Method Detail

filter

IntStream filter​(IntPredicate predicate)

Parameters:

predicate - a non-interfering, stateless predicate to apply to each element to determine if it should be included

Returns:

the new stream

map

IntStream map​(IntUnaryOperator mapper)

Parameters:

mapper - a non-interfering, stateless function to apply to each element

Returns:

the new stream

mapToObj

<U> Stream<U> mapToObj​(IntFunction<? extends U> mapper)

Type Parameters:

U - the element type of the new stream

Parameters:

mapper - a non-interfering, stateless function to apply to each element

Returns:

the new stream

mapToLong

LongStream mapToLong​(IntToLongFunction mapper)

Parameters:

mapper - a non-interfering, stateless function to apply to each element

Returns:

the new stream

mapToDouble

DoubleStream mapToDouble​(IntToDoubleFunction mapper)

Parameters:

mapper - a non-interfering, stateless function to apply to each element

Returns:

the new stream

flatMap

IntStream flatMap​(IntFunction<? extends IntStream> mapper)

Parameters:

mapper - a non-interfering, stateless function to apply to each element which produces an IntStream of new values

Returns:

the new stream

See Also:

Stream.flatMap(Function)

distinct

IntStream distinct()

Returns:

the new stream

sorted

IntStream sorted()

Returns:

the new stream

peek

IntStream peek​(IntConsumer action)

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:

IntStream.of(1, 2, 3, 4)
         .filter(e -> e > 2)
         .peek(e -> System.out.println("Filtered value: " + e))
         .map(e -> e * e)
         .peek(e -> System.out.println("Mapped value: " + e))
         .sum();

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

IntStream limit​(long maxSize)

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(IntSupplier)) 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

IntStream skip​(long n)

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(IntSupplier)) 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 IntStream takeWhile​(IntPredicate predicate)

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(IntSupplier)) 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 IntStream dropWhile​(IntPredicate predicate)

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(IntSupplier)) 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​(IntConsumer action)

Parameters:

action - a non-interfering action to perform on the elements

forEachOrdered

void forEachOrdered​(IntConsumer action)

Parameters:

action - a non-interfering action to perform on the elements

See Also:

forEach(IntConsumer)

toArray

int[] toArray()

Returns:

an array containing the elements of this stream

reduce

int reduce​(int identity,
           IntBinaryOperator op)

int result = identity;
     for (int element : this stream)
         result = accumulator.applyAsInt(result, element)
     return result;

API Note:

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

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

or more compactly:

int 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

op - an associative, non-interfering, stateless function for combining two values

Returns:

the result of the reduction

See Also:

sum(), min(), max(), average()

reduce

OptionalInt reduce​(IntBinaryOperator op)

boolean foundAny = false;
     int result = null;
     for (int element : this stream) {
         if (!foundAny) {
             foundAny = true;
             result = element;
         }
         else
             result = accumulator.applyAsInt(result, element);
     }
     return foundAny ? OptionalInt.of(result) : OptionalInt.empty();

Parameters:

op - an associative, non-interfering, stateless function for combining two values

Returns:

the result of the reduction

See Also:

reduce(int, IntBinaryOperator)

collect

<R> R collect​(Supplier<R> supplier,
              ObjIntConsumer<R> accumulator,
              BiConsumer<R,​R> combiner)

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

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

See Also:

Stream.collect(Supplier, BiConsumer, BiConsumer)

sum

int sum()

return reduce(0, Integer::sum);

Returns:

the sum of elements in this stream

min

OptionalInt min()

return reduce(Integer::min);

Returns:

an OptionalInt containing the minimum element of this stream, or an empty OptionalInt if the stream is empty

max

OptionalInt max()

return reduce(Integer::max);

Returns:

an OptionalInt containing the maximum element of this stream, or an empty OptionalInt if the stream is empty

count

long count()

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

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:

IntStream s = IntStream.of(1, 2, 3, 4);
     long count = s.peek(System.out::println).count();

The number of elements covered by the stream source 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 4 and there is no need to execute the pipeline and, as a side-effect, print out the elements.

Returns:

the count of elements in this stream

average

OptionalDouble average()

Returns:

an OptionalDouble containing the average element of this stream, or an empty optional if the stream is empty

summaryStatistics

IntSummaryStatistics summaryStatistics()

Returns:

an IntSummaryStatistics describing various summary data about the elements of this stream

anyMatch

boolean anyMatch​(IntPredicate predicate)

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​(IntPredicate predicate)

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​(IntPredicate predicate)

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

OptionalInt findFirst()

Returns:

an OptionalInt describing the first element of this stream, or an empty OptionalInt if the stream is empty

findAny

OptionalInt findAny()

Returns:

an OptionalInt describing some element of this stream, or an empty OptionalInt if the stream is empty

See Also:

findFirst()

asLongStream

LongStream asLongStream()

Returns:

a LongStream consisting of the elements of this stream, converted to long

asDoubleStream

DoubleStream asDoubleStream()

Returns:

a DoubleStream consisting of the elements of this stream, converted to double

boxed

Stream<Integer> boxed()

Returns:

a Stream consistent of the elements of this stream, each boxed to an Integer

builder

static IntStream.Builder builder()

Returns a builder for an IntStream.

Returns:

a stream builder

empty

static IntStream empty()

Returns an empty sequential IntStream.

Returns:

an empty sequential stream

of

static IntStream of​(int t)

Returns a sequential IntStream containing a single element.

Parameters:

t - the single element

Returns:

a singleton sequential stream

of

static IntStream of​(int... values)

Returns a sequential ordered stream whose elements are the specified values.

Parameters:

values - the elements of the new stream

Returns:

the new stream

iterate

static IntStream iterate​(int seed,
                         IntUnaryOperator f)

Parameters:

seed - the initial element

f - a function to be applied to the previous element to produce a new element

Returns:

a new sequential IntStream

iterate

static IntStream iterate​(int seed,
                         IntPredicate hasNext,
                         IntUnaryOperator next)

for (int index=seed; hasNext.test(index); index = next.applyAsInt(index)) {
         ...
     }

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 IntStream

Since:

9

generate

static IntStream generate​(IntSupplier s)

Returns an infinite sequential unordered stream where each element is generated by the provided IntSupplier. This is suitable for generating constant streams, streams of random elements, etc.

Parameters:

s - the IntSupplier for generated elements

Returns:

a new infinite sequential unordered IntStream

range

static IntStream range​(int startInclusive,
                       int endExclusive)

Returns a sequential ordered IntStream from startInclusive (inclusive) to endExclusive (exclusive) by an incremental step of 1.

API Note:

An equivalent sequence of increasing values can be produced sequentially using a for loop as follows:

for (int i = startInclusive; i < endExclusive ; i++) { ... }

Parameters:

startInclusive - the (inclusive) initial value

endExclusive - the exclusive upper bound

Returns:

a sequential IntStream for the range of int elements

rangeClosed

static IntStream rangeClosed​(int startInclusive,
                             int endInclusive)

Returns a sequential ordered IntStream from startInclusive (inclusive) to endInclusive (inclusive) by an incremental step of 1.

API Note:

An equivalent sequence of increasing values can be produced sequentially using a for loop as follows:

for (int i = startInclusive; i <= endInclusive ; i++) { ... }

Parameters:

startInclusive - the (inclusive) initial value

endInclusive - the inclusive upper bound

Returns:

a sequential IntStream for the range of int elements

concat

static IntStream concat​(IntStream a,
                        IntStream b)

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:

IntStream concat = Stream.of(s1, s2, s3, s4).flatMapToInt(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.

Parameters:

a - the first stream

b - the second stream

Returns:

the concatenation of the two input streams