package com.nanjing.water.common.extend;
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import com.nanjing.water.common.ToBigDecimalFunction;
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import java.math.BigDecimal;
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import java.util.*;
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import java.util.concurrent.ConcurrentHashMap;
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import java.util.concurrent.ConcurrentMap;
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import java.util.function.*;
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import java.util.stream.Collector;
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import java.util.stream.Stream;
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public class CollectorsPlus {
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static final Set<Collector.Characteristics> CH_CONCURRENT_ID
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= Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.CONCURRENT,
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Collector.Characteristics.UNORDERED,
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Collector.Characteristics.IDENTITY_FINISH));
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static final Set<Collector.Characteristics> CH_CONCURRENT_NOID
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= Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.CONCURRENT,
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Collector.Characteristics.UNORDERED));
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static final Set<Collector.Characteristics> CH_ID
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= Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.IDENTITY_FINISH));
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static final Set<Collector.Characteristics> CH_UNORDERED_ID
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= Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.UNORDERED,
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Collector.Characteristics.IDENTITY_FINISH));
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static final Set<Collector.Characteristics> CH_NOID = Collections.emptySet();
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private CollectorsPlus() { }
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/**
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* Returns a merge function, suitable for use in
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* {@link Map#merge(Object, Object, BiFunction) Map.merge()} or
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* {@link #toMap(Function, Function, BinaryOperator) toMap()}, which always
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* throws {@code IllegalStateException}. This can be used to enforce the
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* assumption that the elements being collected are distinct.
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*
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* @param <T> the type of input arguments to the merge function
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* @return a merge function which always throw {@code IllegalStateException}
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*/
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private static <T> BinaryOperator<T> throwingMerger() {
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return (u,v) -> { throw new IllegalStateException(String.format("Duplicate key %s", u)); };
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}
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@SuppressWarnings("unchecked")
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private static <I, R> Function<I, R> castingIdentity() {
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return i -> (R) i;
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}
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/**
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* Simple implementation class for {@code Collector}.
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*
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* @param <T> the type of elements to be collected
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* @param <R> the type of the result
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*/
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static class CollectorImpl<T, A, R> implements Collector<T, A, R> {
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private final Supplier<A> supplier;
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private final BiConsumer<A, T> accumulator;
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private final BinaryOperator<A> combiner;
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private final Function<A, R> finisher;
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private final Set<Characteristics> characteristics;
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CollectorImpl(Supplier<A> supplier,
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BiConsumer<A, T> accumulator,
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BinaryOperator<A> combiner,
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Function<A,R> finisher,
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Set<Characteristics> characteristics) {
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this.supplier = supplier;
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this.accumulator = accumulator;
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this.combiner = combiner;
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this.finisher = finisher;
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this.characteristics = characteristics;
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}
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CollectorImpl(Supplier<A> supplier,
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BiConsumer<A, T> accumulator,
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BinaryOperator<A> combiner,
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Set<Characteristics> characteristics) {
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this(supplier, accumulator, combiner, castingIdentity(), characteristics);
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}
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@Override
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public BiConsumer<A, T> accumulator() {
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return accumulator;
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}
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@Override
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public Supplier<A> supplier() {
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return supplier;
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}
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@Override
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public BinaryOperator<A> combiner() {
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return combiner;
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}
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@Override
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public Function<A, R> finisher() {
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return finisher;
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}
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@Override
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public Set<Characteristics> characteristics() {
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return characteristics;
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}
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}
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/**
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* Returns a {@code Collector} that accumulates the input elements into a
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* new {@code Collection}, in encounter order. The {@code Collection} is
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* created by the provided factory.
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*
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* @param <T> the type of the input elements
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* @param <C> the type of the resulting {@code Collection}
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* @param collectionFactory a {@code Supplier} which returns a new, empty
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* {@code Collection} of the appropriate type
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* @return a {@code Collector} which collects all the input elements into a
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* {@code Collection}, in encounter order
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*/
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public static <T, C extends Collection<T>>
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Collector<T, ?, C> toCollection(Supplier<C> collectionFactory) {
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return new CollectorImpl<>(collectionFactory, Collection<T>::add,
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(r1, r2) -> { r1.addAll(r2); return r1; },
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CH_ID);
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}
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/**
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* Returns a {@code Collector} that accumulates the input elements into a
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* new {@code List}. There are no guarantees on the type, mutability,
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* serializability, or thread-safety of the {@code List} returned; if more
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* control over the returned {@code List} is required, use {@link #toCollection(Supplier)}.
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*
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* @param <T> the type of the input elements
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* @return a {@code Collector} which collects all the input elements into a
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* {@code List}, in encounter order
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*/
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public static <T>
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Collector<T, ?, List<T>> toList() {
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return new CollectorImpl<>((Supplier<List<T>>) ArrayList::new, List::add,
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(left, right) -> { left.addAll(right); return left; },
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CH_ID);
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}
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/**
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* Returns a {@code Collector} that accumulates the input elements into a
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* new {@code Set}. There are no guarantees on the type, mutability,
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* serializability, or thread-safety of the {@code Set} returned; if more
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* control over the returned {@code Set} is required, use
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* {@link #toCollection(Supplier)}.
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*
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* <p>This is an {@link Collector.Characteristics#UNORDERED unordered}
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* Collector.
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*
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* @param <T> the type of the input elements
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* @return a {@code Collector} which collects all the input elements into a
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* {@code Set}
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*/
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public static <T>
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Collector<T, ?, Set<T>> toSet() {
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return new CollectorImpl<>((Supplier<Set<T>>) HashSet::new, Set::add,
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(left, right) -> { left.addAll(right); return left; },
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CH_UNORDERED_ID);
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}
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/**
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* Returns a {@code Collector} that concatenates the input elements into a
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* {@code String}, in encounter order.
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*
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* @return a {@code Collector} that concatenates the input elements into a
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* {@code String}, in encounter order
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*/
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public static Collector<CharSequence, ?, String> joining() {
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return new CollectorImpl<CharSequence, StringBuilder, String>(
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StringBuilder::new, StringBuilder::append,
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(r1, r2) -> { r1.append(r2); return r1; },
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StringBuilder::toString, CH_NOID);
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}
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/**
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* Returns a {@code Collector} that concatenates the input elements,
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* separated by the specified delimiter, in encounter order.
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*
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* @param delimiter the delimiter to be used between each element
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* @return A {@code Collector} which concatenates CharSequence elements,
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* separated by the specified delimiter, in encounter order
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*/
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public static Collector<CharSequence, ?, String> joining(CharSequence delimiter) {
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return joining(delimiter, "", "");
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}
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/**
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* Returns a {@code Collector} that concatenates the input elements,
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* separated by the specified delimiter, with the specified prefix and
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* suffix, in encounter order.
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*
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* @param delimiter the delimiter to be used between each element
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* @param prefix the sequence of characters to be used at the beginning
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* of the joined result
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* @param suffix the sequence of characters to be used at the end
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* of the joined result
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* @return A {@code Collector} which concatenates CharSequence elements,
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* separated by the specified delimiter, in encounter order
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*/
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public static Collector<CharSequence, ?, String> joining(CharSequence delimiter,
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CharSequence prefix,
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CharSequence suffix) {
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return new CollectorImpl<>(
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() -> new StringJoiner(delimiter, prefix, suffix),
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StringJoiner::add, StringJoiner::merge,
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StringJoiner::toString, CH_NOID);
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}
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/**
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* {@code BinaryOperator<Map>} that merges the contents of its right
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* argument into its left argument, using the provided merge function to
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* handle duplicate keys.
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*
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* @param <K> type of the map keys
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* @param <V> type of the map values
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* @param <M> type of the map
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* @param mergeFunction A merge function suitable for
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* {@link Map#merge(Object, Object, BiFunction) Map.merge()}
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* @return a merge function for two maps
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*/
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private static <K, V, M extends Map<K,V>>
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BinaryOperator<M> mapMerger(BinaryOperator<V> mergeFunction) {
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return (m1, m2) -> {
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for (Map.Entry<K,V> e : m2.entrySet()) {
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m1.merge(e.getKey(), e.getValue(), mergeFunction);
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}
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return m1;
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};
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}
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/**
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* Adapts a {@code Collector} accepting elements of type {@code U} to one
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* accepting elements of type {@code T} by applying a mapping function to
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* each input element before accumulation.
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*
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* @apiNote
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* The {@code mapping()} collectors are most useful when used in a
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* multi-level reduction, such as downstream of a {@code groupingBy} or
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* {@code partitioningBy}. For example, given a stream of
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* {@code Person}, to accumulate the set of last names in each city:
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* <pre>{@code
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* Map<City, Set<String>> lastNamesByCity
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* = people.stream().collect(groupingBy(Person::getCity,
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* mapping(Person::getLastName, toSet())));
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* }</pre>
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*
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* @param <T> the type of the input elements
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* @param <U> type of elements accepted by downstream collector
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* @param <A> intermediate accumulation type of the downstream collector
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* @param <R> result type of collector
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* @param mapper a function to be applied to the input elements
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* @param downstream a collector which will accept mapped values
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* @return a collector which applies the mapping function to the input
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* elements and provides the mapped results to the downstream collector
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*/
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public static <T, U, A, R>
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Collector<T, ?, R> mapping(Function<? super T, ? extends U> mapper,
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Collector<? super U, A, R> downstream) {
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BiConsumer<A, ? super U> downstreamAccumulator = downstream.accumulator();
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return new CollectorImpl<>(downstream.supplier(),
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(r, t) -> downstreamAccumulator.accept(r, mapper.apply(t)),
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downstream.combiner(), downstream.finisher(),
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downstream.characteristics());
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}
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/**
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* Adapts a {@code Collector} to perform an additional finishing
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* transformation. For example, one could adapt the {@link #toList()}
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* collector to always produce an immutable list with:
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* <pre>{@code
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* List<String> people
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* = people.stream().collect(collectingAndThen(toList(), Collections::unmodifiableList));
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* }</pre>
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*
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* @param <T> the type of the input elements
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* @param <A> intermediate accumulation type of the downstream collector
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* @param <R> result type of the downstream collector
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* @param <RR> result type of the resulting collector
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* @param downstream a collector
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* @param finisher a function to be applied to the final result of the downstream collector
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* @return a collector which performs the action of the downstream collector,
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* followed by an additional finishing step
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*/
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public static<T,A,R,RR> Collector<T,A,RR> collectingAndThen(Collector<T,A,R> downstream,
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Function<R,RR> finisher) {
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Set<Collector.Characteristics> characteristics = downstream.characteristics();
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if (characteristics.contains(Collector.Characteristics.IDENTITY_FINISH)) {
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if (characteristics.size() == 1)
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characteristics = CollectorsPlus.CH_NOID;
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else {
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characteristics = EnumSet.copyOf(characteristics);
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characteristics.remove(Collector.Characteristics.IDENTITY_FINISH);
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characteristics = Collections.unmodifiableSet(characteristics);
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}
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}
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return new CollectorImpl<>(downstream.supplier(),
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downstream.accumulator(),
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downstream.combiner(),
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downstream.finisher().andThen(finisher),
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characteristics);
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}
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/**
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* Returns a {@code Collector} accepting elements of type {@code T} that
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* counts the number of input elements. If no elements are present, the
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* result is 0.
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*
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* @implSpec
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* This produces a result equivalent to:
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* <pre>{@code
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* reducing(0L, e -> 1L, Long::sum)
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* }</pre>
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*
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* @param <T> the type of the input elements
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* @return a {@code Collector} that counts the input elements
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*/
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public static <T> Collector<T, ?, Long>
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counting() {
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return reducing(0L, e -> 1L, Long::sum);
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}
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/**
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* Returns a {@code Collector} that produces the minimal element according
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* to a given {@code Comparator}, described as an {@code Optional<T>}.
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*
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* @implSpec
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* This produces a result equivalent to:
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* <pre>{@code
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* reducing(BinaryOperator.minBy(comparator))
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* }</pre>
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*
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* @param <T> the type of the input elements
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* @param comparator a {@code Comparator} for comparing elements
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* @return a {@code Collector} that produces the minimal value
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*/
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public static <T> Collector<T, ?, Optional<T>>
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minBy(Comparator<? super T> comparator) {
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return reducing(BinaryOperator.minBy(comparator));
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}
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/**
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* Returns a {@code Collector} that produces the maximal element according
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* to a given {@code Comparator}, described as an {@code Optional<T>}.
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*
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* @implSpec
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* This produces a result equivalent to:
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* <pre>{@code
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* reducing(BinaryOperator.maxBy(comparator))
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* }</pre>
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*
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* @param <T> the type of the input elements
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* @param comparator a {@code Comparator} for comparing elements
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* @return a {@code Collector} that produces the maximal value
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*/
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public static <T> Collector<T, ?, Optional<T>>
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maxBy(Comparator<? super T> comparator) {
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return reducing(BinaryOperator.maxBy(comparator));
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}
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/**
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* Returns a {@code Collector} that produces the sum of a integer-valued
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* function applied to the input elements. If no elements are present,
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* the result is 0.
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*
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* @param <T> the type of the input elements
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* @param mapper a function extracting the property to be summed
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* @return a {@code Collector} that produces the sum of a derived property
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*/
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public static <T> Collector<T, ?, Integer>
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summingInt(ToIntFunction<? super T> mapper) {
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return new CollectorImpl<>(
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() -> new int[1],
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(a, t) -> { a[0] += mapper.applyAsInt(t); },
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(a, b) -> { a[0] += b[0]; return a; },
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a -> a[0], CH_NOID);
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}
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/**
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* Returns a {@code Collector} that produces the sum of a long-valued
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* function applied to the input elements. If no elements are present,
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* the result is 0.
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*
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* @param <T> the type of the input elements
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* @param mapper a function extracting the property to be summed
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* @return a {@code Collector} that produces the sum of a derived property
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*/
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public static <T> Collector<T, ?, Long>
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summingLong(ToLongFunction<? super T> mapper) {
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return new CollectorImpl<>(
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() -> new long[1],
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(a, t) -> { a[0] += mapper.applyAsLong(t); },
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(a, b) -> { a[0] += b[0]; return a; },
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a -> a[0], CH_NOID);
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}
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/**
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* Returns a {@code Collector} that produces the sum of a double-valued
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* function applied to the input elements. If no elements are present,
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* the result is 0.
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*
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* <p>The sum returned can vary depending upon the order in which
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* values are recorded, due to accumulated rounding error in
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* addition of values of differing magnitudes. Values sorted by increasing
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* absolute magnitude tend to yield more accurate results. If any recorded
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* value is a {@code NaN} or the sum is at any point a {@code NaN} then the
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* sum will be {@code NaN}.
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*
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* @param <T> the type of the input elements
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* @param mapper a function extracting the property to be summed
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* @return a {@code Collector} that produces the sum of a derived property
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*/
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public static <T> Collector<T, ?, Double>
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summingDouble(ToDoubleFunction<? super T> mapper) {
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/*
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* In the arrays allocated for the collect operation, index 0
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* holds the high-order bits of the running sum, index 1 holds
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* the low-order bits of the sum computed via compensated
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* summation, and index 2 holds the simple sum used to compute
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* the proper result if the stream contains infinite values of
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* the same sign.
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*/
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return new CollectorImpl<>(
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() -> new double[3],
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(a, t) -> { sumWithCompensation(a, mapper.applyAsDouble(t));
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a[2] += mapper.applyAsDouble(t);},
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(a, b) -> { sumWithCompensation(a, b[0]);
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a[2] += b[2];
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return sumWithCompensation(a, b[1]); },
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a -> computeFinalSum(a),
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CH_NOID);
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}
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/**
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* Incorporate a new double value using Kahan summation /
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* compensation summation.
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*
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* High-order bits of the sum are in intermediateSum[0], low-order
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* bits of the sum are in intermediateSum[1], any additional
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* elements are application-specific.
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*
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* @param intermediateSum the high-order and low-order words of the intermediate sum
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* @param value the name value to be included in the running sum
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*/
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static double[] sumWithCompensation(double[] intermediateSum, double value) {
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double tmp = value - intermediateSum[1];
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double sum = intermediateSum[0];
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double velvel = sum + tmp; // Little wolf of rounding error
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intermediateSum[1] = (velvel - sum) - tmp;
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intermediateSum[0] = velvel;
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return intermediateSum;
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}
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/**
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* If the compensated sum is spuriously NaN from accumulating one
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* or more same-signed infinite values, return the
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* correctly-signed infinity stored in the simple sum.
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*/
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static double computeFinalSum(double[] summands) {
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// Better error bounds to add both terms as the final sum
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double tmp = summands[0] + summands[1];
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double simpleSum = summands[summands.length - 1];
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if (Double.isNaN(tmp) && Double.isInfinite(simpleSum)) {
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return simpleSum;
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} else {
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return tmp;
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}
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}
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/**
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* Returns a {@code Collector} that produces the arithmetic mean of an integer-valued
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* function applied to the input elements. If no elements are present,
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* the result is 0.
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*
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* @param <T> the type of the input elements
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* @param mapper a function extracting the property to be summed
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* @return a {@code Collector} that produces the sum of a derived property
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*/
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public static <T> Collector<T, ?, Double>
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averagingInt(ToIntFunction<? super T> mapper) {
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return new CollectorImpl<>(
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() -> new long[2],
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(a, t) -> { a[0] += mapper.applyAsInt(t); a[1]++; },
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(a, b) -> { a[0] += b[0]; a[1] += b[1]; return a; },
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a -> (a[1] == 0) ? 0.0d : (double) a[0] / a[1], CH_NOID);
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}
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/**
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* Returns a {@code Collector} that produces the arithmetic mean of a long-valued
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* function applied to the input elements. If no elements are present,
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* the result is 0.
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*
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* @param <T> the type of the input elements
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* @param mapper a function extracting the property to be summed
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* @return a {@code Collector} that produces the sum of a derived property
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*/
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public static <T> Collector<T, ?, Double>
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averagingLong(ToLongFunction<? super T> mapper) {
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return new CollectorImpl<>(
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() -> new long[2],
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(a, t) -> { a[0] += mapper.applyAsLong(t); a[1]++; },
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(a, b) -> { a[0] += b[0]; a[1] += b[1]; return a; },
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a -> (a[1] == 0) ? 0.0d : (double) a[0] / a[1], CH_NOID);
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}
|
|
/**
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* Returns a {@code Collector} that produces the arithmetic mean of a double-valued
|
* function applied to the input elements. If no elements are present,
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* the result is 0.
|
*
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* <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
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* value is a {@code NaN} or the sum is at any point a {@code NaN} then the
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* average will be {@code NaN}.
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*
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* @implNote The {@code double} format can represent all
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* consecutive integers in the range -2<sup>53</sup> to
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* 2<sup>53</sup>. If the pipeline has more than 2<sup>53</sup>
|
* values, the divisor in the average computation will saturate at
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* 2<sup>53</sup>, leading to additional numerical errors.
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*
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* @param <T> the type of the input elements
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* @param mapper a function extracting the property to be summed
|
* @return a {@code Collector} that produces the sum of a derived property
|
*/
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public static <T> Collector<T, ?, Double>
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averagingDouble(ToDoubleFunction<? super T> mapper) {
|
/*
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* In the arrays allocated for the collect operation, index 0
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* holds the high-order bits of the running sum, index 1 holds
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* the low-order bits of the sum computed via compensated
|
* summation, and index 2 holds the number of values seen.
|
*/
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return new CollectorImpl<>(
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() -> new double[4],
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(a, t) -> { sumWithCompensation(a, mapper.applyAsDouble(t)); a[2]++; a[3]+= mapper.applyAsDouble(t);},
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(a, b) -> { sumWithCompensation(a, b[0]); sumWithCompensation(a, b[1]); a[2] += b[2]; a[3] += b[3]; return a; },
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a -> (a[2] == 0) ? 0.0d : (computeFinalSum(a) / a[2]),
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CH_NOID);
|
}
|
|
/**
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* Returns a {@code Collector} which performs a reduction of its
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* input elements under a specified {@code BinaryOperator} using the
|
* provided identity.
|
*
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* @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.
|
*
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* @param <T> element type for the input and output of the reduction
|
* @param identity the identity value for the reduction (also, the value
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* that is returned when there are no input elements)
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* @param op a {@code BinaryOperator<T>} used to reduce the input elements
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* @return a {@code Collector} which implements the reduction operation
|
*
|
* @see #reducing(BinaryOperator)
|
* @see #reducing(Object, Function, BinaryOperator)
|
*/
|
public static <T> Collector<T, ?, T>
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reducing(T identity, BinaryOperator<T> op) {
|
return new CollectorImpl<>(
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boxSupplier(identity),
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(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>
|
*
|
* @implNote
|
* The returned {@code Collector} is not concurrent. For parallel stream
|
* pipelines, the {@code combiner} function operates by merging the keys
|
* from one map into another, which can be an expensive operation. If
|
* preservation of the order in which elements appear in the resulting {@code Map}
|
* collector is not required, using {@link #groupingByConcurrent(Function)}
|
* may offer better parallel performance.
|
*
|
* @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>
|
*
|
* @implNote
|
* The returned {@code Collector} is not concurrent. For parallel stream
|
* pipelines, the {@code combiner} function operates by merging the keys
|
* from one map into another, which can be an expensive operation. If
|
* preservation of the order in which elements are presented to the downstream
|
* collector is not required, using {@link #groupingByConcurrent(Function, Collector)}
|
* may offer better parallel performance.
|
*
|
* @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>
|
*
|
* @implNote
|
* The returned {@code Collector} is not concurrent. For parallel stream
|
* pipelines, the {@code combiner} function operates by merging the keys
|
* from one map into another, which can be an expensive operation. If
|
* preservation of the order in which elements are presented to the downstream
|
* collector is not required, using {@link #groupingByConcurrent(Function, Supplier, Collector)}
|
* may offer better parallel performance.
|
*
|
* @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 = CollectorsPlus.<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 concurrent, unordered {@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 concurrent, unordered {@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 concurrent, unordered {@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 = CollectorsPlus.<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 accumulates 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 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>
|
*
|
* @implNote
|
* The returned {@code Collector} is not concurrent. For parallel stream
|
* pipelines, the {@code combiner} function operates by merging the keys
|
* from one map into another, which can be an expensive operation. If it is
|
* not required that results are inserted into the {@code Map} in encounter
|
* order, using {@link #toConcurrentMap(Function, Function)}
|
* may offer better parallel performance.
|
*
|
* @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 accumulates 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>
|
*
|
* @implNote
|
* The returned {@code Collector} is not concurrent. For parallel stream
|
* pipelines, the {@code combiner} function operates by merging the keys
|
* from one map into another, which can be an expensive operation. If it is
|
* not required that results are merged into the {@code Map} in encounter
|
* order, using {@link #toConcurrentMap(Function, Function, BinaryOperator)}
|
* may offer better parallel performance.
|
*
|
* @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 accumulates 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.
|
*
|
* @implNote
|
* The returned {@code Collector} is not concurrent. For parallel stream
|
* pipelines, the {@code combiner} function operates by merging the keys
|
* from one map into another, which can be an expensive operation. If it is
|
* not required that results are merged into the {@code Map} in encounter
|
* order, using {@link #toConcurrentMap(Function, Function, BinaryOperator, Supplier)}
|
* may offer better parallel performance.
|
*
|
* @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 concurrent {@code Collector} that accumulates 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 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, unordered {@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 concurrent {@code Collector} that accumulates 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, unordered {@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 concurrent {@code Collector} that accumulates 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, unordered {@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);
|
}
|
|
/**
|
* BigDecimal求和
|
* @Author lin.liu
|
* @Description BigDecimal求和
|
* @Date 2021/8/26
|
* @Param [mapper]
|
* @return java.util.stream.Collector<T,?,java.math.BigDecimal>
|
**/
|
public static <T> Collector<T, ?, BigDecimal> summingBigDecimal(ToBigDecimalFunction<? super T> mapper) {
|
return new CollectorImpl<>(() -> new BigDecimal[1], (a, t) -> {
|
if (a[0] == null) {
|
a[0] = BigDecimal.ZERO;
|
}
|
a[0] = a[0].add(mapper.applyAsBigDecimal(t));
|
}, (a, b) -> {
|
a[0] = a[0].add(b[0]);
|
return a;
|
}, a -> a[0], CH_NOID);
|
}
|
|
/**
|
* 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<Entry<Boolean, T>> entrySet() {
|
return new AbstractSet<Entry<Boolean, T>>() {
|
@Override
|
public Iterator<Entry<Boolean, T>> iterator() {
|
Entry<Boolean, T> falseEntry = new SimpleImmutableEntry<>(false, forFalse);
|
Entry<Boolean, T> trueEntry = new SimpleImmutableEntry<>(true, forTrue);
|
return Arrays.asList(falseEntry, trueEntry).iterator();
|
}
|
|
@Override
|
public int size() {
|
return 2;
|
}
|
};
|
}
|
}
|
}
|
