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/**
*
* Copyright (c) 2006-2019, Speedment, Inc. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License"); You may not
* use this file except in compliance with the License. You may obtain a copy of
* the License at:
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations under
* the License.
*/
package com.speedment.common.mapstream;
import com.speedment.common.mapstream.util.CollectorUtil;
import java.util.*;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.ConcurrentNavigableMap;
import java.util.concurrent.ConcurrentSkipListMap;
import java.util.function.*;
import java.util.stream.*;
import static java.util.Collections.newSetFromMap;
/**
* A java {@code Stream} wrapper that stream over Key-Value pairs. With this
* wrapper you get access to additional operators for working with two valued
* collections.
*
* @author Emil Forslund
* @author Per Minborg
* @param the key type
* @param the value type
*
* @since 2.1.0
*/
public final class MapStream implements Stream> {
private Stream> inner;
/**
* Constructs a new {@code MapStream} from a single entry.
*
* @param key type
* @param value type
* @param entry the entry
* @return created {@code MapStream}
*/
public static MapStream of(Map.Entry entry) {
return new MapStream<>(Stream.of(entry));
}
/**
* Constructs a new {@code MapStream} from an array of entries.
*
* @param key type
* @param value type
* @param entries elements to stream over
* @return created {@code MapStream}
*/
@SafeVarargs // Creating a Stream of an array is safe.
@SuppressWarnings({"unchecked", "varargs"})
public static MapStream of(Map.Entry... entries) {
return new MapStream<>(Stream.of(entries));
}
/**
* Constructs a new {@code MapStream} from a map of key-value pairs. The map
* will not be affected.
*
* This is equivalent to writing:
* {@code MapStream.of(map.entrySet().stream());}
*
* @param key type
* @param value type
* @param map elements to stream over
* @return created {@code MapStream}
*/
public static MapStream of(Map map) {
return of(map, false);
}
/**
* Constructs a new {@code MapStream} from a map of key-value pairs. The map
* will not be affected.
*
* This is equivalent to writing the following if {@code parallel} is set to
* {@code true}:
* {@code MapStream.of(map.entrySet().stream().parallel());}
*
* @param key type
* @param value type
* @param map elements to stream over
* @param parallel if the new stream should be executed in parallel
* @return created {@code MapStream}
*/
public static MapStream of(Map map, boolean parallel) {
final MapStream stream = new MapStream<>(map.entrySet().stream());
if (parallel) stream.inner = stream.inner.parallel();
return stream;
}
/**
* Constructs a new {@code MapStream} by wrapping a key-value pair stream.
* The provided stream will be wrapped in this stream. After this method is
* called, no more changes should be done to the stream!
*
* @param key type
* @param value type
* @param stream stream to wrap
* @return created {@code MapStream}
*/
public static MapStream of(Stream> stream) {
return new MapStream<>(stream);
}
/**
* Constructs a new {@code MapStream} by wrapping a key-stream and
* calculating the corresponding values using the supplied function.
*
* @param key type
* @param value type
* @param keys stream of keys to wrap
* @param valueFromKey method for calculating values from keys
* @return created {@code MapStream}
*/
public static MapStream fromKeys(Stream keys, Function valueFromKey) {
return new MapStream<>(keys.map(k -> new AbstractMap.SimpleEntry<>(k, valueFromKey.apply(k))));
}
/**
* Constructs a new {@code MapStream} by wrapping a value-stream and
* calculating the corresponding keys using the supplied function.
*
* @param key type
* @param value type
* @param values stream of values to wrap
* @param keyFromValue method for calculating keys from values
* @return created {@code MapStream}
*/
public static MapStream fromValues(Stream values, Function keyFromValue) {
return new MapStream<>(values.map(v -> new AbstractMap.SimpleEntry<>(keyFromValue.apply(v), v)));
}
/**
* Constructs a new {@code MapStream} by wrapping a stream of objects and
* calculating both keys and values using the supplied functions.
*
* @param original stream type
* @param key type
* @param value type
* @param stream original stream
* @param keyMapper method for calculating keys
* @param valueMapper method for calculating values
* @return created {@code MapStream}
*/
public static MapStream fromStream(Stream stream, Function keyMapper, Function valueMapper) {
return new MapStream<>(stream.map(
e -> new AbstractMap.SimpleEntry<>(
keyMapper.apply(e),
valueMapper.apply(e)
)
));
}
/**
* Constructs an empty {@code MapStream}.
*
* @param key type
* @param value type
* @return an empty {@code MapStream}
*/
public static MapStream empty() {
return new MapStream<>(Stream.empty());
}
/**
* Produces a new MapStream by flipping the specified one so that keys
* become values and values become keys. This will consume the supplied
* stream.
*
* @param original key type
* @param original value type
* @param original original MapStream
* @return new MapStream with keys and values flipped
*/
public static MapStream flip(MapStream original) {
return MapStream.fromStream(
original,
Map.Entry::getValue,
Map.Entry::getKey
);
}
/**
* Returns a stream consisting of the elements of this stream that match
* the given predicate.
*
* This is an intermediate operation.
*
* @param predicate a non-interfering, stateless predicate to apply to each
* element to determine if it should be included
* @return the new stream
*/
@Override
public MapStream filter(Predicate> predicate) {
inner = inner.filter(predicate);
return this;
}
/**
* Returns a stream consisting of the elements of this stream that match
* the given predicate.
*
* This is an intermediate operation.
*
* @param predicate a non-interfering, stateless predicate to apply to each
* key-value pair to determine if it should be included
* @return the new stream
*/
public MapStream filter(BiPredicate predicate) {
return filter(e -> predicate.test(e.getKey(), e.getValue()));
}
/**
* Returns a stream consisting of the elements of this stream where the key
* component matches the given predicate.
*
* This is an intermediate operation.
*
* @param predicate a non-interfering, stateless predicate to apply to each
* key to determine if the entry should be included
* @return the new stream
*/
public MapStream filterKey(Predicate predicate) {
return filter(e -> predicate.test(e.getKey()));
}
/**
* Returns a stream consisting of the elements of this stream where the
* value component matches the given predicate.
*
* This is an intermediate operation.
*
* @param predicate a non-interfering, stateless predicate to apply to each
* value to determine if the entry should be included
* @return the new stream
*/
public MapStream filterValue(Predicate predicate) {
return filter(e -> predicate.test(e.getValue()));
}
/**
* Returns a stream consisting of the results of applying the given
* function to the elements of this stream.
*
* This is an intermediate operation.
*
* @param the element type of the new stream
* @param mapper a non-interfering, stateless function to apply to each
* element
* @return the new stream
*/
@Override
public Stream map(Function, ? extends R> mapper) {
return inner.map(mapper);
}
/**
* Returns a stream consisting of the results of applying the given
* function to the elements of this stream.
*
* This is an intermediate operation.
*
* @param the element type of the new stream
* @param mapper a non-interfering, stateless function to apply to each
* key-value pair
* @return the new stream
*/
public Stream map(BiFunction mapper) {
return map(e -> mapper.apply(e.getKey(), e.getValue()));
}
/**
* Returns a stream consisting of the results of applying the given
* function to the key-component of this stream.
*
* This is an intermediate operation.
*
* @param the element type of the new stream
* @param mapper a non-interfering, stateless function to apply to each
* key in the stream
* @return the new stream
*/
public MapStream mapKey(BiFunction mapper) {
return new MapStream<>(inner.map(e
-> new AbstractMap.SimpleEntry<>(
mapper.apply(e.getKey(), e.getValue()),
e.getValue()
)
));
}
/**
* Returns a stream consisting of the results of applying the given
* function to the key-component of this stream.
*
* This is an intermediate operation.
*
* @param the element type of the new stream
* @param mapper a non-interfering, stateless function to apply to each
* key in the stream
* @return the new stream
*/
public MapStream mapKey(Function mapper) {
return new MapStream<>(inner.map(e
-> new AbstractMap.SimpleEntry<>(
mapper.apply(e.getKey()),
e.getValue()
)
));
}
/**
* Returns a stream consisting of the results of applying the given
* function to the value-component of this stream.
*
* This is an intermediate operation.
*
* @param the element type of the new stream
* @param mapper a non-interfering, stateless function to apply to each
* value in the stream
* @return the new stream
*/
public MapStream mapValue(BiFunction mapper) {
return new MapStream<>(inner.map(e
-> new AbstractMap.SimpleEntry<>(
e.getKey(),
mapper.apply(e.getKey(), e.getValue())
)
));
}
/**
* Returns a stream consisting of the results of applying the given
* function to the value-component of this stream.
*
* This is an intermediate operation.
*
* @param the element type of the new stream
* @param mapper a non-interfering, stateless function to apply to each
* value in the stream
* @return the new stream
*/
public MapStream mapValue(Function mapper) {
return new MapStream<>(inner.map(e
-> new AbstractMap.SimpleEntry<>(
e.getKey(),
mapper.apply(e.getValue())
)
));
}
/**
* Returns an {@code IntStream} consisting of the results of applying the
* given function to the elements of this stream.
*
* This is an intermediate operation.
*
* @param mapper a non-interfering, stateless function to apply to each
* element
* @return the new stream
*/
@Override
public IntStream mapToInt(ToIntFunction> mapper) {
return inner.mapToInt(mapper);
}
/**
* Returns an {@code IntStream} consisting of the results of applying the
* given function to the elements of this stream.
*
* This is an intermediate operation.
*
* @param mapper a non-interfering, stateless function to apply to each
* element
* @return the new stream
*/
public IntStream mapToInt(ToIntBiFunction mapper) {
return inner.mapToInt(e -> mapper.applyAsInt(e.getKey(), e.getValue()));
}
/**
* Returns a {@code LongStream} consisting of the results of applying the
* given function to the elements of this stream.
*
* This is an intermediate operation.
*
* @param mapper a non-interfering, stateless function to apply to each
* element
* @return the new stream
*/
@Override
public LongStream mapToLong(ToLongFunction> mapper) {
return inner.mapToLong(mapper);
}
/**
* Returns a {@code LongStream} consisting of the results of applying the
* given function to the elements of this stream.
*
* This is an intermediate operation.
*
* @param mapper a non-interfering, stateless function to apply to each
* element
* @return the new stream
*/
public LongStream mapToLong(ToLongBiFunction mapper) {
return inner.mapToLong(e -> mapper.applyAsLong(e.getKey(), e.getValue()));
}
/**
* Returns a {@code DoubleStream} consisting of the results of applying the
* given function to the elements of this stream.
*
* This is an intermediate operation.
*
* @param mapper a non-interfering, stateless function to apply to each
* element
* @return the new stream
*/
@Override
public DoubleStream mapToDouble(ToDoubleFunction> mapper) {
return inner.mapToDouble(mapper);
}
/**
* Returns a {@code DoubleStream} consisting of the results of applying the
* given function to the elements of this stream.
*
* This is an intermediate operation.
*
* @param mapper a non-interfering, stateless function to apply to each
* element
* @return the new stream
*/
public DoubleStream mapToDouble(ToDoubleBiFunction mapper) {
return inner.mapToDouble(e -> mapper.applyAsDouble(e.getKey(), e.getValue()));
}
/**
* Returns a stream consisting of the results of replacing each element of
* this stream with the contents of a mapped stream produced by applying
* the provided mapping function to each element. Each mapped stream is
* {@link java.util.stream.BaseStream#close() closed} after its contents
* have been placed into this stream. (If a mapped stream is {@code null}
* an empty stream is used, instead.)
*
* This is an intermediate operation.
*
*
* The {@code flatMap()} operation has the effect of applying a one-to-many
* transformation to the elements of the stream, and then flattening the
* resulting elements into a new stream.
*
* Examples.
*
*
If {@code orders} is a stream of purchase orders, and each purchase
* order contains a collection of line items, then the following produces a
* stream containing all the line items in all the orders:
*
{@code
* orders.flatMap(order -> order.getLineItems().stream())...
* }
*
* If {@code path} is the path to a file, then the following produces a
* stream of the {@code words} contained in that file:
*
{@code
* Stream lines = Files.lines(path, StandardCharsets.UTF_8);
* Stream words = lines.flatMap(line -> Stream.of(line.split(" +")));
* }
* The {@code mapper} function passed to {@code flatMap} splits a line,
* using a simple regular expression, into an array of words, and then
* creates a stream of words from that array.
*
* @param the element type of the new stream
* @param mapper a non-interfering, stateless function to apply to each
* element which produces a stream of new elements
* @return the new stream
*/
@Override
public Stream flatMap(Function, ? extends Stream> mapper) {
return inner.flatMap(mapper);
}
/**
* Returns a stream consisting of the results of replacing each element of
* this stream with the contents of a mapped stream produced by applying
* the provided mapping function to each element. Each mapped stream is
* {@link java.util.stream.BaseStream#close() closed} after its contents
* have been placed into this stream. (If a mapped stream is {@code null}
* an empty stream is used, instead.)
*
* This is an intermediate operation.
*
*
* The {@code flatMap()} operation has the effect of applying a one-to-many
* transformation to the elements of the stream, and then flattening the
* resulting elements into a new stream.
*
* Examples.
*
*
If {@code orders} is a stream of purchase orders, and each purchase
* order contains a collection of line items, then the following produces a
* stream containing all the line items in all the orders:
*
{@code
* orders.flatMap(order -> order.getLineItems().stream())...
* }
*
* If {@code path} is the path to a file, then the following produces a
* stream of the {@code words} contained in that file:
*
{@code
* Stream lines = Files.lines(path, StandardCharsets.UTF_8);
* Stream words = lines.flatMap(line -> Stream.of(line.split(" +")));
* }
* The {@code mapper} function passed to {@code flatMap} splits a line,
* using a simple regular expression, into an array of words, and then
* creates a stream of words from that array.
*
* @param the element type of the new stream
* @param mapper a non-interfering, stateless function to apply to each
* element which produces a stream of new elements
* @return the new stream
*/
public Stream flatMap(BiFunction> mapper) {
return inner.flatMap(e -> mapper.apply(e.getKey(), e.getValue()));
}
/**
* Returns a stream where the key-component of this stream has been replaced
* by the result of applying the specified mapping function to the entry.
* Each mapped stream is {@link java.util.stream.BaseStream#close() closed}
* after its contents have been placed into this stream. (If a mapped stream
* is {@code null} an empty stream is used, instead.)
*
* This is an intermediate operation.
*
*
* The {@code flatMap()} operation has the effect of applying a one-to-many
* transformation to the elements of the stream, and then flattening the
* resulting elements into a new stream.
*
* @param the element type of the new stream
* @param mapper a non-interfering, stateless function to apply to each
* key-value pair which produces a stream of new keys
* @return the new stream
*/
public MapStream flatMapKey(BiFunction> mapper) {
return new MapStream<>(inner.flatMap(e
-> mapper.apply(e.getKey(), e.getValue())
.map(k
-> new AbstractMap.SimpleEntry<>(
k,
e.getValue()
)
)
));
}
/**
* Returns a stream where the key-component of this stream has been replaced
* by the result of applying the specified mapping function to the entry.
* Each mapped stream is {@link java.util.stream.BaseStream#close() closed}
* after its contents have been placed into this stream. (If a mapped stream
* is {@code null} an empty stream is used, instead.)
*
* This is an intermediate operation.
*
*
* The {@code flatMap()} operation has the effect of applying a one-to-many
* transformation to the elements of the stream, and then flattening the
* resulting elements into a new stream.
*
* @param the element type of the new stream
* @param mapper a non-interfering, stateless function to apply to each
* key-value pair which produces a stream of new keys
* @return the new stream
*/
public MapStream flatMapKey(Function> mapper) {
return new MapStream<>(inner.flatMap(e
-> mapper.apply(e.getKey())
.map(k
-> new AbstractMap.SimpleEntry<>(
k,
e.getValue()
)
)
));
}
/**
* Returns a stream where the value-component of this stream has been
* replaced by the result of applying the specified mapping function to the
* entry. Each mapped stream is
* {@link java.util.stream.BaseStream#close() closed} after its contents
* have been placed into this stream. (If a mapped stream is {@code null} an
* empty stream is used, instead.)
*
* This is an intermediate operation.
*
*
* The {@code flatMap()} operation has the effect of applying a one-to-many
* transformation to the elements of the stream, and then flattening the
* resulting elements into a new stream.
*
* @param the element type of the new stream
* @param mapper a non-interfering, stateless function to apply to each
* key-value pair which produces a stream of new values
* @return the new stream
*/
public MapStream flatMapValue(BiFunction> mapper) {
return new MapStream<>(inner.flatMap(e
-> mapper.apply(e.getKey(), e.getValue())
.map(v
-> new AbstractMap.SimpleEntry<>(
e.getKey(),
v
)
)
));
}
/**
* Returns a stream where the value-component of this stream has been
* replaced by the result of applying the specified mapping function to the
* entry. Each mapped stream is
* {@link java.util.stream.BaseStream#close() closed} after its contents
* have been placed into this stream. (If a mapped stream is {@code null} an
* empty stream is used, instead.)
*
* This is an intermediate operation.
*
*
* The {@code flatMap()} operation has the effect of applying a one-to-many
* transformation to the elements of the stream, and then flattening the
* resulting elements into a new stream.
*
* @param the element type of the new stream
* @param mapper a non-interfering, stateless function to apply to each
* key-value pair which produces a stream of new values
* @return the new stream
*/
public MapStream flatMapValue(Function> mapper) {
return new MapStream<>(inner.flatMap(e
-> mapper.apply(e.getValue())
.map(v
-> new AbstractMap.SimpleEntry<>(
e.getKey(),
v
)
)
));
}
/**
* Returns an {@code IntStream} consisting of the results of replacing each
* element of this stream with the contents of a mapped stream produced by
* applying the provided mapping function to each element. Each mapped
* stream is {@link java.util.stream.BaseStream#close() closed} after its
* contents have been placed into this stream. (If a mapped stream is
* {@code null} an empty stream is used, instead.)
*
* This is an intermediate operation.
*
* @param mapper a non-interfering, stateless function to apply to each
* element which produces a stream of new elements
* @return the new stream
*
* @see #flatMap(Function)
*/
@Override
public IntStream flatMapToInt(Function, ? extends IntStream> mapper) {
return inner.flatMapToInt(mapper);
}
/**
* Returns an {@code IntStream} consisting of the results of replacing each
* key-value pair of this stream with the contents of a mapped stream
* produced by applying the provided mapping function to each element. Each
* mapped stream is {@link java.util.stream.BaseStream#close() closed} after
* its contents have been placed into this stream. (If a mapped stream is
* {@code null} an empty stream is used, instead.)
*
* This is an intermediate operation.
*
* @param mapper a non-interfering, stateless function to apply to each
* key-value pair which produces a stream of new elements
* @return the new stream
*
* @see #flatMap(Function)
*/
public IntStream flatMapToInt(BiFunction mapper) {
return inner.flatMapToInt(e -> mapper.apply(e.getKey(), e.getValue()));
}
/**
* Returns an {@code LongStream} consisting of the results of replacing each
* element of this stream with the contents of a mapped stream produced by
* applying the provided mapping function to each element. Each mapped
* stream is {@link java.util.stream.BaseStream#close() closed} after its
* contents have been placed into this stream. (If a mapped stream is
* {@code null} an empty stream is used, instead.)
*
* This is an intermediate operation.
*
* @param mapper a non-interfering, stateless function to apply to each
* element which produces a stream of new elements
* @return the new stream
*
* @see #flatMap(Function)
*/
@Override
public LongStream flatMapToLong(Function, ? extends LongStream> mapper) {
return inner.flatMapToLong(mapper);
}
/**
* Returns an {@code LongStream} consisting of the results of replacing each
* key-value pair of this stream with the contents of a mapped stream
* produced by applying the provided mapping function to each element. Each
* mapped stream is {@link java.util.stream.BaseStream#close() closed} after
* its contents have been placed into this stream. (If a mapped stream is
* {@code null} an empty stream is used, instead.)
*
* This is an intermediate operation.
*
* @param mapper a non-interfering, stateless function to apply to each
* key-value pair which produces a stream of new elements
* @return the new stream
*
* @see #flatMap(Function)
*/
public LongStream flatMapToLong(BiFunction mapper) {
return inner.flatMapToLong(e -> mapper.apply(e.getKey(), e.getValue()));
}
/**
* Returns an {@code DoubleStream} consisting of the results of replacing
* each element of this stream with the contents of a mapped stream produced
* by applying the provided mapping function to each element. Each mapped
* stream is {@link java.util.stream.BaseStream#close() closed} after its
* contents have placed been into this stream. (If a mapped stream is
* {@code null} an empty stream is used, instead.)
*
* This is an intermediate operation.
*
* @param mapper a non-interfering, stateless function to apply to each
* element which produces a stream of new elements
* @return the new stream
*
* @see #flatMap(Function)
*/
@Override
public DoubleStream flatMapToDouble(Function, ? extends DoubleStream> mapper) {
return inner.flatMapToDouble(mapper);
}
/**
* Returns an {@code DoubleStream} consisting of the results of replacing
* each key-value pair of this stream with the contents of a mapped stream
* produced by applying the provided mapping function to each element. Each
* mapped stream is {@link java.util.stream.BaseStream#close() closed} after
* its contents have placed been into this stream. (If a mapped stream is
* {@code null} an empty stream is used, instead.)
*
* This is an intermediate operation.
*
* @param mapper a non-interfering, stateless function to apply to each
* key-value pair which produces a stream of new elements
* @return the new stream
*
* @see #flatMap(Function)
*/
public DoubleStream flatMapToDouble(BiFunction mapper) {
return inner.flatMapToDouble(e -> mapper.apply(e.getKey(), e.getValue()));
}
/**
* Returns a stream of only the keys in this {@code MapStream}.
*
* This is an intermediate operation.
*
* @return a new stream of all keys
*/
public Stream keys() {
return inner.map(Map.Entry::getKey);
}
/**
* Returns a stream of only the values in this {@code MapStream}.
*
* This is an intermediate operation.
*
* @return a new stream of all values
*/
public Stream values() {
return inner.map(Map.Entry::getValue);
}
/**
* Returns a stream consisting of the distinct elements (according to
* {@link Object#equals(Object)}) of this stream.
*
* For ordered streams, the selection of distinct elements is stable
* (for duplicated elements, the element appearing first in the encounter
* order is preserved.) For unordered streams, no stability guarantees
* are made.
*
* This is a stateful intermediate operation.
*
*
* Preserving stability for {@code distinct()} in parallel pipelines is
* relatively expensive (requires that the operation act as a full barrier,
* with substantial buffering overhead), and stability is often not needed.
* Using an unordered stream source (such as {@link #generate(Supplier)})
* or removing the ordering constraint with {@link #unordered()} may result
* in significantly more efficient execution for {@code distinct()} in parallel
* pipelines, if the semantics of your situation permit. If consistency
* with encounter order is required, and you are experiencing poor performance
* or memory utilization with {@code distinct()} in parallel pipelines,
* switching to sequential execution with {@link #sequential()} may improve
* performance.
*
* @return the new stream
*/
@Override
public MapStream distinct() {
inner = inner.distinct();
return this;
}
/**
* Returns a stream consisting of the distinct elements (according to
* {@link Object#equals(Object)}) of this stream based on the key only. If
* the same key is encountered multiple times, only the first occurence will
* be allowed to pass.
*
* This is a stateful intermediate operation.
*
* @return the new stream
*/
public MapStream distinctKeys() {
final Set temp = newSetFromMap(new ConcurrentHashMap<>());
inner = inner.flatMap(e ->
temp.add(e.getKey())
? Stream.of(e)
: Stream.empty()
);
return this;
}
/**
* Returns a stream consisting of the distinct elements (according to
* {@link Object#equals(Object)}) of this stream based on the value only. If
* the same value is encountered multiple times, only the first occurence
* will be allowed to pass.
*
* This is a stateful intermediate operation.
*
* @return the new stream
*/
public MapStream distinctValues() {
final Set temp = newSetFromMap(new ConcurrentHashMap<>());
inner = inner.flatMap(e ->
temp.add(e.getValue())
? Stream.of(e)
: Stream.empty()
);
return this;
}
/**
* Returns a stream consisting of the distinct elements (according to
* {@link Object#equals(Object)}) of this stream based on the key only. If
* the same key is encountered multiple times, the specified value merger
* will be used to determine which value can pass.
*
* This operation will consume the wrapped stream and produce a new one. The
* complexity of this operation is therefore O(n).
*
* This is a stateful intermediate operation.
*
* @param merger the merging operation to use
* @return the new stream
*/
public MapStream distinctKeys(BinaryOperator merger) {
final boolean parallel = isParallel();
final Map result = parallel
? Collections.synchronizedMap(new LinkedHashMap<>())
: new LinkedHashMap<>();
inner.forEachOrdered(e -> {
result.compute(e.getKey(), (k, v) ->
v == null
? e.getValue()
: merger.apply(e.getValue(), v)
);
});
return MapStream.of(result, parallel);
}
/**
* Returns a stream consisting of the distinct elements (according to
* {@link Object#equals(Object)}) of this stream based on the value only. If
* the same value is encountered multiple times, the specified key merger
* will be used to determine which value can pass.
*
* This operation will consume the wrapped stream and produce a new one. The
* complexity of this operation is therefore O(n).
*
* This is a stateful intermediate operation.
*
* @param merger the merging operation to use
* @return the new stream
*/
public MapStream distinctValues(BinaryOperator merger) {
return MapStream.flip(MapStream.flip(this).distinctKeys(merger));
}
/**
* Returns a stream consisting of the elements of this stream, sorted
* according to natural order. If the elements of this stream are not
* {@code Comparable}, a {@code java.lang.ClassCastException} may be thrown
* when the terminal operation is executed.
*
* For ordered streams, the sort is stable. For unordered streams, no
* stability guarantees are made.
*
* This is a stateful intermediate operation.
*
* @return the new stream
*/
@Override
public MapStream sorted() {
final Comparator c = (a, b) -> {
if (a == null && b == null) {
return 0;
} else if (a != null && b != null) {
if (a instanceof Comparable) {
@SuppressWarnings("unchecked")
final Comparable ac = (Comparable) a;
return ac.compareTo(b);
}
}
throw new UnsupportedOperationException("Can only sort keys that implement Comparable.");
};
inner = inner.sorted((a, b) -> c.compare(a.getKey(), b.getKey()));
return this;
}
/**
* Returns a stream consisting of the elements of this stream, sorted
* according to the provided {@code Comparator}.
*
* For ordered streams, the sort is stable. For unordered streams, no
* stability guarantees are made.
*
* This is a stateful intermediate operation.
*
* @param comparator a non-interfering, stateless {@code Comparator} to be
* used to compare stream elements
* @return the new stream
*/
@Override
public MapStream sorted(Comparator> comparator) {
inner = inner.sorted(comparator);
return this;
}
/**
* Returns a stream consisting of the elements of this stream, sorted
* according to the provided {@code Comparator} applied to the keys of the
* entries.
*
* For ordered streams, the sort is stable. For unordered streams, no
* stability guarantees are made.
*
* This is a stateful intermediate operation.
*
* @param comparator a non-interfering, stateless {@code Comparator} to be
* used to compare entity keys
* @return the new stream
*/
public MapStream sortedByKey(Comparator comparator) {
inner = inner.sorted(byKeyOnly(comparator));
return this;
}
/**
* Returns a stream consisting of the elements of this stream, sorted
* according to the provided {@code Comparator} applied to the values of the
* entries.
*
* For ordered streams, the sort is stable. For unordered streams, no
* stability guarantees are made.
*
* This is a stateful intermediate operation.
*
* @param comparator a non-interfering, stateless {@code Comparator} to be
* used to compare entity values
* @return the new stream
*/
public MapStream sortedByValue(Comparator comparator) {
inner = inner.sorted(byValueOnly(comparator));
return this;
}
/**
* Returns a stream consisting of the elements of this stream, additionally
* performing the provided action on each element as elements are consumed
* from the resulting stream.
*
* This is an intermediate operation.
*
* For parallel stream pipelines, the action may be called at
* whatever time and in whatever thread the element is made available by the
* upstream operation. If the action modifies shared state,
* it is responsible for providing the required synchronization.
*
*
This method exists mainly to support debugging, where you want
* to see the elements as they flow past a certain point in a pipeline:
*
{@code
* Stream.of("one", "two", "three", "four")
* .filter(e -> e.length() > 3)
* .peek(e -> System.out.println("Filtered value: " + e))
* .map(String::toUpperCase)
* .peek(e -> System.out.println("Mapped value: " + e))
* .collect(Collectors.toList());
* }
*
* @param action a non-interfering action to perform on the elements as
* they are consumed from the stream
* @return the new stream
*/
@Override
public MapStream peek(Consumer> action) {
inner = inner.peek(action);
return this;
}
/**
* Returns a stream consisting of the key-value pairs of this stream,
* additionally performing the provided action on each element as elements
* are consumed from the resulting stream.
*
* This is an intermediate operation.
*
* For parallel stream pipelines, the action may be called at
* whatever time and in whatever thread the element is made available by the
* upstream operation. If the action modifies shared state,
* it is responsible for providing the required synchronization.
*
*
This method exists mainly to support debugging, where you want
* to see the elements as they flow past a certain point in a pipeline:
*
{@code
* Stream.of("one", "two", "three", "four")
* .filter(e -> e.length() > 3)
* .peek(e -> System.out.println("Filtered value: " + e))
* .map(String::toUpperCase)
* .peek(e -> System.out.println("Mapped value: " + e))
* .collect(Collectors.toList());
* }
*
* @param action a non-interfering action to perform on the key-value pairs
* as they are consumed from the stream
* @return the new stream
*/
public MapStream peek(BiConsumer action) {
inner = inner.peek(e -> action.accept(e.getKey(), e.getValue()));
return this;
}
/**
* Returns a stream consisting of the elements of this stream, truncated
* to be no longer than {@code maxSize} in length.
*
* This is a short-circuiting stateful intermediate operation.
*
*
* While {@code limit()} is generally a cheap operation on sequential
* stream pipelines, it can be quite expensive on ordered parallel pipelines,
* especially for large values of {@code maxSize}, since {@code limit(n)}
* is constrained to return not just any n elements, but the
* first n elements in the encounter order. Using an unordered
* stream source (such as {@link #generate(Supplier)}) or removing the
* ordering constraint with {@link #unordered()} may result in significant
* speedups of {@code limit()} in parallel pipelines, if the semantics of
* your situation permit. If consistency with encounter order is required,
* and you are experiencing poor performance or memory utilization with
* {@code limit()} in parallel pipelines, switching to sequential execution
* with {@link #sequential()} may improve performance.
*
* @param maxSize the number of elements the stream should be limited to
* @return the new stream
* @throws IllegalArgumentException if {@code maxSize} is negative
*/
@Override
public MapStream limit(long maxSize) {
inner = inner.limit(maxSize);
return this;
}
/**
* Returns a stream consisting of the remaining elements of this stream
* after discarding the first {@code n} elements of the stream.
* If this stream contains fewer than {@code n} elements then an
* empty stream will be returned.
*
* This is a stateful intermediate operation.
*
*
* While {@code skip()} is generally a cheap operation on sequential
* stream pipelines, it can be quite expensive on ordered parallel pipelines,
* especially for large values of {@code n}, since {@code skip(n)}
* is constrained to skip not just any n elements, but the
* first n elements in the encounter order. Using an unordered
* stream source (such as {@link #generate(Supplier)}) or removing the
* ordering constraint with {@link #unordered()} may result in significant
* speedups of {@code skip()} in parallel pipelines, if the semantics of
* your situation permit. If consistency with encounter order is required,
* and you are experiencing poor performance or memory utilization with
* {@code skip()} in parallel pipelines, switching to sequential execution
* with {@link #sequential()} may improve performance.
*
* @param n the number of leading elements to skip
* @return the new stream
* @throws IllegalArgumentException if {@code n} is negative
*/
@Override
public MapStream skip(long n) {
inner = inner.skip(n);
return this;
}
/**
* Performs an action for each element of this stream.
*
* This is a terminal operation.
*
* The behavior of this operation is explicitly nondeterministic.
* For parallel stream pipelines, this operation does not
* guarantee to respect the encounter order of the stream, as doing so
* would sacrifice the benefit of parallelism. For any given element, the
* action may be performed at whatever time and in whatever thread the
* library chooses. If the action accesses shared state, it is
* responsible for providing the required synchronization.
*
* @param action a non-interfering action to perform on the elements
*/
@Override
public void forEach(Consumer> action) {
inner.forEach(action);
}
/**
* Performs an action for each key-value pair of this stream.
*
* This is a terminal operation.
*
* The behavior of this operation is explicitly nondeterministic.
* For parallel stream pipelines, this operation does not
* guarantee to respect the encounter order of the stream, as doing so
* would sacrifice the benefit of parallelism. For any given element, the
* action may be performed at whatever time and in whatever thread the
* library chooses. If the action accesses shared state, it is
* responsible for providing the required synchronization.
*
* @param action a non-interfering action to perform on the key-value pairs
*/
public void forEach(BiConsumer action) {
inner.forEach(e -> action.accept(e.getKey(), e.getValue()));
}
/**
* Performs an action for each element of this stream, in the encounter
* order of the stream if the stream has a defined encounter order.
*
* This is a terminal operation.
*
* This operation processes the elements one at a time, in encounter
* order if one exists. Performing the action for one element
* happens-before performing the action for subsequent elements, but
* for any given element, the action may be performed in whatever thread the
* library chooses.
*
* @param action a non-interfering action to perform on the elements
* @see #forEach(Consumer)
*/
@Override
public void forEachOrdered(Consumer> action) {
inner.forEachOrdered(action);
}
/**
* Performs an action for each key-value pair of this stream, in the
* encounter order of the stream if the stream has a defined encounter
* order.
*
* This is a terminal operation.
*
* This operation processes the key-value pairs one at a time, in encounter
* order if one exists. Performing the action for one element
* happens-before performing the action for subsequent key-value
* pairs, but for any given element, the action may be performed in whatever
* thread the library chooses.
*
* @param action a non-interfering action to perform on the key-value pairs
* @see #forEach(Consumer)
*/
public void forEachOrdered(BiConsumer action) {
inner.forEachOrdered(e -> action.accept(e.getKey(), e.getValue()));
}
/**
* Returns an array containing the elements of this stream.
*
* This is a terminal operation.
*
* @return an array containing the elements of this stream
*/
@Override
public Object[] toArray() {
return inner.toArray();
}
/**
* Returns an array containing the elements of this stream, using the
* provided {@code generator} function to allocate the returned array, as
* well as any additional arrays that might be required for a partitioned
* execution or for resizing.
*
* This is a terminal operation.
*
*
* The generator function takes an integer, which is the size of the
* desired array, and produces an array of the desired size. This can be
* concisely expressed with an array constructor reference:
*
{@code
* Person[] men = people.stream()
* .filter(p -> p.getGender() == MALE)
* .toArray(Person[]::new);
* }
*
* @param the element type of the resulting array
* @param generator a function which produces a new array of the desired
* type and the provided length
* @return an array containing the elements in this stream
* @throws ArrayStoreException if the runtime type of the array
* returned from the array generator is not a supertype of
* the runtime type of every element in this stream
*/
@Override
public A[] toArray(IntFunction generator) {
return inner.toArray(generator);
}
/**
* Performs a reduction on the elements of this stream, using the provided
* identity value and an associative accumulation function, and returns the
* reduced value. This is equivalent to:
* {@code
* T result = identity;
* for (T element : this stream)
* result = accumulator.apply(result, element)
* return result;
* }
*
* but is not constrained to execute sequentially.
*
* The {@code identity} value must be an identity for the accumulator
* function. This means that for all {@code t},
* {@code accumulator.apply(identity, t)} is equal to {@code t}.
* The {@code accumulator} function must be an associative function.
*
* This is a terminal operation.
*
*
Sum, min, max, average, and string concatenation are all special
* cases of reduction. Summing a stream of numbers can be expressed as:
*
*
{@code
* Integer sum = integers.reduce(0, (a, b) -> a+b);
* }
*
* or:
*
* {@code
* Integer sum = integers.reduce(0, Integer::sum);
* }
*
* While this may seem a more roundabout way to perform an aggregation
* compared to simply mutating a running total in a loop, reduction
* operations parallelize more gracefully, without needing additional
* synchronization and with greatly reduced risk of data races.
*
* @param identity the identity value for the accumulating function
* @param accumulator an associative, non-interfering stateless function
* for combining two values
* @return the result of the reduction
*/
@Override
public Map.Entry reduce(Map.Entry identity, BinaryOperator> accumulator) {
return inner.reduce(identity, accumulator);
}
/**
* Performs a reduction on the elements of this stream, using an associative
* accumulation function, and returns an {@code Optional} describing the
* reduced value, if any. This is equivalent to:
* {@code
* boolean foundAny = false;
* T result = null;
* for (T element : this stream) {
* if (!foundAny) {
* foundAny = true;
* result = element;
* }
* else
* result = accumulator.apply(result, element);
* }
* return foundAny ? Optional.of(result) : Optional.empty();
* }
*
* but is not constrained to execute sequentially.
*
* The {@code accumulator} function must be an associative function.
*
* This is a terminal operation.
*
* @param accumulator an associative, non-interfering, stateless function
* for combining two values
* @return an {@link Optional} describing the result of the
* reduction
* @throws NullPointerException if the result of the reduction is null
*
* @see #reduce(Object, BinaryOperator)
* @see #min(Comparator)
* @see #max(Comparator)
*/
@Override
public Optional> reduce(BinaryOperator> accumulator) {
return inner.reduce(accumulator);
}
/**
* Performs a reduction on the elements of this stream, using the provided
* identity, accumulation and combining functions. This is equivalent to:
* {@code
* U result = identity;
* for (T element : this stream)
* result = accumulator.apply(result, element)
* return result;
* }
*
* but is not constrained to execute sequentially.
*
* The {@code identity} value must be an identity for the combiner
* function. This means that for all {@code u}, {@code combiner(identity, u)}
* is equal to {@code u}. Additionally, the {@code combiner} function
* must be compatible with the {@code accumulator} function; for all
* {@code u} and {@code t}, the following must hold:
*
{@code
* combiner.apply(u, accumulator.apply(identity, t)) == accumulator.apply(u, t)
* }
*
* This is a terminal operation.
*
*
Many reductions using this form can be represented more simply
* by an explicit combination of {@code map} and {@code reduce} operations.
* The {@code accumulator} function acts as a fused mapper and accumulator,
* which can sometimes be more efficient than separate mapping and reduction,
* such as when knowing the previously reduced value allows you to avoid
* some computation.
*
* @param the type of the result
* @param identity the identity value for the combiner function
* @param accumulator an associative, non-interfering, stateless function
* for incorporating an additional element into a result
* @param combiner an associative, non-interfering, stateless
* function for combining two values, which must be
* compatible with the accumulator function
* @return the result of the reduction
*
* @see #reduce(BinaryOperator)
* @see #reduce(Object, BinaryOperator)
*/
@Override
public U reduce(U identity, BiFunction, U> accumulator, BinaryOperator combiner) {
return inner.reduce(identity, accumulator, combiner);
}
/**
* Performs a mutable reduction operation on the elements of this stream. A
* mutable reduction is one in which the reduced value is a mutable result
* container, such as an {@code ArrayList}, and elements are incorporated by
* updating the state of the result rather than by replacing the result.
* This produces a result equivalent to:
* {@code
* R result = supplier.get();
* for (T element : this stream)
* accumulator.accept(result, element);
* return result;
* }
*
* Like {@link #reduce(Object, BinaryOperator)}, {@code collect} operations
* can be parallelized without requiring additional synchronization.
*
* This is a terminal operation.
*
*
There are many existing classes in the JDK whose signatures are
* well-suited for use with method references as arguments to {@code collect()}.
* For example, the following will accumulate strings into an {@code ArrayList}:
*
{@code
* List asList = stringStream.collect(ArrayList::new, ArrayList::add,
* ArrayList::addAll);
* }
*
* The following will take a stream of strings and concatenates them into a
* single string:
*
{@code
* String concat = stringStream.collect(StringBuilder::new, StringBuilder::append,
* StringBuilder::append)
* .toString();
* }
*
* @param type of the result
* @param supplier a function that creates a new result container. For a
* parallel execution, this function may be called
* multiple times and must return a fresh value each
* time.
* @param accumulator an associative, non-interfering, stateless function
* for incorporating an additional element into a result
* @param combiner an associative, non-interfering, stateless function
* for combining two values, which must be compatible
* with the accumulator function
* @return the result of the reduction
*/
@Override
public R collect(Supplier supplier, BiConsumer> accumulator, BiConsumer combiner) {
return inner.collect(supplier, accumulator, combiner);
}
/**
* Performs a mutable reduction operation on the elements of this stream
* using a {@code Collector}. A {@code Collector} encapsulates the functions
* used as arguments to {@link #collect(Supplier, BiConsumer, BiConsumer)},
* allowing for reuse of collection strategies and composition of collect
* operations such as multiple-level grouping or partitioning.
*
* If the stream is parallel, and the {@code Collector} is
* {@link Collector.Characteristics#CONCURRENT concurrent}, and either the
* stream is unordered or the collector is
* {@link Collector.Characteristics#UNORDERED unordered},
* then a concurrent reduction will be performed (see {@link Collector} for
* details on concurrent reduction.)
*
* This is a terminal operation.
*
* When executed in parallel, multiple intermediate results may be
* instantiated, populated, and merged so as to maintain isolation of
* mutable data structures. Therefore, even when executed in parallel
* with non-thread-safe data structures (such as {@code ArrayList}), no
* additional synchronization is needed for a parallel reduction.
*
*
* The following will accumulate strings into an ArrayList:
*
{@code
* List asList = stringStream.collect(Collectors.toList());
* }
*
* The following will classify {@code Person} objects by city:
*
{@code
* Map> peopleByCity
* = personStream.collect(Collectors.groupingBy(Person::getCity));
* }
*
* The following will classify {@code Person} objects by state and city,
* cascading two {@code Collector}s together:
*
{@code
* Map>> peopleByStateAndCity
* = personStream.collect(Collectors.groupingBy(Person::getState,
* Collectors.groupingBy(Person::getCity)));
* }
*
* @param the type of the result
* @param the intermediate accumulation type of the
* {@code Collector}
* @param collector the {@code Collector} describing the reduction
* @return the result of the reduction
*
* @see #collect(Supplier, BiConsumer, BiConsumer)
* @see Collectors
*/
@Override
public R collect(Collector, A, R> collector) {
return inner.collect(collector);
}
/**
* Returns a new {@code MapStream} where the key component is calculated by
* applying the specified grouper function to the values of this stream and
* the value is a stream consisting of all the entries that produced the
* same key.
*
* This is a stateful intermediate operation.
*
* @param the type of the new key
* @param grouper the function to use for grouping entries
* @return the new stream
*/
public MapStream> groupingBy(Function grouper) {
return inner.map(Map.Entry::getValue)
.collect(CollectorUtil.groupBy(grouper));
}
/**
* Returns the minimum element of this stream according to the provided
* {@code Comparator}. This is a special case of a reduction.
*
* This is a terminal operation.
*
* @param comparator a non-interfering, stateless {@code Comparator} to
* compare elements of this stream
* @return an {@code Optional} describing the minimum element of
* this stream, or an empty {@code Optional} if the
* stream is empty
*
* @throws NullPointerException if the minimum element is null
*/
@Override
public Optional> min(Comparator> comparator) {
return inner.min(comparator);
}
/**
* Returns the minimum element of this stream according to the provided
* {@code Comparator} applied to the key-components of this stream. This is
* a special case of a reduction.
*
* This is a terminal operation.
*
* @param comparator a non-interfering, stateless {@code Comparator} to
* compare keys of this stream
* @return an {@code Optional} describing the minimum element of
* this stream, or an empty {@code Optional} if the
* stream is empty
*
* @throws NullPointerException if the minimum element is null
*/
public Optional> minByKey(Comparator comparator) {
return inner.min(byKeyOnly(comparator));
}
/**
* Returns the minimum element of this stream according to the provided
* {@code Comparator} applied to the value-components of this stream. This
* is a special case of a reduction.
*
* This is a terminal operation.
*
* @param comparator a non-interfering, stateless {@code Comparator} to
* compare values of this stream
* @return an {@code Optional} describing the minimum element of
* this stream, or an empty {@code Optional} if the
* stream is empty
*
* @throws NullPointerException if the minimum element is null
*/
public Optional> minByValue(Comparator comparator) {
return inner.min(byValueOnly(comparator));
}
/**
* Returns the maximum element of this stream according to the provided
* {@code Comparator}. This is a special case of a reduction.
*
* This is a terminal operation.
*
* @param comparator a non-interfering, stateless {@code Comparator} to
* compare elements of this stream
* @return an {@code Optional} describing the maximum element of
* this stream, or an empty {@code Optional} if the
* stream is empty
*
* @throws NullPointerException if the maximum element is null
*/
@Override
public Optional> max(Comparator> comparator) {
return inner.max(comparator);
}
/**
* Returns the maximum element of this stream according to the provided
* {@code Comparator} applied to the key-components of this stream. This
* is a special case of a reduction.
*
* This is a terminal operation.
*
* @param comparator a non-interfering, stateless {@code Comparator} to
* compare keys of this stream
* @return an {@code Optional} describing the maximum element of
* this stream, or an empty {@code Optional} if the
* stream is empty
*
* @throws NullPointerException if the maximum element is null
*/
public Optional> maxByKey(Comparator comparator) {
return inner.max(byKeyOnly(comparator));
}
/**
* Returns the maximum element of this stream according to the provided
* {@code Comparator} applied to the value-components of this stream. This
* is a special case of a reduction.
*
* This is a terminal operation.
*
* @param comparator a non-interfering, stateless {@code Comparator} to
* compare values of this stream
* @return an {@code Optional} describing the maximum element of
* this stream, or an empty {@code Optional} if the
* stream is empty
*
* @throws NullPointerException if the maximum element is null
*/
public Optional> maxByValue(Comparator comparator) {
return inner.max(byValueOnly(comparator));
}
/**
* Returns the count of elements in this stream. This is a special case of
* a reduction and is equivalent to:
* {@code
* return mapToLong(e -> 1L).sum();
* }
*
* This is a terminal operation.
*
* @return the count of elements in this stream
*/
@Override
public long count() {
return inner.count();
}
/**
* Returns whether any elements of this stream match the provided
* predicate. May not evaluate the predicate on all elements if not
* necessary for determining the result. If the stream is empty then
* {@code false} is returned and the predicate is not evaluated.
*
* This is a short-circuiting terminal operation.
*
*
* This method evaluates the existential quantification of the
* predicate over the elements of the stream (for some x P(x)).
*
* @param predicate a non-interfering, stateless predicate to apply to
* elements of this stream
* @return {@code true} if any elements of the stream match the
* provided predicate, otherwise {@code false}
*/
@Override
public boolean anyMatch(Predicate> predicate) {
return inner.anyMatch(predicate);
}
/**
* Returns whether any key-value pairs of this stream match the provided
* predicate. May not evaluate the predicate on all elements if not
* necessary for determining the result. If the stream is empty then
* {@code false} is returned and the predicate is not evaluated.
*
* This is a short-circuiting terminal operation.
*
*
* This method evaluates the existential quantification of the
* predicate over the elements of the stream (for some x P(x)).
*
* @param predicate a non-interfering, stateless predicate to apply to
* key-value pairs of this stream
* @return {@code true} if any key-value pairs of the stream match
* the provided predicate, otherwise {@code false}
*/
public boolean anyMatch(BiPredicate predicate) {
return inner.anyMatch(e -> predicate.test(e.getKey(), e.getValue()));
}
/**
* Returns whether all elements of this stream match the provided predicate.
* May not evaluate the predicate on all elements if not necessary for
* determining the result. If the stream is empty then {@code true} is
* returned and the predicate is not evaluated.
*
* This is a short-circuiting terminal operation.
*
*
* This method evaluates the universal quantification of the
* predicate over the elements of the stream (for all x P(x)). If the
* stream is empty, the quantification is said to be vacuously
* satisfied and is always {@code true} (regardless of P(x)).
*
* @param predicate a non-interfering, stateless predicate to apply to
* elements of this stream
* @return {@code true} if either all elements of the stream match
* the provided predicate or the stream is empty,
* otherwise {@code false}
*/
@Override
public boolean allMatch(Predicate> predicate) {
return inner.allMatch(predicate);
}
/**
* Returns whether all key-value pairs of this stream match the provided
* predicate. May not evaluate the predicate on all key-value pairs if not
* necessary for determining the result. If the stream is empty then
* {@code true} is returned and the predicate is not evaluated.
*
* This is a short-circuiting terminal operation.
*
*
* This method evaluates the universal quantification of the
* predicate over the elements of the stream (for all x P(x)). If the
* stream is empty, the quantification is said to be vacuously
* satisfied and is always {@code true} (regardless of P(x)).
*
* @param predicate a non-interfering, stateless predicate to apply to
* key-value pairs of this stream
* @return {@code true} if either all key-value pairs of the
* stream match the provided predicate or the stream is
* empty, otherwise {@code false}
*/
public boolean allMatch(BiPredicate predicate) {
return inner.allMatch(e -> predicate.test(e.getKey(), e.getValue()));
}
/**
* Returns whether no elements of this stream match the provided predicate.
* May not evaluate the predicate on all elements if not necessary for
* determining the result. If the stream is empty then {@code true} is
* returned and the predicate is not evaluated.
*
* This is a short-circuiting terminal operation.
*
*
* This method evaluates the universal quantification of the
* negated predicate over the elements of the stream (for all x ~P(x)). If
* the stream is empty, the quantification is said to be vacuously satisfied
* and is always {@code true}, regardless of P(x).
*
* @param predicate a non-interfering, stateless predicate to apply to
* elements of this stream
* @return {@code true} if either no elements of the stream match
* the provided predicate or the stream is empty,
* otherwise {@code false}
*/
@Override
public boolean noneMatch(Predicate> predicate) {
return inner.noneMatch(predicate);
}
/**
* Returns whether no key-value pairs of this stream match the provided
* predicate. May not evaluate the predicate on all key-value pairs if not
* necessary for determining the result. If the stream is empty then
* {@code true} is returned and the predicate is not evaluated.
*
* This is a short-circuiting terminal operation.
*
*
* This method evaluates the universal quantification of the
* negated predicate over the elements of the stream (for all x ~P(x)). If
* the stream is empty, the quantification is said to be vacuously satisfied
* and is always {@code true}, regardless of P(x).
*
* @param predicate a non-interfering, stateless predicate to apply to
* key-value pairs of this stream
* @return {@code true} if either no key-value pairs of the
* stream match the provided predicate or the stream is
* empty, otherwise {@code false}
*/
public boolean noneMatch(BiPredicate predicate) {
return inner.noneMatch(e -> predicate.test(e.getKey(), e.getValue()));
}
/**
* Returns an {@link Optional} describing the first element of this stream,
* or an empty {@code Optional} if the stream is empty. If the stream has
* no encounter order, then any element may be returned.
*
* This is a short-circuiting terminal operation.
*
* @return an {@code Optional} describing the first element of this stream,
* or an empty {@code Optional} if the stream is empty
*
* @throws NullPointerException if the element selected is null
*/
@Override
public Optional> findFirst() {
return inner.findFirst();
}
/**
* Returns an {@link Optional} describing some element of the stream, or an
* empty {@code Optional} if the stream is empty.
*
* This is a short-circuiting terminal operation.
*
* The behavior of this operation is explicitly nondeterministic; it is
* free to select any element in the stream. This is to allow for maximal
* performance in parallel operations; the cost is that multiple invocations
* on the same source may not return the same result. (If a stable result
* is desired, use {@link #findFirst()} instead.)
*
* @return an {@code Optional} describing some element of this stream, or an
* empty {@code Optional} if the stream is empty
*
* @throws NullPointerException if the element selected is null
* @see #findFirst()
*/
@Override
public Optional> findAny() {
return inner.findAny();
}
/**
* Returns an iterator for the elements of this stream.
*
* This is a terminal operation.
*
* @return the element iterator for this stream
*/
@Override
public Iterator> iterator() {
return inner.iterator();
}
/**
* Returns a spliterator for the elements of this stream.
*
* This is a terminal operation.
*
* @return the element spliterator for this stream
*/
@Override
public Spliterator> spliterator() {
return inner.spliterator();
}
/**
* Returns whether this stream, if a terminal operation were to be executed,
* would execute in parallel. Calling this method after invoking an
* terminal stream operation method may yield unpredictable results.
*
* @return {@code true} if this stream would execute in parallel if executed
*/
@Override
public boolean isParallel() {
return inner.isParallel();
}
/**
* Returns an equivalent stream that is sequential. May return
* itself, either because the stream was already sequential, or because
* the underlying stream state was modified to be sequential.
*
* This is an intermediate operation.
*
* @return a sequential stream
*/
@Override
public MapStream sequential() {
inner = inner.sequential();
return this;
}
/**
* Returns an equivalent stream that is parallel. May return
* itself, either because the stream was already parallel, or because
* the underlying stream state was modified to be parallel.
*
* This is an intermediate operation.
*
* @return a parallel stream
*/
@Override
public MapStream parallel() {
inner = inner.parallel();
return this;
}
/**
* Returns an equivalent stream that is
* unordered. May return
* itself, either because the stream was already unordered, or because
* the underlying stream state was modified to be unordered.
*
* This is an intermediate operation.
*
* @return an unordered stream
*/
@Override
public MapStream unordered() {
inner = inner.unordered();
return this;
}
/**
* Returns an equivalent stream with an additional close handler. Close
* handlers are run when the {@link #close()} method
* is called on the stream, and are executed in the order they were
* added. All close handlers are run, even if earlier close handlers throw
* exceptions. If any close handler throws an exception, the first
* exception thrown will be relayed to the caller of {@code close()}, with
* any remaining exceptions added to that exception as suppressed exceptions
* (unless one of the remaining exceptions is the same exception as the
* first exception, since an exception cannot suppress itself.) May
* return itself.
*
* This is an intermediate operation.
*
* @param closeHandler a task to execute when the stream is closed
* @return a stream with a handler that is run if the stream is
* closed
*/
@Override
public MapStream onClose(Runnable closeHandler) {
inner = inner.onClose(closeHandler);
return this;
}
/**
* Closes this stream, causing all close handlers for this stream pipeline
* to be called.
*
* @see AutoCloseable#close()
*/
@Override
public void close() {
inner.close();
}
/**
* Accumulates all key-value pairs of this {@code MapStream} into a {@code Map}.
*
* 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(BinaryOperator)}
* instead.
*
*
* The returned {@code Map} 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()}
* may offer better parallel performance.
*
* @return a {@code Map} whose keys and values are identical to the entries
* of this stream
*
* @see #toMap(BinaryOperator)
* @see #toConcurrentMap()
*/
public Map toMap() {
return inner.collect(Collectors.toMap(
Map.Entry::getKey,
Map.Entry::getValue
));
}
/**
* Accumulates all key-value pairs of this {@code MapStream} into a {@code Map}.
*
* If the mapped keys contains duplicates (according to
* {@link Object#equals(Object)}), the values are merged using the provided
* merging function.
*
*
* 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.
*
*
* The returned {@code Map} 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(BinaryOperator)}
* may offer better parallel performance.
*
* @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 Map} whose keys and values are identical
* to the entries of this stream with any collisions
* handled
*
* @see #toMap()
* @see #toConcurrentMap(BinaryOperator)
*/
public Map toMap(BinaryOperator mergeFunction) {
return inner.collect(Collectors.toMap(
Map.Entry::getKey,
Map.Entry::getValue,
mergeFunction
));
}
/**
* Accumulates all key-value pairs of this {@code MapStream} into a
* {@code ConcurrentMap}.
*
* 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(BinaryOperator)} instead.
*
*
* 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.
*
* This is a {@link Collector.Characteristics#CONCURRENT concurrent} and
* {@link Collector.Characteristics#UNORDERED unordered} Collector.
*
* @return a {@code ConcurrentMap} whose keys are taken from this stream
*
* @see #toMap()
* @see #toConcurrentMap(BinaryOperator)
*/
public Map toConcurrentMap() {
return inner.collect(Collectors.toConcurrentMap(
Map.Entry::getKey,
Map.Entry::getValue
));
}
/**
* Accumulates all key-value pairs of this {@code MapStream} into a
* {@code ConcurrentMap}.
*
* 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.
*
*
* 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.
*
* @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 ConcurrentMap} whose keys are taken from this stream
*
* @see #toConcurrentMap()
* @see #toMap(BinaryOperator)
*/
public Map toConcurrentMap(BinaryOperator mergeFunction) {
return inner.collect(Collectors.toConcurrentMap(
Map.Entry::getKey,
Map.Entry::getValue,
mergeFunction
));
}
/**
* Accumulates all key-value pairs of this {@code MapStream} into a
* {@code SortedMap}.
*
* 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 #toSortedMap(BinaryOperator)}
* instead.
*
* If the keys are not {@link Comparable}, a
* {@code java.lang.ClassCastException} may be thrown when the terminal
* operation is executed. It is therefore better to use
* {@link #toSortedMapByKey(Comparator)} since it allows you to specify
* a comparator to use when comparing the keys.
*
*
* The returned {@code Map} is not concurrent. For parallel stream
* pipelines, use {@link #toConcurrentNavigableMap()} instead.
*
* @return a {@code Map} whose keys and values are identical to the entries
* of this stream
*
* @see #toMap(BinaryOperator)
* @see #toConcurrentMap()
*/
public SortedMap toSortedMap() {
return inner.collect(Collectors.toMap(
Map.Entry::getKey,
Map.Entry::getValue,
throwingMerger(),
TreeMap::new
));
}
/**
* Accumulates all key-value pairs of this {@code MapStream} into a
* {@code SortedMap}, sorting the entries by applying the specified
* comparator to the keys of the stream.
*
* 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 #toSortedMap(Comparator, BinaryOperator)}
* instead.
*
*
* The returned {@code Map} is not concurrent. For parallel stream
* pipelines, use {@link #toConcurrentNavigableMap()} instead.
*
* @param keyComparator the comparator to use when sorting the keys
* @return a {@code SortedMap} whose keys and values are
* identical to the entries of this stream
*
* @see #toMap(BinaryOperator)
* @see #toConcurrentMap()
* @see #toSortedMap()
*/
public SortedMap toSortedMapByKey(Comparator keyComparator) {
return inner.collect(Collectors.toMap(
Map.Entry::getKey,
Map.Entry::getValue,
throwingMerger(),
() -> new TreeMap<>(keyComparator)
));
}
/**
* Accumulates all key-value pairs of this {@code MapStream} into a
* {@code SortedMap}.
*
* If the mapped keys contains duplicates (according to
* {@link Object#equals(Object)}), the values are merged using the provided
* merging function.
*
*
* There are multiple ways to deal with collisions between multiple elements
* mapping to the same key. The other forms of {@code toSortedMap} simply
* use a merge function that throws unconditionally, but you can easily
* write more flexible merge policies.
*
*
* The returned {@code SortedMap} 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 #toConcurrentNavigableMap(BinaryOperator)}
* may offer better parallel performance.
*
* @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 SortedMap} whose keys and values are identical
* to the entries of this stream with any collisions
* handled
*
* @see #toMap()
* @see #toSortedMap()
* @see #toConcurrentMap(BinaryOperator)
*/
public SortedMap toSortedMap(BinaryOperator mergeFunction) {
return inner.collect(Collectors.toMap(
Map.Entry::getKey,
Map.Entry::getValue,
mergeFunction,
TreeMap::new
));
}
/**
* Accumulates all key-value pairs of this {@code MapStream} into a
* {@code SortedMap}, sorting the entries by applying the specified
* comparator to the keys of the stream.
*
* If the mapped keys contains duplicates (according to
* {@link Object#equals(Object)}), the values are merged using the provided
* merging function.
*
*
* There are multiple ways to deal with collisions between multiple elements
* mapping to the same key. The other forms of {@code toSortedMap} simply
* use a merge function that throws unconditionally, but you can easily
* write more flexible merge policies.
*
*
* The returned {@code SortedMap} 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 #toConcurrentNavigableMap(Comparator, BinaryOperator)}
* may offer better parallel performance.
*
* @param keyComparator the comparator to use for determining the order of
* the keys
* @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 SortedMap} whose keys and values are identical
* to the entries of this stream with any collisions
* handled
*
* @see #toMap()
* @see #toSortedMap()
* @see #toConcurrentMap(BinaryOperator)
*/
public SortedMap toSortedMap(Comparator keyComparator, BinaryOperator mergeFunction) {
return inner.collect(Collectors.toMap(
Map.Entry::getKey,
Map.Entry::getValue,
mergeFunction,
() -> new TreeMap<>(keyComparator)
));
}
/**
* Accumulates all key-value pairs of this {@code MapStream} into a
* {@code ConcurrentNavigableMap}.
*
* 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 #toConcurrentNavigableMap(BinaryOperator)}
* instead.
*
* If the keys are not {@link Comparable}, a
* {@code java.lang.ClassCastException} may be thrown when the terminal
* operation is executed. It is therefore better to use
* {@link #toConcurrentNavigableMapByKey(Comparator)} since it allows you to specify
* a comparator to use when comparing the keys.
*
* @return a {@code ConcurrentNavigableMap} whose keys and values are
* identical to the entries of this stream
*
* @see #toMap(BinaryOperator)
* @see #toConcurrentMap()
*/
public ConcurrentNavigableMap toConcurrentNavigableMap() {
return inner.collect(Collectors.toConcurrentMap(
Map.Entry::getKey,
Map.Entry::getValue,
throwingMerger(),
ConcurrentSkipListMap::new
));
}
/**
* Accumulates all key-value pairs of this {@code MapStream} into a
* {@code ConcurrentNavigableMap}, sorting the entries by applying the
* specified comparator to the keys of the stream.
*
* 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 #toConcurrentNavigableMap(Comparator, BinaryOperator)}
* instead.
*
* @param keyComparator the comparator to use when sorting the keys
* @return a {@code ConcurrentNavigableMap} whose keys and
* values are identical to the entries of this stream
*
* @see #toMap(BinaryOperator)
* @see #toConcurrentMap()
* @see #toSortedMap()
*/
public ConcurrentNavigableMap toConcurrentNavigableMapByKey(Comparator keyComparator) {
return inner.collect(Collectors.toConcurrentMap(
Map.Entry::getKey,
Map.Entry::getValue,
throwingMerger(),
() -> new ConcurrentSkipListMap<>(keyComparator)
));
}
/**
* Accumulates all key-value pairs of this {@code MapStream} into a
* {@code ConcurrentNavigableMap}.
*
* If the mapped keys contains duplicates (according to
* {@link Object#equals(Object)}), the values are merged using the provided
* merging function.
*
*
* There are multiple ways to deal with collisions between multiple elements
* mapping to the same key. The other forms of {@code toConcurrentNavigableMap} simply
* use a merge function that throws unconditionally, but you can easily
* write more flexible merge policies.
*
* @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 ConcurrentNavigableMap} whose keys and
* values are identical to the entries of this stream
* with any collisions handled
*
* @see #toMap()
* @see #toSortedMap()
* @see #toConcurrentMap(BinaryOperator)
*/
public ConcurrentNavigableMap toConcurrentNavigableMap(BinaryOperator mergeFunction) {
return inner.collect(Collectors.toConcurrentMap(
Map.Entry::getKey,
Map.Entry::getValue,
mergeFunction,
ConcurrentSkipListMap::new
));
}
/**
* Accumulates all key-value pairs of this {@code MapStream} into a
* {@code ConcurrentNavigableMap}, sorting the entries by applying the
* specified comparator to the keys of the stream.
*
* If the mapped keys contains duplicates (according to
* {@link Object#equals(Object)}), the values are merged using the provided
* merging function.
*
*
* There are multiple ways to deal with collisions between multiple elements
* mapping to the same key. The other forms of
* {@code toConcurrentNavigableMap} simply use a merge function that throws
* unconditionally, but you can easily write more flexible merge policies.
*
* @param keyComparator the comparator to use for determining the order of
* the keys
* @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 ConcurrentNavigableMap} whose keys and
* values are identical to the entries of this stream
* with any collisions handled
*
* @see #toMap()
* @see #toSortedMap()
* @see #toConcurrentMap(BinaryOperator)
*/
public ConcurrentNavigableMap toConcurrentNavigableMap(Comparator keyComparator, BinaryOperator mergeFunction) {
return inner.collect(Collectors.toConcurrentMap(
Map.Entry::getKey,
Map.Entry::getValue,
mergeFunction,
() -> new ConcurrentSkipListMap<>(keyComparator)
));
}
/**
* Accumulates all entries of this {@code MapStream} into a {@code List}.
*
*
* The returned {@code List} is not concurrent.
*
* @return a {@code List} that contains all the entities of the stream
*/
public List> toList() {
return inner.collect(Collectors.toList());
}
/**
* Utility method for creating a composed comparator that begins by
* comparing the first value and if it is equal, continues to the next one.
*
* @param the type of the key to compare
* @param methods methods for comparing the key ordered by priority
* @return a composite comparator that checks the key using the
* supplied methods in order
*/
@SuppressWarnings("varargs")
@SafeVarargs // Iterating over an array is safe.
public static Comparator