--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/jdk/src/share/classes/java/util/stream/Collectors.java Mon Apr 29 22:03:04 2013 -0700
@@ -0,0 +1,1320 @@
+/*
+ * 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.Collection;
+import java.util.Collections;
+import java.util.Comparator;
+import java.util.Comparators;
+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.NoSuchElementException;
+import java.util.Objects;
+import java.util.Set;
+import java.util.StringJoiner;
+import java.util.concurrent.ConcurrentHashMap;
+import java.util.concurrent.ConcurrentMap;
+import java.util.function.BiFunction;
+import java.util.function.BinaryOperator;
+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 {@code Collector}
+ * implementations in {@link Collectors} with the {@code Stream} API to perform
+ * mutable reduction tasks:
+ *
+ * <pre>{@code
+ * // Accumulate elements into a List
+ * List<Person> list = people.collect(Collectors.toList());
+ *
+ * // Accumulate elements into a TreeSet
+ * List<Person> list = people.collect(Collectors.toCollection(TreeSet::new));
+ *
+ * // Convert elements to strings and concatenate them, separated by commas
+ * String joined = stream.map(Object::toString)
+ * .collect(Collectors.toStringJoiner(", "))
+ * .toString();
+ *
+ * // Find highest-paid employee
+ * Employee highestPaid = employees.stream()
+ * .collect(Collectors.maxBy(Comparators.comparing(Employee::getSalary)));
+ *
+ * // Group employees by department
+ * Map<Department, List<Employee>> byDept
+ * = employees.stream()
+ * .collect(Collectors.groupingBy(Employee::getDepartment));
+ *
+ * // Find highest-paid employee by department
+ * Map<Department, Employee> highestPaidByDept
+ * = employees.stream()
+ * .collect(Collectors.groupingBy(Employee::getDepartment,
+ * Collectors.maxBy(Comparators.comparing(Employee::getSalary))));
+ *
+ * // Partition students into passing and failing
+ * Map<Boolean, List<Student>> passingFailing =
+ * students.stream()
+ * .collect(Collectors.partitioningBy(s -> s.getGrade() >= PASS_THRESHOLD);
+ *
+ * }</pre>
+ *
+ * TODO explanation of parallel collection
+ *
+ * @since 1.8
+ */
+public final class Collectors {
+
+ private static final Set<Collector.Characteristics> CH_CONCURRENT
+ = Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.CONCURRENT,
+ Collector.Characteristics.STRICTLY_MUTATIVE,
+ Collector.Characteristics.UNORDERED));
+ private static final Set<Collector.Characteristics> CH_STRICT
+ = Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.STRICTLY_MUTATIVE));
+ private static final Set<Collector.Characteristics> CH_STRICT_UNORDERED
+ = Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.STRICTLY_MUTATIVE,
+ Collector.Characteristics.UNORDERED));
+
+ 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}
+ *
+ * @see #firstWinsMerger()
+ * @see #lastWinsMerger()
+ */
+ public static <T> BinaryOperator<T> throwingMerger() {
+ return (u,v) -> { throw new IllegalStateException(String.format("Duplicate key %s", u)); };
+ }
+
+ /**
+ * Returns a merge function, suitable for use in
+ * {@link Map#merge(Object, Object, BiFunction) Map.merge()} or
+ * {@link #toMap(Function, Function, BinaryOperator) toMap()},
+ * which implements a "first wins" policy.
+ *
+ * @param <T> the type of input arguments to the merge function
+ * @return a merge function which always returns its first argument
+ * @see #lastWinsMerger()
+ * @see #throwingMerger()
+ */
+ public static <T> BinaryOperator<T> firstWinsMerger() {
+ return (u,v) -> u;
+ }
+
+ /**
+ * Returns a merge function, suitable for use in
+ * {@link Map#merge(Object, Object, BiFunction) Map.merge()} or
+ * {@link #toMap(Function, Function, BinaryOperator) toMap()},
+ * which implements a "last wins" policy.
+ *
+ * @param <T> the type of input arguments to the merge function
+ * @return a merge function which always returns its second argument
+ * @see #firstWinsMerger()
+ * @see #throwingMerger()
+ */
+ public static <T> BinaryOperator<T> lastWinsMerger() {
+ return (u,v) -> v;
+ }
+
+ /**
+ * Simple implementation class for {@code Collector}.
+ *
+ * @param <T> the type of elements to be collected
+ * @param <R> the type of the result
+ */
+ private static final class CollectorImpl<T, R> implements Collector<T,R> {
+ private final Supplier<R> resultSupplier;
+ private final BiFunction<R, T, R> accumulator;
+ private final BinaryOperator<R> combiner;
+ private final Set<Characteristics> characteristics;
+
+ CollectorImpl(Supplier<R> resultSupplier,
+ BiFunction<R, T, R> accumulator,
+ BinaryOperator<R> combiner,
+ Set<Characteristics> characteristics) {
+ this.resultSupplier = resultSupplier;
+ this.accumulator = accumulator;
+ this.combiner = combiner;
+ this.characteristics = characteristics;
+ }
+
+ CollectorImpl(Supplier<R> resultSupplier,
+ BiFunction<R, T, R> accumulator,
+ BinaryOperator<R> combiner) {
+ this(resultSupplier, accumulator, combiner, Collections.emptySet());
+ }
+
+ @Override
+ public BiFunction<R, T, R> accumulator() {
+ return accumulator;
+ }
+
+ @Override
+ public Supplier<R> resultSupplier() {
+ return resultSupplier;
+ }
+
+ @Override
+ public BinaryOperator<R> combiner() {
+ return combiner;
+ }
+
+ @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,
+ (r, t) -> { r.add(t); return r; },
+ (r1, r2) -> { r1.addAll(r2); return r1; },
+ CH_STRICT);
+ }
+
+ /**
+ * 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.
+ *
+ * @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() {
+ BiFunction<List<T>, T, List<T>> accumulator = (list, t) -> {
+ switch (list.size()) {
+ case 0:
+ return Collections.singletonList(t);
+ case 1:
+ List<T> newList = new ArrayList<>();
+ newList.add(list.get(0));
+ newList.add(t);
+ return newList;
+ default:
+ list.add(t);
+ return list;
+ }
+ };
+ BinaryOperator<List<T>> combiner = (left, right) -> {
+ switch (left.size()) {
+ case 0:
+ return right;
+ case 1:
+ List<T> newList = new ArrayList<>(left.size() + right.size());
+ newList.addAll(left);
+ newList.addAll(right);
+ return newList;
+ default:
+ left.addAll(right);
+ return left;
+ }
+ };
+ return new CollectorImpl<>(Collections::emptyList, accumulator, combiner);
+ }
+
+ /**
+ * 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.
+ *
+ * <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,
+ (r, t) -> { r.add(t); return r; },
+ (r1, r2) -> { r1.addAll(r2); return r1; },
+ CH_STRICT_UNORDERED);
+ }
+
+ /**
+ * Returns a {@code Collector} that concatenates the input elements into a
+ * new {@link StringBuilder}.
+ *
+ * @return a {@code Collector} which collects String elements into a
+ * {@code StringBuilder}, in encounter order
+ */
+ public static Collector<String, StringBuilder> toStringBuilder() {
+ return new CollectorImpl<>(StringBuilder::new,
+ (r, t) -> { r.append(t); return r; },
+ (r1, r2) -> { r1.append(r2); return r1; },
+ CH_STRICT);
+ }
+
+ /**
+ * Returns a {@code Collector} that concatenates the input elements into a
+ * new {@link StringJoiner}, using the specified delimiter.
+ *
+ * @param delimiter the delimiter to be used between each element
+ * @return A {@code Collector} which collects String elements into a
+ * {@code StringJoiner}, in encounter order
+ */
+ public static Collector<CharSequence, StringJoiner> toStringJoiner(CharSequence delimiter) {
+ BinaryOperator<StringJoiner> merger = (sj, other) -> {
+ if (other.length() > 0)
+ sj.add(other.toString());
+ return sj;
+ };
+ return new CollectorImpl<>(() -> new StringJoiner(delimiter),
+ (r, t) -> { r.add(t); return r; },
+ merger, CH_STRICT);
+ }
+
+ /**
+ * {@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<U,R>} to a {@code Collector<T,R>} 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, downstream of {@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 <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, R> Collector<T, R>
+ mapping(Function<? super T, ? extends U> mapper, Collector<? super U, R> downstream) {
+ BiFunction<R, ? super U, R> downstreamAccumulator = downstream.accumulator();
+ return new CollectorImpl<>(downstream.resultSupplier(),
+ (r, t) -> downstreamAccumulator.apply(r, mapper.apply(t)),
+ downstream.combiner(), downstream.characteristics());
+ }
+
+ /**
+ * Returns a {@code Collector<T, Long>} that counts the number of input
+ * elements.
+ *
+ * @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<T, T>} that produces the minimal element
+ * according to a given {@code Comparator}.
+ *
+ * @implSpec
+ * This produces a result equivalent to:
+ * <pre>{@code
+ * reducing(Comparators.lesserOf(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, T>
+ minBy(Comparator<? super T> comparator) {
+ return reducing(Comparators.lesserOf(comparator));
+ }
+
+ /**
+ * Returns a {@code Collector<T, T>} that produces the maximal element
+ * according to a given {@code Comparator}.
+ *
+ * @implSpec
+ * This produces a result equivalent to:
+ * <pre>{@code
+ * reducing(Comparators.greaterOf(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, T>
+ maxBy(Comparator<? super T> comparator) {
+ return reducing(Comparators.greaterOf(comparator));
+ }
+
+ /**
+ * Returns a {@code Collector<T, Long>} that produces the sum of a
+ * long-valued function applied to the input element.
+ *
+ * @implSpec
+ * This produces a result equivalent to:
+ * <pre>{@code
+ * reducing(0L, mapper, Long::sum)
+ * }</pre>
+ *
+ * @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>
+ sumBy(Function<? super T, Long> mapper) {
+ return reducing(0L, mapper, Long::sum);
+ }
+
+ /**
+ * Returns a {@code Collector<T,T>} which performs a reduction of its
+ * input elements under a specified {@code BinaryOperator}.
+ *
+ * @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.
+ *
+ * @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<>(() -> identity, (r, t) -> (r == null ? t : op.apply(r, t)), op);
+ }
+
+ /**
+ * Returns a {@code Collector<T,T>} which performs a reduction of its
+ * input elements under a specified {@code BinaryOperator}.
+ *
+ * @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 = Comparators.comparing(Person::getHeight);
+ * BinaryOperator<Person> tallerOf = Comparators.greaterOf(byHeight);
+ * Map<City, Person> tallestByCity
+ * = people.stream().collect(groupingBy(Person::getCity, reducing(tallerOf)));
+ * }</pre>
+ *
+ * @implSpec
+ * The default implementation is equivalent to:
+ * <pre>{@code
+ * reducing(null, op);
+ * }</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, T>
+ reducing(BinaryOperator<T> op) {
+ return reducing(null, op);
+ }
+
+ /**
+ * Returns a {@code Collector<T,U>} 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 reduction on a stream,
+ * use {@link Stream#reduce(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 = Comparators.comparing(String::length);
+ * BinaryOperator<String> longerOf = Comparators.greaterOf(byLength);
+ * Map<City, String> longestLastNameByCity
+ * = people.stream().collect(groupingBy(Person::getCity,
+ * reducing(Person::getLastName, longerOf)));
+ * }</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<>(() -> identity,
+ (r, t) -> (r == null ? mapper.apply(t) : op.apply(r, mapper.apply(t))),
+ op);
+ }
+
+ /**
+ * Returns a {@code Collector} implementing a "group by" operation on
+ * input elements of type {@code T}, grouping elements according to a
+ * classification function.
+ *
+ * <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, HashMap::new, 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 <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, D>
+ Collector<T, Map<K, D>> groupingBy(Function<? super T, ? extends K> classifier,
+ Collector<? super T, 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 <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, M extends Map<K, D>>
+ Collector<T, M> groupingBy(Function<? super T, ? extends K> classifier,
+ Supplier<M> mapFactory,
+ Collector<? super T, D> downstream) {
+ Supplier<D> downstreamSupplier = downstream.resultSupplier();
+ BiFunction<D, ? super T, D> downstreamAccumulator = downstream.accumulator();
+ BiFunction<M, T, M> accumulator = (m, t) -> {
+ K key = Objects.requireNonNull(classifier.apply(t), "element cannot be mapped to a null key");
+ D oldContainer = m.computeIfAbsent(key, k -> downstreamSupplier.get());
+ D newContainer = downstreamAccumulator.apply(oldContainer, t);
+ if (newContainer != oldContainer)
+ m.put(key, newContainer);
+ return m;
+ };
+ return new CollectorImpl<>(mapFactory, accumulator, mapMerger(downstream.combiner()), CH_STRICT);
+ }
+
+ /**
+ * Returns a {@code Collector} implementing a concurrent "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 {@code Collector} implementing a concurrent 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, TreeMap::new,
+ * mapping(Person::getLastName, toSet())));
+ * }</pre>
+ *
+ * @param <T> the type of the input elements
+ * @param <K> the type of the keys
+ * @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, D>
+ Collector<T, ConcurrentMap<K, D>> groupingByConcurrent(Function<? super T, ? extends K> classifier,
+ Collector<? super T, 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 <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, D, M extends ConcurrentMap<K, D>>
+ Collector<T, M> groupingByConcurrent(Function<? super T, ? extends K> classifier,
+ Supplier<M> mapFactory,
+ Collector<? super T, D> downstream) {
+ Supplier<D> downstreamSupplier = downstream.resultSupplier();
+ BiFunction<D, ? super T, D> downstreamAccumulator = downstream.accumulator();
+ BinaryOperator<M> combiner = mapMerger(downstream.combiner());
+ if (downstream.characteristics().contains(Collector.Characteristics.CONCURRENT)) {
+ BiFunction<M, T, M> accumulator = (m, t) -> {
+ K key = Objects.requireNonNull(classifier.apply(t), "element cannot be mapped to a null key");
+ downstreamAccumulator.apply(m.computeIfAbsent(key, k -> downstreamSupplier.get()), t);
+ return m;
+ };
+ return new CollectorImpl<>(mapFactory, accumulator, combiner, CH_CONCURRENT);
+ } else if (downstream.characteristics().contains(Collector.Characteristics.STRICTLY_MUTATIVE)) {
+ BiFunction<M, T, M> accumulator = (m, t) -> {
+ K key = Objects.requireNonNull(classifier.apply(t), "element cannot be mapped to a null key");
+ D resultContainer = m.computeIfAbsent(key, k -> downstreamSupplier.get());
+ synchronized (resultContainer) {
+ downstreamAccumulator.apply(resultContainer, t);
+ }
+ return m;
+ };
+ return new CollectorImpl<>(mapFactory, accumulator, combiner, CH_CONCURRENT);
+ } else {
+ BiFunction<M, T, M> accumulator = (m, t) -> {
+ K key = Objects.requireNonNull(classifier.apply(t), "element cannot be mapped to a null key");
+ do {
+ D oldResult = m.computeIfAbsent(key, k -> downstreamSupplier.get());
+ if (oldResult == null) {
+ if (m.putIfAbsent(key, downstreamAccumulator.apply(null, t)) == null)
+ return m;
+ } else {
+ synchronized (oldResult) {
+ if (m.get(key) != oldResult)
+ continue;
+ D newResult = downstreamAccumulator.apply(oldResult, t);
+ if (oldResult != newResult)
+ m.put(key, newResult);
+ return m;
+ }
+ }
+ } while (true);
+ };
+ return new CollectorImpl<>(mapFactory, accumulator, combiner, CH_CONCURRENT);
+ }
+ }
+
+ /**
+ * 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 <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>
+ Collector<T, Map<Boolean, D>> partitioningBy(Predicate<? super T> predicate,
+ Collector<? super T, D> downstream) {
+ BiFunction<D, ? super T, D> downstreamAccumulator = downstream.accumulator();
+ BiFunction<Map<Boolean, D>, T, Map<Boolean, D>> accumulator = (result, t) -> {
+ Partition<D> asPartition = ((Partition<D>) result);
+ if (predicate.test(t)) {
+ D newResult = downstreamAccumulator.apply(asPartition.forTrue, t);
+ if (newResult != asPartition.forTrue)
+ asPartition.forTrue = newResult;
+ } else {
+ D newResult = downstreamAccumulator.apply(asPartition.forFalse, t);
+ if (newResult != asPartition.forFalse)
+ asPartition.forFalse = newResult;
+ }
+ return result;
+ };
+ return new CollectorImpl<>(() -> new Partition<>(downstream.resultSupplier().get(),
+ downstream.resultSupplier().get()),
+ accumulator, partitionMerger(downstream.combiner()), CH_STRICT);
+ }
+
+ /**
+ * Merge function for two partitions, given a merge function for the
+ * elements.
+ */
+ private static <D> BinaryOperator<Map<Boolean, D>> partitionMerger(BinaryOperator<D> op) {
+ return (m1, m2) -> {
+ Partition<D> left = (Partition<D>) m1;
+ Partition<D> right = (Partition<D>) m2;
+ if (left.forFalse == null)
+ left.forFalse = right.forFalse;
+ else if (right.forFalse != null)
+ left.forFalse = op.apply(left.forFalse, right.forFalse);
+ if (left.forTrue == null)
+ left.forTrue = right.forTrue;
+ else if (right.forTrue != null)
+ left.forTrue = op.apply(left.forTrue, right.forTrue);
+ return left;
+ };
+ }
+
+ /**
+ * Accumulate elements into a {@code Map} whose keys and values are the
+ * result of applying mapping functions to the input elements.
+ * 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);
+ }
+
+ /**
+ * Accumulate elements into a {@code Map} whose keys and values are the
+ * result of applying mapping functions to the input elements. 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. There are some predefined merging functions,
+ * such as {@link #throwingMerger()}, {@link #firstWinsMerger()}, and
+ * {@link #lastWinsMerger()}, that implement common policies, or you can
+ * implement custom policies easily. 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);
+ }
+
+ /**
+ * Accumulate elements into a {@code Map} whose keys and values are the
+ * result of applying mapping functions to the input elements. 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) {
+ BiFunction<M, T, M> accumulator
+ = (map, element) -> {
+ map.merge(keyMapper.apply(element), valueMapper.apply(element), mergeFunction);
+ return map;
+ };
+ return new CollectorImpl<>(mapSupplier, accumulator, mapMerger(mergeFunction), CH_STRICT);
+ }
+
+ /**
+ * Accumulate elements into a {@code ConcurrentMap} whose keys and values
+ * are the result of applying mapping functions to the input elements.
+ * 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);
+ }
+
+ /**
+ * Accumulate elements into a {@code ConcurrentMap} whose keys and values
+ * are the result of applying mapping functions to the input elements. 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. There are some predefined merging functions,
+ * such as {@link #throwingMerger()}, {@link #firstWinsMerger()}, and
+ * {@link #lastWinsMerger()}, that implement common policies, or you can
+ * implement custom policies easily. 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);
+ }
+
+ /**
+ * Accumulate elements into a {@code ConcurrentMap} whose keys and values
+ * are the result of applying mapping functions to the input elements. 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) {
+ BiFunction<M, T, M> accumulator = (map, element) -> {
+ map.merge(keyMapper.apply(element), valueMapper.apply(element), mergeFunction);
+ return map;
+ };
+ return new CollectorImpl<>(mapSupplier, accumulator, mapMerger(mergeFunction), CH_CONCURRENT);
+ }
+
+ /**
+ * 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 #toDoubleSummaryStatistics(ToDoubleFunction)
+ * @see #toLongSummaryStatistics(ToLongFunction)
+ */
+ public static <T>
+ Collector<T, IntSummaryStatistics> toIntSummaryStatistics(ToIntFunction<? super T> mapper) {
+ return new CollectorImpl<>(IntSummaryStatistics::new,
+ (r, t) -> { r.accept(mapper.applyAsInt(t)); return r; },
+ (l, r) -> { l.combine(r); return l; }, CH_STRICT);
+ }
+
+ /**
+ * 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 #toDoubleSummaryStatistics(ToDoubleFunction)
+ * @see #toIntSummaryStatistics(ToIntFunction)
+ */
+ public static <T>
+ Collector<T, LongSummaryStatistics> toLongSummaryStatistics(ToLongFunction<? super T> mapper) {
+ return new CollectorImpl<>(LongSummaryStatistics::new,
+ (r, t) -> { r.accept(mapper.applyAsLong(t)); return r; },
+ (l, r) -> { l.combine(r); return l; }, CH_STRICT);
+ }
+
+ /**
+ * 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 #toLongSummaryStatistics(ToLongFunction)
+ * @see #toIntSummaryStatistics(ToIntFunction)
+ */
+ public static <T>
+ Collector<T, DoubleSummaryStatistics> toDoubleSummaryStatistics(ToDoubleFunction<? super T> mapper) {
+ return new CollectorImpl<>(DoubleSummaryStatistics::new,
+ (r, t) -> { r.accept(mapper.applyAsDouble(t)); return r; },
+ (l, r) -> { l.combine(r); return l; }, CH_STRICT);
+ }
+
+ /**
+ * Implementation class used by partitioningBy.
+ */
+ private static final class Partition<T>
+ extends AbstractMap<Boolean, T>
+ implements Map<Boolean, T> {
+ T forTrue;
+ 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() {
+
+ return new Iterator<Map.Entry<Boolean, T>>() {
+ int state = 0;
+
+ @Override
+ public boolean hasNext() {
+ return state < 2;
+ }
+
+ @Override
+ public Map.Entry<Boolean, T> next() {
+ if (state >= 2)
+ throw new NoSuchElementException();
+ return (state++ == 0)
+ ? new SimpleImmutableEntry<>(false, forFalse)
+ : new SimpleImmutableEntry<>(true, forTrue);
+ }
+ };
+ }
+
+ @Override
+ public int size() {
+ return 2;
+ }
+ };
+ }
+ }
+}