java.lang.Object
java.util.stream.Gatherers
Gatherers
is a preview API of the Java platform.
Preview features may be removed in a future release, or upgraded to permanent features of the Java platform.
Implementations of
Gatherer
PREVIEW that provide useful intermediate
operations, such as windowing functions, folding functions,
transforming elements concurrently, etc.- Since:
- 22
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Method Summary
Modifier and TypeMethodDescriptionfold
(Supplier<R> initial, BiFunction<? super R, ? super T, ? extends R> folder) Returns a Gatherer that performs an ordered, reduction-like, transformation for scenarios where no combiner-function can be implemented, or for reductions which are intrinsically order-dependent.mapConcurrent
(int maxConcurrency, Function<? super T, ? extends R> mapper) An operation which executes a function concurrently with a configured level of max concurrency, using virtual threads.scan
(Supplier<R> initial, BiFunction<? super R, ? super T, ? extends R> scanner) Returns a Gatherer that performs a Prefix Scan -- an incremental accumulation -- using the provided functions.windowFixed
(int windowSize) Returns a Gatherer that gathers elements into windows -- encounter-ordered groups of elements -- of a fixed size.windowSliding
(int windowSize) Returns a Gatherer that gathers elements into windows -- encounter-ordered groups of elements -- of a given size, where each subsequent window includes all elements of the previous window except for the least recent, and adds the next element in the stream.
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Method Details
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windowFixed
Returns a Gatherer that gathers elements into windows -- encounter-ordered groups of elements -- of a fixed size. If the stream is empty then no window will be produced. The last window may contain fewer elements than the supplied window size.Example:
// will contain: [[1, 2, 3], [4, 5, 6], [7, 8]] List<List<Integer>> windows = Stream.of(1,2,3,4,5,6,7,8).gather(Gatherers.windowFixed(3)).toList();
- API Note:
- For efficiency reasons, windows may be allocated contiguously and eagerly. This means that choosing large window sizes for small streams may use excessive memory for the duration of evaluation of this operation.
- Implementation Requirements:
- Each window produced is an unmodifiable List; calls to any
mutator method will always cause
UnsupportedOperationException
to be thrown. There are no guarantees on the implementation type or serializability of the produced Lists. - Type Parameters:
TR
- the type of elements the returned gatherer consumes and the contents of the windows it produces- Parameters:
windowSize
- the size of the windows- Returns:
- a new gatherer which groups elements into fixed-size windows
- Throws:
IllegalArgumentException
- whenwindowSize
is less than 1
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windowSliding
Returns a Gatherer that gathers elements into windows -- encounter-ordered groups of elements -- of a given size, where each subsequent window includes all elements of the previous window except for the least recent, and adds the next element in the stream. If the stream is empty then no window will be produced. If the size of the stream is smaller than the window size then only one window will be produced, containing all elements in the stream.Example:
// will contain: [[1, 2], [2, 3], [3, 4], [4, 5], [5, 6], [6, 7], [7, 8]] List<List<Integer>> windows2 = Stream.of(1,2,3,4,5,6,7,8).gather(Gatherers.windowSliding(2)).toList(); // will contain: [[1, 2, 3, 4, 5, 6], [2, 3, 4, 5, 6, 7], [3, 4, 5, 6, 7, 8]] List<List<Integer>> windows6 = Stream.of(1,2,3,4,5,6,7,8).gather(Gatherers.windowSliding(6)).toList();
- API Note:
- For efficiency reasons, windows may be allocated contiguously and eagerly. This means that choosing large window sizes for small streams may use excessive memory for the duration of evaluation of this operation.
- Implementation Requirements:
- Each window produced is an unmodifiable List; calls to any
mutator method will always cause
UnsupportedOperationException
to be thrown. There are no guarantees on the implementation type or serializability of the produced Lists. - Type Parameters:
TR
- the type of elements the returned gatherer consumes and the contents of the windows it produces- Parameters:
windowSize
- the size of the windows- Returns:
- a new gatherer which groups elements into sliding windows
- Throws:
IllegalArgumentException
- when windowSize is less than 1
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fold
public static <T,R> GathererPREVIEW<T,?, foldR> (Supplier<R> initial, BiFunction<? super R, ? super T, ? extends R> folder) Returns a Gatherer that performs an ordered, reduction-like, transformation for scenarios where no combiner-function can be implemented, or for reductions which are intrinsically order-dependent.- Implementation Requirements:
- If no exceptions are thrown during processing, then this
operation only ever produces a single element.
Example:
// will contain: Optional["123456789"] Optional<String> numberString = Stream.of(1,2,3,4,5,6,7,8,9) .gather( Gatherers.fold(() -> "", (string, number) -> string + number) ) .findFirst();
- Type Parameters:
T
- the type of elements the returned gatherer consumesR
- the type of elements the returned gatherer produces- Parameters:
initial
- the identity value for the fold operationfolder
- the folding function- Returns:
- a new Gatherer
- Throws:
NullPointerException
- if any of the parameters arenull
- See Also:
-
scan
public static <T,R> GathererPREVIEW<T,?, scanR> (Supplier<R> initial, BiFunction<? super R, ? super T, ? extends R> scanner) Returns a Gatherer that performs a Prefix Scan -- an incremental accumulation -- using the provided functions. Starting with an initial value obtained from theSupplier
, each subsequent value is obtained by applying theBiFunction
to the current value and the next input element, after which the resulting value is produced downstream.Example:
// will contain: ["1", "12", "123", "1234", "12345", "123456", "1234567", "12345678", "123456789"] List<String> numberStrings = Stream.of(1,2,3,4,5,6,7,8,9) .gather( Gatherers.scan(() -> "", (string, number) -> string + number) ) .toList();
- Type Parameters:
T
- the type of element which this gatherer consumesR
- the type of element which this gatherer produces- Parameters:
initial
- the supplier of the initial value for the scannerscanner
- the function to apply for each element- Returns:
- a new Gatherer which performs a prefix scan
- Throws:
NullPointerException
- if any of the parameters arenull
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mapConcurrent
public static <T,R> GathererPREVIEW<T,?, mapConcurrentR> (int maxConcurrency, Function<? super T, ? extends R> mapper) An operation which executes a function concurrently with a configured level of max concurrency, using virtual threads. This operation preserves the ordering of the stream.- API Note:
- In progress tasks will be attempted to be cancelled, on a best-effort basis, in situations where the downstream no longer wants to receive any more elements.
- Implementation Requirements:
- If a result of the function is to be pushed downstream but
instead the function completed exceptionally then the corresponding
exception will instead be rethrown by this method as an instance of
RuntimeException
, after which any remaining tasks are canceled. - Type Parameters:
T
- the type of inputR
- the type of output- Parameters:
maxConcurrency
- the maximum concurrency desiredmapper
- a function to be executed concurrently- Returns:
- a new Gatherer
- Throws:
IllegalArgumentException
- ifmaxConcurrency
is less than 1NullPointerException
- ifmapper
isnull
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Gatherers
when preview features are enabled.