# Interface Stream<T>

Type Parameters:
  `T` - the type of the stream elements

All Superinterfaces:
  `AutoCloseable, BaseStream<T, Stream<T>>`

public interface Stream<T> extends BaseStream<T, Stream<T>>
A sequence of elements supporting sequential and parallel aggregate operations. The following example illustrates an aggregate operation using `Stream` and `IntStream`:

        int sum = widgets.stream()
                         .filter(w -> w.getColor() == RED)
                         .mapToInt(w -> w.getWeight())
                         .sum();

In this example, `widgets` is a `Collection<Widget>`. We create a stream of `Widget` objects via `Collection.stream()`, filter it to produce a stream containing only the red widgets, and then transform it into a stream of `int` values representing the weight of each red widget. Then this stream is summed to produce a total weight.

In addition to `Stream`, which is a stream of object references, there are primitive specializations for `IntStream`, `LongStream`, and `DoubleStream`, all of which are referred to as "streams" and conform to the characteristics and restrictions described here.

To perform a computation, stream operations are composed into a stream pipeline. 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 intermediate operations (which transform a stream into another stream, such as `filter(Predicate)`), and a terminal operation (which produces a result or side-effect, such as `count()` or `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.

A stream implementation is permitted significant latitude in optimizing the computation of the result. For example, a stream implementation is free to elide operations (or entire stages) from a stream pipeline -- and therefore elide invocation of behavioral parameters -- if it can prove that it would not affect the result of the computation. This means that side-effects of behavioral parameters may not always be executed and should not be relied upon, unless otherwise specified (such as by the terminal operations `forEach` and `forEachOrdered`). (For a specific example of such an optimization, see the API note documented on the `count()` operation. For more detail, see the side-effects section of the stream package documentation.)

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 `BaseStream.iterator()` and `BaseStream.spliterator()` operations can be used to perform a controlled traversal.

A stream pipeline, like the "widgets" example above, can be viewed as a query on the stream source. Unless the source was explicitly designed for concurrent modification (such as a `ConcurrentHashMap`), unpredictable or erroneous behavior may result from modifying the stream source while it is being queried.

Most stream operations accept parameters that describe user-specified behavior, such as the lambda expression `w -> w.getWeight()` passed to `mapToInt` in the example above. To preserve correct behavior, these behavioral parameters:

- must be non-interfering (they do not modify the stream source); and
- in most cases must be stateless (their result should not depend on any state that might change during execution of the stream pipeline).

Such parameters are always instances of a functional interface such as `Function`, and are often lambda expressions or method references. Unless otherwise specified these parameters must be non-null.

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 `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.

Streams have a `BaseStream.close()` method and implement `AutoCloseable`. Operating on a stream after it has been closed will throw `IllegalStateException`. Most stream instances do not actually need to be closed after use, as they are backed by collections, arrays, or generating functions, which require no special resource management. Generally, only streams whose source is an IO channel, such as those returned by `Files.lines(Path)`, will require closing. If a stream does require closing, it must be opened as a resource within a try-with-resources statement or similar control structure to ensure that it is closed promptly after its operations have completed.

Stream pipelines may execute either sequentially or in parallel. This execution mode is a property of the stream. Streams are created with an initial choice of sequential or parallel execution. (For example, `Collection.stream()` creates a sequential stream, and `Collection.parallelStream()` creates a parallel one.) This choice of execution mode may be modified by the `BaseStream.sequential()` or `BaseStream.parallel()` methods, and may be queried with the `BaseStream.isParallel()` method.

Since:
  1.8
See Also:
  - `IntStream`
  - `LongStream`
  - `DoubleStream`
  - java.util.stream

## Nested Class Summary

Nested Classes
Modifier and Type
Interface
Description
`static interface`
`Stream.Builder<T>`
A mutable builder for a `Stream`.

## Method Summary

Modifier and Type
Method
Description
`boolean`
`allMatch(Predicate<? super T> predicate)`
Returns whether all elements of this stream match the provided predicate.
`boolean`
`anyMatch(Predicate<? super T> predicate)`
Returns whether any elements of this stream match the provided predicate.
`static <T> Stream.Builder<T>`
`builder()`
Returns a builder for a `Stream`.
`<R> R`
`collect(Supplier<R> supplier, BiConsumer<R, ? super T> accumulator, BiConsumer<R,R> combiner)`
Performs a mutable reduction operation on the elements of this stream.
`<R,A> R`
`collect(Collector<? super T, A, R> collector)`
Performs a mutable reduction operation on the elements of this stream using a `Collector`.
`static <T> Stream<T>`
`concat(Stream<? extends T> a, Stream<? extends T> b)`
Creates a lazily concatenated stream whose elements are all the elements of the first stream followed by all the elements of the second stream.
`long`
`count()`
Returns the count of elements in this stream.
`Stream<T>`
`distinct()`
Returns a stream consisting of the distinct elements (according to `Object.equals(Object)`) of this stream.
`default Stream<T>`
`dropWhile(Predicate<? super T> predicate)`
Returns, if this stream is ordered, a stream consisting of the remaining elements of this stream after dropping the longest prefix of elements that match the given predicate.
`static <T> Stream<T>`
`empty()`
Returns an empty sequential `Stream`.
`Stream<T>`
`filter(Predicate<? super T> predicate)`
Returns a stream consisting of the elements of this stream that match the given predicate.
`Optional<T>`
`findAny()`
Returns an `Optional` describing some element of the stream, or an empty `Optional` if the stream is empty.
`Optional<T>`
`findFirst()`
Returns an `Optional` describing the first element of this stream, or an empty `Optional` if the stream is empty.
`<R> Stream<R>`
`flatMap(Function<? super T, ? extends Stream<? extends R>> 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.
`DoubleStream`
`flatMapToDouble(Function<? super T, ? extends DoubleStream> mapper)`
Returns an `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.
`IntStream`
`flatMapToInt(Function<? super T, ? extends IntStream> mapper)`
Returns an `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.
`LongStream`
`flatMapToLong(Function<? super T, ? extends LongStream> mapper)`
Returns an `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.
`void`
`forEach(Consumer<? super T> action)`
Performs an action for each element of this stream.
`void`
`forEachOrdered(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.
`default <R> Stream<R>`
`gather(Gatherer<? super T, ?, R> gatherer)`
Returns a stream consisting of the results of applying the given `Gatherer` to the elements of this stream.
`static <T> Stream<T>`
`generate(Supplier<? extends T> s)`
Returns an infinite sequential unordered stream where each element is generated by the provided `Supplier`.
`static <T> Stream<T>`
`iterate(T seed, Predicate<? super T> hasNext, UnaryOperator<T> next)`
Returns a sequential ordered `Stream` produced by iterative application of the given `next` function to an initial element, conditioned on satisfying the given `hasNext` predicate.
`static <T> Stream<T>`
`iterate(T seed, UnaryOperator<T> f)`
Returns an infinite sequential ordered `Stream` produced by iterative application of a function `f` to an initial element `seed`, producing a `Stream` consisting of `seed`, `f(seed)`, `f(f(seed))`, etc.
`Stream<T>`
`limit(long maxSize)`
Returns a stream consisting of the elements of this stream, truncated to be no longer than `maxSize` in length.
`<R> Stream<R>`
`map(Function<? super T, ? extends R> mapper)`
Returns a stream consisting of the results of applying the given function to the elements of this stream.
`default <R> Stream<R>`
`mapMulti(BiConsumer<? super T, ? super Consumer<R>> mapper)`
Returns a stream consisting of the results of replacing each element of this stream with multiple elements, specifically zero or more elements.
`default DoubleStream`
`mapMultiToDouble(BiConsumer<? super T, ? super DoubleConsumer> mapper)`
Returns a `DoubleStream` consisting of the results of replacing each element of this stream with multiple elements, specifically zero or more elements.
`default IntStream`
`mapMultiToInt(BiConsumer<? super T, ? super IntConsumer> mapper)`
Returns an `IntStream` consisting of the results of replacing each element of this stream with multiple elements, specifically zero or more elements.
`default LongStream`
`mapMultiToLong(BiConsumer<? super T, ? super LongConsumer> mapper)`
Returns a `LongStream` consisting of the results of replacing each element of this stream with multiple elements, specifically zero or more elements.
`DoubleStream`
`mapToDouble(ToDoubleFunction<? super T> mapper)`
Returns a `DoubleStream` consisting of the results of applying the given function to the elements of this stream.
`IntStream`
`mapToInt(ToIntFunction<? super T> mapper)`
Returns an `IntStream` consisting of the results of applying the given function to the elements of this stream.
`LongStream`
`mapToLong(ToLongFunction<? super T> mapper)`
Returns a `LongStream` consisting of the results of applying the given function to the elements of this stream.
`Optional<T>`
`max(Comparator<? super T> comparator)`
Returns the maximum element of this stream according to the provided `Comparator`.
`Optional<T>`
`min(Comparator<? super T> comparator)`
Returns the minimum element of this stream according to the provided `Comparator`.
`boolean`
`noneMatch(Predicate<? super T> predicate)`
Returns whether no elements of this stream match the provided predicate.
`static <T> Stream<T>`
`of(T t)`
Returns a sequential `Stream` containing a single element.
`static <T> Stream<T>`
`of(T... values)`
Returns a sequential ordered stream whose elements are the specified values.
`static <T> Stream<T>`
`ofNullable(T t)`
Returns a sequential `Stream` containing a single element, if non-null, otherwise returns an empty `Stream`.
`Stream<T>`
`peek(Consumer<? super T> action)`
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.
`Optional<T>`
`reduce(BinaryOperator<T> accumulator)`
Performs a reduction on the elements of this stream, using an associative accumulation function, and returns an `Optional` describing the reduced value, if any.
`T`
`reduce(T identity, BinaryOperator<T> accumulator)`
Performs a reduction on the elements of this stream, using the provided identity value and an associative accumulation function, and returns the reduced value.
`<U> U`
`reduce(U identity, BiFunction<U, ? super T, U> accumulator, BinaryOperator<U> combiner)`
Performs a reduction on the elements of this stream, using the provided identity, accumulation and combining functions.
`Stream<T>`
`skip(long n)`
Returns a stream consisting of the remaining elements of this stream after discarding the first `n` elements of the stream.
`Stream<T>`
`sorted()`
Returns a stream consisting of the elements of this stream, sorted according to natural order.
`Stream<T>`
`sorted(Comparator<? super T> comparator)`
Returns a stream consisting of the elements of this stream, sorted according to the provided `Comparator`.
`default Stream<T>`
`takeWhile(Predicate<? super T> predicate)`
Returns, if this stream is ordered, a stream consisting of the longest prefix of elements taken from this stream that match the given predicate.
`Object[]`
`toArray()`
Returns an array containing the elements of this stream.
`<A> A[]`
`toArray(IntFunction<A[]> generator)`
Returns an array containing the elements of this stream, using the provided `generator` function to allocate the returned array, as well as any additional arrays that might be required for a partitioned execution or for resizing.
`default List<T>`
`toList()`
Accumulates the elements of this stream into a `List`.

### Methods declared in interface BaseStream

`close, isParallel, iterator, onClose, parallel, sequential, spliterator, unordered`
Modifier and Type
Method
Description
`void`
`close()`
Closes this stream, causing all close handlers for this stream pipeline to be called.
`boolean`
`isParallel()`
Returns whether this stream, if a terminal operation were to be executed, would execute in parallel.
`Iterator<T>`
`iterator()`
Returns an iterator for the elements of this stream.
`Stream<T>`
`onClose(Runnable closeHandler)`
Returns an equivalent stream with an additional close handler.
`Stream<T>`
`parallel()`
Returns an equivalent stream that is parallel.
`Stream<T>`
`sequential()`
Returns an equivalent stream that is sequential.
`Spliterator<T>`
`spliterator()`
Returns a spliterator for the elements of this stream.
`Stream<T>`
`unordered()`
Returns an equivalent stream that is unordered.

## Method Details

### filter

Stream<T> filter(Predicate<? super T> predicate)
Returns a stream consisting of the elements of this stream that match the given predicate.

This is an intermediate operation.

Parameters:
  `predicate` - a non-interfering, stateless predicate to apply to each element to determine if it should be included
Returns:
  the new stream

### map

<R> Stream<R> map(Function<? super T, ? extends R> mapper)
Returns a stream consisting of the results of applying the given function to the elements of this stream.

This is an intermediate operation.

Type Parameters:
  `R` - The element type of the new stream
Parameters:
  `mapper` - a non-interfering, stateless function to apply to each element
Returns:
  the new stream

### mapToInt

IntStream mapToInt(ToIntFunction<? super T> mapper)
Returns an `IntStream` consisting of the results of applying the given function to the elements of this stream.

This is an intermediate operation.

Parameters:
  `mapper` - a non-interfering, stateless function to apply to each element
Returns:
  the new stream

### mapToLong

LongStream mapToLong(ToLongFunction<? super T> mapper)
Returns a `LongStream` consisting of the results of applying the given function to the elements of this stream.

This is an intermediate operation.

Parameters:
  `mapper` - a non-interfering, stateless function to apply to each element
Returns:
  the new stream

### mapToDouble

DoubleStream mapToDouble(ToDoubleFunction<? super T> mapper)
Returns a `DoubleStream` consisting of the results of applying the given function to the elements of this stream.

This is an intermediate operation.

Parameters:
  `mapper` - a non-interfering, stateless function to apply to each element
Returns:
  the new stream

### flatMap

<R> Stream<R> flatMap(Function<? super T, ? extends Stream<? extends R>> 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 `closed` after its contents have been placed into this stream. (If a mapped stream is `null` an empty stream is used, instead.)

This is an intermediate operation.

API Note:
  The `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.

  Examples.

  If `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:

          orders.flatMap(order -> order.getLineItems().stream())...

  If `path` is the path to a file, then the following produces a stream of the `words` contained in that file:

          Stream<String> lines = Files.lines(path, StandardCharsets.UTF_8);
          Stream<String> words = lines.flatMap(line -> Stream.of(line.split(" +")));

  The `mapper` function passed to `flatMap` splits a line, using a simple regular expression, into an array of words, and then creates a stream of words from that array.
Type Parameters:
  `R` - The element type of the new stream
Parameters:
  `mapper` - a non-interfering, stateless function to apply to each element which produces a stream of new values
Returns:
  the new stream
See Also:
  - `mapMulti`

### flatMapToInt

IntStream flatMapToInt(Function<? super T, ? extends IntStream> mapper)
Returns an `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 `closed` after its contents have been placed into this stream. (If a mapped stream is `null` an empty stream is used, instead.)

This is an intermediate operation.

Parameters:
  `mapper` - a non-interfering, stateless function to apply to each element which produces a stream of new values
Returns:
  the new stream
See Also:
  - `flatMap`

### flatMapToLong

LongStream flatMapToLong(Function<? super T, ? extends LongStream> mapper)
Returns an `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 `closed` after its contents have been placed into this stream. (If a mapped stream is `null` an empty stream is used, instead.)

This is an intermediate operation.

Parameters:
  `mapper` - a non-interfering, stateless function to apply to each element which produces a stream of new values
Returns:
  the new stream
See Also:
  - `flatMap`

### flatMapToDouble

DoubleStream flatMapToDouble(Function<? super T, ? extends DoubleStream> mapper)
Returns an `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 `closed` after its contents have placed been into this stream. (If a mapped stream is `null` an empty stream is used, instead.)

This is an intermediate operation.

Parameters:
  `mapper` - a non-interfering, stateless function to apply to each element which produces a stream of new values
Returns:
  the new stream
See Also:
  - `flatMap`

### mapMulti

default <R> Stream<R> mapMulti(BiConsumer<? super T, ? super Consumer<R>> mapper)
Returns a stream consisting of the results of replacing each element of this stream with multiple elements, specifically zero or more elements. Replacement is performed by applying the provided mapping function to each element in conjunction with a consumer argument that accepts replacement elements. The mapping function calls the consumer zero or more times to provide the replacement elements.

This is an intermediate operation.

If the consumer argument is used outside the scope of its application to the mapping function, the results are undefined.

API Note:
  This method is similar to `flatMap` in that it applies a one-to-many transformation to the elements of the stream and flattens the result elements into a new stream. This method is preferable to `flatMap` in the following circumstances:
  - When replacing each stream element with a small (possibly zero) number of elements. Using this method avoids the overhead of creating a new Stream instance for every group of result elements, as required by `flatMap`.
  - When it is easier to use an imperative approach for generating result elements than it is to return them in the form of a Stream.

  If a lambda expression is provided as the mapper function argument, additional type information may be necessary for proper inference of the element type `<R>` of the returned stream. This can be provided in the form of explicit type declarations for the lambda parameters or as an explicit type argument to the `mapMulti` call.

  Examples

  Given a stream of `Number` objects, the following produces a list containing only the `Integer` objects:

          Stream<Number> numbers = ... ;
          List<Integer> integers = numbers.<Integer>mapMulti((number, consumer) -> {
                  if (number instanceof Integer i)
                      consumer.accept(i);
              })
              .collect(Collectors.toList());

  If we have an `Iterable<Object>` and need to recursively expand its elements that are themselves of type `Iterable`, we can use `mapMulti` as follows:

      class C {
          static void expandIterable(Object e, Consumer<Object> c) {
              if (e instanceof Iterable<?> elements) {
                  for (Object ie : elements) {
                      expandIterable(ie, c);
                  }
              } else if (e != null) {
                  c.accept(e);
              }
          }

          public static void main(String[] args) {
              var nestedList = List.of(1, List.of(2, List.of(3, 4)), 5);
              Stream<Object> expandedStream = nestedList.stream().mapMulti(C::expandIterable);
          }
      }

Implementation Requirements:
  The default implementation invokes `flatMap` on this stream, passing a function that behaves as follows. First, it calls the mapper function with a `Consumer` that accumulates replacement elements into a newly created internal buffer. When the mapper function returns, it creates a stream from the internal buffer. Finally, it returns this stream to `flatMap`.
Type Parameters:
  `R` - The element type of the new stream
Parameters:
  `mapper` - a non-interfering, stateless function that generates replacement elements
Returns:
  the new stream
Since:
  16
See Also:
  - `flatMap`

### mapMultiToInt

default IntStream mapMultiToInt(BiConsumer<? super T, ? super IntConsumer> mapper)
Returns an `IntStream` consisting of the results of replacing each element of this stream with multiple elements, specifically zero or more elements. Replacement is performed by applying the provided mapping function to each element in conjunction with a consumer argument that accepts replacement elements. The mapping function calls the consumer zero or more times to provide the replacement elements.

This is an intermediate operation.

If the consumer argument is used outside the scope of its application to the mapping function, the results are undefined.

Implementation Requirements:
  The default implementation invokes `flatMapToInt` on this stream, passing a function that behaves as follows. First, it calls the mapper function with an `IntConsumer` that accumulates replacement elements into a newly created internal buffer. When the mapper function returns, it creates an `IntStream` from the internal buffer. Finally, it returns this stream to `flatMapToInt`.
Parameters:
  `mapper` - a non-interfering, stateless function that generates replacement elements
Returns:
  the new stream
Since:
  16
See Also:
  - `mapMulti`

### mapMultiToLong

default LongStream mapMultiToLong(BiConsumer<? super T, ? super LongConsumer> mapper)
Returns a `LongStream` consisting of the results of replacing each element of this stream with multiple elements, specifically zero or more elements. Replacement is performed by applying the provided mapping function to each element in conjunction with a consumer argument that accepts replacement elements. The mapping function calls the consumer zero or more times to provide the replacement elements.

This is an intermediate operation.

If the consumer argument is used outside the scope of its application to the mapping function, the results are undefined.

Implementation Requirements:
  The default implementation invokes `flatMapToLong` on this stream, passing a function that behaves as follows. First, it calls the mapper function with a `LongConsumer` that accumulates replacement elements into a newly created internal buffer. When the mapper function returns, it creates a `LongStream` from the internal buffer. Finally, it returns this stream to `flatMapToLong`.
Parameters:
  `mapper` - a non-interfering, stateless function that generates replacement elements
Returns:
  the new stream
Since:
  16
See Also:
  - `mapMulti`

### mapMultiToDouble

default DoubleStream mapMultiToDouble(BiConsumer<? super T, ? super DoubleConsumer> mapper)
Returns a `DoubleStream` consisting of the results of replacing each element of this stream with multiple elements, specifically zero or more elements. Replacement is performed by applying the provided mapping function to each element in conjunction with a consumer argument that accepts replacement elements. The mapping function calls the consumer zero or more times to provide the replacement elements.

This is an intermediate operation.

If the consumer argument is used outside the scope of its application to the mapping function, the results are undefined.

Implementation Requirements:
  The default implementation invokes `flatMapToDouble` on this stream, passing a function that behaves as follows. First, it calls the mapper function with an `DoubleConsumer` that accumulates replacement elements into a newly created internal buffer. When the mapper function returns, it creates a `DoubleStream` from the internal buffer. Finally, it returns this stream to `flatMapToDouble`.
Parameters:
  `mapper` - a non-interfering, stateless function that generates replacement elements
Returns:
  the new stream
Since:
  16
See Also:
  - `mapMulti`

### distinct

Stream<T> distinct()
Returns a stream consisting of the distinct elements (according to `Object.equals(Object)`) of this stream.

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.

This is a stateful intermediate operation.

API Note:
  Preserving stability for `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 `generate(Supplier)`) or removing the ordering constraint with `BaseStream.unordered()` may result in significantly more efficient execution for `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 `distinct()` in parallel pipelines, switching to sequential execution with `BaseStream.sequential()` may improve performance.
Returns:
  the new stream

### sorted

Stream<T> sorted()
Returns a stream consisting of the elements of this stream, sorted according to natural order. If the elements of this stream are not `Comparable`, a `java.lang.ClassCastException` may be thrown when the terminal operation is executed.

For ordered streams, the sort is stable. For unordered streams, no stability guarantees are made.

This is a stateful intermediate operation.

Returns:
  the new stream

### sorted

Stream<T> sorted(Comparator<? super T> comparator)
Returns a stream consisting of the elements of this stream, sorted according to the provided `Comparator`.

For ordered streams, the sort is stable. For unordered streams, no stability guarantees are made.

This is a stateful intermediate operation.

Parameters:
  `comparator` - a non-interfering, stateless `Comparator` to be used to compare stream elements
Returns:
  the new stream

### peek

Stream<T> peek(Consumer<? super T> action)
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.

This is an intermediate operation.

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.

API Note:
  This method exists mainly to support debugging, where you want to see the elements as they flow past a certain point in a pipeline:

          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());

  In cases where the stream implementation is able to optimize away the production of some or all the elements (such as with short-circuiting operations like `findFirst`, or in the example described in `count()`), the action will not be invoked for those elements.

Parameters:
  `action` - a non-interfering action to perform on the elements as they are consumed from the stream
Returns:
  the new stream

### limit

Stream<T> limit(long maxSize)
Returns a stream consisting of the elements of this stream, truncated to be no longer than `maxSize` in length.

This is a short-circuiting stateful intermediate operation.

API Note:
  While `limit()` is generally a cheap operation on sequential stream pipelines, it can be quite expensive on ordered parallel pipelines, especially for large values of `maxSize`, since `limit(n)` is constrained to return not just any n elements, but the first n elements in the encounter order. Using an unordered stream source (such as `generate(Supplier)`) or removing the ordering constraint with `BaseStream.unordered()` may result in significant speedups of `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 `limit()` in parallel pipelines, switching to sequential execution with `BaseStream.sequential()` may improve performance.
Parameters:
  `maxSize` - the number of elements the stream should be limited to
Returns:
  the new stream
Throws:
  `IllegalArgumentException` - if `maxSize` is negative

### skip

Stream<T> skip(long n)
Returns a stream consisting of the remaining elements of this stream after discarding the first `n` elements of the stream. If this stream contains fewer than `n` elements then an empty stream will be returned.

This is a stateful intermediate operation.

API Note:
  While `skip()` is generally a cheap operation on sequential stream pipelines, it can be quite expensive on ordered parallel pipelines, especially for large values of `n`, since `skip(n)` is constrained to skip not just any n elements, but the first n elements in the encounter order. Using an unordered stream source (such as `generate(Supplier)`) or removing the ordering constraint with `BaseStream.unordered()` may result in significant speedups of `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 `skip()` in parallel pipelines, switching to sequential execution with `BaseStream.sequential()` may improve performance.
Parameters:
  `n` - the number of leading elements to skip
Returns:
  the new stream
Throws:
  `IllegalArgumentException` - if `n` is negative

### takeWhile

default Stream<T> takeWhile(Predicate<? super T> predicate)
Returns, if this stream is ordered, a stream consisting of the longest prefix of elements taken from this stream that match the given predicate. Otherwise returns, if this stream is unordered, a stream consisting of a subset of elements taken from this stream that match the given predicate.

If this stream is ordered then the longest prefix is a contiguous sequence of elements of this stream that match the given predicate. The first element of the sequence is the first element of this stream, and the element immediately following the last element of the sequence does not match the given predicate.

If this stream is unordered, and some (but not all) elements of this stream match the given predicate, then the behavior of this operation is nondeterministic; it is free to take any subset of matching elements (which includes the empty set).

Independent of whether this stream is ordered or unordered if all elements of this stream match the given predicate then this operation takes all elements (the result is the same as the input), or if no elements of the stream match the given predicate then no elements are taken (the result is an empty stream).

This is a short-circuiting stateful intermediate operation.

API Note:
  While `takeWhile()` is generally a cheap operation on sequential stream pipelines, it can be quite expensive on ordered parallel pipelines, since the operation is constrained to return not just any valid prefix, but the longest prefix of elements in the encounter order. Using an unordered stream source (such as `generate(Supplier)`) or removing the ordering constraint with `BaseStream.unordered()` may result in significant speedups of `takeWhile()` 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 `takeWhile()` in parallel pipelines, switching to sequential execution with `BaseStream.sequential()` may improve performance.
Implementation Requirements:
  The default implementation obtains the `spliterator` of this stream, wraps that spliterator so as to support the semantics of this operation on traversal, and returns a new stream associated with the wrapped spliterator. The returned stream preserves the execution characteristics of this stream (namely parallel or sequential execution as per `BaseStream.isParallel()`) but the wrapped spliterator may choose to not support splitting. When the returned stream is closed, the close handlers for both the returned and this stream are invoked.
Parameters:
  `predicate` - a non-interfering, stateless predicate to apply to elements to determine the longest prefix of elements.
Returns:
  the new stream
Since:
  9

### dropWhile

default Stream<T> dropWhile(Predicate<? super T> predicate)
Returns, if this stream is ordered, a stream consisting of the remaining elements of this stream after dropping the longest prefix of elements that match the given predicate. Otherwise returns, if this stream is unordered, a stream consisting of the remaining elements of this stream after dropping a subset of elements that match the given predicate.

If this stream is ordered then the longest prefix is a contiguous sequence of elements of this stream that match the given predicate. The first element of the sequence is the first element of this stream, and the element immediately following the last element of the sequence does not match the given predicate.

If this stream is unordered, and some (but not all) elements of this stream match the given predicate, then the behavior of this operation is nondeterministic; it is free to drop any subset of matching elements (which includes the empty set).

Independent of whether this stream is ordered or unordered if all elements of this stream match the given predicate then this operation drops all elements (the result is an empty stream), or if no elements of the stream match the given predicate then no elements are dropped (the result is the same as the input).

This is a stateful intermediate operation.

API Note:
  While `dropWhile()` is generally a cheap operation on sequential stream pipelines, it can be quite expensive on ordered parallel pipelines, since the operation is constrained to return not just any valid prefix, but the longest prefix of elements in the encounter order. Using an unordered stream source (such as `generate(Supplier)`) or removing the ordering constraint with `BaseStream.unordered()` may result in significant speedups of `dropWhile()` 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 `dropWhile()` in parallel pipelines, switching to sequential execution with `BaseStream.sequential()` may improve performance.
Implementation Requirements:
  The default implementation obtains the `spliterator` of this stream, wraps that spliterator so as to support the semantics of this operation on traversal, and returns a new stream associated with the wrapped spliterator. The returned stream preserves the execution characteristics of this stream (namely parallel or sequential execution as per `BaseStream.isParallel()`) but the wrapped spliterator may choose to not support splitting. When the returned stream is closed, the close handlers for both the returned and this stream are invoked.
Parameters:
  `predicate` - a non-interfering, stateless predicate to apply to elements to determine the longest prefix of elements.
Returns:
  the new stream
Since:
  9

### forEach

void forEach(Consumer<? super T> action)
Performs an action for each element of this stream.

This is a terminal operation.

The behavior of this operation is explicitly nondeterministic. For parallel stream pipelines, this operation does not 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.

Parameters:
  `action` - a non-interfering action to perform on the elements

### forEachOrdered

void forEachOrdered(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.

This is a terminal operation.

This operation processes the elements one at a time, in encounter order if one exists. Performing the action for one element happens-before performing the action for subsequent elements, but for any given element, the action may be performed in whatever thread the library chooses.

Parameters:
  `action` - a non-interfering action to perform on the elements
See Also:
  - `forEach(Consumer)`

### toArray

Object[] toArray()
Returns an array containing the elements of this stream.

This is a terminal operation.

Returns:
  an array, whose runtime component type is `Object`, containing the elements of this stream

### toArray

<A> A[] toArray(IntFunction<A[]> generator)
Returns an array containing the elements of this stream, using the provided `generator` function to allocate the returned array, as well as any additional arrays that might be required for a partitioned execution or for resizing.

This is a terminal operation.

API Note:
  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:

          Person[] men = people.stream()
                               .filter(p -> p.getGender() == MALE)
                               .toArray(Person[]::new);

Type Parameters:
  `A` - the component type of the resulting array
Parameters:
  `generator` - a function which produces a new array of the desired type and the provided length
Returns:
  an array containing the elements in this stream
Throws:
  `ArrayStoreException` - if the runtime type of any element of this stream is not assignable to the runtime component type of the generated array

### reduce

T reduce(T identity, BinaryOperator<T> accumulator)
Performs a reduction on the elements of this stream, using the provided identity value and an associative accumulation function, and returns the reduced value. This is equivalent to:

        T result = identity;
        for (T element : this stream)
            result = accumulator.apply(result, element)
        return result;

but is not constrained to execute sequentially.

The `identity` value must be an identity for the accumulator function. This means that for all `t`, `accumulator.apply(identity, t)` is equal to `t`. The `accumulator` function must be an associative function.

This is a terminal operation.

API Note:
  Sum, min, max, average, and string concatenation are all special cases of reduction. Summing a stream of numbers can be expressed as:

          Integer sum = integers.reduce(0, (a, b) -> a+b);

  or:

          Integer sum = integers.reduce(0, Integer::sum);

  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.

Parameters:
  `identity` - the identity value for the accumulating function
  `accumulator` - an associative, non-interfering, stateless function for combining two values
Returns:
  the result of the reduction

### reduce

Optional<T> reduce(BinaryOperator<T> accumulator)
Performs a reduction on the elements of this stream, using an associative accumulation function, and returns an `Optional` describing the reduced value, if any. This is equivalent to:

        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();

but is not constrained to execute sequentially.

The `accumulator` function must be an associative function.

This is a terminal operation.

Parameters:
  `accumulator` - an associative, non-interfering, stateless function for combining two values
Returns:
  an `Optional` describing the result of the reduction
Throws:
  `NullPointerException` - if the result of the reduction is null
See Also:
  - `reduce(Object, BinaryOperator)`
  - `min(Comparator)`
  - `max(Comparator)`

### reduce

<U> U reduce(U identity, BiFunction<U, ? super T, U> accumulator, BinaryOperator<U> combiner)
Performs a reduction on the elements of this stream, using the provided identity, accumulation and combining functions. This is equivalent to:

        U result = identity;
        for (T element : this stream)
            result = accumulator.apply(result, element)
        return result;

but is not constrained to execute sequentially.

The `identity` value must be an identity for the combiner function. This means that for all `u`, `combiner(identity, u)` is equal to `u`. Additionally, the `combiner` function must be compatible with the `accumulator` function; for all `u` and `t`, the following must hold:

        combiner.apply(u, accumulator.apply(identity, t)) == accumulator.apply(u, t)

This is a terminal operation.

API Note:
  Many reductions using this form can be represented more simply by an explicit combination of `map` and `reduce` operations. The `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.
Type Parameters:
  `U` - The type of the result
Parameters:
  `identity` - the identity value for the combiner function
  `accumulator` - an associative, non-interfering, stateless function for incorporating an additional element into a result
  `combiner` - an associative, non-interfering, stateless function for combining two values, which must be compatible with the accumulator function
Returns:
  the result of the reduction
See Also:
  - `reduce(BinaryOperator)`
  - `reduce(Object, BinaryOperator)`

### gather

default <R> Stream<R> gather(Gatherer<? super T, ?, R> gatherer)
Returns a stream consisting of the results of applying the given `Gatherer` to the elements of this stream.

This is a stateful intermediate operation that is an extension point.

Gatherers are highly flexible and can describe a vast array of possibly stateful operations, with support for short-circuiting, and parallelization.

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 `ArrayList`), no additional synchronization is needed for a parallel reduction.

Implementations are allowed, but not required, to detect consecutive invocations and compose them into a single, fused, operation. This would make the first expression below behave like the second:

        var stream1 = Stream.of(...).gather(gatherer1).gather(gatherer2);
        var stream2 = Stream.of(...).gather(gatherer1.andThen(gatherer2));

Implementation Requirements:
  The default implementation obtains the `spliterator` of this stream, wraps that spliterator so as to support the semantics of this operation on traversal, and returns a new stream associated with the wrapped spliterator. The returned stream preserves the execution characteristics of this stream (namely parallel or sequential execution as per `BaseStream.isParallel()`) but the wrapped spliterator may choose to not support splitting. When the returned stream is closed, the close handlers for both the returned and this stream are invoked. Implementations of this interface should provide their own implementation of this method.
Type Parameters:
  `R` - The element type of the new stream
Parameters:
  `gatherer` - a gatherer
Returns:
  the new stream
Since:
  24
See Also:
  - `Gatherers`

### collect

<R> R collect(Supplier<R> supplier, BiConsumer<R, ? super T> accumulator, BiConsumer<R,R> combiner)
Performs a mutable reduction 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 `ArrayList`, and elements are incorporated by updating the state of the result rather than by replacing the result. This produces a result equivalent to:

        R result = supplier.get();
        for (T element : this stream)
            accumulator.accept(result, element);
        return result;

Like `reduce(Object, BinaryOperator)`, `collect` operations can be parallelized without requiring additional synchronization.

This is a terminal operation.

API Note:
  There are many existing classes in the JDK whose signatures are well-suited for use with method references as arguments to `collect()`. For example, the following will accumulate strings into an `ArrayList`:

          List<String> asList = stringStream.collect(ArrayList::new, ArrayList::add,
                                                     ArrayList::addAll);

  The following will take a stream of strings and concatenates them into a single string:

          String concat = stringStream.collect(StringBuilder::new, StringBuilder::append,
                                               StringBuilder::append)
                                      .toString();

Type Parameters:
  `R` - the type of the mutable result container
Parameters:
  `supplier` - a function that creates a new mutable result container. For a parallel execution, this function may be called multiple times and must return a fresh value each time.
  `accumulator` - an associative, non-interfering, stateless function that must fold an element into a result container.
  `combiner` - an associative, non-interfering, stateless function that accepts two partial result containers and merges them, which must be compatible with the accumulator function. The combiner function must fold the elements from the second result container into the first result container.
Returns:
  the result of the reduction

### collect

<R,A> R collect(Collector<? super T, A, R> collector)
Performs a mutable reduction operation on the elements of this stream using a `Collector`. A `Collector` encapsulates the functions used as arguments to `collect(Supplier, BiConsumer, BiConsumer)`, allowing for reuse of collection strategies and composition of collect operations such as multiple-level grouping or partitioning.

If the stream is parallel, and the `Collector` is `concurrent`, and either the stream is unordered or the collector is `unordered`, then a concurrent reduction will be performed (see `Collector` for details on concurrent reduction.)

This is a terminal operation.

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 `ArrayList`), no additional synchronization is needed for a parallel reduction.

API Note:
  The following will accumulate strings into a List:

          List<String> asList = stringStream.collect(Collectors.toList());

  The following will classify `Person` objects by city:

          Map<String, List<Person>> peopleByCity
              = personStream.collect(Collectors.groupingBy(Person::getCity));

  The following will classify `Person` objects by state and city, cascading two `Collector`s together:

          Map<String, Map<String, List<Person>>> peopleByStateAndCity
              = personStream.collect(Collectors.groupingBy(Person::getState,
                                                           Collectors.groupingBy(Person::getCity)));

Type Parameters:
  `R` - the type of the result
  `A` - the intermediate accumulation type of the `Collector`
Parameters:
  `collector` - the `Collector` describing the reduction
Returns:
  the result of the reduction
See Also:
  - `collect(Supplier, BiConsumer, BiConsumer)`
  - `Collectors`

### toList

default List<T> toList()
Accumulates the elements of this stream into a `List`. The elements in the list will be in this stream's encounter order, if one exists. The returned List is unmodifiable; calls to any mutator method will always cause `UnsupportedOperationException` to be thrown. There are no guarantees on the implementation type or serializability of the returned List.

The returned instance may be value-based. Callers should make no assumptions about the identity of the returned instances. Identity-sensitive operations on these instances (reference equality (`==`), identity hash code, and synchronization) are unreliable and should be avoided.

This is a terminal operation.

API Note:
  If more control over the returned object is required, use `Collectors.toCollection(Supplier)`.
Implementation Requirements:
  The implementation in this interface returns a List produced as if by the following:

      Collections.unmodifiableList(new ArrayList<>(Arrays.asList(this.toArray())))

Implementation Note:
  Most instances of Stream will override this method and provide an implementation that is highly optimized compared to the implementation in this interface.
Returns:
  a List containing the stream elements
Since:
  16

### min

Optional<T> min(Comparator<? super T> comparator)
Returns the minimum element of this stream according to the provided `Comparator`. This is a special case of a reduction.

This is a terminal operation.

Parameters:
  `comparator` - a non-interfering, stateless `Comparator` to compare elements of this stream
Returns:
  an `Optional` describing the minimum element of this stream, or an empty `Optional` if the stream is empty
Throws:
  `NullPointerException` - if the minimum element is null

### max

Optional<T> max(Comparator<? super T> comparator)
Returns the maximum element of this stream according to the provided `Comparator`. This is a special case of a reduction.

This is a terminal operation.

Parameters:
  `comparator` - a non-interfering, stateless `Comparator` to compare elements of this stream
Returns:
  an `Optional` describing the maximum element of this stream, or an empty `Optional` if the stream is empty
Throws:
  `NullPointerException` - if the maximum element is null

### count

long count()
Returns the count of elements in this stream. This is a special case of a reduction and is equivalent to:

        return mapToLong(e -> 1L).sum();

This is a terminal operation.

API Note:
  An implementation may choose to not execute the stream pipeline (either sequentially or in parallel) if it is capable of computing the count directly from the stream source. In such cases no source elements will be traversed and no intermediate operations will be evaluated. Behavioral parameters with side-effects, which are strongly discouraged except for harmless cases such as debugging, may be affected. For example, consider the following stream:

          List<String> l = Arrays.asList("A", "B", "C", "D");
          long count = l.stream().peek(System.out::println).count();

  The number of elements covered by the stream source, a `List`, is known and the intermediate operation, `peek`, does not inject into or remove elements from the stream (as may be the case for `flatMap` or `filter` operations). Thus the count is the size of the `List` and there is no need to execute the pipeline and, as a side-effect, print out the list elements.
Returns:
  the count of elements in this stream

### anyMatch

boolean anyMatch(Predicate<? super T> predicate)
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 `false` is returned and the predicate is not evaluated.

This is a short-circuiting terminal operation.

API Note:
  This method evaluates the existential quantification of the predicate over the elements of the stream (for some x P(x)).
Parameters:
  `predicate` - a non-interfering, stateless predicate to apply to elements of this stream
Returns:
  `true` if any elements of the stream match the provided predicate, otherwise `false`

### allMatch

boolean allMatch(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 `true` is returned and the predicate is not evaluated.

This is a short-circuiting terminal operation.

API Note:
  This method evaluates the universal quantification 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 vacuously satisfied and is always `true` (regardless of P(x)).
Parameters:
  `predicate` - a non-interfering, stateless predicate to apply to elements of this stream
Returns:
  `true` if either all elements of the stream match the provided predicate or the stream is empty, otherwise `false`

### noneMatch

boolean noneMatch(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 `true` is returned and the predicate is not evaluated.

This is a short-circuiting terminal operation.

API Note:
  This method evaluates the universal quantification 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 `true`, regardless of P(x).
Parameters:
  `predicate` - a non-interfering, stateless predicate to apply to elements of this stream
Returns:
  `true` if either no elements of the stream match the provided predicate or the stream is empty, otherwise `false`

### findFirst

Optional<T> findFirst()
Returns an `Optional` describing the first element of this stream, or an empty `Optional` if the stream is empty. If the stream has no encounter order, then any element may be returned.

This is a short-circuiting terminal operation.

Returns:
  an `Optional` describing the first element of this stream, or an empty `Optional` if the stream is empty
Throws:
  `NullPointerException` - if the element selected is null

### findAny

Optional<T> findAny()
Returns an `Optional` describing some element of the stream, or an empty `Optional` if the stream is empty.

This is a short-circuiting terminal operation.

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 `findFirst()` instead.)

Returns:
  an `Optional` describing some element of this stream, or an empty `Optional` if the stream is empty
Throws:
  `NullPointerException` - if the element selected is null
See Also:
  - `findFirst()`

### builder

static <T> Stream.Builder<T> builder()
Returns a builder for a `Stream`.

Type Parameters:
  `T` - type of elements
Returns:
  a stream builder

### empty

static <T> Stream<T> empty()
Returns an empty sequential `Stream`.

Type Parameters:
  `T` - the type of stream elements
Returns:
  an empty sequential stream

### of

static <T> Stream<T> of(T t)
Returns a sequential `Stream` containing a single element.

Type Parameters:
  `T` - the type of stream elements
Parameters:
  `t` - the single element
Returns:
  a singleton sequential stream

### ofNullable

static <T> Stream<T> ofNullable(T t)
Returns a sequential `Stream` containing a single element, if non-null, otherwise returns an empty `Stream`.

Type Parameters:
  `T` - the type of stream elements
Parameters:
  `t` - the single element
Returns:
  a stream with a single element if the specified element is non-null, otherwise an empty stream
Since:
  9

### of

@SafeVarargs static <T> Stream<T> of(T... values)
Returns a sequential ordered stream whose elements are the specified values.

Type Parameters:
  `T` - the type of stream elements
Parameters:
  `values` - the elements of the new stream
Returns:
  the new stream

### iterate

static <T> Stream<T> iterate(T seed, UnaryOperator<T> f)
Returns an infinite sequential ordered `Stream` produced by iterative application of a function `f` to an initial element `seed`, producing a `Stream` consisting of `seed`, `f(seed)`, `f(f(seed))`, etc.

The first element (position `0`) in the `Stream` will be the provided `seed`. For `n > 0`, the element at position `n`, will be the result of applying the function `f` to the element at position `n - 1`.

The action of applying `f` for one element happens-before the action of applying `f` for subsequent elements. For any given element the action may be performed in whatever thread the library chooses.

Type Parameters:
  `T` - the type of stream elements
Parameters:
  `seed` - the initial element
  `f` - a function to be applied to the previous element to produce a new element
Returns:
  a new sequential `Stream`

### iterate

static <T> Stream<T> iterate(T seed, Predicate<? super T> hasNext, UnaryOperator<T> next)
Returns a sequential ordered `Stream` produced by iterative application of the given `next` function to an initial element, conditioned on satisfying the given `hasNext` predicate. The stream terminates as soon as the `hasNext` predicate returns false.

`Stream.iterate` should produce the same sequence of elements as produced by the corresponding for-loop:

        for (T index=seed; hasNext.test(index); index = next.apply(index)) {
            ...
        }

The resulting sequence may be empty if the `hasNext` predicate does not hold on the seed value. Otherwise the first element will be the supplied `seed` value, the next element (if present) will be the result of applying the `next` function to the `seed` value, and so on iteratively until the `hasNext` predicate indicates that the stream should terminate.

The action of applying the `hasNext` predicate to an element happens-before the action of applying the `next` function to that element. The action of applying the `next` function for one element happens-before the action of applying the `hasNext` predicate for subsequent elements. For any given element an action may be performed in whatever thread the library chooses.

Type Parameters:
  `T` - the type of stream elements
Parameters:
  `seed` - the initial element
  `hasNext` - a predicate to apply to elements to determine when the stream must terminate.
  `next` - a function to be applied to the previous element to produce a new element
Returns:
  a new sequential `Stream`
Since:
  9

### generate

static <T> Stream<T> generate(Supplier<? extends T> s)
Returns an infinite sequential unordered stream where each element is generated by the provided `Supplier`. This is suitable for generating constant streams, streams of random elements, etc.

Type Parameters:
  `T` - the type of stream elements
Parameters:
  `s` - the `Supplier` of generated elements
Returns:
  a new infinite sequential unordered `Stream`

### concat

static <T> Stream<T> concat(Stream<? extends T> a, Stream<? extends T> b)
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.

This method operates on the two input streams and binds each stream to its source. As a result subsequent modifications to an input stream source may not be reflected in the concatenated stream result.

API Note:
  To preserve optimization opportunities this method binds each stream to its source and accepts only two streams as parameters. For example, the exact size of the concatenated stream source can be computed if the exact size of each input stream source is known. To concatenate more streams without binding, or without nested calls to this method, try creating a stream of streams and flat-mapping with the identity function, for example:

          Stream<T> concat = Stream.of(s1, s2, s3, s4).flatMap(s -> s);

Implementation Note:
  Use caution when constructing streams from repeated concatenation. Accessing an element of a deeply concatenated stream can result in deep call chains, or even `StackOverflowError`.

  Subsequent changes to the sequential/parallel execution mode of the returned stream are not guaranteed to be propagated to the input streams.

Type Parameters:
  `T` - The type of stream elements
Parameters:
  `a` - the first stream
  `b` - the second stream
Returns:
  the concatenation of the two input streams