/* * Copyright (c) 2012, 2013, Oracle and/or its affiliates. All rights reserved. * DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. * * This code is free software; you can redistribute it and/or modify it * under the terms of the GNU General Public License version 2 only, as * published by the Free Software Foundation. Oracle designates this * particular file as subject to the "Classpath" exception as provided * by Oracle in the LICENSE file that accompanied this code. * * This code is distributed in the hope that it will be useful, but WITHOUT * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or * FITNESS FOR A PARTICULAR PURPOSE. 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.AbstractMap; import java.util.AbstractSet; import java.util.ArrayList; import java.util.Arrays; import java.util.Collection; import java.util.Collections; import java.util.Comparator; import java.util.DoubleSummaryStatistics; import java.util.EnumSet; import java.util.HashMap; import java.util.HashSet; import java.util.IntSummaryStatistics; import java.util.Iterator; import java.util.List; import java.util.LongSummaryStatistics; import java.util.Map; import java.util.Objects; import java.util.Optional; import java.util.Set; import java.util.StringJoiner; import java.util.concurrent.ConcurrentHashMap; import java.util.concurrent.ConcurrentMap; import java.util.function.BiConsumer; import java.util.function.BiFunction; import java.util.function.BinaryOperator; import java.util.function.Consumer; import java.util.function.Function; import java.util.function.Predicate; import java.util.function.Supplier; import java.util.function.ToDoubleFunction; import java.util.function.ToIntFunction; import java.util.function.ToLongFunction; /** * Implementations of {@link Collector} that implement various useful reduction * operations, such as accumulating elements into collections, summarizing * elements according to various criteria, etc. * * <p>The following are examples of using the predefined collectors to perform * common mutable reduction tasks: * * <pre>{@code * // Accumulate names into a List * List<String> list = people.stream().map(Person::getName).collect(Collectors.toList()); * * // Accumulate names into a TreeSet * Set<String> set = people.stream().map(Person::getName).collect(Collectors.toCollection(TreeSet::new)); * * // Convert elements to strings and concatenate them, separated by commas * String joined = things.stream() * .map(Object::toString) * .collect(Collectors.joining(", ")); * * // Compute sum of salaries of employee * int total = employees.stream() * .collect(Collectors.summingInt(Employee::getSalary))); * * // Group employees by department * Map<Department, List<Employee>> byDept * = employees.stream() * .collect(Collectors.groupingBy(Employee::getDepartment)); * * // Compute sum of salaries by department * Map<Department, Integer> totalByDept * = employees.stream() * .collect(Collectors.groupingBy(Employee::getDepartment, * Collectors.summingInt(Employee::getSalary))); * * // Partition students into passing and failing * Map<Boolean, List<Student>> passingFailing = * students.stream() * .collect(Collectors.partitioningBy(s -> s.getGrade() >= PASS_THRESHOLD)); * * }</pre> * * @since 1.8 */ public final class Collectors { static final Set<Collector.Characteristics> CH_CONCURRENT_ID = Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.CONCURRENT, Collector.Characteristics.UNORDERED, Collector.Characteristics.IDENTITY_FINISH)); static final Set<Collector.Characteristics> CH_CONCURRENT_NOID = Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.CONCURRENT, Collector.Characteristics.UNORDERED)); static final Set<Collector.Characteristics> CH_ID = Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.IDENTITY_FINISH)); static final Set<Collector.Characteristics> CH_UNORDERED_ID = Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.UNORDERED, Collector.Characteristics.IDENTITY_FINISH)); static final Set<Collector.Characteristics> CH_NOID = Collections.emptySet(); private Collectors() { } /** * Returns a merge function, suitable for use in * {@link Map#merge(Object, Object, BiFunction) Map.merge()} or * {@link #toMap(Function, Function, BinaryOperator) toMap()}, which always * throws {@code IllegalStateException}. This can be used to enforce the * assumption that the elements being collected are distinct. * * @param <T> the type of input arguments to the merge function * @return a merge function which always throw {@code IllegalStateException} */ private static <T> BinaryOperator<T> throwingMerger() { return (u,v) -> { throw new IllegalStateException(String.format("Duplicate key %s", u)); }; } @SuppressWarnings("unchecked") private static <I, R> Function<I, R> castingIdentity() { return i -> (R) i; } /** * Simple implementation class for {@code Collector}. * * @param <T> the type of elements to be collected * @param <R> the type of the result */ static class CollectorImpl<T, A, R> implements Collector<T, A, R> { private final Supplier<A> supplier; private final BiConsumer<A, T> accumulator; private final BinaryOperator<A> combiner; private final Function<A, R> finisher; private final Set<Characteristics> characteristics; CollectorImpl(Supplier<A> supplier, BiConsumer<A, T> accumulator, BinaryOperator<A> combiner, Function<A,R> finisher, Set<Characteristics> characteristics) { this.supplier = supplier; this.accumulator = accumulator; this.combiner = combiner; this.finisher = finisher; this.characteristics = characteristics; } CollectorImpl(Supplier<A> supplier, BiConsumer<A, T> accumulator, BinaryOperator<A> combiner, Set<Characteristics> characteristics) { this(supplier, accumulator, combiner, castingIdentity(), characteristics); } @Override public BiConsumer<A, T> accumulator() { return accumulator; } @Override public Supplier<A> supplier() { return supplier; } @Override public BinaryOperator<A> combiner() { return combiner; } @Override public Function<A, R> finisher() { return finisher; } @Override public Set<Characteristics> characteristics() { return characteristics; } } /** * Returns a {@code Collector} that accumulates the input elements into a * new {@code Collection}, in encounter order. The {@code Collection} is * created by the provided factory. * * @param <T> the type of the input elements * @param <C> the type of the resulting {@code Collection} * @param collectionFactory a {@code Supplier} which returns a new, empty * {@code Collection} of the appropriate type * @return a {@code Collector} which collects all the input elements into a * {@code Collection}, in encounter order */ public static <T, C extends Collection<T>> Collector<T, ?, C> toCollection(Supplier<C> collectionFactory) { return new CollectorImpl<>(collectionFactory, Collection<T>::add, (r1, r2) -> { r1.addAll(r2); return r1; }, CH_ID); } /** * Returns a {@code Collector} that accumulates the input elements into a * new {@code List}. There are no guarantees on the type, mutability, * serializability, or thread-safety of the {@code List} returned; if more * control over the returned {@code List} is required, use {@link #toCollection(Supplier)}. * * @param <T> the type of the input elements * @return a {@code Collector} which collects all the input elements into a * {@code List}, in encounter order */ public static <T> Collector<T, ?, List<T>> toList() { return new CollectorImpl<>((Supplier<List<T>>) ArrayList::new, List::add, (left, right) -> { left.addAll(right); return left; }, CH_ID); } /** * Returns a {@code Collector} that accumulates the input elements into a * new {@code Set}. There are no guarantees on the type, mutability, * serializability, or thread-safety of the {@code Set} returned; if more * control over the returned {@code Set} is required, use * {@link #toCollection(Supplier)}. * * <p>This is an {@link Collector.Characteristics#UNORDERED unordered} * Collector. * * @param <T> the type of the input elements * @return a {@code Collector} which collects all the input elements into a * {@code Set} */ public static <T> Collector<T, ?, Set<T>> toSet() { return new CollectorImpl<>((Supplier<Set<T>>) HashSet::new, Set::add, (left, right) -> { left.addAll(right); return left; }, CH_UNORDERED_ID); } /** * Returns a {@code Collector} that concatenates the input elements into a * {@code String}, in encounter order. * * @return a {@code Collector} that concatenates the input elements into a * {@code String}, in encounter order */ public static Collector<CharSequence, ?, String> joining() { return new CollectorImpl<CharSequence, StringBuilder, String>( StringBuilder::new, StringBuilder::append, (r1, r2) -> { r1.append(r2); return r1; }, StringBuilder::toString, CH_NOID); } /** * Returns a {@code Collector} that concatenates the input elements, * separated by the specified delimiter, in encounter order. * * @param delimiter the delimiter to be used between each element * @return A {@code Collector} which concatenates CharSequence elements, * separated by the specified delimiter, in encounter order */ public static Collector<CharSequence, ?, String> joining(CharSequence delimiter) { return joining(delimiter, "", ""); } /** * Returns a {@code Collector} that concatenates the input elements, * separated by the specified delimiter, with the specified prefix and * suffix, in encounter order. * * @param delimiter the delimiter to be used between each element * @param prefix the sequence of characters to be used at the beginning * of the joined result * @param suffix the sequence of characters to be used at the end * of the joined result * @return A {@code Collector} which concatenates CharSequence elements, * separated by the specified delimiter, in encounter order */ public static Collector<CharSequence, ?, String> joining(CharSequence delimiter, CharSequence prefix, CharSequence suffix) { return new CollectorImpl<>( () -> new StringJoiner(delimiter, prefix, suffix), StringJoiner::add, StringJoiner::merge, StringJoiner::toString, CH_NOID); } /** * {@code BinaryOperator<Map>} that merges the contents of its right * argument into its left argument, using the provided merge function to * handle duplicate keys. * * @param <K> type of the map keys * @param <V> type of the map values * @param <M> type of the map * @param mergeFunction A merge function suitable for * {@link Map#merge(Object, Object, BiFunction) Map.merge()} * @return a merge function for two maps */ private static <K, V, M extends Map<K,V>> BinaryOperator<M> mapMerger(BinaryOperator<V> mergeFunction) { return (m1, m2) -> { for (Map.Entry<K,V> e : m2.entrySet()) m1.merge(e.getKey(), e.getValue(), mergeFunction); return m1; }; } /** * Adapts a {@code Collector} accepting elements of type {@code U} to one * accepting elements of type {@code T} by applying a mapping function to * each input element before accumulation. * * @apiNote * The {@code mapping()} collectors are most useful when used in a * multi-level reduction, such as downstream of a {@code groupingBy} or * {@code partitioningBy}. For example, given a stream of * {@code Person}, to accumulate the set of last names in each city: * <pre>{@code * Map<City, Set<String>> lastNamesByCity * = people.stream().collect(groupingBy(Person::getCity, * mapping(Person::getLastName, toSet()))); * }</pre> * * @param <T> the type of the input elements * @param <U> type of elements accepted by downstream collector * @param <A> intermediate accumulation type of the downstream collector * @param <R> result type of collector * @param mapper a function to be applied to the input elements * @param downstream a collector which will accept mapped values * @return a collector which applies the mapping function to the input * elements and provides the mapped results to the downstream collector */ public static <T, U, A, R> Collector<T, ?, R> mapping(Function<? super T, ? extends U> mapper, Collector<? super U, A, R> downstream) { BiConsumer<A, ? super U> downstreamAccumulator = downstream.accumulator(); return new CollectorImpl<>(downstream.supplier(), (r, t) -> downstreamAccumulator.accept(r, mapper.apply(t)), downstream.combiner(), downstream.finisher(), downstream.characteristics()); } /** * Adapts a {@code Collector} to perform an additional finishing * transformation. For example, one could adapt the {@link #toList()} * collector to always produce an immutable list with: * <pre>{@code * List<String> people * = people.stream().collect(collectingAndThen(toList(), Collections::unmodifiableList)); * }</pre> * * @param <T> the type of the input elements * @param <A> intermediate accumulation type of the downstream collector * @param <R> result type of the downstream collector * @param <RR> result type of the resulting collector * @param downstream a collector * @param finisher a function to be applied to the final result of the downstream collector * @return a collector which performs the action of the downstream collector, * followed by an additional finishing step */ public static<T,A,R,RR> Collector<T,A,RR> collectingAndThen(Collector<T,A,R> downstream, Function<R,RR> finisher) { Set<Collector.Characteristics> characteristics = downstream.characteristics(); if (characteristics.contains(Collector.Characteristics.IDENTITY_FINISH)) { if (characteristics.size() == 1) characteristics = Collectors.CH_NOID; else { characteristics = EnumSet.copyOf(characteristics); characteristics.remove(Collector.Characteristics.IDENTITY_FINISH); characteristics = Collections.unmodifiableSet(characteristics); } } return new CollectorImpl<>(downstream.supplier(), downstream.accumulator(), downstream.combiner(), downstream.finisher().andThen(finisher), characteristics); } /** * Returns a {@code Collector} accepting elements of type {@code T} that * counts the number of input elements. If no elements are present, the * result is 0. * * @implSpec * This produces a result equivalent to: * <pre>{@code * reducing(0L, e -> 1L, Long::sum) * }</pre> * * @param <T> the type of the input elements * @return a {@code Collector} that counts the input elements */ public static <T> Collector<T, ?, Long> counting() { return reducing(0L, e -> 1L, Long::sum); } /** * Returns a {@code Collector} that produces the minimal element according * to a given {@code Comparator}, described as an {@code Optional<T>}. * * @implSpec * This produces a result equivalent to: * <pre>{@code * reducing(BinaryOperator.minBy(comparator)) * }</pre> * * @param <T> the type of the input elements * @param comparator a {@code Comparator} for comparing elements * @return a {@code Collector} that produces the minimal value */ public static <T> Collector<T, ?, Optional<T>> minBy(Comparator<? super T> comparator) { return reducing(BinaryOperator.minBy(comparator)); } /** * Returns a {@code Collector} that produces the maximal element according * to a given {@code Comparator}, described as an {@code Optional<T>}. * * @implSpec * This produces a result equivalent to: * <pre>{@code * reducing(BinaryOperator.maxBy(comparator)) * }</pre> * * @param <T> the type of the input elements * @param comparator a {@code Comparator} for comparing elements * @return a {@code Collector} that produces the maximal value */ public static <T> Collector<T, ?, Optional<T>> maxBy(Comparator<? super T> comparator) { return reducing(BinaryOperator.maxBy(comparator)); } /** * Returns a {@code Collector} that produces the sum of a integer-valued * function applied to the input elements. If no elements are present, * the result is 0. * * @param <T> the type of the input elements * @param mapper a function extracting the property to be summed * @return a {@code Collector} that produces the sum of a derived property */ public static <T> Collector<T, ?, Integer> summingInt(ToIntFunction<? super T> mapper) { return new CollectorImpl<T, int[], Integer>( () -> new int[1], (a, t) -> { a[0] += mapper.applyAsInt(t); }, (a, b) -> { a[0] += b[0]; return a; }, a -> a[0], CH_NOID); } /** * Returns a {@code Collector} that produces the sum of a long-valued * function applied to the input elements. If no elements are present, * the result is 0. * * @param <T> the type of the input elements * @param mapper a function extracting the property to be summed * @return a {@code Collector} that produces the sum of a derived property */ public static <T> Collector<T, ?, Long> summingLong(ToLongFunction<? super T> mapper) { return new CollectorImpl<T, long[], Long>( () -> new long[1], (a, t) -> { a[0] += mapper.applyAsLong(t); }, (a, b) -> { a[0] += b[0]; return a; }, a -> a[0], CH_NOID); } /** * Returns a {@code Collector} that produces the sum of a double-valued * function applied to the input elements. If no elements are present, * the result is 0. * * <p>The sum returned can vary depending upon the order in which * values are recorded, due to accumulated rounding error in * addition of values of differing magnitudes. Values sorted by increasing * absolute magnitude tend to yield more accurate results. If any recorded * value is a {@code NaN} or the sum is at any point a {@code NaN} then the * sum will be {@code NaN}. * * @param <T> the type of the input elements * @param mapper a function extracting the property to be summed * @return a {@code Collector} that produces the sum of a derived property */ public static <T> Collector<T, ?, Double> summingDouble(ToDoubleFunction<? super T> mapper) { return new CollectorImpl<T, double[], Double>( () -> new double[1], (a, t) -> { a[0] += mapper.applyAsDouble(t); }, (a, b) -> { a[0] += b[0]; return a; }, a -> a[0], CH_NOID); } /** * Returns a {@code Collector} that produces the arithmetic mean of an integer-valued * function applied to the input elements. If no elements are present, * the result is 0. * * @param <T> the type of the input elements * @param mapper a function extracting the property to be summed * @return a {@code Collector} that produces the sum of a derived property */ public static <T> Collector<T, ?, Double> averagingInt(ToIntFunction<? super T> mapper) { return new CollectorImpl<T, long[], Double>( () -> new long[2], (a, t) -> { a[0] += mapper.applyAsInt(t); a[1]++; }, (a, b) -> { a[0] += b[0]; a[1] += b[1]; return a; }, a -> (a[1] == 0) ? 0.0d : (double) a[0] / a[1], CH_NOID); } /** * Returns a {@code Collector} that produces the arithmetic mean of a long-valued * function applied to the input elements. If no elements are present, * the result is 0. * * @param <T> the type of the input elements * @param mapper a function extracting the property to be summed * @return a {@code Collector} that produces the sum of a derived property */ public static <T> Collector<T, ?, Double> averagingLong(ToLongFunction<? super T> mapper) { return new CollectorImpl<T, long[], Double>( () -> new long[2], (a, t) -> { a[0] += mapper.applyAsLong(t); a[1]++; }, (a, b) -> { a[0] += b[0]; a[1] += b[1]; return a; }, a -> (a[1] == 0) ? 0.0d : (double) a[0] / a[1], CH_NOID); } /** * Returns a {@code Collector} that produces the arithmetic mean of a double-valued * function applied to the input elements. If no elements are present, * the result is 0. * * <p>The average returned can vary depending upon the order in which * values are recorded, due to accumulated rounding error in * addition of values of differing magnitudes. Values sorted by increasing * absolute magnitude tend to yield more accurate results. If any recorded * value is a {@code NaN} or the sum is at any point a {@code NaN} then the * average will be {@code NaN}. * * @param <T> the type of the input elements * @param mapper a function extracting the property to be summed * @return a {@code Collector} that produces the sum of a derived property */ public static <T> Collector<T, ?, Double> averagingDouble(ToDoubleFunction<? super T> mapper) { return new CollectorImpl<T, double[], Double>( () -> new double[2], (a, t) -> { a[0] += mapper.applyAsDouble(t); a[1]++; }, (a, b) -> { a[0] += b[0]; a[1] += b[1]; return a; }, a -> (a[1] == 0) ? 0.0d : a[0] / a[1], CH_NOID); } /** * Returns a {@code Collector} which performs a reduction of its * input elements under a specified {@code BinaryOperator} using the * provided identity. * * @apiNote * The {@code reducing()} collectors are most useful when used in a * multi-level reduction, downstream of {@code groupingBy} or * {@code partitioningBy}. To perform a simple reduction on a stream, * use {@link Stream#reduce(Object, BinaryOperator)}} instead. * * @param <T> element type for the input and output of the reduction * @param identity the identity value for the reduction (also, the value * that is returned when there are no input elements) * @param op a {@code BinaryOperator<T>} used to reduce the input elements * @return a {@code Collector} which implements the reduction operation * * @see #reducing(BinaryOperator) * @see #reducing(Object, Function, BinaryOperator) */ public static <T> Collector<T, ?, T> reducing(T identity, BinaryOperator<T> op) { return new CollectorImpl<>( boxSupplier(identity), (a, t) -> { a[0] = op.apply(a[0], t); }, (a, b) -> { a[0] = op.apply(a[0], b[0]); return a; }, a -> a[0], CH_NOID); } @SuppressWarnings("unchecked") private static <T> Supplier<T[]> boxSupplier(T identity) { return () -> (T[]) new Object[] { identity }; } /** * Returns a {@code Collector} which performs a reduction of its * input elements under a specified {@code BinaryOperator}. The result * is described as an {@code Optional<T>}. * * @apiNote * The {@code reducing()} collectors are most useful when used in a * multi-level reduction, downstream of {@code groupingBy} or * {@code partitioningBy}. To perform a simple reduction on a stream, * use {@link Stream#reduce(BinaryOperator)} instead. * * <p>For example, given a stream of {@code Person}, to calculate tallest * person in each city: * <pre>{@code * Comparator<Person> byHeight = Comparator.comparing(Person::getHeight); * Map<City, Person> tallestByCity * = people.stream().collect(groupingBy(Person::getCity, reducing(BinaryOperator.maxBy(byHeight)))); * }</pre> * * @param <T> element type for the input and output of the reduction * @param op a {@code BinaryOperator<T>} used to reduce the input elements * @return a {@code Collector} which implements the reduction operation * * @see #reducing(Object, BinaryOperator) * @see #reducing(Object, Function, BinaryOperator) */ public static <T> Collector<T, ?, Optional<T>> reducing(BinaryOperator<T> op) { class OptionalBox implements Consumer<T> { T value = null; boolean present = false; @Override public void accept(T t) { if (present) { value = op.apply(value, t); } else { value = t; present = true; } } } return new CollectorImpl<T, OptionalBox, Optional<T>>( OptionalBox::new, OptionalBox::accept, (a, b) -> { if (b.present) a.accept(b.value); return a; }, a -> Optional.ofNullable(a.value), CH_NOID); } /** * Returns a {@code Collector} which performs a reduction of its * input elements under a specified mapping function and * {@code BinaryOperator}. This is a generalization of * {@link #reducing(Object, BinaryOperator)} which allows a transformation * of the elements before reduction. * * @apiNote * The {@code reducing()} collectors are most useful when used in a * multi-level reduction, downstream of {@code groupingBy} or * {@code partitioningBy}. To perform a simple map-reduce on a stream, * use {@link Stream#map(Function)} and {@link Stream#reduce(Object, BinaryOperator)} * instead. * * <p>For example, given a stream of {@code Person}, to calculate the longest * last name of residents in each city: * <pre>{@code * Comparator<String> byLength = Comparator.comparing(String::length); * Map<City, String> longestLastNameByCity * = people.stream().collect(groupingBy(Person::getCity, * reducing(Person::getLastName, BinaryOperator.maxBy(byLength)))); * }</pre> * * @param <T> the type of the input elements * @param <U> the type of the mapped values * @param identity the identity value for the reduction (also, the value * that is returned when there are no input elements) * @param mapper a mapping function to apply to each input value * @param op a {@code BinaryOperator<U>} used to reduce the mapped values * @return a {@code Collector} implementing the map-reduce operation * * @see #reducing(Object, BinaryOperator) * @see #reducing(BinaryOperator) */ public static <T, U> Collector<T, ?, U> reducing(U identity, Function<? super T, ? extends U> mapper, BinaryOperator<U> op) { return new CollectorImpl<>( boxSupplier(identity), (a, t) -> { a[0] = op.apply(a[0], mapper.apply(t)); }, (a, b) -> { a[0] = op.apply(a[0], b[0]); return a; }, a -> a[0], CH_NOID); } /** * Returns a {@code Collector} implementing a "group by" operation on * input elements of type {@code T}, grouping elements according to a * classification function, and returning the results in a {@code Map}. * * <p>The classification function maps elements to some key type {@code K}. * The collector produces a {@code Map<K, List<T>>} whose keys are the * values resulting from applying the classification function to the input * elements, and whose corresponding values are {@code List}s containing the * input elements which map to the associated key under the classification * function. * * <p>There are no guarantees on the type, mutability, serializability, or * thread-safety of the {@code Map} or {@code List} objects returned. * @implSpec * This produces a result similar to: * <pre>{@code * groupingBy(classifier, toList()); * }</pre> * * @param <T> the type of the input elements * @param <K> the type of the keys * @param classifier the classifier function mapping input elements to keys * @return a {@code Collector} implementing the group-by operation * * @see #groupingBy(Function, Collector) * @see #groupingBy(Function, Supplier, Collector) * @see #groupingByConcurrent(Function) */ public static <T, K> Collector<T, ?, Map<K, List<T>>> groupingBy(Function<? super T, ? extends K> classifier) { return groupingBy(classifier, toList()); } /** * Returns a {@code Collector} implementing a cascaded "group by" operation * on input elements of type {@code T}, grouping elements according to a * classification function, and then performing a reduction operation on * the values associated with a given key using the specified downstream * {@code Collector}. * * <p>The classification function maps elements to some key type {@code K}. * The downstream collector operates on elements of type {@code T} and * produces a result of type {@code D}. The resulting collector produces a * {@code Map<K, D>}. * * <p>There are no guarantees on the type, mutability, * serializability, or thread-safety of the {@code Map} returned. * * <p>For example, to compute the set of last names of people in each city: * <pre>{@code * Map<City, Set<String>> namesByCity * = people.stream().collect(groupingBy(Person::getCity, * mapping(Person::getLastName, toSet()))); * }</pre> * * @param <T> the type of the input elements * @param <K> the type of the keys * @param <A> the intermediate accumulation type of the downstream collector * @param <D> the result type of the downstream reduction * @param classifier a classifier function mapping input elements to keys * @param downstream a {@code Collector} implementing the downstream reduction * @return a {@code Collector} implementing the cascaded group-by operation * @see #groupingBy(Function) * * @see #groupingBy(Function, Supplier, Collector) * @see #groupingByConcurrent(Function, Collector) */ public static <T, K, A, D> Collector<T, ?, Map<K, D>> groupingBy(Function<? super T, ? extends K> classifier, Collector<? super T, A, D> downstream) { return groupingBy(classifier, HashMap::new, downstream); } /** * Returns a {@code Collector} implementing a cascaded "group by" operation * on input elements of type {@code T}, grouping elements according to a * classification function, and then performing a reduction operation on * the values associated with a given key using the specified downstream * {@code Collector}. The {@code Map} produced by the Collector is created * with the supplied factory function. * * <p>The classification function maps elements to some key type {@code K}. * The downstream collector operates on elements of type {@code T} and * produces a result of type {@code D}. The resulting collector produces a * {@code Map<K, D>}. * * <p>For example, to compute the set of last names of people in each city, * where the city names are sorted: * <pre>{@code * Map<City, Set<String>> namesByCity * = people.stream().collect(groupingBy(Person::getCity, TreeMap::new, * mapping(Person::getLastName, toSet()))); * }</pre> * * @param <T> the type of the input elements * @param <K> the type of the keys * @param <A> the intermediate accumulation type of the downstream collector * @param <D> the result type of the downstream reduction * @param <M> the type of the resulting {@code Map} * @param classifier a classifier function mapping input elements to keys * @param downstream a {@code Collector} implementing the downstream reduction * @param mapFactory a function which, when called, produces a new empty * {@code Map} of the desired type * @return a {@code Collector} implementing the cascaded group-by operation * * @see #groupingBy(Function, Collector) * @see #groupingBy(Function) * @see #groupingByConcurrent(Function, Supplier, Collector) */ public static <T, K, D, A, M extends Map<K, D>> Collector<T, ?, M> groupingBy(Function<? super T, ? extends K> classifier, Supplier<M> mapFactory, Collector<? super T, A, D> downstream) { Supplier<A> downstreamSupplier = downstream.supplier(); BiConsumer<A, ? super T> downstreamAccumulator = downstream.accumulator(); BiConsumer<Map<K, A>, T> accumulator = (m, t) -> { K key = Objects.requireNonNull(classifier.apply(t), "element cannot be mapped to a null key"); A container = m.computeIfAbsent(key, k -> downstreamSupplier.get()); downstreamAccumulator.accept(container, t); }; BinaryOperator<Map<K, A>> merger = Collectors.<K, A, Map<K, A>>mapMerger(downstream.combiner()); @SuppressWarnings("unchecked") Supplier<Map<K, A>> mangledFactory = (Supplier<Map<K, A>>) mapFactory; if (downstream.characteristics().contains(Collector.Characteristics.IDENTITY_FINISH)) { return new CollectorImpl<>(mangledFactory, accumulator, merger, CH_ID); } else { @SuppressWarnings("unchecked") Function<A, A> downstreamFinisher = (Function<A, A>) downstream.finisher(); Function<Map<K, A>, M> finisher = intermediate -> { intermediate.replaceAll((k, v) -> downstreamFinisher.apply(v)); @SuppressWarnings("unchecked") M castResult = (M) intermediate; return castResult; }; return new CollectorImpl<>(mangledFactory, accumulator, merger, finisher, CH_NOID); } } /** * Returns a concurrent {@code Collector} implementing a "group by" * operation on input elements of type {@code T}, grouping elements * according to a classification function. * * <p>This is a {@link Collector.Characteristics#CONCURRENT concurrent} and * {@link Collector.Characteristics#UNORDERED unordered} Collector. * * <p>The classification function maps elements to some key type {@code K}. * The collector produces a {@code ConcurrentMap<K, List<T>>} whose keys are the * values resulting from applying the classification function to the input * elements, and whose corresponding values are {@code List}s containing the * input elements which map to the associated key under the classification * function. * * <p>There are no guarantees on the type, mutability, or serializability * of the {@code Map} or {@code List} objects returned, or of the * thread-safety of the {@code List} objects returned. * @implSpec * This produces a result similar to: * <pre>{@code * groupingByConcurrent(classifier, toList()); * }</pre> * * @param <T> the type of the input elements * @param <K> the type of the keys * @param classifier a classifier function mapping input elements to keys * @return a {@code Collector} implementing the group-by operation * * @see #groupingBy(Function) * @see #groupingByConcurrent(Function, Collector) * @see #groupingByConcurrent(Function, Supplier, Collector) */ public static <T, K> Collector<T, ?, ConcurrentMap<K, List<T>>> groupingByConcurrent(Function<? super T, ? extends K> classifier) { return groupingByConcurrent(classifier, ConcurrentHashMap::new, toList()); } /** * Returns a concurrent {@code Collector} implementing a cascaded "group by" * operation on input elements of type {@code T}, grouping elements * according to a classification function, and then performing a reduction * operation on the values associated with a given key using the specified * downstream {@code Collector}. * * <p>This is a {@link Collector.Characteristics#CONCURRENT concurrent} and * {@link Collector.Characteristics#UNORDERED unordered} Collector. * * <p>The classification function maps elements to some key type {@code K}. * The downstream collector operates on elements of type {@code T} and * produces a result of type {@code D}. The resulting collector produces a * {@code Map<K, D>}. * * <p>For example, to compute the set of last names of people in each city, * where the city names are sorted: * <pre>{@code * ConcurrentMap<City, Set<String>> namesByCity * = people.stream().collect(groupingByConcurrent(Person::getCity, * mapping(Person::getLastName, toSet()))); * }</pre> * * @param <T> the type of the input elements * @param <K> the type of the keys * @param <A> the intermediate accumulation type of the downstream collector * @param <D> the result type of the downstream reduction * @param classifier a classifier function mapping input elements to keys * @param downstream a {@code Collector} implementing the downstream reduction * @return a {@code Collector} implementing the cascaded group-by operation * * @see #groupingBy(Function, Collector) * @see #groupingByConcurrent(Function) * @see #groupingByConcurrent(Function, Supplier, Collector) */ public static <T, K, A, D> Collector<T, ?, ConcurrentMap<K, D>> groupingByConcurrent(Function<? super T, ? extends K> classifier, Collector<? super T, A, D> downstream) { return groupingByConcurrent(classifier, ConcurrentHashMap::new, downstream); } /** * Returns a concurrent {@code Collector} implementing a cascaded "group by" * operation on input elements of type {@code T}, grouping elements * according to a classification function, and then performing a reduction * operation on the values associated with a given key using the specified * downstream {@code Collector}. The {@code ConcurrentMap} produced by the * Collector is created with the supplied factory function. * * <p>This is a {@link Collector.Characteristics#CONCURRENT concurrent} and * {@link Collector.Characteristics#UNORDERED unordered} Collector. * * <p>The classification function maps elements to some key type {@code K}. * The downstream collector operates on elements of type {@code T} and * produces a result of type {@code D}. The resulting collector produces a * {@code Map<K, D>}. * * <p>For example, to compute the set of last names of people in each city, * where the city names are sorted: * <pre>{@code * ConcurrentMap<City, Set<String>> namesByCity * = people.stream().collect(groupingBy(Person::getCity, ConcurrentSkipListMap::new, * mapping(Person::getLastName, toSet()))); * }</pre> * * * @param <T> the type of the input elements * @param <K> the type of the keys * @param <A> the intermediate accumulation type of the downstream collector * @param <D> the result type of the downstream reduction * @param <M> the type of the resulting {@code ConcurrentMap} * @param classifier a classifier function mapping input elements to keys * @param downstream a {@code Collector} implementing the downstream reduction * @param mapFactory a function which, when called, produces a new empty * {@code ConcurrentMap} of the desired type * @return a {@code Collector} implementing the cascaded group-by operation * * @see #groupingByConcurrent(Function) * @see #groupingByConcurrent(Function, Collector) * @see #groupingBy(Function, Supplier, Collector) */ public static <T, K, A, D, M extends ConcurrentMap<K, D>> Collector<T, ?, M> groupingByConcurrent(Function<? super T, ? extends K> classifier, Supplier<M> mapFactory, Collector<? super T, A, D> downstream) { Supplier<A> downstreamSupplier = downstream.supplier(); BiConsumer<A, ? super T> downstreamAccumulator = downstream.accumulator(); BinaryOperator<ConcurrentMap<K, A>> merger = Collectors.<K, A, ConcurrentMap<K, A>>mapMerger(downstream.combiner()); @SuppressWarnings("unchecked") Supplier<ConcurrentMap<K, A>> mangledFactory = (Supplier<ConcurrentMap<K, A>>) mapFactory; BiConsumer<ConcurrentMap<K, A>, T> accumulator; if (downstream.characteristics().contains(Collector.Characteristics.CONCURRENT)) { accumulator = (m, t) -> { K key = Objects.requireNonNull(classifier.apply(t), "element cannot be mapped to a null key"); A resultContainer = m.computeIfAbsent(key, k -> downstreamSupplier.get()); downstreamAccumulator.accept(resultContainer, t); }; } else { accumulator = (m, t) -> { K key = Objects.requireNonNull(classifier.apply(t), "element cannot be mapped to a null key"); A resultContainer = m.computeIfAbsent(key, k -> downstreamSupplier.get()); synchronized (resultContainer) { downstreamAccumulator.accept(resultContainer, t); } }; } if (downstream.characteristics().contains(Collector.Characteristics.IDENTITY_FINISH)) { return new CollectorImpl<>(mangledFactory, accumulator, merger, CH_CONCURRENT_ID); } else { @SuppressWarnings("unchecked") Function<A, A> downstreamFinisher = (Function<A, A>) downstream.finisher(); Function<ConcurrentMap<K, A>, M> finisher = intermediate -> { intermediate.replaceAll((k, v) -> downstreamFinisher.apply(v)); @SuppressWarnings("unchecked") M castResult = (M) intermediate; return castResult; }; return new CollectorImpl<>(mangledFactory, accumulator, merger, finisher, CH_CONCURRENT_NOID); } } /** * Returns a {@code Collector} which partitions the input elements according * to a {@code Predicate}, and organizes them into a * {@code Map<Boolean, List<T>>}. * * There are no guarantees on the type, mutability, * serializability, or thread-safety of the {@code Map} returned. * * @param <T> the type of the input elements * @param predicate a predicate used for classifying input elements * @return a {@code Collector} implementing the partitioning operation * * @see #partitioningBy(Predicate, Collector) */ public static <T> Collector<T, ?, Map<Boolean, List<T>>> partitioningBy(Predicate<? super T> predicate) { return partitioningBy(predicate, toList()); } /** * Returns a {@code Collector} which partitions the input elements according * to a {@code Predicate}, reduces the values in each partition according to * another {@code Collector}, and organizes them into a * {@code Map<Boolean, D>} whose values are the result of the downstream * reduction. * * <p>There are no guarantees on the type, mutability, * serializability, or thread-safety of the {@code Map} returned. * * @param <T> the type of the input elements * @param <A> the intermediate accumulation type of the downstream collector * @param <D> the result type of the downstream reduction * @param predicate a predicate used for classifying input elements * @param downstream a {@code Collector} implementing the downstream * reduction * @return a {@code Collector} implementing the cascaded partitioning * operation * * @see #partitioningBy(Predicate) */ public static <T, D, A> Collector<T, ?, Map<Boolean, D>> partitioningBy(Predicate<? super T> predicate, Collector<? super T, A, D> downstream) { BiConsumer<A, ? super T> downstreamAccumulator = downstream.accumulator(); BiConsumer<Partition<A>, T> accumulator = (result, t) -> downstreamAccumulator.accept(predicate.test(t) ? result.forTrue : result.forFalse, t); BinaryOperator<A> op = downstream.combiner(); BinaryOperator<Partition<A>> merger = (left, right) -> new Partition<>(op.apply(left.forTrue, right.forTrue), op.apply(left.forFalse, right.forFalse)); Supplier<Partition<A>> supplier = () -> new Partition<>(downstream.supplier().get(), downstream.supplier().get()); if (downstream.characteristics().contains(Collector.Characteristics.IDENTITY_FINISH)) { return new CollectorImpl<>(supplier, accumulator, merger, CH_ID); } else { Function<Partition<A>, Map<Boolean, D>> finisher = par -> new Partition<>(downstream.finisher().apply(par.forTrue), downstream.finisher().apply(par.forFalse)); return new CollectorImpl<>(supplier, accumulator, merger, finisher, CH_NOID); } } /** * Returns a {@code Collector} that accumulate elements into a * {@code Map} whose keys and values are the result of applying the provided * mapping functions to the input elements. * * <p>If the mapped keys contains duplicates (according to * {@link Object#equals(Object)}), an {@code IllegalStateException} is * thrown when the collection operation is performed. If the mapped keys * may have duplicates, use {@link #toMap(Function, Function, BinaryOperator)} * instead. * * @apiNote * It is common for either the key or the value to be the input elements. * In this case, the utility method * {@link java.util.function.Function#identity()} may be helpful. * For example, the following produces a {@code Map} mapping * students to their grade point average: * <pre>{@code * Map<Student, Double> studentToGPA * students.stream().collect(toMap(Functions.identity(), * student -> computeGPA(student))); * }</pre> * And the following produces a {@code Map} mapping a unique identifier to * students: * <pre>{@code * Map<String, Student> studentIdToStudent * students.stream().collect(toMap(Student::getId, * Functions.identity()); * }</pre> * * @param <T> the type of the input elements * @param <K> the output type of the key mapping function * @param <U> the output type of the value mapping function * @param keyMapper a mapping function to produce keys * @param valueMapper a mapping function to produce values * @return a {@code Collector} which collects elements into a {@code Map} * whose keys and values are the result of applying mapping functions to * the input elements * * @see #toMap(Function, Function, BinaryOperator) * @see #toMap(Function, Function, BinaryOperator, Supplier) * @see #toConcurrentMap(Function, Function) */ public static <T, K, U> Collector<T, ?, Map<K,U>> toMap(Function<? super T, ? extends K> keyMapper, Function<? super T, ? extends U> valueMapper) { return toMap(keyMapper, valueMapper, throwingMerger(), HashMap::new); } /** * Returns a {@code Collector} that accumulate elements into a * {@code Map} whose keys and values are the result of applying the provided * mapping functions to the input elements. * * <p>If the mapped * keys contains duplicates (according to {@link Object#equals(Object)}), * the value mapping function is applied to each equal element, and the * results are merged using the provided merging function. * * @apiNote * There are multiple ways to deal with collisions between multiple elements * mapping to the same key. The other forms of {@code toMap} simply use * a merge function that throws unconditionally, but you can easily write * more flexible merge policies. For example, if you have a stream * of {@code Person}, and you want to produce a "phone book" mapping name to * address, but it is possible that two persons have the same name, you can * do as follows to gracefully deals with these collisions, and produce a * {@code Map} mapping names to a concatenated list of addresses: * <pre>{@code * Map<String, String> phoneBook * people.stream().collect(toMap(Person::getName, * Person::getAddress, * (s, a) -> s + ", " + a)); * }</pre> * * @param <T> the type of the input elements * @param <K> the output type of the key mapping function * @param <U> the output type of the value mapping function * @param keyMapper a mapping function to produce keys * @param valueMapper a mapping function to produce values * @param mergeFunction a merge function, used to resolve collisions between * values associated with the same key, as supplied * to {@link Map#merge(Object, Object, BiFunction)} * @return a {@code Collector} which collects elements into a {@code Map} * whose keys are the result of applying a key mapping function to the input * elements, and whose values are the result of applying a value mapping * function to all input elements equal to the key and combining them * using the merge function * * @see #toMap(Function, Function) * @see #toMap(Function, Function, BinaryOperator, Supplier) * @see #toConcurrentMap(Function, Function, BinaryOperator) */ public static <T, K, U> Collector<T, ?, Map<K,U>> toMap(Function<? super T, ? extends K> keyMapper, Function<? super T, ? extends U> valueMapper, BinaryOperator<U> mergeFunction) { return toMap(keyMapper, valueMapper, mergeFunction, HashMap::new); } /** * Returns a {@code Collector} that accumulate elements into a * {@code Map} whose keys and values are the result of applying the provided * mapping functions to the input elements. * * <p>If the mapped * keys contains duplicates (according to {@link Object#equals(Object)}), * the value mapping function is applied to each equal element, and the * results are merged using the provided merging function. The {@code Map} * is created by a provided supplier function. * * @param <T> the type of the input elements * @param <K> the output type of the key mapping function * @param <U> the output type of the value mapping function * @param <M> the type of the resulting {@code Map} * @param keyMapper a mapping function to produce keys * @param valueMapper a mapping function to produce values * @param mergeFunction a merge function, used to resolve collisions between * values associated with the same key, as supplied * to {@link Map#merge(Object, Object, BiFunction)} * @param mapSupplier a function which returns a new, empty {@code Map} into * which the results will be inserted * @return a {@code Collector} which collects elements into a {@code Map} * whose keys are the result of applying a key mapping function to the input * elements, and whose values are the result of applying a value mapping * function to all input elements equal to the key and combining them * using the merge function * * @see #toMap(Function, Function) * @see #toMap(Function, Function, BinaryOperator) * @see #toConcurrentMap(Function, Function, BinaryOperator, Supplier) */ public static <T, K, U, M extends Map<K, U>> Collector<T, ?, M> toMap(Function<? super T, ? extends K> keyMapper, Function<? super T, ? extends U> valueMapper, BinaryOperator<U> mergeFunction, Supplier<M> mapSupplier) { BiConsumer<M, T> accumulator = (map, element) -> map.merge(keyMapper.apply(element), valueMapper.apply(element), mergeFunction); return new CollectorImpl<>(mapSupplier, accumulator, mapMerger(mergeFunction), CH_ID); } /** * Returns a {@code Collector} that accumulate elements into a * {@code ConcurrentMap} whose keys and values are the result of applying * the provided mapping functions to the input elements. * * <p>If the mapped keys contains duplicates (according to * {@link Object#equals(Object)}), an {@code IllegalStateException} is * thrown when the collection operation is performed. If the mapped keys * may have duplicates, use * {@link #toConcurrentMap(Function, Function, BinaryOperator)} instead. * * @apiNote * It is common for either the key or the value to be the input elements. * In this case, the utility method * {@link java.util.function.Function#identity()} may be helpful. * For example, the following produces a {@code Map} mapping * students to their grade point average: * <pre>{@code * Map<Student, Double> studentToGPA * students.stream().collect(toMap(Functions.identity(), * student -> computeGPA(student))); * }</pre> * And the following produces a {@code Map} mapping a unique identifier to * students: * <pre>{@code * Map<String, Student> studentIdToStudent * students.stream().collect(toConcurrentMap(Student::getId, * Functions.identity()); * }</pre> * * <p>This is a {@link Collector.Characteristics#CONCURRENT concurrent} and * {@link Collector.Characteristics#UNORDERED unordered} Collector. * * @param <T> the type of the input elements * @param <K> the output type of the key mapping function * @param <U> the output type of the value mapping function * @param keyMapper the mapping function to produce keys * @param valueMapper the mapping function to produce values * @return a concurrent {@code Collector} which collects elements into a * {@code ConcurrentMap} whose keys are the result of applying a key mapping * function to the input elements, and whose values are the result of * applying a value mapping function to the input elements * * @see #toMap(Function, Function) * @see #toConcurrentMap(Function, Function, BinaryOperator) * @see #toConcurrentMap(Function, Function, BinaryOperator, Supplier) */ public static <T, K, U> Collector<T, ?, ConcurrentMap<K,U>> toConcurrentMap(Function<? super T, ? extends K> keyMapper, Function<? super T, ? extends U> valueMapper) { return toConcurrentMap(keyMapper, valueMapper, throwingMerger(), ConcurrentHashMap::new); } /** * Returns a {@code Collector} that accumulate elements into a * {@code ConcurrentMap} whose keys and values are the result of applying * the provided mapping functions to the input elements. * * <p>If the mapped keys contains duplicates (according to {@link Object#equals(Object)}), * the value mapping function is applied to each equal element, and the * results are merged using the provided merging function. * * @apiNote * There are multiple ways to deal with collisions between multiple elements * mapping to the same key. The other forms of {@code toConcurrentMap} simply use * a merge function that throws unconditionally, but you can easily write * more flexible merge policies. For example, if you have a stream * of {@code Person}, and you want to produce a "phone book" mapping name to * address, but it is possible that two persons have the same name, you can * do as follows to gracefully deals with these collisions, and produce a * {@code Map} mapping names to a concatenated list of addresses: * <pre>{@code * Map<String, String> phoneBook * people.stream().collect(toConcurrentMap(Person::getName, * Person::getAddress, * (s, a) -> s + ", " + a)); * }</pre> * * <p>This is a {@link Collector.Characteristics#CONCURRENT concurrent} and * {@link Collector.Characteristics#UNORDERED unordered} Collector. * * @param <T> the type of the input elements * @param <K> the output type of the key mapping function * @param <U> the output type of the value mapping function * @param keyMapper a mapping function to produce keys * @param valueMapper a mapping function to produce values * @param mergeFunction a merge function, used to resolve collisions between * values associated with the same key, as supplied * to {@link Map#merge(Object, Object, BiFunction)} * @return a concurrent {@code Collector} which collects elements into a * {@code ConcurrentMap} whose keys are the result of applying a key mapping * function to the input elements, and whose values are the result of * applying a value mapping function to all input elements equal to the key * and combining them using the merge function * * @see #toConcurrentMap(Function, Function) * @see #toConcurrentMap(Function, Function, BinaryOperator, Supplier) * @see #toMap(Function, Function, BinaryOperator) */ public static <T, K, U> Collector<T, ?, ConcurrentMap<K,U>> toConcurrentMap(Function<? super T, ? extends K> keyMapper, Function<? super T, ? extends U> valueMapper, BinaryOperator<U> mergeFunction) { return toConcurrentMap(keyMapper, valueMapper, mergeFunction, ConcurrentHashMap::new); } /** * Returns a {@code Collector} that accumulate elements into a * {@code ConcurrentMap} whose keys and values are the result of applying * the provided mapping functions to the input elements. * * <p>If the mapped keys contains duplicates (according to {@link Object#equals(Object)}), * the value mapping function is applied to each equal element, and the * results are merged using the provided merging function. The * {@code ConcurrentMap} is created by a provided supplier function. * * <p>This is a {@link Collector.Characteristics#CONCURRENT concurrent} and * {@link Collector.Characteristics#UNORDERED unordered} Collector. * * @param <T> the type of the input elements * @param <K> the output type of the key mapping function * @param <U> the output type of the value mapping function * @param <M> the type of the resulting {@code ConcurrentMap} * @param keyMapper a mapping function to produce keys * @param valueMapper a mapping function to produce values * @param mergeFunction a merge function, used to resolve collisions between * values associated with the same key, as supplied * to {@link Map#merge(Object, Object, BiFunction)} * @param mapSupplier a function which returns a new, empty {@code Map} into * which the results will be inserted * @return a concurrent {@code Collector} which collects elements into a * {@code ConcurrentMap} whose keys are the result of applying a key mapping * function to the input elements, and whose values are the result of * applying a value mapping function to all input elements equal to the key * and combining them using the merge function * * @see #toConcurrentMap(Function, Function) * @see #toConcurrentMap(Function, Function, BinaryOperator) * @see #toMap(Function, Function, BinaryOperator, Supplier) */ public static <T, K, U, M extends ConcurrentMap<K, U>> Collector<T, ?, M> toConcurrentMap(Function<? super T, ? extends K> keyMapper, Function<? super T, ? extends U> valueMapper, BinaryOperator<U> mergeFunction, Supplier<M> mapSupplier) { BiConsumer<M, T> accumulator = (map, element) -> map.merge(keyMapper.apply(element), valueMapper.apply(element), mergeFunction); return new CollectorImpl<>(mapSupplier, accumulator, mapMerger(mergeFunction), CH_CONCURRENT_ID); } /** * Returns a {@code Collector} which applies an {@code int}-producing * mapping function to each input element, and returns summary statistics * for the resulting values. * * @param <T> the type of the input elements * @param mapper a mapping function to apply to each element * @return a {@code Collector} implementing the summary-statistics reduction * * @see #summarizingDouble(ToDoubleFunction) * @see #summarizingLong(ToLongFunction) */ public static <T> Collector<T, ?, IntSummaryStatistics> summarizingInt(ToIntFunction<? super T> mapper) { return new CollectorImpl<T, IntSummaryStatistics, IntSummaryStatistics>( IntSummaryStatistics::new, (r, t) -> r.accept(mapper.applyAsInt(t)), (l, r) -> { l.combine(r); return l; }, CH_ID); } /** * Returns a {@code Collector} which applies an {@code long}-producing * mapping function to each input element, and returns summary statistics * for the resulting values. * * @param <T> the type of the input elements * @param mapper the mapping function to apply to each element * @return a {@code Collector} implementing the summary-statistics reduction * * @see #summarizingDouble(ToDoubleFunction) * @see #summarizingInt(ToIntFunction) */ public static <T> Collector<T, ?, LongSummaryStatistics> summarizingLong(ToLongFunction<? super T> mapper) { return new CollectorImpl<T, LongSummaryStatistics, LongSummaryStatistics>( LongSummaryStatistics::new, (r, t) -> r.accept(mapper.applyAsLong(t)), (l, r) -> { l.combine(r); return l; }, CH_ID); } /** * Returns a {@code Collector} which applies an {@code double}-producing * mapping function to each input element, and returns summary statistics * for the resulting values. * * @param <T> the type of the input elements * @param mapper a mapping function to apply to each element * @return a {@code Collector} implementing the summary-statistics reduction * * @see #summarizingLong(ToLongFunction) * @see #summarizingInt(ToIntFunction) */ public static <T> Collector<T, ?, DoubleSummaryStatistics> summarizingDouble(ToDoubleFunction<? super T> mapper) { return new CollectorImpl<T, DoubleSummaryStatistics, DoubleSummaryStatistics>( DoubleSummaryStatistics::new, (r, t) -> r.accept(mapper.applyAsDouble(t)), (l, r) -> { l.combine(r); return l; }, CH_ID); } /** * Implementation class used by partitioningBy. */ private static final class Partition<T> extends AbstractMap<Boolean, T> implements Map<Boolean, T> { final T forTrue; final T forFalse; Partition(T forTrue, T forFalse) { this.forTrue = forTrue; this.forFalse = forFalse; } @Override public Set<Map.Entry<Boolean, T>> entrySet() { return new AbstractSet<Map.Entry<Boolean, T>>() { @Override public Iterator<Map.Entry<Boolean, T>> iterator() { Map.Entry<Boolean, T> falseEntry = new SimpleImmutableEntry<>(false, forFalse); Map.Entry<Boolean, T> trueEntry = new SimpleImmutableEntry<>(true, forTrue); return Arrays.asList(falseEntry, trueEntry).iterator(); } @Override public int size() { return 2; } }; } } }