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jdk.util.stream.Collector

A mutable reduction operation that accumulates input elements into a mutable result container, optionally transforming the accumulated result into a final representation after all input elements have been processed. Reduction operations can be performed either sequentially or in parallel.

Examples of mutable reduction operations include: accumulating elements into a Collection; concatenating strings using a StringBuilder; computing summary information about elements such as sum, min, max, or average; computing "pivot table" summaries such as "maximum valued transaction by seller", etc. The class Collectors provides implementations of many common mutable reductions.

A Collector is specified by four functions that work together to accumulate entries into a mutable result container, and optionally perform a final transform on the result. They are: creation of a new result container (supplier()) incorporating a new data element into a result container (accumulator()) combining two result containers into one (combiner()) performing an optional final transform on the container (finisher())

Collectors also have a set of characteristics, such as Collector.Characteristics.CONCURRENT, that provide hints that can be used by a reduction implementation to provide better performance.

A sequential implementation of a reduction using a collector would create a single result container using the supplier function, and invoke the accumulator function once for each input element. A parallel implementation would partition the input, create a result container for each partition, accumulate the contents of each partition into a subresult for that partition, and then use the combiner function to merge the subresults into a combined result.

To ensure that sequential and parallel executions produce equivalent results, the collector functions must satisfy an identity and an associativity constraints.

The identity constraint says that for any partially accumulated result, combining it with an empty result container must produce an equivalent result. That is, for a partially accumulated result a that is the result of any series of accumulator and combiner invocations, a must be equivalent to combiner.apply(a, supplier.get()).

The associativity constraint says that splitting the computation must produce an equivalent result. That is, for any input elements t1 and t2, the results r1 and r2 in the computation below must be equivalent:

A a1 = supplier.get();
accumulator.accept(a1, t1);
accumulator.accept(a1, t2);
R r1 = finisher.apply(a1);  // result without splitting

A a2 = supplier.get();
accumulator.accept(a2, t1);
A a3 = supplier.get();
accumulator.accept(a3, t2);
R r2 = finisher.apply(combiner.apply(a2, a3));  // result with splitting

For collectors that do not have the UNORDERED characteristic, two accumulated results a1 and a2 are equivalent if finisher.apply(a1).equals(finisher.apply(a2)). For unordered collectors, equivalence is relaxed to allow for non-equality related to differences in order. (For example, an unordered collector that accumulated elements to a List would consider two lists equivalent if they contained the same elements, ignoring order.)

Libraries that implement reduction based on Collector, such as Stream.collect(Collector), must adhere to the following constraints:

The first argument passed to the accumulator function, both
arguments passed to the combiner function, and the argument passed to the
finisher function must be the result of a previous invocation of the
result supplier, accumulator, or combiner functions.
The implementation should not do anything with the result of any of
the result supplier, accumulator, or combiner functions other than to
pass them again to the accumulator, combiner, or finisher functions,
or return them to the caller of the reduction operation.
If a result is passed to the combiner or finisher
function, and the same object is not returned from that function, it is
never used again.
Once a result is passed to the combiner or finisher function, it
is never passed to the accumulator function again.
For non-concurrent collectors, any result returned from the result
supplier, accumulator, or combiner functions must be serially
thread-confined.  This enables collection to occur in parallel without
the Collector needing to implement any additional synchronization.
The reduction implementation must manage that the input is properly
partitioned, that partitions are processed in isolation, and combining
happens only after accumulation is complete.
For concurrent collectors, an implementation is free to (but not
required to) implement reduction concurrently.  A concurrent reduction
is one where the accumulator function is called concurrently from
multiple threads, using the same concurrently-modifiable result container,
rather than keeping the result isolated during accumulation.
A concurrent reduction should only be applied if the collector has the
Collector.Characteristics.UNORDERED characteristics or if the
originating data is unordered.

In addition to the predefined implementations in Collectors, the static factory methods of(Supplier, BiConsumer, BinaryOperator, Characteristics...) can be used to construct collectors. For example, you could create a collector that accumulates widgets into a TreeSet with:

Collector<Widget, ?, TreeSet<Widget>> intoSet =
    Collector.of(TreeSet::new, TreeSet::add,
                 (left, right) -> { left.addAll(right); return left; });

(This behavior is also implemented by the predefined collector Collectors.toCollection(Supplier)).

A mutable reduction operation that
accumulates input elements into a mutable result container, optionally transforming
the accumulated result into a final representation after all input elements
have been processed.  Reduction operations can be performed either sequentially
or in parallel.

Examples of mutable reduction operations include:
accumulating elements into a Collection; concatenating
strings using a StringBuilder; computing summary information about
elements such as sum, min, max, or average; computing "pivot table" summaries
such as "maximum valued transaction by seller", etc.  The class Collectors
provides implementations of many common mutable reductions.

A Collector is specified by four functions that work together to
accumulate entries into a mutable result container, and optionally perform
a final transform on the result.  They are:
    creation of a new result container (supplier())
    incorporating a new data element into a result container (accumulator())
    combining two result containers into one (combiner())
    performing an optional final transform on the container (finisher())


Collectors also have a set of characteristics, such as
Collector.Characteristics.CONCURRENT, that provide hints that can be used by a
reduction implementation to provide better performance.

A sequential implementation of a reduction using a collector would
create a single result container using the supplier function, and invoke the
accumulator function once for each input element.  A parallel implementation
would partition the input, create a result container for each partition,
accumulate the contents of each partition into a subresult for that partition,
and then use the combiner function to merge the subresults into a combined
result.

To ensure that sequential and parallel executions produce equivalent
results, the collector functions must satisfy an identity and an
associativity constraints.

The identity constraint says that for any partially accumulated result,
combining it with an empty result container must produce an equivalent
result.  That is, for a partially accumulated result a that is the
result of any series of accumulator and combiner invocations, a must
be equivalent to combiner.apply(a, supplier.get()).

The associativity constraint says that splitting the computation must
produce an equivalent result.  That is, for any input elements t1
and t2, the results r1 and r2 in the computation
below must be equivalent:


    A a1 = supplier.get();
    accumulator.accept(a1, t1);
    accumulator.accept(a1, t2);
    R r1 = finisher.apply(a1);  // result without splitting

    A a2 = supplier.get();
    accumulator.accept(a2, t1);
    A a3 = supplier.get();
    accumulator.accept(a3, t2);
    R r2 = finisher.apply(combiner.apply(a2, a3));  // result with splitting

For collectors that do not have the UNORDERED characteristic,
two accumulated results a1 and a2 are equivalent if
finisher.apply(a1).equals(finisher.apply(a2)).  For unordered
collectors, equivalence is relaxed to allow for non-equality related to
differences in order.  (For example, an unordered collector that accumulated
elements to a List would consider two lists equivalent if they
contained the same elements, ignoring order.)

Libraries that implement reduction based on Collector, such as
Stream.collect(Collector), must adhere to the following constraints:

    The first argument passed to the accumulator function, both
    arguments passed to the combiner function, and the argument passed to the
    finisher function must be the result of a previous invocation of the
    result supplier, accumulator, or combiner functions.
    The implementation should not do anything with the result of any of
    the result supplier, accumulator, or combiner functions other than to
    pass them again to the accumulator, combiner, or finisher functions,
    or return them to the caller of the reduction operation.
    If a result is passed to the combiner or finisher
    function, and the same object is not returned from that function, it is
    never used again.
    Once a result is passed to the combiner or finisher function, it
    is never passed to the accumulator function again.
    For non-concurrent collectors, any result returned from the result
    supplier, accumulator, or combiner functions must be serially
    thread-confined.  This enables collection to occur in parallel without
    the Collector needing to implement any additional synchronization.
    The reduction implementation must manage that the input is properly
    partitioned, that partitions are processed in isolation, and combining
    happens only after accumulation is complete.
    For concurrent collectors, an implementation is free to (but not
    required to) implement reduction concurrently.  A concurrent reduction
    is one where the accumulator function is called concurrently from
    multiple threads, using the same concurrently-modifiable result container,
    rather than keeping the result isolated during accumulation.
    A concurrent reduction should only be applied if the collector has the
    Collector.Characteristics.UNORDERED characteristics or if the
    originating data is unordered.


In addition to the predefined implementations in Collectors, the
static factory methods of(Supplier, BiConsumer, BinaryOperator, Characteristics...)
can be used to construct collectors.  For example, you could create a collector
that accumulates widgets into a TreeSet with:



    Collector<Widget, ?, TreeSet<Widget>> intoSet =
        Collector.of(TreeSet::new, TreeSet::add,
                     (left, right) -> { left.addAll(right); return left; });

(This behavior is also implemented by the predefined collector
Collectors.toCollection(Supplier)).
raw docstring

*ofclj

(*of supplier accumulator combiner characteristics)
(*of supplier accumulator combiner finisher characteristics)

Returns a new Collector described by the given supplier, accumulator, combiner, and finisher functions.

supplier - The supplier function for the new collector - java.util.function.Supplier accumulator - The accumulator function for the new collector - java.util.function.BiConsumer combiner - The combiner function for the new collector - java.util.function.BinaryOperator finisher - The finisher function for the new collector - java.util.function.Function characteristics - The collector characteristics for the new collector - java.util.stream.Collector$Characteristics

returns: the new Collector - <T,A,R> java.util.stream.Collector<T,A,R>

throws: java.lang.NullPointerException - if any argument is null

Returns a new Collector described by the given supplier,
 accumulator, combiner, and finisher functions.

supplier - The supplier function for the new collector - `java.util.function.Supplier`
accumulator - The accumulator function for the new collector - `java.util.function.BiConsumer`
combiner - The combiner function for the new collector - `java.util.function.BinaryOperator`
finisher - The finisher function for the new collector - `java.util.function.Function`
characteristics - The collector characteristics for the new collector - `java.util.stream.Collector$Characteristics`

returns: the new Collector - `<T,A,R> java.util.stream.Collector<T,A,R>`

throws: java.lang.NullPointerException - if any argument is null
raw docstring

accumulatorclj

(accumulator this)

A function that folds a value into a mutable result container.

returns: a function which folds a value into a mutable result container - java.util.function.BiConsumer<A,T>

A function that folds a value into a mutable result container.

returns: a function which folds a value into a mutable result container - `java.util.function.BiConsumer<A,T>`
raw docstring

characteristicsclj

(characteristics this)

Returns a Set of Collector.Characteristics indicating the characteristics of this Collector. This set should be immutable.

returns: an immutable set of collector characteristics - java.util.Set<java.util.stream.Collector$Characteristics>

Returns a Set of Collector.Characteristics indicating
 the characteristics of this Collector.  This set should be immutable.

returns: an immutable set of collector characteristics - `java.util.Set<java.util.stream.Collector$Characteristics>`
raw docstring

combinerclj

(combiner this)

A function that accepts two partial results and merges them. The combiner function may fold state from one argument into the other and return that, or may return a new result container.

returns: a function which combines two partial results into a combined result - java.util.function.BinaryOperator<A>

A function that accepts two partial results and merges them.  The
 combiner function may fold state from one argument into the other and
 return that, or may return a new result container.

returns: a function which combines two partial results into a combined
 result - `java.util.function.BinaryOperator<A>`
raw docstring

finisherclj

(finisher this)

Perform the final transformation from the intermediate accumulation type A to the final result type R.

If the characteristic IDENTITY_TRANSFORM is set, this function may be presumed to be an identity transform with an unchecked cast from A to R.

returns: a function which transforms the intermediate result to the final result - java.util.function.Function<A,R>

Perform the final transformation from the intermediate accumulation type
 A to the final result type R.

 If the characteristic IDENTITY_TRANSFORM is
 set, this function may be presumed to be an identity transform with an
 unchecked cast from A to R.

returns: a function which transforms the intermediate result to the final
 result - `java.util.function.Function<A,R>`
raw docstring

supplierclj

(supplier this)

A function that creates and returns a new mutable result container.

returns: a function which returns a new, mutable result container - java.util.function.Supplier<A>

A function that creates and returns a new mutable result container.

returns: a function which returns a new, mutable result container - `java.util.function.Supplier<A>`
raw docstring

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