談?wù)剆tream的運行原理

public class StreamUtilTest {
    @Test    public void testArrayStream() {        // 1. 過濾值；改變值；排序；        Integer[] intArr = {1, 2, 3, 5, 22, 8, 5};        List<Integer> iArrList = Arrays.stream(intArr)                                .filter(r -> r < 20)                                .map(r -> r + 1)                                .sorted().collect(Collectors.toList());        System.out.println("result:" + iArrList);
        String[] strArr = {"a1,a2", "q,y,h", "ddd,bb,n", null};        // 2. 過濾數(shù)組；拆分值；輸出；        Arrays.stream(strArr).filter(Objects::nonNull)                .flatMap(r -> Arrays.stream(r.split(",")))                .forEach(System.out::println);    }
    @Test    public void testListStream() {        List<String> list = new ArrayList<>();        list.add("ab");        list.add("ccc");        list.add("ddd");        // 3. 求list中的最大值        Optional<String> maxStr = list.stream().max(Comparator.naturalOrder());        System.out.println(maxStr);    }}

# 調(diào)用lamda表達(dá)式示例...        59: invokestatic  #4                  // Method java/util/Arrays.stream:([Ljava/lang/Object;)Ljava/util/stream/Stream;        62: invokedynamic #5,  0              // InvokeDynamic #0:test:()Ljava/util/function/Predicate;        67: invokeinterface #6,  2            // InterfaceMethod java/util/stream/Stream.filter:(Ljava/util/function/Predicate;)Ljava/util/stream/Stream;        72: invokedynamic #7,  0              // InvokeDynamic #1:apply:()Ljava/util/function/Function;        77: invokeinterface #8,  2            // InterfaceMethod java/util/stream/Stream.map:(Ljava/util/function/Function;)Ljava/util/stream/Stream;...# 常量池定義，實際是定義了lamda的實現(xiàn)方式為 #0 號方法    #5 = InvokeDynamic      #0:#102       // #0:test:()Ljava/util/function/Predicate;# lamda表達(dá)式的具體實現(xiàn)1示例BootstrapMethods:  0: #98 invokestatic java/lang/invoke/LambdaMetafactory.metafactory:(Ljava/lang/invoke/MethodHandles$Lookup;Ljava/lang/String;Ljava/lang/invoke/MethodType;Ljava/lang/invoke/MethodType;Ljava/lang/invoke/MethodHandle;Ljava/lang/invoke/MethodType;)Ljava/lang/invoke/CallSite;    Method arguments:      #99 (Ljava/lang/Object;)Z      // 此處為調(diào)用具體的實現(xiàn)方法      #100 invokestatic com/my/test/common/util/StreamUtilTest.lambda$testArrayStream$0:(Ljava/lang/Integer;)Z      #101 (Ljava/lang/Integer;)Z  1: #98 invokestatic java/lang/invoke/LambdaMetafactory.metafactory:(Ljava/lang/invoke/MethodHandles$Lookup;Ljava/lang/String;Ljava/lang/invoke/MethodType;Ljava/lang/invoke/MethodType;Ljava/lang/invoke/MethodHandle;Ljava/lang/invoke/MethodType;)Ljava/lang/invoke/CallSite;    Method arguments:      #105 (Ljava/lang/Object;)Ljava/lang/Object;      #106 invokestatic com/my/test/common/util/StreamUtilTest.lambda$testArrayStream$1:(Ljava/lang/Integer;)Ljava/lang/Integer;      #107 (Ljava/lang/Integer;)Ljava/lang/Integer;
# lamda表達(dá)式具體實現(xiàn)2, 上一步的靜態(tài)調(diào)用  private static boolean lambda$testArrayStream$0(java.lang.Integer);    descriptor: (Ljava/lang/Integer;)Z    flags: ACC_PRIVATE, ACC_STATIC, ACC_SYNTHETIC    Code:      stack=2, locals=1, args_size=1         0: aload_0         1: invokevirtual #48                 // Method java/lang/Integer.intValue:()I         4: bipush        20         6: if_icmpge     13         9: iconst_1        10: goto          14        13: iconst_0        14: ireturn      LineNumberTable:        line 16: 0      LocalVariableTable:        Start  Length  Slot  Name   Signature            0      15     0     r   Ljava/lang/Integer;      StackMapTable: number_of_entries = 2        frame_type = 13 /* same */        frame_type = 64 /* same_locals_1_stack_item */          stack = [ int ]    MethodParameters:      Name                           Flags      r                              synthetic

/** * A sequence of elements supporting sequential and parallel aggregate * operations.  The following example illustrates an aggregate operation using * {@link Stream} and {@link IntStream}: * * <pre>{@code *     int sum = widgets.stream() *                      .filter(w -> w.getColor() == RED) *                      .mapToInt(w -> w.getWeight()) *                      .sum(); * }</pre> * * In this example, {@code widgets} is a {@code Collection<Widget>}.  We create * a stream of {@code Widget} objects via {@link Collection#stream Collection.stream()}, * filter it to produce a stream containing only the red widgets, and then * transform it into a stream of {@code int} values representing the weight of * each red widget. Then this stream is summed to produce a total weight. * * <p>In addition to {@code Stream}, which is a stream of object references, * there are primitive specializations for {@link IntStream}, {@link LongStream}, * and {@link DoubleStream}, all of which are referred to as "streams" and * conform to the characteristics and restrictions described here. * * <p>To perform a computation, stream * <a href="package-summary.html#StreamOps">operations</a> are composed into a * <em>stream pipeline</em>.  A stream pipeline consists of a source (which * might be an array, a collection, a generator function, an I/O channel, * etc), zero or more <em>intermediate operations</em> (which transform a * stream into another stream, such as {@link Stream#filter(Predicate)}), and a * <em>terminal operation</em> (which produces a result or side-effect, such * as {@link Stream#count()} or {@link Stream#forEach(Consumer)}). * Streams are lazy; computation on the source data is only performed when the * terminal operation is initiated, and source elements are consumed only * as needed. * * <p>Collections and streams, while bearing some superficial similarities, * have different goals.  Collections are primarily concerned with the efficient * management of, and access to, their elements.  By contrast, streams do not * provide a means to directly access or manipulate their elements, and are * instead concerned with declaratively describing their source and the * computational operations which will be performed in aggregate on that source. * However, if the provided stream operations do not offer the desired * functionality, the {@link #iterator()} and {@link #spliterator()} operations * can be used to perform a controlled traversal. * * <p>A stream pipeline, like the "widgets" example above, can be viewed as * a <em>query</em> on the stream source.  Unless the source was explicitly * designed for concurrent modification (such as a {@link ConcurrentHashMap}), * unpredictable or erroneous behavior may result from modifying the stream * source while it is being queried. * * <p>Most stream operations accept parameters that describe user-specified * behavior, such as the lambda expression {@code w -> w.getWeight()} passed to * {@code mapToInt} in the example above.  To preserve correct behavior, * these <em>behavioral parameters</em>: * <ul> * <li>must be <a href="package-summary.html#NonInterference">non-interfering</a> * (they do not modify the stream source); and</li> * <li>in most cases must be <a href="package-summary.html#Statelessness">stateless</a> * (their result should not depend on any state that might change during execution * of the stream pipeline).</li> * </ul> * * <p>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.  Unless otherwise specified these parameters must be * <em>non-null</em>. * * <p>A stream should be operated on (invoking an intermediate or terminal stream * operation) only once.  This rules out, for example, "forked" streams, where * the same source feeds two or more pipelines, or multiple traversals of the * same stream.  A stream implementation may throw {@link IllegalStateException} * if it detects that the stream is being reused. However, since some stream * operations may return their receiver rather than a new stream object, it may * not be possible to detect reuse in all cases. * * <p>Streams have a {@link #close()} method and implement {@link AutoCloseable}, * but nearly all stream instances do not actually need to be closed after use. * Generally, only streams whose source is an IO channel (such as those returned * by {@link Files#lines(Path, Charset)}) will require closing.  Most streams * are backed by collections, arrays, or generating functions, which require no * special resource management.  (If a stream does require closing, it can be * declared as a resource in a {@code try}-with-resources statement.) * * <p>Stream pipelines may execute either sequentially or in * <a href="package-summary.html#Parallelism">parallel</a>.  This * execution mode is a property of the stream.  Streams are created * with an initial choice of sequential or parallel execution.  (For example, * {@link Collection#stream() Collection.stream()} creates a sequential stream, * and {@link Collection#parallelStream() Collection.parallelStream()} creates * a parallel one.)  This choice of execution mode may be modified by the * {@link #sequential()} or {@link #parallel()} methods, and may be queried with * the {@link #isParallel()} method. * * @param <T> the type of the stream elements * @since 1.8 * @see IntStream * @see LongStream * @see DoubleStream * @see <a href="package-summary.html">java.util.stream</a> */public interface Stream<T> extends BaseStream<T, Stream<T>> {
    /**     * Returns a stream consisting of the elements of this stream that match     * the given predicate.     *     * <p>This is an <a href="package-summary.html#StreamOps">intermediate     * operation</a>.     *     * @param predicate a <a href="package-summary.html#NonInterference">non-interfering</a>,     *                  <a href="package-summary.html#Statelessness">stateless</a>     *                  predicate to apply to each element to determine if it     *                  should be included     * @return the new stream     */    Stream<T> filter(Predicate<? super T> predicate);
    /**     * Returns a stream consisting of the results of applying the given     * function to the elements of this stream.     *     * <p>This is an <a href="package-summary.html#StreamOps">intermediate     * operation</a>.     *     * @param <R> The element type of the new stream     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering</a>,     *               <a href="package-summary.html#Statelessness">stateless</a>     *               function to apply to each element     * @return the new stream     */    <R> Stream<R> map(Function<? super T, ? extends R> mapper);
    /**     * Returns an {@code IntStream} consisting of the results of applying the     * given function to the elements of this stream.     *     * <p>This is an <a href="package-summary.html#StreamOps">     *     intermediate operation</a>.     *     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering</a>,     *               <a href="package-summary.html#Statelessness">stateless</a>     *               function to apply to each element     * @return the new stream     */    IntStream mapToInt(ToIntFunction<? super T> mapper);
    /**     * Returns a {@code LongStream} consisting of the results of applying the     * given function to the elements of this stream.     *     * <p>This is an <a href="package-summary.html#StreamOps">intermediate     * operation</a>.     *     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering</a>,     *               <a href="package-summary.html#Statelessness">stateless</a>     *               function to apply to each element     * @return the new stream     */    LongStream mapToLong(ToLongFunction<? super T> mapper);
    /**     * Returns a {@code DoubleStream} consisting of the results of applying the     * given function to the elements of this stream.     *     * <p>This is an <a href="package-summary.html#StreamOps">intermediate     * operation</a>.     *     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering</a>,     *               <a href="package-summary.html#Statelessness">stateless</a>     *               function to apply to each element     * @return the new stream     */    DoubleStream mapToDouble(ToDoubleFunction<? super T> mapper);
    /**     * Returns a stream consisting of the results of replacing each element of     * this stream with the contents of a mapped stream produced by applying     * the provided mapping function to each element.  Each mapped stream is     * {@link java.util.stream.BaseStream#close() closed} after its contents     * have been placed into this stream.  (If a mapped stream is {@code null}     * an empty stream is used, instead.)     *     * <p>This is an <a href="package-summary.html#StreamOps">intermediate     * operation</a>.     *     * @apiNote     * The {@code flatMap()} operation has the effect of applying a one-to-many     * transformation to the elements of the stream, and then flattening the     * resulting elements into a new stream.     *     * <p><b>Examples.</b>     *     * <p>If {@code orders} is a stream of purchase orders, and each purchase     * order contains a collection of line items, then the following produces a     * stream containing all the line items in all the orders:     * <pre>{@code     *     orders.flatMap(order -> order.getLineItems().stream())...     * }</pre>     *     * <p>If {@code path} is the path to a file, then the following produces a     * stream of the {@code words} contained in that file:     * <pre>{@code     *     Stream<String> lines = Files.lines(path, StandardCharsets.UTF_8);     *     Stream<String> words = lines.flatMap(line -> Stream.of(line.split(" +")));     * }</pre>     * The {@code mapper} function passed to {@code flatMap} splits a line,     * using a simple regular expression, into an array of words, and then     * creates a stream of words from that array.     *     * @param <R> The element type of the new stream     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering</a>,     *               <a href="package-summary.html#Statelessness">stateless</a>     *               function to apply to each element which produces a stream     *               of new values     * @return the new stream     */    <R> Stream<R> flatMap(Function<? super T, ? extends Stream<? extends R>> mapper);
    /**     * Returns an {@code IntStream} consisting of the results of replacing each     * element of this stream with the contents of a mapped stream produced by     * applying the provided mapping function to each element.  Each mapped     * stream is {@link java.util.stream.BaseStream#close() closed} after its     * contents have been placed into this stream.  (If a mapped stream is     * {@code null} an empty stream is used, instead.)     *     * <p>This is an <a href="package-summary.html#StreamOps">intermediate     * operation</a>.     *     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering</a>,     *               <a href="package-summary.html#Statelessness">stateless</a>     *               function to apply to each element which produces a stream     *               of new values     * @return the new stream     * @see #flatMap(Function)     */    IntStream flatMapToInt(Function<? super T, ? extends IntStream> mapper);
    /**     * Returns an {@code LongStream} consisting of the results of replacing each     * element of this stream with the contents of a mapped stream produced by     * applying the provided mapping function to each element.  Each mapped     * stream is {@link java.util.stream.BaseStream#close() closed} after its     * contents have been placed into this stream.  (If a mapped stream is     * {@code null} an empty stream is used, instead.)     *     * <p>This is an <a href="package-summary.html#StreamOps">intermediate     * operation</a>.     *     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering</a>,     *               <a href="package-summary.html#Statelessness">stateless</a>     *               function to apply to each element which produces a stream     *               of new values     * @return the new stream     * @see #flatMap(Function)     */    LongStream flatMapToLong(Function<? super T, ? extends LongStream> mapper);
    /**     * Returns an {@code DoubleStream} consisting of the results of replacing     * each element of this stream with the contents of a mapped stream produced     * by applying the provided mapping function to each element.  Each mapped     * stream is {@link java.util.stream.BaseStream#close() closed} after its     * contents have placed been into this stream.  (If a mapped stream is     * {@code null} an empty stream is used, instead.)     *     * <p>This is an <a href="package-summary.html#StreamOps">intermediate     * operation</a>.     *     * @param mapper a <a href="package-summary.html#NonInterference">non-interfering</a>,     *               <a href="package-summary.html#Statelessness">stateless</a>     *               function to apply to each element which produces a stream     *               of new values     * @return the new stream     * @see #flatMap(Function)     */    DoubleStream flatMapToDouble(Function<? super T, ? extends DoubleStream> mapper);
    /**     * Returns a stream consisting of the distinct elements (according to     * {@link Object#equals(Object)}) of this stream.     *     * <p>For ordered streams, the selection of distinct elements is stable     * (for duplicated elements, the element appearing first in the encounter     * order is preserved.)  For unordered streams, no stability guarantees     * are made.     *     * <p>This is a <a href="package-summary.html#StreamOps">stateful     * intermediate operation</a>.     *     * @apiNote     * Preserving stability for {@code distinct()} in parallel pipelines is     * relatively expensive (requires that the operation act as a full barrier,     * with substantial buffering overhead), and stability is often not needed.     * Using an unordered stream source (such as {@link #generate(Supplier)})     * or removing the ordering constraint with {@link #unordered()} may result     * in significantly more efficient execution for {@code distinct()} in parallel     * pipelines, if the semantics of your situation permit.  If consistency     * with encounter order is required, and you are experiencing poor performance     * or memory utilization with {@code distinct()} in parallel pipelines,     * switching to sequential execution with {@link #sequential()} may improve     * performance.     *     * @return the new stream     */    Stream<T> distinct();
    /**     * Returns a stream consisting of the elements of this stream, sorted     * according to natural order.  If the elements of this stream are not     * {@code Comparable}, a {@code java.lang.ClassCastException} may be thrown     * when the terminal operation is executed.     *     * <p>For ordered streams, the sort is stable.  For unordered streams, no     * stability guarantees are made.     *     * <p>This is a <a href="package-summary.html#StreamOps">stateful     * intermediate operation</a>.     *     * @return the new stream     */    Stream<T> sorted();
    /**     * Returns a stream consisting of the elements of this stream, sorted     * according to the provided {@code Comparator}.     *     * <p>For ordered streams, the sort is stable.  For unordered streams, no     * stability guarantees are made.     *     * <p>This is a <a href="package-summary.html#StreamOps">stateful     * intermediate operation</a>.     *     * @param comparator a <a href="package-summary.html#NonInterference">non-interfering</a>,     *                   <a href="package-summary.html#Statelessness">stateless</a>     *                   {@code Comparator} to be used to compare stream elements     * @return the new stream     */    Stream<T> sorted(Comparator<? super T> comparator);
    /**     * Returns a stream consisting of the elements of this stream, additionally     * performing the provided action on each element as elements are consumed     * from the resulting stream.     *     * <p>This is an <a href="package-summary.html#StreamOps">intermediate     * operation</a>.     *     * <p>For parallel stream pipelines, the action may be called at     * whatever time and in whatever thread the element is made available by the     * upstream operation.  If the action modifies shared state,     * it is responsible for providing the required synchronization.     *     * @apiNote This method exists mainly to support debugging, where you want     * to see the elements as they flow past a certain point in a pipeline:     * <pre>{@code     *     Stream.of("one", "two", "three", "four")     *         .filter(e -> e.length() > 3)     *         .peek(e -> System.out.println("Filtered value: " + e))     *         .map(String::toUpperCase)     *         .peek(e -> System.out.println("Mapped value: " + e))     *         .collect(Collectors.toList());     * }</pre>     *     * @param action a <a href="package-summary.html#NonInterference">     *                 non-interfering</a> action to perform on the elements as     *                 they are consumed from the stream     * @return the new stream     */    Stream<T> peek(Consumer<? super T> action);
    /**     * Returns a stream consisting of the elements of this stream, truncated     * to be no longer than {@code maxSize} in length.     *     * <p>This is a <a href="package-summary.html#StreamOps">short-circuiting     * stateful intermediate operation</a>.     *     * @apiNote     * While {@code limit()} is generally a cheap operation on sequential     * stream pipelines, it can be quite expensive on ordered parallel pipelines,     * especially for large values of {@code maxSize}, since {@code limit(n)}     * is constrained to return not just any <em>n</em> elements, but the     * <em>first n</em> elements in the encounter order.  Using an unordered     * stream source (such as {@link #generate(Supplier)}) or removing the     * ordering constraint with {@link #unordered()} may result in significant     * speedups of {@code limit()} in parallel pipelines, if the semantics of     * your situation permit.  If consistency with encounter order is required,     * and you are experiencing poor performance or memory utilization with     * {@code limit()} in parallel pipelines, switching to sequential execution     * with {@link #sequential()} may improve performance.     *     * @param maxSize the number of elements the stream should be limited to     * @return the new stream     * @throws IllegalArgumentException if {@code maxSize} is negative     */    Stream<T> limit(long maxSize);
    /**     * Returns a stream consisting of the remaining elements of this stream     * after discarding the first {@code n} elements of the stream.     * If this stream contains fewer than {@code n} elements then an     * empty stream will be returned.     *     * <p>This is a <a href="package-summary.html#StreamOps">stateful     * intermediate operation</a>.     *     * @apiNote     * While {@code skip()} is generally a cheap operation on sequential     * stream pipelines, it can be quite expensive on ordered parallel pipelines,     * especially for large values of {@code n}, since {@code skip(n)}     * is constrained to skip not just any <em>n</em> elements, but the     * <em>first n</em> elements in the encounter order.  Using an unordered     * stream source (such as {@link #generate(Supplier)}) or removing the     * ordering constraint with {@link #unordered()} may result in significant     * speedups of {@code skip()} in parallel pipelines, if the semantics of     * your situation permit.  If consistency with encounter order is required,     * and you are experiencing poor performance or memory utilization with     * {@code skip()} in parallel pipelines, switching to sequential execution     * with {@link #sequential()} may improve performance.     *     * @param n the number of leading elements to skip     * @return the new stream     * @throws IllegalArgumentException if {@code n} is negative     */    Stream<T> skip(long n);
    /**     * Performs an action for each element of this stream.     *     * <p>This is a <a href="package-summary.html#StreamOps">terminal     * operation</a>.     *     * <p>The behavior of this operation is explicitly nondeterministic.     * For parallel stream pipelines, this operation does <em>not</em>     * guarantee to respect the encounter order of the stream, as doing so     * would sacrifice the benefit of parallelism.  For any given element, the     * action may be performed at whatever time and in whatever thread the     * library chooses.  If the action accesses shared state, it is     * responsible for providing the required synchronization.     *     * @param action a <a href="package-summary.html#NonInterference">     *               non-interfering</a> action to perform on the elements     */    void forEach(Consumer<? super T> action);
    /**     * Performs an action for each element of this stream, in the encounter     * order of the stream if the stream has a defined encounter order.     *     * <p>This is a <a href="package-summary.html#StreamOps">terminal     * operation</a>.     *     * <p>This operation processes the elements one at a time, in encounter     * order if one exists.  Performing the action for one element     * <a href="../concurrent/package-summary.html#MemoryVisibility"><i>happens-before</i></a>     * performing the action for subsequent elements, but for any given element,     * the action may be performed in whatever thread the library chooses.     *     * @param action a <a href="package-summary.html#NonInterference">     *               non-interfering</a> action to perform on the elements     * @see #forEach(Consumer)     */    void forEachOrdered(Consumer<? super T> action);
    /**     * Returns an array containing the elements of this stream.     *     * <p>This is a <a href="package-summary.html#StreamOps">terminal     * operation</a>.     *     * @return an array containing the elements of this stream     */    Object[] toArray();
    /**     * Returns an array containing the elements of this stream, using the     * provided {@code generator} function to allocate the returned array, as     * well as any additional arrays that might be required for a partitioned     * execution or for resizing.     *     * <p>This is a <a href="package-summary.html#StreamOps">terminal     * operation</a>.     *     * @apiNote     * The generator function takes an integer, which is the size of the     * desired array, and produces an array of the desired size.  This can be     * concisely expressed with an array constructor reference:     * <pre>{@code     *     Person[] men = people.stream()     *                          .filter(p -> p.getGender() == MALE)     *                          .toArray(Person[]::new);     * }</pre>     *     * @param <A> the element type of the resulting array     * @param generator a function which produces a new array of the desired     *                  type and the provided length     * @return an array containing the elements in this stream     * @throws ArrayStoreException if the runtime type of the array returned     * from the array generator is not a supertype of the runtime type of every     * element in this stream     */    <A> A[] toArray(IntFunction<A[]> generator);
    /**     * Performs a <a href="package-summary.html#Reduction">reduction</a> on the     * elements of this stream, using the provided identity value and an     * <a href="package-summary.html#Associativity">associative</a>     * accumulation function, and returns the reduced value.  This is equivalent     * to:     * <pre>{@code     *     T result = identity;     *     for (T element : this stream)     *         result = accumulator.apply(result, element)     *     return result;     * }</pre>     *     * but is not constrained to execute sequentially.     *     * <p>The {@code identity} value must be an identity for the accumulator     * function. This means that for all {@code t},     * {@code accumulator.apply(identity, t)} is equal to {@code t}.     * The {@code accumulator} function must be an     * <a href="package-summary.html#Associativity">associative</a> function.     *     * <p>This is a <a href="package-summary.html#StreamOps">terminal     * operation</a>.     *     * @apiNote Sum, min, max, average, and string concatenation are all special     * cases of reduction. Summing a stream of numbers can be expressed as:     *     * <pre>{@code     *     Integer sum = integers.reduce(0, (a, b) -> a+b);     * }</pre>     *     * or:     *     * <pre>{@code     *     Integer sum = integers.reduce(0, Integer::sum);     * }</pre>     *     * <p>While this may seem a more roundabout way to perform an aggregation     * compared to simply mutating a running total in a loop, reduction     * operations parallelize more gracefully, without needing additional     * synchronization and with greatly reduced risk of data races.     *     * @param identity the identity value for the accumulating function     * @param accumulator an <a href="package-summary.html#Associativity">associative</a>,     *                    <a href="package-summary.html#NonInterference">non-interfering</a>,     *                    <a href="package-summary.html#Statelessness">stateless</a>     *                    function for combining two values     * @return the result of the reduction     */    T reduce(T identity, BinaryOperator<T> accumulator);
    /**     * Performs a <a href="package-summary.html#Reduction">reduction</a> on the     * elements of this stream, using an     * <a href="package-summary.html#Associativity">associative</a> accumulation     * function, and returns an {@code Optional} describing the reduced value,     * if any. This is equivalent to:     * <pre>{@code     *     boolean foundAny = false;     *     T result = null;     *     for (T element : this stream) {     *         if (!foundAny) {     *             foundAny = true;     *             result = element;     *         }     *         else     *             result = accumulator.apply(result, element);     *     }     *     return foundAny ? Optional.of(result) : Optional.empty();     * }</pre>     *     * but is not constrained to execute sequentially.     *     * <p>The {@code accumulator} function must be an     * <a href="package-summary.html#Associativity">associative</a> function.     *     * <p>This is a <a href="package-summary.html#StreamOps">terminal     * operation</a>.     *     * @param accumulator an <a href="package-summary.html#Associativity">associative</a>,     *                    <a href="package-summary.html#NonInterference">non-interfering</a>,     *                    <a href="package-summary.html#Statelessness">stateless</a>     *                    function for combining two values     * @return an {@link Optional} describing the result of the reduction     * @throws NullPointerException if the result of the reduction is null     * @see #reduce(Object, BinaryOperator)     * @see #min(Comparator)     * @see #max(Comparator)     */    Optional<T> reduce(BinaryOperator<T> accumulator);
    /**     * Performs a <a href="package-summary.html#Reduction">reduction</a> on the     * elements of this stream, using the provided identity, accumulation and     * combining functions.  This is equivalent to:     * <pre>{@code     *     U result = identity;     *     for (T element : this stream)     *         result = accumulator.apply(result, element)     *     return result;     * }</pre>     *     * but is not constrained to execute sequentially.     *     * <p>The {@code identity} value must be an identity for the combiner     * function.  This means that for all {@code u}, {@code combiner(identity, u)}     * is equal to {@code u}.  Additionally, the {@code combiner} function     * must be compatible with the {@code accumulator} function; for all     * {@code u} and {@code t}, the following must hold:     * <pre>{@code     *     combiner.apply(u, accumulator.apply(identity, t)) == accumulator.apply(u, t)     * }</pre>     *     * <p>This is a <a href="package-summary.html#StreamOps">terminal     * operation</a>.     *     * @apiNote Many reductions using this form can be represented more simply     * by an explicit combination of {@code map} and {@code reduce} operations.     * The {@code accumulator} function acts as a fused mapper and accumulator,     * which can sometimes be more efficient than separate mapping and reduction,     * such as when knowing the previously reduced value allows you to avoid     * some computation.     *     * @param <U> The type of the result     * @param identity the identity value for the combiner function     * @param accumulator an <a href="package-summary.html#Associativity">associative</a>,     *                    <a href="package-summary.html#NonInterference">non-interfering</a>,     *                    <a href="package-summary.html#Statelessness">stateless</a>     *                    function for incorporating an additional element into a result     * @param combiner an <a href="package-summary.html#Associativity">associative</a>,     *                    <a href="package-summary.html#NonInterference">non-interfering</a>,     *                    <a href="package-summary.html#Statelessness">stateless</a>     *                    function for combining two values, which must be     *                    compatible with the accumulator function     * @return the result of the reduction     * @see #reduce(BinaryOperator)     * @see #reduce(Object, BinaryOperator)     */    <U> U reduce(U identity,                 BiFunction<U, ? super T, U> accumulator,                 BinaryOperator<U> combiner);
    /**     * Performs a <a href="package-summary.html#MutableReduction">mutable     * reduction</a> operation on the elements of this stream.  A mutable     * reduction is one in which the reduced value is a mutable result container,     * such as an {@code ArrayList}, and elements are incorporated by updating     * the state of the result rather than by replacing the result.  This     * produces a result equivalent to:     * <pre>{@code     *     R result = supplier.get();     *     for (T element : this stream)     *         accumulator.accept(result, element);     *     return result;     * }</pre>     *     * <p>Like {@link #reduce(Object, BinaryOperator)}, {@code collect} operations     * can be parallelized without requiring additional synchronization.     *     * <p>This is a <a href="package-summary.html#StreamOps">terminal     * operation</a>.     *     * @apiNote There are many existing classes in the JDK whose signatures are     * well-suited for use with method references as arguments to {@code collect()}.     * For example, the following will accumulate strings into an {@code ArrayList}:     * <pre>{@code     *     List<String> asList = stringStream.collect(ArrayList::new, ArrayList::add,     *                                                ArrayList::addAll);     * }</pre>     *     * <p>The following will take a stream of strings and concatenates them into a     * single string:     * <pre>{@code     *     String concat = stringStream.collect(StringBuilder::new, StringBuilder::append,     *                                          StringBuilder::append)     *                                 .toString();     * }</pre>     *     * @param <R> type of the result     * @param supplier a function that creates a new result container. For a     *                 parallel execution, this function may be called     *                 multiple times and must return a fresh value each time.     * @param accumulator an <a href="package-summary.html#Associativity">associative</a>,     *                    <a href="package-summary.html#NonInterference">non-interfering</a>,     *                    <a href="package-summary.html#Statelessness">stateless</a>     *                    function for incorporating an additional element into a result     * @param combiner an <a href="package-summary.html#Associativity">associative</a>,     *                    <a href="package-summary.html#NonInterference">non-interfering</a>,     *                    <a href="package-summary.html#Statelessness">stateless</a>     *                    function for combining two values, which must be     *                    compatible with the accumulator function     * @return the result of the reduction     */    <R> R collect(Supplier<R> supplier,                  BiConsumer<R, ? super T> accumulator,                  BiConsumer<R, R> combiner);
    /**     * Performs a <a href="package-summary.html#MutableReduction">mutable     * reduction</a> operation on the elements of this stream using a     * {@code Collector}.  A {@code Collector}     * encapsulates the functions used as arguments to     * {@link #collect(Supplier, BiConsumer, BiConsumer)}, allowing for reuse of     * collection strategies and composition of collect operations such as     * multiple-level grouping or partitioning.     *     * <p>If the stream is parallel, and the {@code Collector}     * is {@link Collector.Characteristics#CONCURRENT concurrent}, and     * either the stream is unordered or the collector is     * {@link Collector.Characteristics#UNORDERED unordered},     * then a concurrent reduction will be performed (see {@link Collector} for     * details on concurrent reduction.)     *     * <p>This is a <a href="package-summary.html#StreamOps">terminal     * operation</a>.     *     * <p>When executed in parallel, multiple intermediate results may be     * instantiated, populated, and merged so as to maintain isolation of     * mutable data structures.  Therefore, even when executed in parallel     * with non-thread-safe data structures (such as {@code ArrayList}), no     * additional synchronization is needed for a parallel reduction.     *     * @apiNote     * The following will accumulate strings into an ArrayList:     * <pre>{@code     *     List<String> asList = stringStream.collect(Collectors.toList());     * }</pre>     *     * <p>The following will classify {@code Person} objects by city:     * <pre>{@code     *     Map<String, List<Person>> peopleByCity     *         = personStream.collect(Collectors.groupingBy(Person::getCity));     * }</pre>     *     * <p>The following will classify {@code Person} objects by state and city,     * cascading two {@code Collector}s together:     * <pre>{@code     *     Map<String, Map<String, List<Person>>> peopleByStateAndCity     *         = personStream.collect(Collectors.groupingBy(Person::getState,     *                                                      Collectors.groupingBy(Person::getCity)));     * }</pre>     *     * @param <R> the type of the result     * @param <A> the intermediate accumulation type of the {@code Collector}     * @param collector the {@code Collector} describing the reduction     * @return the result of the reduction     * @see #collect(Supplier, BiConsumer, BiConsumer)     * @see Collectors     */    <R, A> R collect(Collector<? super T, A, R> collector);
    /**     * Returns the minimum element of this stream according to the provided     * {@code Comparator}.  This is a special case of a     * <a href="package-summary.html#Reduction">reduction</a>.     *     * <p>This is a <a href="package-summary.html#StreamOps">terminal operation</a>.     *     * @param comparator a <a href="package-summary.html#NonInterference">non-interfering</a>,     *                   <a href="package-summary.html#Statelessness">stateless</a>     *                   {@code Comparator} to compare elements of this stream     * @return an {@code Optional} describing the minimum element of this stream,     * or an empty {@code Optional} if the stream is empty     * @throws NullPointerException if the minimum element is null     */    Optional<T> min(Comparator<? super T> comparator);
    /**     * Returns the maximum element of this stream according to the provided     * {@code Comparator}.  This is a special case of a     * <a href="package-summary.html#Reduction">reduction</a>.     *     * <p>This is a <a href="package-summary.html#StreamOps">terminal     * operation</a>.     *     * @param comparator a <a href="package-summary.html#NonInterference">non-interfering</a>,     *                   <a href="package-summary.html#Statelessness">stateless</a>     *                   {@code Comparator} to compare elements of this stream     * @return an {@code Optional} describing the maximum element of this stream,     * or an empty {@code Optional} if the stream is empty     * @throws NullPointerException if the maximum element is null     */    Optional<T> max(Comparator<? super T> comparator);
    /**     * Returns the count of elements in this stream.  This is a special case of     * a <a href="package-summary.html#Reduction">reduction</a> and is     * equivalent to:     * <pre>{@code     *     return mapToLong(e -> 1L).sum();     * }</pre>     *     * <p>This is a <a href="package-summary.html#StreamOps">terminal operation</a>.     *     * @return the count of elements in this stream     */    long count();
    /**     * Returns whether any elements of this stream match the provided     * predicate.  May not evaluate the predicate on all elements if not     * necessary for determining the result.  If the stream is empty then     * {@code false} is returned and the predicate is not evaluated.     *     * <p>This is a <a href="package-summary.html#StreamOps">short-circuiting     * terminal operation</a>.     *     * @apiNote     * This method evaluates the <em>existential quantification</em> of the     * predicate over the elements of the stream (for some x P(x)).     *     * @param predicate a <a href="package-summary.html#NonInterference">non-interfering</a>,     *                  <a href="package-summary.html#Statelessness">stateless</a>     *                  predicate to apply to elements of this stream     * @return {@code true} if any elements of the stream match the provided     * predicate, otherwise {@code false}     */    boolean anyMatch(Predicate<? super T> predicate);
    /**     * Returns whether all elements of this stream match the provided predicate.     * May not evaluate the predicate on all elements if not necessary for     * determining the result.  If the stream is empty then {@code true} is     * returned and the predicate is not evaluated.     *     * <p>This is a <a href="package-summary.html#StreamOps">short-circuiting     * terminal operation</a>.     *     * @apiNote     * This method evaluates the <em>universal quantification</em> of the     * predicate over the elements of the stream (for all x P(x)).  If the     * stream is empty, the quantification is said to be <em>vacuously     * satisfied</em> and is always {@code true} (regardless of P(x)).     *     * @param predicate a <a href="package-summary.html#NonInterference">non-interfering</a>,     *                  <a href="package-summary.html#Statelessness">stateless</a>     *                  predicate to apply to elements of this stream     * @return {@code true} if either all elements of the stream match the     * provided predicate or the stream is empty, otherwise {@code false}     */    boolean allMatch(Predicate<? super T> predicate);
    /**     * Returns whether no elements of this stream match the provided predicate.     * May not evaluate the predicate on all elements if not necessary for     * determining the result.  If the stream is empty then {@code true} is     * returned and the predicate is not evaluated.     *     * <p>This is a <a href="package-summary.html#StreamOps">short-circuiting     * terminal operation</a>.     *     * @apiNote     * This method evaluates the <em>universal quantification</em> of the     * negated predicate over the elements of the stream (for all x ~P(x)).  If     * the stream is empty, the quantification is said to be vacuously satisfied     * and is always {@code true}, regardless of P(x).     *     * @param predicate a <a href="package-summary.html#NonInterference">non-interfering</a>,     *                  <a href="package-summary.html#Statelessness">stateless</a>     *                  predicate to apply to elements of this stream     * @return {@code true} if either no elements of the stream match the     * provided predicate or the stream is empty, otherwise {@code false}     */    boolean noneMatch(Predicate<? super T> predicate);
    /**     * Returns an {@link Optional} describing the first element of this stream,     * or an empty {@code Optional} if the stream is empty.  If the stream has     * no encounter order, then any element may be returned.     *     * <p>This is a <a href="package-summary.html#StreamOps">short-circuiting     * terminal operation</a>.     *     * @return an {@code Optional} describing the first element of this stream,     * or an empty {@code Optional} if the stream is empty     * @throws NullPointerException if the element selected is null     */    Optional<T> findFirst();
    /**     * Returns an {@link Optional} describing some element of the stream, or an     * empty {@code Optional} if the stream is empty.     *     * <p>This is a <a href="package-summary.html#StreamOps">short-circuiting     * terminal operation</a>.     *     * <p>The behavior of this operation is explicitly nondeterministic; it is     * free to select any element in the stream.  This is to allow for maximal     * performance in parallel operations; the cost is that multiple invocations     * on the same source may not return the same result.  (If a stable result     * is desired, use {@link #findFirst()} instead.)     *     * @return an {@code Optional} describing some element of this stream, or an     * empty {@code Optional} if the stream is empty     * @throws NullPointerException if the element selected is null     * @see #findFirst()     */    Optional<T> findAny();
    // Static factories
    /**     * Returns a builder for a {@code Stream}.     *     * @param <T> type of elements     * @return a stream builder     */    public static<T> Builder<T> builder() {        return new Streams.StreamBuilderImpl<>();    }
    /**     * Returns an empty sequential {@code Stream}.     *     * @param <T> the type of stream elements     * @return an empty sequential stream     */    public static<T> Stream<T> empty() {        return StreamSupport.stream(Spliterators.<T>emptySpliterator(), false);    }
    /**     * Returns a sequential {@code Stream} containing a single element.     *     * @param t the single element     * @param <T> the type of stream elements     * @return a singleton sequential stream     */    public static<T> Stream<T> of(T t) {        return StreamSupport.stream(new Streams.StreamBuilderImpl<>(t), false);    }
    /**     * Returns a sequential ordered stream whose elements are the specified values.     *     * @param <T> the type of stream elements     * @param values the elements of the new stream     * @return the new stream     */    @SafeVarargs    @SuppressWarnings("varargs") // Creating a stream from an array is safe    public static<T> Stream<T> of(T... values) {        return Arrays.stream(values);    }
    /**     * Returns an infinite sequential ordered {@code Stream} produced by iterative     * application of a function {@code f} to an initial element {@code seed},     * producing a {@code Stream} consisting of {@code seed}, {@code f(seed)},     * {@code f(f(seed))}, etc.     *     * <p>The first element (position {@code 0}) in the {@code Stream} will be     * the provided {@code seed}.  For {@code n > 0}, the element at position     * {@code n}, will be the result of applying the function {@code f} to the     * element at position {@code n - 1}.     *     * @param <T> the type of stream elements     * @param seed the initial element     * @param f a function to be applied to to the previous element to produce     *          a new element     * @return a new sequential {@code Stream}     */    public static<T> Stream<T> iterate(final T seed, final UnaryOperator<T> f) {        Objects.requireNonNull(f);        final Iterator<T> iterator = new Iterator<T>() {            @SuppressWarnings("unchecked")            T t = (T) Streams.NONE;
            @Override            public boolean hasNext() {                return true;            }
            @Override            public T next() {                return t = (t == Streams.NONE) ? seed : f.apply(t);            }        };        return StreamSupport.stream(Spliterators.spliteratorUnknownSize(                iterator,                Spliterator.ORDERED | Spliterator.IMMUTABLE), false);    }
    /**     * Returns an infinite sequential unordered stream where each element is     * generated by the provided {@code Supplier}.  This is suitable for     * generating constant streams, streams of random elements, etc.     *     * @param <T> the type of stream elements     * @param s the {@code Supplier} of generated elements     * @return a new infinite sequential unordered {@code Stream}     */    public static<T> Stream<T> generate(Supplier<T> s) {        Objects.requireNonNull(s);        return StreamSupport.stream(                new StreamSpliterators.InfiniteSupplyingSpliterator.OfRef<>(Long.MAX_VALUE, s), false);    }
    /**     * Creates a lazily concatenated stream whose elements are all the     * elements of the first stream followed by all the elements of the     * second stream.  The resulting stream is ordered if both     * of the input streams are ordered, and parallel if either of the input     * streams is parallel.  When the resulting stream is closed, the close     * handlers for both input streams are invoked.     *     * @implNote     * Use caution when constructing streams from repeated concatenation.     * Accessing an element of a deeply concatenated stream can result in deep     * call chains, or even {@code StackOverflowException}.     *     * @param <T> The type of stream elements     * @param a the first stream     * @param b the second stream     * @return the concatenation of the two input streams     */    public static <T> Stream<T> concat(Stream<? extends T> a, Stream<? extends T> b) {        Objects.requireNonNull(a);        Objects.requireNonNull(b);
        @SuppressWarnings("unchecked")        Spliterator<T> split = new Streams.ConcatSpliterator.OfRef<>(                (Spliterator<T>) a.spliterator(), (Spliterator<T>) b.spliterator());        Stream<T> stream = StreamSupport.stream(split, a.isParallel() || b.isParallel());        return stream.onClose(Streams.composedClose(a, b));    }
    /**     * A mutable builder for a {@code Stream}.  This allows the creation of a     * {@code Stream} by generating elements individually and adding them to the     * {@code Builder} (without the copying overhead that comes from using     * an {@code ArrayList} as a temporary buffer.)     *     * <p>A stream builder has a lifecycle, which starts in a building     * phase, during which elements can be added, and then transitions to a built     * phase, after which elements may not be added.  The built phase begins     * when the {@link #build()} method is called, which creates an ordered     * {@code Stream} whose elements are the elements that were added to the stream     * builder, in the order they were added.     *     * @param <T> the type of stream elements     * @see Stream#builder()     * @since 1.8     */    public interface Builder<T> extends Consumer<T> {
        /**         * Adds an element to the stream being built.         *         * @throws IllegalStateException if the builder has already transitioned to         * the built state         */        @Override        void accept(T t);
        /**         * Adds an element to the stream being built.         *         * @implSpec         * The default implementation behaves as if:         * <pre>{@code         *     accept(t)         *     return this;         * }</pre>         *         * @param t the element to add         * @return {@code this} builder         * @throws IllegalStateException if the builder has already transitioned to         * the built state         */        default Builder<T> add(T t) {            accept(t);            return this;        }
        /**         * Builds the stream, transitioning this builder to the built state.         * An {@code IllegalStateException} is thrown if there are further attempts         * to operate on the builder after it has entered the built state.         *         * @return the built stream         * @throws IllegalStateException if the builder has already transitioned to         * the built state         */        Stream<T> build();
    }}

// java.util.Arrays#stream(T[])    /**     * Returns a sequential {@link Stream} with the specified array as its     * source.     *     * @param <T> The type of the array elements     * @param array The array, assumed to be unmodified during use     * @return a {@code Stream} for the array     * @since 1.8     */    public static <T> Stream<T> stream(T[] array) {        return stream(array, 0, array.length);    }    // java.util.Arrays#stream(T[], int, int)    /**     * Returns a sequential {@link Stream} with the specified range of the     * specified array as its source.     *     * @param <T> the type of the array elements     * @param array the array, assumed to be unmodified during use     * @param startInclusive the first index to cover, inclusive     * @param endExclusive index immediately past the last index to cover     * @return a {@code Stream} for the array range     * @throws ArrayIndexOutOfBoundsException if {@code startInclusive} is     *         negative, {@code endExclusive} is less than     *         {@code startInclusive}, or {@code endExclusive} is greater than     *         the array size     * @since 1.8     */    public static <T> Stream<T> stream(T[] array, int startInclusive, int endExclusive) {        // 構(gòu)造 iterator, 帶入 StreamSupport 中        return StreamSupport.stream(spliterator(array, startInclusive, endExclusive), false);    }
    /**     * Returns a {@link Spliterator} covering the specified range of the     * specified array.     *     * <p>The spliterator reports {@link Spliterator#SIZED},     * {@link Spliterator#SUBSIZED}, {@link Spliterator#ORDERED}, and     * {@link Spliterator#IMMUTABLE}.     *     * @param <T> type of elements     * @param array the array, assumed to be unmodified during use     * @param startInclusive the first index to cover, inclusive     * @param endExclusive index immediately past the last index to cover     * @return a spliterator for the array elements     * @throws ArrayIndexOutOfBoundsException if {@code startInclusive} is     *         negative, {@code endExclusive} is less than     *         {@code startInclusive}, or {@code endExclusive} is greater than     *         the array size     * @since 1.8     */    public static <T> Spliterator<T> spliterator(T[] array, int startInclusive, int endExclusive) {        return Spliterators.spliterator(array, startInclusive, endExclusive,                                        Spliterator.ORDERED | Spliterator.IMMUTABLE);    }    // java.util.stream.StreamSupport#stream(java.util.Spliterator<T>, boolean)    /**     * 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);    }        // java.util.stream.ReferencePipeline.Head#Head(java.util.Spliterator<?>, int, boolean)        /**         * 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);        }    // java.util.stream.ReferencePipeline#ReferencePipeline(java.util.Spliterator<?>, int, boolean)    /**     * 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);    }    // java.util.stream.AbstractPipeline#AbstractPipeline(java.util.Spliterator<?>, int, boolean)    /**     * 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;    }    如上，就返回了一 Stream 的具體實例，即是 ReferencePipeline.Head 的實例。故而，之后的每個stream操作如 filter,map,foreach方法，都盡在該 head 中進行實現(xiàn)了。一瞅便知。    // java.util.stream.ReferencePipeline#filter    @Override    public final Stream<P_OUT> filter(Predicate<? super P_OUT> predicate) {        Objects.requireNonNull(predicate);        // 只返回了一個 StreamlessOp實例        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) {                        // 在必要時候調(diào)用 test() 方法即可                        // 當(dāng)test返回 true 時，該元素被保留傳入下一級調(diào)用中，此即filter的語義                        if (predicate.test(u))                            downstream.accept(u);                    }                };            }        };    }    // java.util.stream.ReferencePipeline#map    @Override    @SuppressWarnings("unchecked")    public final <R> Stream<R> map(Function<? super P_OUT, ? extends R> mapper) {        Objects.requireNonNull(mapper);        // 同樣，僅返回一個 StatelessOp 的實例        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) {                        // 同樣，在必要的時候調(diào)用 apply 方法                        // 即 map 的語義為 每個元素都會調(diào)用該方法                        downstream.accept(mapper.apply(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) {                        // flatmap 語義，所得結(jié)果，依次往下傳輸                        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);                        }                    }                };            }        };    }

// java.util.stream.ReferencePipeline#collect(java.util.stream.Collector<? super P_OUT,A,R>)    @Override    @SuppressWarnings("unchecked")    public final <R, A> R collect(Collector<? super P_OUT, A, R> collector) {        A container;        // 即分并行與串行        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 {            // 串行執(zhí)行            container = evaluate(ReduceOps.makeRef(collector));        }        return collector.characteristics().contains(Collector.Characteristics.IDENTITY_FINISH)               ? (R) container               : collector.finisher().apply(container);    }
    /**     * 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);            }        }        // 返回ReuceOp        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;            }        };    }
    // 運算一系列任務(wù)    /**     * 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()));    }
        // java.util.stream.ReduceOps.ReduceOp#evaluateSequential        @Override        public <P_IN> R evaluateSequential(PipelineHelper<T> helper,                                           Spliterator<P_IN> spliterator) {            return helper.wrapAndCopyInto(makeSink(), spliterator).get();        }
    // java.util.stream.AbstractPipeline#wrapAndCopyInto    @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;    }
    // java.util.stream.AbstractPipeline#wrapSink    @Override    @SuppressWarnings("unchecked")    final <P_IN> Sink<P_IN> wrapSink(Sink<E_OUT> sink) {        Objects.requireNonNull(sink);        // 基本是按照倒序來排的        for ( @SuppressWarnings("rawtypes") AbstractPipeline p=AbstractPipeline.this; p.depth > 0; p=p.previousStage) {            // 一層層包裝算子            sink = p.opWrapSink(p.previousStage.combinedFlags, sink);        }        return (Sink<P_IN>) sink;    }
    // java.util.stream.AbstractPipeline#copyInto    @Override    final <P_IN> void copyInto(Sink<P_IN> wrappedSink, Spliterator<P_IN> spliterator) {        Objects.requireNonNull(wrappedSink);        // 依次調(diào)用 begin, foreach, end 方法        if (!StreamOpFlag.SHORT_CIRCUIT.isKnown(getStreamAndOpFlags())) {            wrappedSink.begin(spliterator.getExactSizeIfKnown());            // 每個元素依次迭代, 一層層退出來            spliterator.forEachRemaining(wrappedSink);            wrappedSink.end();        }        else {            copyIntoWithCancel(wrappedSink, spliterator);        }    }
        // java.util.Spliterators.ArraySpliterator#forEachRemaining        @SuppressWarnings("unchecked")        @Override        public void forEachRemaining(Consumer<? super T> action) {            Object[] a; int i, hi; // hoist accesses and checks from loop            if (action == null)                throw new NullPointerException();            if ((a = array).length >= (hi = fence) &&                (i = index) >= 0 && i < (index = hi)) {                do { action.accept((T)a[i]); } while (++i < hi);            }        }

@FunctionalInterfacepublic interface Consumer<T> {
    /**     * Performs this operation on the given argument.     *     * @param t the input argument     */    void accept(T t);
    /**     * Returns a composed {@code Consumer} that performs, in sequence, this     * operation followed by the {@code after} operation. If performing either     * operation throws an exception, it is relayed to the caller of the     * composed operation.  If performing this operation throws an exception,     * the {@code after} operation will not be performed.     *     * @param after the operation to perform after this operation     * @return a composed {@code Consumer} that performs in sequence this     * operation followed by the {@code after} operation     * @throws NullPointerException if {@code after} is null     */    default Consumer<T> andThen(Consumer<? super T> after) {        Objects.requireNonNull(after);        return (T t) -> { accept(t); after.accept(t); };    }}@FunctionalInterfacepublic interface Function<T, R> {
    /**     * Applies this function to the given argument.     *     * @param t the function argument     * @return the function result     */    R apply(T t);
    /**     * Returns a composed function that first applies the {@code before}     * function to its input, and then applies this function to the result.     * If evaluation of either function throws an exception, it is relayed to     * the caller of the composed function.     *     * @param <V> the type of input to the {@code before} function, and to the     *           composed function     * @param before the function to apply before this function is applied     * @return a composed function that first applies the {@code before}     * function and then applies this function     * @throws NullPointerException if before is null     *     * @see #andThen(Function)     */    default <V> Function<V, R> compose(Function<? super V, ? extends T> before) {        Objects.requireNonNull(before);        return (V v) -> apply(before.apply(v));    }
    /**     * Returns a composed function that first applies this function to     * its input, and then applies the {@code after} function to the result.     * If evaluation of either function throws an exception, it is relayed to     * the caller of the composed function.     *     * @param <V> the type of output of the {@code after} function, and of the     *           composed function     * @param after the function to apply after this function is applied     * @return a composed function that first applies this function and then     * applies the {@code after} function     * @throws NullPointerException if after is null     *     * @see #compose(Function)     */    default <V> Function<T, V> andThen(Function<? super R, ? extends V> after) {        Objects.requireNonNull(after);        return (T t) -> after.apply(apply(t));    }
    /**     * Returns a function that always returns its input argument.     *     * @param <T> the type of the input and output objects to the function     * @return a function that always returns its input argument     */    static <T> Function<T, T> identity() {        return t -> t;    }}
@FunctionalInterfacepublic interface Supplier<T> {
    /**     * Gets a result.     *     * @return a result     */    T get();}