For sequential stream pipelines, all operations are performed in the * encounter order of the pipeline * source, if the pipeline source has a defined encounter order. * *
For parallel stream pipelines, unless otherwise specified, intermediate * stream operations preserve the * encounter order of their source, and terminal operations * respect the encounter order of their source, if the source * has an encounter order. Provided that and parameters to stream operations * satisfy the non-interference * requirements, and excepting differences arising from the absence of * a defined encounter order, the result of a stream pipeline should be the * stable across multiple executions of the same operations on the same source. * However, the timing and thread in which side-effects occur (for those * operations which are allowed to produce side-effects, such as * {@link #forEach(Consumer)}), are explicitly nondeterministic for parallel * execution of stream pipelines. * *
Unless otherwise noted, passing a {@code null} argument to any stream
* method may result in a {@link NullPointerException}.
*
* @apiNote
* Streams are not data structures; they do not manage the storage for their
* elements, nor do they support access to individual elements. However,
* you can use the {@link #iterator()} or {@link #spliterator()} operations to
* perform a controlled traversal.
*
* @param This is an intermediate
* operation.
*
* @param predicate a
* non-interfering, stateless predicate to apply to
* each element to determine if it should be included
* @return the new stream
*/
Stream This is an intermediate
* operation.
*
* @param This is an
* intermediate operation.
*
* @param mapper a
* non-interfering, stateless function to apply to each
* element
* @return the new stream
*/
IntStream mapToInt(ToIntFunction mapper);
/**
* Returns a {@code LongStream} consisting of the results of applying the
* given function to the elements of this stream.
*
* This is an intermediate
* operation.
*
* @param mapper a
* non-interfering, stateless function to apply to each
* element
* @return the new stream
*/
LongStream mapToLong(ToLongFunction mapper);
/**
* Returns a {@code DoubleStream} consisting of the results of applying the
* given function to the elements of this stream.
*
* This is an intermediate
* operation.
*
* @param mapper a
* non-interfering, stateless function to apply to each
* element
* @return the new stream
*/
DoubleStream mapToDouble(ToDoubleFunction mapper);
/**
* Returns a stream consisting of the results of replacing each element of
* this stream with the contents of the stream produced by applying the
* provided mapping function to each element. If the result of the mapping
* function is {@code null}, this is treated as if the result is an empty
* stream.
*
* This is an intermediate
* operation.
*
* @apiNote
* The {@code flatMap()} operation has the effect of applying a one-to-many
* tranformation to the elements of the stream, and then flattening the
* resulting elements into a new stream. For example, if {@code orders}
* is a stream of purchase orders, and each purchase order contains a
* collection of line items, then the following produces a stream of line
* items:
* This is an intermediate
* operation.
*
* @param mapper a
* non-interfering, stateless function to apply to each
* element which produces a stream of new values
* @return the new stream
*/
IntStream flatMapToInt(Function mapper);
/**
* Returns a {@code LongStream} consisting of the results of replacing each
* element of this stream with the contents of the stream produced
* by applying the provided mapping function to each element. If the result
* of the mapping function is {@code null}, this is treated as if the
* result is an empty stream.
*
* This is an intermediate
* operation.
*
* @param mapper a
* non-interfering, stateless function to apply to
* each element which produces a stream of new values
* @return the new stream
*/
LongStream flatMapToLong(Function mapper);
/**
* Returns a {@code DoubleStream} consisting of the results of replacing each
* element of this stream with the contents of the stream produced
* by applying the provided mapping function to each element. If the result
* of the mapping function is {@code null}, this is treated as if the result
* is an empty stream.
*
* This is an intermediate
* operation.
*
* @param mapper a
* non-interfering, stateless function to apply to each
* element which produces a stream of new values
* @return the new stream
*/
DoubleStream flatMapToDouble(Function mapper);
/**
* Returns a stream consisting of the distinct elements (according to
* {@link Object#equals(Object)}) of this stream.
*
* This is a stateful
* intermediate operation.
*
* @return the new stream
*/
Stream This is a stateful
* intermediate operation.
*
* @return the new stream
*/
Stream This is a stateful
* intermediate operation.
*
* @param comparator a
* non-interfering, stateless {@code Comparator} to
* be used to compare stream elements
* @return the new stream
*/
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.
*
* @apiNote This method exists mainly to support debugging, where you want
* to see the elements as they flow past a certain point in a pipeline:
* This is a short-circuiting
* stateful intermediate operation.
*
* @param maxSize the number of elements the stream should be limited to
* @return the new stream
* @throws IllegalArgumentException if {@code maxSize} is negative
*/
Stream This is a stateful
* intermediate operation.
*
* @param startInclusive the number of leading elements to skip
* @return the new stream
* @throws IllegalArgumentException if {@code startInclusive} is negative
*/
Stream This is a short-circuiting
* stateful intermediate operation.
*
* @param startInclusive the starting position of the substream, inclusive
* @param endExclusive the ending position of the substream, exclusive
* @return the new stream
* @throws IllegalArgumentException if {@code startInclusive} or
* {@code endExclusive} is negative or {@code startInclusive} is greater
* than {@code endExclusive}
*/
Stream This is a terminal
* operation.
*
* 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.
*
* @param action a
* non-interfering action to perform on the elements
*/
void forEach(Consumer action);
/**
* Performs an action for each element of this stream, guaranteeing that
* each element is processed in encounter order for streams that have a
* defined encounter order.
*
* This is a terminal
* operation.
*
* @param action a
* non-interfering action to perform on the elements
* @see #forEach(Consumer)
*/
void forEachOrdered(Consumer action);
/**
* Returns an array containing the elements of this stream.
*
* This is a terminal
* operation.
*
* @return an array containing the elements of this stream
*/
Object[] toArray();
/**
* Returns an array containing the elements of this stream, using the
* provided {@code generator} function to allocate the returned array.
*
* This is a terminal
* operation.
*
* @param the element type of the resulting array
* @param generator a function which produces a new array of the desired
* type and the provided length
* @return an array containing the elements in this stream
* @throws ArrayStoreException if the runtime type of the array returned
* from the array generator is not a supertype of the runtime type of every
* element in this stream
*/
A[] toArray(IntFunction The {@code identity} value must be an identity for the accumulator
* function. This means that for all {@code t},
* {@code accumulator.apply(identity, t)} is equal to {@code t}.
* The {@code accumulator} function must be an
* associative function.
*
* This is a terminal
* operation.
*
* @apiNote Sum, min, max, average, and string concatenation are all special
* cases of reduction. Summing a stream of numbers can be expressed as:
*
* 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.
*
* @param identity the identity value for the accumulating function
* @param accumulator an associative
* non-interfering,
* stateless function for combining two values
* @return the result of the reduction
*/
T reduce(T identity, BinaryOperator The {@code accumulator} function must be an
* associative function.
*
* This is a terminal
* operation.
*
* @param accumulator an associative
* non-interfering,
* stateless function for combining two values
* @return the result of the reduction
* @see #reduce(Object, BinaryOperator)
* @see #min(java.util.Comparator)
* @see #max(java.util.Comparator)
*/
Optional The {@code identity} value must be an identity for the combiner
* function. This means that for all {@code u}, {@code combiner(identity, u)}
* is equal to {@code u}. Additionally, the {@code combiner} function
* must be compatible with the {@code accumulator} function; for all
* {@code u} and {@code t}, the following must hold:
* This is a terminal
* operation.
*
* @apiNote Many reductions using this form can be represented more simply
* by an explicit combination of {@code map} and {@code reduce} operations.
* The {@code accumulator} function acts as a fused mapper and accumulator,
* which can sometimes be more efficient than separate mapping and reduction,
* such as in the case where knowing the previously reduced value allows you
* to avoid some computation.
*
* @param The type of the result
* @param identity the identity value for the combiner function
* @param accumulator an associative
* non-interfering,
* stateless function for incorporating an additional
* element into a result
* @param combiner an associative
* non-interfering,
* stateless function for combining two values, which
* must be compatible with the accumulator function
* @return the result of the reduction
* @see #reduce(BinaryOperator)
* @see #reduce(Object, BinaryOperator)
*/
U reduce(U identity,
BiFunction Like {@link #reduce(Object, BinaryOperator)}, {@code collect} operations
* can be parallelized without requiring additional synchronization.
*
* This is a terminal
* operation.
*
* @apiNote There are many existing classes in the JDK whose signatures are
* a good match for use as arguments to {@code collect()}. For example,
* the following will accumulate strings into an ArrayList:
* The following will take a stream of strings and concatenates them into a
* single string:
* 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 {@code ArrayList}), no
* additional synchronization is needed for a parallel reduction.
*
* @apiNote
* The following will accumulate strings into an ArrayList:
* The following will classify {@code Person} objects by city:
* The following will classify {@code Person} objects by state and city,
* cascading two {@code Collector}s together:
* This is a terminal operation.
*
* @param comparator a non-interfering,
* stateless {@code Comparator} to use to compare
* elements of this stream
* @return an {@code Optional} describing the minimum element of this stream,
* or an empty {@code Optional} if the stream is empty
*/
Optional This is a terminal
* operation.
*
* @param comparator a non-interfering,
* stateless {@code Comparator} to use to compare
* elements of this stream
* @return an {@code Optional} describing the maximum element of this stream,
* or an empty {@code Optional} if the stream is empty
*/
Optional This is a terminal operation.
*
* @return the count of elements in this stream
*/
long count();
/**
* 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.
*
* This is a short-circuiting
* terminal operation.
*
* @param predicate a non-interfering,
* stateless predicate to apply to elements of this
* stream
* @return {@code true} if any elements of the stream match the provided
* predicate otherwise {@code false}
*/
boolean anyMatch(Predicate 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.
*
* This is a short-circuiting
* terminal operation.
*
* @param predicate a non-interfering,
* stateless predicate to apply to elements of this
* stream
* @return {@code true} if all elements of the stream match the provided
* predicate otherwise {@code false}
*/
boolean allMatch(Predicate 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.
*
* This is a short-circuiting
* terminal operation.
*
* @param predicate a non-interfering,
* stateless predicate to apply to elements of this
* stream
* @return {@code true} if no elements of the stream match the provided
* predicate otherwise {@code false}
*/
boolean noneMatch(Predicate predicate);
/**
* Returns an {@link Optional} describing the first element of this stream
* (in the encounter order), or an empty {@code 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.
*
* @return an {@code Optional} describing the first element of this stream,
* or an empty {@code Optional} if the stream is empty
* @throws NullPointerException if the element selected is null
*/
Optional 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 the first element
* in the encounter order is desired, use {@link #findFirst()} instead.)
*
* @return an {@code Optional} describing some element of this stream, or an
* empty {@code Optional} if the stream is empty
* @throws NullPointerException if the element selected is null
* @see #findFirst()
*/
Optional The first element (position {@code 0}) in the {@code Stream} will be
* the provided {@code seed}. For {@code n > 0}, the element at position
* {@code n}, will be the result of applying the function {@code f} to the
* element at position {@code n - 1}.
*
* @param {@code
* orderStream.flatMap(order -> order.getLineItems().stream())...
* }
*
* @param {@code
* list.stream()
* .filter(filteringFunction)
* .peek(e -> {System.out.println("Filtered value: " + e); });
* .map(mappingFunction)
* .peek(e -> {System.out.println("Mapped value: " + e); });
* .collect(Collectors.intoList());
* }
*
* @param consumer a
* non-interfering action to perform on the elements as
* they are consumed from the stream
* @return the new stream
*/
Stream{@code
* T result = identity;
* for (T element : this stream)
* result = accumulator.apply(result, element)
* return result;
* }
*
* but is not constrained to execute sequentially.
*
* {@code
* Integer sum = integers.reduce(0, (a, b) -> a+b);
* }
*
* or more compactly:
*
* {@code
* Integer sum = integers.reduce(0, Integer::sum);
* }
*
* {@code
* 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.
*
* {@code
* U result = identity;
* for (T element : this stream)
* result = accumulator.apply(result, element)
* return result;
* }
*
* but is not constrained to execute sequentially.
*
* {@code
* combiner.apply(u, accumulator.apply(identity, t)) == accumulator.apply(u, t)
* }
*
* {@code
* R result = resultFactory.get();
* for (T element : this stream)
* accumulator.accept(result, element);
* return result;
* }
*
* {@code
* List
*
* {@code
* String concat = stringStream.collect(StringBuilder::new, StringBuilder::append,
* StringBuilder::append)
* .toString();
* }
*
* @param {@code
* List
*
* {@code
* Map
*
* {@code
* Map
*
* @param {@code
* return mapToLong(e -> 1L).sum();
* }
*
*