Stream (net.sourceforge.streamsupport:streamsupport 1.6.0 API)

Type Parameters:

T - the type of the stream elements

All Superinterfaces:

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, 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 Files.lines(java.nio.file.Path, java.nio.charset.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 try-with-resources statement.)
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, java8.util.stream

Nested Class Summary

Nested Classes
Modifier and Type Interface and Description

static interface Stream.Builder<T>
A mutable builder for a Stream.

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

Method Summary

All Methods Instance Methods Abstract Methods
Modifier and Type	Method and 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.
`<R,A> R`	`collect(Collector<? super T,A,R> collector)` Performs a mutable reduction operation on the elements of this stream using a `Collector`.
`<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.
`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.
`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.
`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.
`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.
`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.
`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`.
`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.

Methods inherited from interface java8.util.stream.BaseStream
close, isParallel, iterator, onClose, parallel, sequential, spliterator, unordered

- Method Detail
  - 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 -> RefStreams.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
  - 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(Function)
  - 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(Function)
  - 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(Function)
  - 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 RefStreams.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:
```
     RefStreams.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 RefStreams.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 RefStreams.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
```
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.
    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.
    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 RefStreams.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.
    One use-case for takeWhile is executing a stream pipeline for a certain duration. The following example will calculate as many probable primes as is possible, in parallel, during 5 seconds:
```
     long t = System.currentTimeMillis();
     List<BigInteger> pps = RefStreams
         .generate(() -> BigInteger.probablePrime(1024, ThreadLocalRandom.current()))
         .parallel()
         .takeWhile(e -> (System.currentTimeMillis() - t) < TimeUnit.SECONDS.toMillis(5))
         .collect(toList());

 
```
    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
```
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.
    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.
    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 RefStreams.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.
    
    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)
  - 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 an ArrayList:
```
     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 Collectors 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
  - 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 (at least in the predominant case where the count can't be directly obtained from the stream source) 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()

Interface Stream<T>

Nested Class Summary

Method Summary

Methods inherited from interface java8.util.stream.BaseStream

Method Detail

filter

map

mapToInt

mapToLong

mapToDouble

flatMap

flatMapToInt

flatMapToLong

flatMapToDouble

distinct

sorted

sorted

peek

limit

skip

takeWhile

dropWhile

forEach

forEachOrdered

toArray

toArray

reduce

reduce

reduce

collect

collect

min

max

count

anyMatch

allMatch

noneMatch

findFirst

findAny