Java tutorial
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See the GNU General Public License * version 2 for more details (a copy is included in the LICENSE file that * accompanied this code). * * You should have received a copy of the GNU General Public License version * 2 along with this work; if not, write to the Free Software Foundation, * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. * * Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA * or visit www.oracle.com if you need additional information or have any * questions. */ package java.util.stream; import java.util.Collections; import java.util.EnumSet; import java.util.Objects; import java.util.Set; import java.util.function.BiConsumer; import java.util.function.BinaryOperator; import java.util.function.Function; import java.util.function.Supplier; /** * A <a href="package-summary.html#Reduction">mutable reduction operation</a> 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. * * <p>Examples of mutable reduction operations include: * accumulating elements into a {@code Collection}; concatenating * strings using a {@code 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 {@link Collectors} * provides implementations of many common mutable reductions. * * <p>A {@code 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: <ul> * <li>creation of a new result container ({@link #supplier()})</li> * <li>incorporating a new data element into a result container ({@link #accumulator()})</li> * <li>combining two result containers into one ({@link #combiner()})</li> * <li>performing an optional final transform on the container ({@link #finisher()})</li> * </ul> * * <p>Collectors also have a set of characteristics, such as * {@link Characteristics#CONCURRENT}, that provide hints that can be used by a * reduction implementation to provide better performance. * * <p>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. * * <p>To ensure that sequential and parallel executions produce equivalent * results, the collector functions must satisfy an <em>identity</em> and an * <a href="package-summary.html#Associativity">associativity</a> constraints. * * <p>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 {@code a} that is the * result of any series of accumulator and combiner invocations, {@code a} must * be equivalent to {@code combiner.apply(a, supplier.get())}. * * <p>The associativity constraint says that splitting the computation must * produce an equivalent result. That is, for any input elements {@code t1} * and {@code t2}, the results {@code r1} and {@code r2} in the computation * below must be equivalent: * <pre>{@code * 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 * } </pre> * * <p>For collectors that do not have the {@code UNORDERED} characteristic, * two accumulated results {@code a1} and {@code a2} are equivalent if * {@code 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 {@code List} would consider two lists equivalent if they * contained the same elements, ignoring order.) * * <p>Libraries that implement reduction based on {@code Collector}, such as * {@link Stream#collect(Collector)}, must adhere to the following constraints: * <ul> * <li>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.</li> * <li>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.</li> * <li>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.</li> * <li>Once a result is passed to the combiner or finisher function, it * is never passed to the accumulator function again.</li> * <li>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 {@code 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.</li> * <li>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 * {@link Characteristics#UNORDERED} characteristics or if the * originating data is unordered.</li> * </ul> * * <p>In addition to the predefined implementations in {@link Collectors}, the * static factory methods {@link #of(Supplier, BiConsumer, BinaryOperator, Characteristics...)} * can be used to construct collectors. For example, you could create a collector * that accumulates widgets into a {@code TreeSet} with: * * <pre>{@code * Collector<Widget, ?, TreeSet<Widget>> intoSet = * Collector.of(TreeSet::new, TreeSet::add, * (left, right) -> { left.addAll(right); return left; }); * }</pre> * * (This behavior is also implemented by the predefined collector * {@link Collectors#toCollection(Supplier)}). * * @apiNote * Performing a reduction operation with a {@code Collector} should produce a * result equivalent to: * <pre>{@code * R container = collector.supplier().get(); * for (T t : data) * collector.accumulator().accept(container, t); * return collector.finisher().apply(container); * }</pre> * * <p>However, the library is free to partition the input, perform the reduction * on the partitions, and then use the combiner function to combine the partial * results to achieve a parallel reduction. (Depending on the specific reduction * operation, this may perform better or worse, depending on the relative cost * of the accumulator and combiner functions.) * * <p>Collectors are designed to be <em>composed</em>; many of the methods * in {@link Collectors} are functions that take a collector and produce * a new collector. For example, given the following collector that computes * the sum of the salaries of a stream of employees: * * <pre>{@code * Collector<Employee, ?, Integer> summingSalaries * = Collectors.summingInt(Employee::getSalary)) * }</pre> * * If we wanted to create a collector to tabulate the sum of salaries by * department, we could reuse the "sum of salaries" logic using * {@link Collectors#groupingBy(Function, Collector)}: * * <pre>{@code * Collector<Employee, ?, Map<Department, Integer>> summingSalariesByDept * = Collectors.groupingBy(Employee::getDepartment, summingSalaries); * }</pre> * * @see Stream#collect(Collector) * @see Collectors * * @param <T> the type of input elements to the reduction operation * @param <A> the mutable accumulation type of the reduction operation (often * hidden as an implementation detail) * @param <R> the result type of the reduction operation * @since 1.8 */ public interface Collector<T, A, R> { /** * A function that creates and returns a new mutable result container. * * @return a function which returns a new, mutable result container */ Supplier<A> supplier(); /** * A function that folds a value into a mutable result container. * * @return a function which folds a value into a mutable result container */ BiConsumer<A, T> accumulator(); /** * 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. * * @return a function which combines two partial results into a combined * result */ BinaryOperator<A> combiner(); /** * Perform the final transformation from the intermediate accumulation type * {@code A} to the final result type {@code R}. * * <p>If the characteristic {@code IDENTITY_FINISH} is * set, this function may be presumed to be an identity transform with an * unchecked cast from {@code A} to {@code R}. * * @return a function which transforms the intermediate result to the final * result */ Function<A, R> finisher(); /** * Returns a {@code Set} of {@code Collector.Characteristics} indicating * the characteristics of this Collector. This set should be immutable. * * @return an immutable set of collector characteristics */ Set<Characteristics> characteristics(); /** * Returns a new {@code Collector} described by the given {@code supplier}, * {@code accumulator}, and {@code combiner} functions. The resulting * {@code Collector} has the {@code Collector.Characteristics.IDENTITY_FINISH} * characteristic. * * @param supplier The supplier function for the new collector * @param accumulator The accumulator function for the new collector * @param combiner The combiner function for the new collector * @param characteristics The collector characteristics for the new * collector * @param <T> The type of input elements for the new collector * @param <R> The type of intermediate accumulation result, and final result, * for the new collector * @throws NullPointerException if any argument is null * @return the new {@code Collector} */ public static <T, R> Collector<T, R, R> of(Supplier<R> supplier, BiConsumer<R, T> accumulator, BinaryOperator<R> combiner, Characteristics... characteristics) { Objects.requireNonNull(supplier); Objects.requireNonNull(accumulator); Objects.requireNonNull(combiner); Objects.requireNonNull(characteristics); Set<Characteristics> cs = (characteristics.length == 0) ? Collectors.CH_ID : Collections .unmodifiableSet(EnumSet.of(Collector.Characteristics.IDENTITY_FINISH, characteristics)); return new Collectors.CollectorImpl<>(supplier, accumulator, combiner, cs); } /** * Returns a new {@code Collector} described by the given {@code supplier}, * {@code accumulator}, {@code combiner}, and {@code finisher} functions. * * @param supplier The supplier function for the new collector * @param accumulator The accumulator function for the new collector * @param combiner The combiner function for the new collector * @param finisher The finisher function for the new collector * @param characteristics The collector characteristics for the new * collector * @param <T> The type of input elements for the new collector * @param <A> The intermediate accumulation type of the new collector * @param <R> The final result type of the new collector * @throws NullPointerException if any argument is null * @return the new {@code Collector} */ public static <T, A, R> Collector<T, A, R> of(Supplier<A> supplier, BiConsumer<A, T> accumulator, BinaryOperator<A> combiner, Function<A, R> finisher, Characteristics... characteristics) { Objects.requireNonNull(supplier); Objects.requireNonNull(accumulator); Objects.requireNonNull(combiner); Objects.requireNonNull(finisher); Objects.requireNonNull(characteristics); Set<Characteristics> cs = Collectors.CH_NOID; if (characteristics.length > 0) { cs = EnumSet.noneOf(Characteristics.class); Collections.addAll(cs, characteristics); cs = Collections.unmodifiableSet(cs); } return new Collectors.CollectorImpl<>(supplier, accumulator, combiner, finisher, cs); } /** * Characteristics indicating properties of a {@code Collector}, which can * be used to optimize reduction implementations. */ enum Characteristics { /** * Indicates that this collector is <em>concurrent</em>, meaning that * the result container can support the accumulator function being * called concurrently with the same result container from multiple * threads. * * <p>If a {@code CONCURRENT} collector is not also {@code UNORDERED}, * then it should only be evaluated concurrently if applied to an * unordered data source. */ CONCURRENT, /** * Indicates that the collection operation does not commit to preserving * the encounter order of input elements. (This might be true if the * result container has no intrinsic order, such as a {@link Set}.) */ UNORDERED, /** * Indicates that the finisher function is the identity function and * can be elided. If set, it must be the case that an unchecked cast * from A to R will succeed. */ IDENTITY_FINISH } }