Interface Stream<T>
- Type Parameters:
T
- the type of the stream elements
- All Superinterfaces:
AutoCloseable
,BaseStream<T, Stream<T>>
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:
-
Nested Class Summary
Modifier and TypeInterfaceDescriptionstatic interface
A mutable builder for aStream
. -
Method Summary
Modifier and TypeMethodDescriptionboolean
Returns whether all elements of this stream match the provided predicate.boolean
Returns whether any elements of this stream match the provided predicate.static <T> Stream.Builder
<T> builder()
Returns a builder for aStream
.<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 Performs a mutable reduction operation on the elements of this stream using aCollector
.static <T> Stream
<T> 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.distinct()
Returns a stream consisting of the distinct elements (according toObject.equals(Object)
) of this stream.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 sequentialStream
.Returns a stream consisting of the elements of this stream that match the given predicate.findAny()
Returns anOptional
describing some element of the stream, or an emptyOptional
if the stream is empty.Returns anOptional
describing the first element of this stream, or an emptyOptional
if the stream is empty.<R> Stream
<R> 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.flatMapToDouble
(Function<? super T, ? extends DoubleStream> mapper) Returns anDoubleStream
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.flatMapToInt
(Function<? super T, ? extends IntStream> mapper) Returns anIntStream
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.flatMapToLong
(Function<? super T, ? extends LongStream> mapper) Returns anLongStream
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
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> Returns a stream consisting of the results of applying the givenGatherer
to the elements of this stream.static <T> Stream
<T> Returns an infinite sequential unordered stream where each element is generated by the providedSupplier
.static <T> Stream
<T> iterate
(T seed, Predicate<? super T> hasNext, UnaryOperator<T> next) Returns a sequential orderedStream
produced by iterative application of the givennext
function to an initial element, conditioned on satisfying the givenhasNext
predicate.static <T> Stream
<T> iterate
(T seed, UnaryOperator<T> f) Returns an infinite sequential orderedStream
produced by iterative application of a functionf
to an initial elementseed
, producing aStream
consisting ofseed
,f(seed)
,f(f(seed))
, etc.limit
(long maxSize) Returns a stream consisting of the elements of this stream, truncated to be no longer thanmaxSize
in length.<R> Stream
<R> 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 aDoubleStream
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 anIntStream
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 aLongStream
consisting of the results of replacing each element of this stream with multiple elements, specifically zero or more elements.mapToDouble
(ToDoubleFunction<? super T> mapper) Returns aDoubleStream
consisting of the results of applying the given function to the elements of this stream.mapToInt
(ToIntFunction<? super T> mapper) Returns anIntStream
consisting of the results of applying the given function to the elements of this stream.mapToLong
(ToLongFunction<? super T> mapper) Returns aLongStream
consisting of the results of applying the given function to the elements of this stream.max
(Comparator<? super T> comparator) Returns the maximum element of this stream according to the providedComparator
.min
(Comparator<? super T> comparator) Returns the minimum element of this stream according to the providedComparator
.boolean
Returns whether no elements of this stream match the provided predicate.static <T> Stream
<T> of
(T t) Returns a sequentialStream
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 sequentialStream
containing a single element, if non-null, otherwise returns an emptyStream
.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.reduce
(BinaryOperator<T> accumulator) Performs a reduction on the elements of this stream, using an associative accumulation function, and returns anOptional
describing the reduced value, if any.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.skip
(long n) Returns a stream consisting of the remaining elements of this stream after discarding the firstn
elements of the stream.sorted()
Returns a stream consisting of the elements of this stream, sorted according to natural order.sorted
(Comparator<? super T> comparator) Returns a stream consisting of the elements of this stream, sorted according to the providedComparator
.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 providedgenerator
function to allocate the returned array, as well as any additional arrays that might be required for a partitioned execution or for resizing.toList()
Accumulates the elements of this stream into aList
.Methods declared in interface java.util.stream.BaseStream
close, isParallel, iterator, onClose, parallel, sequential, spliterator, unordered
-
Method Details
-
filter
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
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
Returns anIntStream
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
Returns aLongStream
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
Returns aDoubleStream
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
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 isclosed
after its contents have been placed into this stream. (If a mapped stream isnull
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 thewords
contained in that file:
TheStream<String> lines = Files.lines(path, StandardCharsets.UTF_8); Stream<String> words = lines.flatMap(line -> Stream.of(line.split(" +")));
mapper
function passed toflatMap
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:
-
flatMapToInt
Returns anIntStream
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 isclosed
after its contents have been placed into this stream. (If a mapped stream isnull
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:
-
flatMapToLong
Returns anLongStream
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 isclosed
after its contents have been placed into this stream. (If a mapped stream isnull
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:
-
flatMapToDouble
Returns anDoubleStream
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 isclosed
after its contents have placed been into this stream. (If a mapped stream isnull
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:
-
mapMulti
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 toflatMap
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 themapMulti
call.Examples
Given a stream of
Number
objects, the following produces a list containing only theInteger
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 typeIterable
, we can usemapMulti
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); } }
- 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
- Implementation Requirements:
- The default implementation invokes
flatMap
on this stream, passing a function that behaves as follows. First, it calls the mapper function with aConsumer
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 toflatMap
. - 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:
-
mapMultiToInt
Returns anIntStream
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 anIntConsumer
that accumulates replacement elements into a newly created internal buffer. When the mapper function returns, it creates anIntStream
from the internal buffer. Finally, it returns this stream toflatMapToInt
. - Parameters:
mapper
- a non-interfering, stateless function that generates replacement elements- Returns:
- the new stream
- Since:
- 16
- See Also:
-
mapMultiToLong
Returns aLongStream
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 aLongConsumer
that accumulates replacement elements into a newly created internal buffer. When the mapper function returns, it creates aLongStream
from the internal buffer. Finally, it returns this stream toflatMapToLong
. - Parameters:
mapper
- a non-interfering, stateless function that generates replacement elements- Returns:
- the new stream
- Since:
- 16
- See Also:
-
mapMultiToDouble
Returns aDoubleStream
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 anDoubleConsumer
that accumulates replacement elements into a newly created internal buffer. When the mapper function returns, it creates aDoubleStream
from the internal buffer. Finally, it returns this stream toflatMapToDouble
. - Parameters:
mapper
- a non-interfering, stateless function that generates replacement elements- Returns:
- the new stream
- Since:
- 16
- See Also:
-
distinct
Returns a stream consisting of the distinct elements (according toObject.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 asgenerate(Supplier)
) or removing the ordering constraint withBaseStream.unordered()
may result in significantly more efficient execution fordistinct()
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 withdistinct()
in parallel pipelines, switching to sequential execution withBaseStream.sequential()
may improve performance. - Returns:
- the new stream
-
sorted
Returns a stream consisting of the elements of this stream, sorted according to natural order. If the elements of this stream are notComparable
, ajava.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
Returns a stream consisting of the elements of this stream, sorted according to the providedComparator
.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, statelessComparator
to be used to compare stream elements- Returns:
- the new stream
-
peek
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 incount()
), 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
Returns a stream consisting of the elements of this stream, truncated to be no longer thanmaxSize
in length.- 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 ofmaxSize
, sincelimit(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 asgenerate(Supplier)
) or removing the ordering constraint withBaseStream.unordered()
may result in significant speedups oflimit()
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 withlimit()
in parallel pipelines, switching to sequential execution withBaseStream.sequential()
may improve performance. - Parameters:
maxSize
- the number of elements the stream should be limited to- Returns:
- the new stream
- Throws:
IllegalArgumentException
- ifmaxSize
is negative
-
skip
Returns a stream consisting of the remaining elements of this stream after discarding the firstn
elements of the stream. If this stream contains fewer thann
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 ofn
, sinceskip(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 asgenerate(Supplier)
) or removing the ordering constraint withBaseStream.unordered()
may result in significant speedups ofskip()
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 withskip()
in parallel pipelines, switching to sequential execution withBaseStream.sequential()
may improve performance. - Parameters:
n
- the number of leading elements to skip- Returns:
- the new stream
- Throws:
IllegalArgumentException
- ifn
is negative
-
takeWhile
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).
- 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 asgenerate(Supplier)
) or removing the ordering constraint withBaseStream.unordered()
may result in significant speedups oftakeWhile()
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 withtakeWhile()
in parallel pipelines, switching to sequential execution withBaseStream.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 perBaseStream.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
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 asgenerate(Supplier)
) or removing the ordering constraint withBaseStream.unordered()
may result in significant speedups ofdropWhile()
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 withdropWhile()
in parallel pipelines, switching to sequential execution withBaseStream.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 perBaseStream.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
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
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:
-
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
Returns an array containing the elements of this stream, using the providedgenerator
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
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:
but is not constrained to execute sequentially.T result = identity; for (T element : this stream) result = accumulator.apply(result, element) return result;
The
identity
value must be an identity for the accumulator function. This means that for allt
,accumulator.apply(identity, t)
is equal tot
. Theaccumulator
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:
or:Integer sum = integers.reduce(0, (a, b) -> a+b);
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 functionaccumulator
- an associative, non-interfering, stateless function for combining two values- Returns:
- the result of the reduction
-
reduce
Performs a reduction on the elements of this stream, using an associative accumulation function, and returns anOptional
describing the reduced value, if any. This is equivalent to:
but is not constrained to execute sequentially.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();
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
Performs a reduction on the elements of this stream, using the provided identity, accumulation and combining functions. This is equivalent to:
but is not constrained to execute sequentially.U result = identity; for (T element : this stream) result = accumulator.apply(result, element) return result;
The
identity
value must be an identity for the combiner function. This means that for allu
,combiner(identity, u)
is equal tou
. Additionally, thecombiner
function must be compatible with theaccumulator
function; for allu
andt
, 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
andreduce
operations. Theaccumulator
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 functionaccumulator
- an associative, non-interfering, stateless function for incorporating an additional element into a resultcombiner
- 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:
-
gather
Returns a stream consisting of the results of applying the givenGatherer
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 perBaseStream.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:
-
collect
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 anArrayList
, 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 anArrayList
: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
Performs a mutable reduction operation on the elements of this stream using aCollector
. ACollector
encapsulates the functions used as arguments tocollect(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
isconcurrent
, and either the stream is unordered or the collector isunordered
, then a concurrent reduction will be performed (seeCollector
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 twoCollector
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 resultA
- the intermediate accumulation type of theCollector
- Parameters:
collector
- theCollector
describing the reduction- Returns:
- the result of the reduction
- See Also:
-
toList
Accumulates the elements of this stream into aList
. 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 causeUnsupportedOperationException
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
Returns the minimum element of this stream according to the providedComparator
. This is a special case of a reduction.This is a terminal operation.
- Parameters:
comparator
- a non-interfering, statelessComparator
to compare elements of this stream- Returns:
- an
Optional
describing the minimum element of this stream, or an emptyOptional
if the stream is empty - Throws:
NullPointerException
- if the minimum element is null
-
max
Returns the maximum element of this stream according to the providedComparator
. This is a special case of a reduction.This is a terminal operation.
- Parameters:
comparator
- a non-interfering, statelessComparator
to compare elements of this stream- Returns:
- an
Optional
describing the maximum element of this stream, or an emptyOptional
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:
The number of elements covered by the stream source, aList<String> l = Arrays.asList("A", "B", "C", "D"); long count = l.stream().peek(System.out::println).count();
List
, is known and the intermediate operation,peek
, does not inject into or remove elements from the stream (as may be the case forflatMap
orfilter
operations). Thus the count is the size of theList
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
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 thenfalse
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, otherwisefalse
-
allMatch
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 thentrue
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, otherwisefalse
-
noneMatch
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 thentrue
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, otherwisefalse
-
findFirst
Returns anOptional
describing the first element of this stream, or an emptyOptional
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 emptyOptional
if the stream is empty - Throws:
NullPointerException
- if the element selected is null
-
findAny
Returns anOptional
describing some element of the stream, or an emptyOptional
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 emptyOptional
if the stream is empty - Throws:
NullPointerException
- if the element selected is null- See Also:
-
builder
Returns a builder for aStream
.- Type Parameters:
T
- type of elements- Returns:
- a stream builder
-
empty
Returns an empty sequentialStream
.- Type Parameters:
T
- the type of stream elements- Returns:
- an empty sequential stream
-
of
Returns a sequentialStream
containing a single element.- Type Parameters:
T
- the type of stream elements- Parameters:
t
- the single element- Returns:
- a singleton sequential stream
-
ofNullable
Returns a sequentialStream
containing a single element, if non-null, otherwise returns an emptyStream
.- 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
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
Returns an infinite sequential orderedStream
produced by iterative application of a functionf
to an initial elementseed
, producing aStream
consisting ofseed
,f(seed)
,f(f(seed))
, etc.The first element (position
0
) in theStream
will be the providedseed
. Forn > 0
, the element at positionn
, will be the result of applying the functionf
to the element at positionn - 1
.The action of applying
f
for one element happens-before the action of applyingf
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 elementf
- a function to be applied to the previous element to produce a new element- Returns:
- a new sequential
Stream
-
iterate
Returns a sequential orderedStream
produced by iterative application of the givennext
function to an initial element, conditioned on satisfying the givenhasNext
predicate. The stream terminates as soon as thehasNext
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 suppliedseed
value, the next element (if present) will be the result of applying thenext
function to theseed
value, and so on iteratively until thehasNext
predicate indicates that the stream should terminate.The action of applying the
hasNext
predicate to an element happens-before the action of applying thenext
function to that element. The action of applying thenext
function for one element happens-before the action of applying thehasNext
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 elementhasNext
- 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
Returns an infinite sequential unordered stream where each element is generated by the providedSupplier
. This is suitable for generating constant streams, streams of random elements, etc.- Type Parameters:
T
- the type of stream elements- Parameters:
s
- theSupplier
of generated elements- Returns:
- a new infinite sequential unordered
Stream
-
concat
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 streamb
- the second stream- Returns:
- the concatenation of the two input streams
-