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 then true is returned and the predicate is not evaluated.

This is a short-circuiting terminal operation.

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:Functions.FailablePredicate<O, ?>

A non-interfering, stateless predicate to apply to elements of this stream.

Returns:boolean

true If either all elements of the stream match the provided predicate or the stream is empty, otherwise false.

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 then false is returned and the predicate is not evaluated.

This is a short-circuiting terminal operation.

Parameters

predicate:Functions.FailablePredicate<O, ?>

A non-interfering, stateless predicate to apply to elements of this stream.

Returns:boolean

true if any elements of the stream match the provided predicate, otherwise false.

Performs a mutable reduction operation on the elements of this stream using a Collector. A Collector encapsulates the functions used as arguments to collect(Supplier, BiConsumer, BiConsumer), allowing for reuse of collection strategies and composition of collect operations such as multiple-level grouping or partitioning.

If the underlying stream is parallel, and the Collector is concurrent, and either the stream is unordered or the collector is unordered, then a concurrent reduction will be performed (see Collector for details on concurrent reduction.)

This is an intermediate 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.

Note The following will accumulate strings into an ArrayList:

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 two Collectors together:

Map<String, Map<String, List<Person>>> peopleByStateAndCity
        = personStream.collect(Collectors.groupingBy(Person::getState,
                                                     Collectors.groupingBy(Person::getCity)));

Parameters

<A>

the intermediate accumulation type of the Collector.

<R>

the type of the result.

collector:Collector<? super O, A, R>

the Collector describing the reduction.

Returns:R

the result of the reduction.

See Also

collect(Supplier, BiConsumer, BiConsumer), Collectors

Performs a mutable reduction operation on the elements of this FailableStream. A mutable reduction is one in which the reduced value is a mutable result container, such as an ArrayList, 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 an intermediate operation.

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 an ArrayList:

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();

Parameters

<A>

Type of the accumulator.

<R>

type of the result.

supplier:Supplier<R>

a function that creates a new result container. For a parallel execution, this function may be called multiple times and must return a fresh value each time.

accumulator:BiConsumer<R, ? super O>

An associative, non-interfering, stateless function for incorporating an additional element into a result.

combiner:BiConsumer<R, R>

An associative, non-interfering, stateless function for combining two values, which must be compatible with the accumulator function.

Returns:R

The result of the reduction.

Returns a FailableStream consisting of the elements of this stream that match the given FailablePredicate.

This is an intermediate operation.

Parameters

predicate:Functions.FailablePredicate<O, ?>

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

Returns:Streams.FailableStream<O>

the new stream.

Performs an action for each element of this stream.

This is an intermediate 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:Functions.FailableConsumer<O, ?>

a non-interfering action to perform on the elements.

Returns a stream consisting of the results of applying the given function to the elements of this stream.

This is an intermediate operation.

Parameters

<R>

The element type of the new stream.

mapper:Functions.FailableFunction<O, R, ?>

A non-interfering, stateless function to apply to each element.

Returns:Streams.FailableStream<R>

the new stream.

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:

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 all t, accumulator.apply(identity, t) is equal to t. The accumulator function must be an associative function.

This is an intermediate operation.

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:O

the identity value for the accumulating function.

accumulator:BinaryOperator<O>

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

Returns:O

the result of the reduction.

Converts the FailableStream into an equivalent stream.

Returns:Stream<O>

A stream, which will return the same elements, which this FailableStream would return.