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Class Gatherers

java.lang.Object

java.util.stream.Gatherers

public final class Gatherers extends Object

Implementations of Gatherer that provide useful intermediate operations, such as windowing functions, folding functions, transforming elements concurrently, etc.

Since:: 24

Method Summary

Modifier and Type	Method	Description
`static <T,R> Gatherer<T,?,R>`	`fold(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.
`static <T,R> Gatherer<T,?,R>`	`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.
`static <T,R> Gatherer<T,?,R>`	`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.
`static <TR> Gatherer<TR,?,List<TR>>`	`windowFixed(int windowSize)`	Returns a Gatherer that gathers elements into windows -- encounter-ordered groups of elements -- of a fixed size.
`static <TR> Gatherer<TR,?,List<TR>>`	`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.

Methods declared in class Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

windowFixed

public static <TR> Gatherer<TR,?,List<TR>> windowFixed(int windowSize)

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 - when windowSize is less than 1

windowSliding

public static <TR> Gatherer<TR,?,List<TR>> 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. 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

fold

public static <T,R> Gatherer<T,?,R> fold(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 consumes

R - the type of elements the returned gatherer produces

Parameters:

initial - the identity value for the fold operation

folder - the folding function

Returns:

a new Gatherer

Throws:

NullPointerException - if any of the parameters are null

See Also:

scan

public static <T,R> Gatherer<T,?,R> 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. Starting with an initial value obtained from the Supplier, each subsequent value is obtained by applying the BiFunction 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 consumes; R - the type of element which this gatherer produces
Parameters:: initial - the supplier of the initial value for the scanner; scanner - the function to apply for each element
Returns:: a new Gatherer which performs a prefix scan
Throws:: NullPointerException - if any of the parameters are null

mapConcurrent

public static <T,R> Gatherer<T,?,R> 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. 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 input; R - the type of output
Parameters:: maxConcurrency - the maximum concurrency desired; mapper - a function to be executed concurrently
Returns:: a new Gatherer
Throws:: IllegalArgumentException - if maxConcurrency is less than 1; NullPointerException - if mapper is null

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