ({@code Collectors.groupingBy()}) can be implemented more efficiently if ordering of elements
* is not relevant. Similarly, operations that are intrinsically tied to encounter order,
* such as {@code limit()}, may require
* buffering to ensure proper ordering, undermining the benefit of parallelism.
* In cases where the stream has an encounter order, but the user does not
* particularly <em>care</em> about that encounter order, explicitly de-ordering
* the stream with {@link java.util.stream.BaseStream#unordered() unordered()} may
* improve parallel performance for some stateful or terminal operations.
* However, most stream pipelines, such as the "sum of weight of blocks" example
* above, still parallelize efficiently even under ordering constraints.
*
* <h2><a id="Reduction">Reduction operations</a></h2>
*
* A <em>reduction</em> operation (also called a <em>fold</em>) takes a sequence
* of input elements and combines them into a single summary result by repeated
* application of a combining operation, such as finding the sum or maximum of
* a set of numbers, or accumulating elements into a list. The streams classes have
* multiple forms of general reduction operations, called
* {@link java.util.stream.Stream#reduce(java.util.function.BinaryOperator) reduce()}
* and {@link java.util.stream.Stream#collect(java.util.stream.Collector) collect()},
* as well as multiple specialized reduction forms such as
* {@link java.util.stream.IntStream#sum() sum()}, {@link java.util.stream.IntStream#max() max()},
* or {@link java.util.stream.IntStream#count() count()}.
*
* <p>Of course, such operations can be readily implemented as simple sequential
* loops, as in:
* <pre>{@code
* int sum = 0;
* for (int x : numbers) {
* sum += x;
* }
* }</pre>
* However, there are good reasons to prefer a reduce operation
* over a mutative accumulation such as the above. Not only is a reduction
* "more abstract" -- it operates on the stream as a whole rather than individual
* elements -- but a properly constructed reduce operation is inherently
* parallelizable, so long as the function(s) used to process the elements
* are <a href="package-summary.html#Associativity">associative</a> and
* <a href="package-summary.html#Statelessness">stateless</a>.
* For example, given a stream of numbers for which we want to find the sum, we
* can write:
* <pre>{@code
* int sum = numbers.stream().reduce(0, (x,y) -> x+y);
* }</pre>
* or:
* <pre>{@code
* int sum = numbers.stream().reduce(0, Integer::sum);
* }</pre>
*
* <p>These reduction operations can run safely in parallel with almost no
* modification:
* <pre>{@code
* int sum = numbers.parallelStream().reduce(0, Integer::sum);
* }</pre>
*
* <p>Reduction parallellizes well because the implementation
* can operate on subsets of the data in parallel, and then combine the
* intermediate results to get the final correct answer. (Even if the language
* had a "parallel for-each" construct, the mutative accumulation approach would
* still required the developer to provide
* thread-safe updates to the shared accumulating variable {@code sum}, and
* the required synchronization would then likely eliminate any performance gain from
* parallelism.) Using {@code reduce()} instead removes all of the
* burden of parallelizing the reduction operation, and the library can provide
* an efficient parallel implementation with no additional synchronization
* required.
*
* <p>The "widgets" examples shown earlier shows how reduction combines with
* other operations to replace for loops with bulk operations. If {@code widgets}
* is a collection of {@code Widget} objects, which have a {@code getWeight} method,
* we can find the heaviest widget with:
* <pre>{@code
* OptionalInt heaviest = widgets.parallelStream()
* .mapToInt(Widget::getWeight)
* .max();
* }</pre>
*
* <p>In its more general form, a {@code reduce} operation on elements of type
* {@code <T>} yielding a result of type {@code <U>} requires three parameters:
* <pre>{@code
* <U> U reduce(U identity,
* BiFunction<U, ? super T, U> accumulator,
* BinaryOperator<U> combiner);
* }</pre>
* Here, the <em>identity</em> element is both an initial seed value for the reduction
* and a default result if there are no input elements. The <em>accumulator</em>
* function takes a partial result and the next element, and produces a new
* partial result. The <em>combiner</em> function combines two partial results
* to produce a new partial result. (The combiner is necessary in parallel
* reductions, where the input is partitioned, a partial accumulation computed
* for each partition, and then the partial results are combined to produce a
* final result.)
*
* <p>More formally, the {@code identity} value must be an <em>identity</em> for
* the combiner function. This means that for all {@code u},
* {@code combiner.apply(identity, u)} is equal to {@code u}. Additionally, the
* {@code combiner} function must be <a href="package-summary.html#Associativity">associative</a> and
* must be compatible with the {@code accumulator} function: for all {@code u}
* and {@code t}, {@code combiner.apply(u, accumulator.apply(identity, t))} must
* be {@code equals()} to {@code accumulator.apply(u, t)}.
*
* <p>The three-argument form is a generalization of the two-argument form,
* incorporating a mapping step into the accumulation step. We could
* re-cast the simple sum-of-weights example using the more general form as
* follows:
* <pre>{@code
* int sumOfWeights = widgets.stream()
* .reduce(0,
* (sum, b) -> sum + b.getWeight(),
* Integer::sum);
* }</pre>
* though the explicit map-reduce form is more readable and therefore should
* usually be preferred. The generalized form is provided for cases where
* significant work can be optimized away by combining mapping and reducing
* into a single function.
*
* <h3><a id="MutableReduction">Mutable reduction</a></h3>
*
* A <em>mutable reduction operation</em> accumulates input elements into a
* mutable result container, such as a {@code Collection} or {@code StringBuilder},
* as it processes the elements in the stream.
*
* <p>If we wanted to take a stream of strings and concatenate them into a
* single long string, we <em>could</em> achieve this with ordinary reduction:
* <pre>{@code
* String concatenated = strings.reduce("", String::concat)
* }</pre>
*
* <p>We would get the desired result, and it would even work in parallel. However,
* we might not be happy about the performance! Such an implementation would do
* a great deal of string copying, and the run time would be <em>O(n^2)</em> in
* the number of characters. A more performant approach would be to accumulate
* the results into a {@link java.lang.StringBuilder}, which is a mutable
* container for accumulating strings. We can use the same technique to
* parallelize mutable reduction as we do with ordinary reduction.
*
* <p>The mutable reduction operation is called
* {@link java.util.stream.Stream#collect(Collector) collect()},
* as it collects together the desired results into a result container such
* as a {@code Collection}.
* A {@code collect} operation requires three functions:
* a supplier function to construct new instances of the result container, an
* accumulator function to incorporate an input element into a result
* container, and a combining function to merge the contents of one result
* container into another. The form of this is very similar to the general
* form of ordinary reduction:
* <pre>{@code
* <R> R collect(Supplier<R> supplier,
* BiConsumer<R, ? super T> accumulator,
* BiConsumer<R, R> combiner);
* }</pre>
* <p>As with {@code reduce()}, a benefit of expressing {@code collect} in this
* abstract way is that it is directly amenable to parallelization: we can
* accumulate partial results in parallel and then combine them, so long as the
* accumulation and combining functions satisfy the appropriate requirements.
* For example, to collect the String representations of the elements in a
* stream into an {@code ArrayList}, we could write the obvious sequential
* for-each form:
* <pre>{@code
* ArrayList<String> strings = new ArrayList<>();
* for (T element : stream) {
* strings.add(element.toString());
* }
* }</pre>
* Or we could use a parallelizable collect form:
* <pre>{@code
* ArrayList<String> strings = stream.collect(() -> new ArrayList<>(),
* (c, e) -> c.add(e.toString()),
* (c1, c2) -> c1.addAll(c2));
* }</pre>
* or, pulling the mapping operation out of the accumulator function, we could
* express it more succinctly as:
* <pre>{@code
* List<String> strings = stream.map(Object::toString)
* .collect(ArrayList::new, ArrayList::add, ArrayList::addAll);
* }</pre>
* Here, our supplier is just the {@link java.util.ArrayList#ArrayList()
* ArrayList constructor}, the accumulator adds the stringified element to an
* {@code ArrayList}, and the combiner simply uses {@link java.util.ArrayList#addAll addAll}
* to copy the strings from one container into the other.
*
* <p>The three aspects of {@code collect} -- supplier, accumulator, and
* combiner -- are tightly coupled. We can use the abstraction of a
* {@link java.util.stream.Collector} to capture all three aspects. The
* above example for collecting strings into a {@code List} can be rewritten
* using a standard {@code Collector} as:
* <pre>{@code
* List<String> strings = stream.map(Object::toString)
* .collect(Collectors.toList());
* }</pre>
*
* <p>Packaging mutable reductions into a Collector has another advantage:
* composability. The class {@link java.util.stream.Collectors} contains a
* number of predefined factories for collectors, including combinators
* that transform one collector into another. For example, suppose we have a
* collector that computes the sum of the salaries of a stream of
* employees, as follows:
*
* <pre>{@code
* Collector<Employee, ?, Integer> summingSalaries
* = Collectors.summingInt(Employee::getSalary);
* }</pre>
*
* (The {@code ?} for the second type parameter merely indicates that we don't
* care about the intermediate representation used by this collector.)
* If we wanted to create a collector to tabulate the sum of salaries by
* department, we could reuse {@code summingSalaries} using
* {@link java.util.stream.Collectors#groupingBy(java.util.function.Function, java.util.stream.Collector) groupingBy}:
*
* <pre>{@code
* Map<Department, Integer> salariesByDept
* = employees.stream().collect(Collectors.groupingBy(Employee::getDepartment,
* summingSalaries));
* }</pre>
*
* <p>As with the regular reduction operation, {@code collect()} operations can
* only be parallelized if appropriate conditions are met. For any partially
* accumulated result, combining it with an empty result container must
* produce an equivalent result. That is, for a partially accumulated result
* {@code p} that is the result of any series of accumulator and combiner
* invocations, {@code p} must be equivalent to
* {@code combiner.apply(p, supplier.get())}.
*
* <p>Further, however the computation is split, it must produce an equivalent
* result. For any input elements {@code t1} and {@code t2}, the results
* {@code r1} and {@code r2} in the computation below must be equivalent:
* <pre>{@code
* A a1 = supplier.get();
* accumulator.accept(a1, t1);
* accumulator.accept(a1, t2);
* R r1 = finisher.apply(a1); // result without splitting
*
* A a2 = supplier.get();
* accumulator.accept(a2, t1);
* A a3 = supplier.get();
* accumulator.accept(a3, t2);
* R r2 = finisher.apply(combiner.apply(a2, a3)); // result with splitting
* }</pre>
*
* <p>Here, equivalence generally means according to {@link java.lang.Object#equals(Object)}.
* but in some cases equivalence may be relaxed to account for differences in
* order.
*
* <h3><a id="ConcurrentReduction">Reduction, concurrency, and ordering</a></h3>
*
* With some complex reduction operations, for example a {@code collect()} that
* produces a {@code Map}, such as:
* <pre>{@code
* Map<Buyer, List<Transaction>> salesByBuyer
* = txns.parallelStream()
* .collect(Collectors.groupingBy(Transaction::getBuyer));
* }</pre>
* it may actually be counterproductive to perform the operation in parallel.
* This is because the combining step (merging one {@code Map} into another by
* key) can be expensive for some {@code Map} implementations.
*
* <p>Suppose, however, that the result container used in this reduction
* was a concurrently modifiable collection -- such as a
* {@link java.util.concurrent.ConcurrentHashMap}. In that case, the parallel
* invocations of the accumulator could actually deposit their results
* concurrently into the same shared result container, eliminating the need for
* the combiner to merge distinct result containers. This potentially provides
* a boost to the parallel execution performance. We call this a
* <em>concurrent</em> reduction.
*
* <p>A {@link java.util.stream.Collector} that supports concurrent reduction is
* marked with the {@link java.util.stream.Collector.Characteristics#CONCURRENT}
* characteristic. However, a concurrent collection also has a downside. If
* multiple threads are depositing results concurrently into a shared container,
* the order in which results are deposited is non-deterministic. Consequently,
* a concurrent reduction is only possible if ordering is not important for the
* stream being processed. The {@link java.util.stream.Stream#collect(Collector)}
* implementation will only perform a concurrent reduction if
* <ul>
* <li>The stream is parallel;</li>
* <li>The collector has the
* {@link java.util.stream.Collector.Characteristics#CONCURRENT} characteristic,
* and;</li>
* <li>Either the stream is unordered, or the collector has the
* {@link java.util.stream.Collector.Characteristics#UNORDERED} characteristic.
* </ul>
* You can ensure the stream is unordered by using the
* {@link java.util.stream.BaseStream#unordered()} method. For example:
* <pre>{@code
* Map<Buyer, List<Transaction>> salesByBuyer
* = txns.parallelStream()
* .unordered()
* .collect(groupingByConcurrent(Transaction::getBuyer));
* }</pre>
* (where {@link java.util.stream.Collectors#groupingByConcurrent} is the
* concurrent equivalent of {@code groupingBy}).
*
* <p>Note that if it is important that the elements for a given key appear in
* the order they appear in the source, then we cannot use a concurrent
* reduction, as ordering is one of the casualties of concurrent insertion.
* We would then be constrained to implement either a sequential reduction or
* a merge-based parallel reduction.
*
* <h3><a id="Associativity">Associativity</a></h3>
*
* An operator or function {@code op} is <em>associative</em> if the following
* holds:
* <pre>{@code
* (a op b) op c == a op (b op c)
* }</pre>
* The importance of this to parallel evaluation can be seen if we expand this
* to four terms:
* <pre>{@code
* a op b op c op d == (a op b) op (c op d)
* }</pre>
* So we can evaluate {@code (a op b)} in parallel with {@code (c op d)}, and
* then invoke {@code op} on the results.
*
* <p>Examples of associative operations include numeric addition, min, and
* max, and string concatenation.
*
* <h2><a id="StreamSources">Low-level stream construction</a></h2>
*
* So far, all the stream examples have used methods like
* {@link java.util.Collection#stream()} or {@link java.util.Arrays#stream(Object[])}
* to obtain a stream. How are those stream-bearing methods implemented?
*
* <p>The class {@link java.util.stream.StreamSupport} has a number of
* low-level methods for creating a stream, all using some form of a
* {@link java.util.Spliterator}. A spliterator is the parallel analogue of an
* {@link java.util.Iterator}; it describes a (possibly infinite) collection of
* elements, with support for sequentially advancing, bulk traversal, and
* splitting off some portion of the input into another spliterator which can
* be processed in parallel. At the lowest level, all streams are driven by a
* spliterator.
*
* <p>There are a number of implementation choices in implementing a
* spliterator, nearly all of which are tradeoffs between simplicity of
* implementation and runtime performance of streams using that spliterator.
* The simplest, but least performant, way to create a spliterator is to
* create one from an iterator using
* {@link java.util.Spliterators#spliteratorUnknownSize(java.util.Iterator, int)}.
* While such a spliterator will work, it will likely offer poor parallel
* performance, since we have lost sizing information (how big is the
* underlying data set), as well as being constrained to a simplistic
* splitting algorithm.
*
* <p>A higher-quality spliterator will provide balanced and known-size
* splits, accurate sizing information, and a number of other
* {@link java.util.Spliterator#characteristics() characteristics} of the
* spliterator or data that can be used by implementations to optimize
* execution.
*
* <p>Spliterators for mutable data sources have an additional challenge;
* timing of binding to the data, since the data could change between the time
* the spliterator is created and the time the stream pipeline is executed.
* Ideally, a spliterator for a stream would report a characteristic of
* {@code IMMUTABLE} or {@code CONCURRENT}; if not it should be
* <a href="../Spliterator.html#binding"><em>late-binding</em></a>. If a source
* cannot directly supply a recommended spliterator, it may indirectly supply
* a spliterator using a {@code Supplier}, and construct a stream via the
* {@code Supplier}-accepting versions of
* {@link java.util.stream.StreamSupport#stream(Supplier, int, boolean) stream()}.
* The spliterator is obtained from the supplier only after the terminal
* operation of the stream pipeline commences.
*
* <p>These requirements significantly reduce the scope of potential
* interference between mutations of the stream source and execution of stream
* pipelines. Streams based on spliterators with the desired characteristics,
* or those using the Supplier-based factory forms, are immune to
* modifications of the data source prior to commencement of the terminal
* operation (provided the behavioral parameters to the stream operations meet
* the required criteria for non-interference and statelessness). See
* <a href="package-summary.html#NonInterference">Non-Interference</a>
* for more details.
*
* @since 1.8
*/
package java.util.stream;
import java.util.function.BinaryOperator;
import java.util.function.UnaryOperator;