Weird Stream API

Тагир ВалеевJetBrains

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Почему мне можно верить?https://github.com/amaembo/streamex

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Почему мне можно верить?• JDK-8072727 Add variation of Stream.iterate() that's finite• JDK-8136686 Collectors.counting can use Collectors.summingLong to reduce boxing• JDK-8141630 Specification of Collections.synchronized* need to state traversal constraints• JDK-8145007 Pattern splitAsStream is not late binding as required by the specification• JDK-8146218 Add LocalDate.datesUntil method producing Stream<LocalDate>• JDK-8147505 BaseStream.onClose() should not allow registering new handlers after stream is consumed• JDK-8148115 Stream.findFirst for unordered source optimization• JDK-8148250 Stream.limit() parallel tasks with ordered non-SUBSIZED source should short-circuit• JDK-8148838 Stream.flatMap(...).spliterator() cannot properly split after tryAdvance()• JDK-8148748 ArrayList.subList().spliterator() is not late-binding• JDK-8151123 Collectors.summingDouble/averagingDouble unnecessarily call mapper twice• JDK-8153293 Preserve SORTED and DISTINCT characteristics for boxed() and asLongStream() operations• JDK-8154387 Parallel unordered Stream.limit() tries to collect 128 elements even if limit is less• JDK-8155600 Performance optimization of Arrays.asList().iterator()• JDK-8164189 Collectors.toSet() parallel performance improvement

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source.stream()

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.map(x -> x.squash())

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.filter(x -> x.getColor() != YELLOW)

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.forEach(System.out::println)

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source.stream() .map(x -> x.squash()) .filter(x -> x.getColor() != YELLOW) .forEach(System.out::println)

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AtomicLong cnt = new AtomicLong();

.peek(x -> cnt.incrementAndGet())

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AtomicLong cnt = new AtomicLong();

source.stream() .map(x -> x.squash()) .peek(x -> cnt.incrementAndGet()) .filter(x -> x.getColor() != YELLOW) .forEach(System.out::println)

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LongStream.range(1, 100) .count();

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LongStream.range(1, 100) .count();>> 99

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LongStream.range(0, 1_000_000_000_000_000_000L) .count();

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LongStream.range(0, 1_000_000_000_000_000_000L) .count();

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LongStream.range(0, 1_000_000_000_000_000_000L) .count();>> 1000000000000000000

Java 9:JDK-8067969 Optimize Stream.count for SIZED Streams

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public interface Spliterator<T> { boolean tryAdvance(Consumer<? super T> action); default void forEachRemaining(Consumer<? super T> action) { … }

Spliterator<T> trySplit();

long estimateSize(); default long getExactSizeIfKnown() { … }

int characteristics(); default boolean hasCharacteristics(int characteristics) { … }

default Comparator<? super T> getComparator() { … } …}

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Характеристики

SIZEDSUBSIZEDSORTEDORDERED

DISTINCTNONNULLIMMUTABLECONCURRENT

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list.stream() .peek(data -> process(data)) .peek(data -> processInAnotherWay(data)) .count(); // какая-нибудь терминальная операция

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Характеристики

SIZEDSUBSIZEDSORTEDORDERED

DISTINCTNONNULLIMMUTABLECONCURRENT

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Характеристики

SIZEDSUBSIZEDSORTEDORDERED

DISTINCTNONNULLIMMUTABLECONCURRENT

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Stream<T>IntStreamLongStreamDoubleStream

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Stream<T>IntStream Stream<Integer>

LongStream Stream<Long>DoubleStream Stream<Double>

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Primitive is faster!

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int[] ints;Integer[] integers;

@Setuppublic void setup() { ints = new Random(1).ints(1000000, 0, 1000) .toArray(); integers = new Random(1).ints(1000000, 0, 1000) .boxed().toArray(Integer[]::new);}

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@Benchmarkpublic long stream() { return Stream.of(integers).distinct().count();}

@Benchmarkpublic long intStream() { return IntStream.of(ints).distinct().count();}

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@Benchmarkpublic long stream() { return Stream.of(integers).distinct().count();}

@Benchmarkpublic long intStream() { return IntStream.of(ints).distinct().count();}

# VM version: JDK 1.8.0_92, VM 25.92-b14Benchmark Mode Cnt Score Error UnitsintStream avgt 30 17.121 ± 0.296 ms/opstream avgt 30 15.764 ± 0.116 ms/op

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Stream<T> ⇒ ReferencePipelineIntStream ⇒ IntPipelineLongStream ⇒ LongPipelineDoubleStream ⇒ DoublePipeline

AbstractPipeline

package java.util.stream;

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// java.util.stream.IntPipeline

@Overridepublic final IntStream distinct() { // While functional and quick to implement, // this approach is not very efficient. // An efficient version requires // an int-specific map/set implementation. return boxed().distinct().mapToInt(i -> i);}

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@Benchmarkpublic long stream() { return Stream.of(integers).distinct().count();}

@Benchmarkpublic long intStream() { // IntStream.of(ints).distinct().count(); return IntStream.of(ints).boxed().distinct() .mapToInt(i -> i).count();}

-prof gcstream 48870 B/opintStream 13642536 B/op

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Задача: вычислить сумму 5 различных псевдослучайных чисел от 1 до 20.

Image courtesy: http://magenta-stock.deviantart.com/

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Задача: вычислить сумму 5 различных псевдослучайных чисел от 1 до 20.

// IntStream ints(long streamSize, int origin, int bound)new Random().ints(5, 1, 20+1).sum();

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Задача: вычислить сумму 5 различных псевдослучайных чисел от 1 до 20.

// IntStream ints(long streamSize, int origin, int bound)new Random().ints(5, 1, 20+1).sum();

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Задача: вычислить сумму 5 различных псевдослучайных чисел от 1 до 20.

// IntStream ints(long streamSize, int origin, int bound)new Random().ints(5, 1, 20+1).sum();

new Random().ints(5, 1, 20+1).distinct().sum();

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Задача: вычислить сумму 5 различных псевдослучайных чисел от 1 до 20.

// IntStream ints(long streamSize, int origin, int bound)new Random().ints(5, 1, 20+1).sum();

new Random().ints(5, 1, 20+1).distinct().sum();

// IntStream ints(int origin, int bound)new Random().ints(1, 20+1).distinct().limit(5).sum();

…

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Задача: вычислить сумму 5 различных псевдослучайных чисел от 1 до 20.

new Random().ints(1, 20+1).distinct().limit(5).sum();

new Random().ints(1, 20+1).parallel().distinct().limit(5).sum();

new Random().ints(1, 20+1).distinct().parallel().limit(5).sum();

new Random().ints(1, 20+1).distinct().limit(5).parallel().sum();

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Задача: вычислить сумму 5 различных псевдослучайных чисел от 1 до 20.

new Random().ints(1, 20+1).distinct().limit(5).sum();

new Random().ints(1, 20+1).parallel().distinct().limit(5).sum();

new Random().ints(1, 20+1).distinct().parallel().limit(5).sum();

new Random().ints(1, 20+1).distinct().limit(5).parallel().sum();

new Random().ints(1, 20+1).parallel().distinct().limit(5) .sequential().sum();

JDK-8132800 clarify stream package documentation regarding sequential vs parallel modes

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Задача: вычислить сумму 5 различных псевдослучайных чисел от 1 до 20.

new Random().ints(1, 20+1).distinct().limit(5).sum();

# VM version: JDK 1.8.0_92, VM 25.92-b14Benchmark Mode Cnt Score Error UnitsrndSum avgt 30 0.286 ± 0.001 us/op

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Задача: вычислить сумму 5 различных псевдослучайных чисел от 1 до 20.

new Random().ints(1, 20+1).distinct().limit(5).sum();

# VM version: JDK 1.8.0_92, VM 25.92-b14Benchmark Mode Cnt Score Error UnitsrndSum avgt 30 0.286 ± 0.001 us/oprndSumPar ~6080 years/op

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Задача: вычислить сумму 5 различных псевдослучайных чисел от 1 до 20.

new Random().ints(1, 20+1).distinct().limit(5).sum();

# VM version: JDK 1.8.0_92, VM 25.92-b14Benchmark Mode Cnt Score Error UnitsrndSum avgt 30 0.286 ± 0.001 us/oprndSumPar ~6080 years/op

java.util.stream.StreamSpliterators.UnorderedSliceSpliterator<T, T_SPLITR>

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Задача: вычислить сумму 5 различных псевдослучайных чисел от 1 до 20.

public IntStream ints(int randomNumberOrigin, int randomNumberBound) Returns an effectively unlimited stream of pseudorandom int values, each conformingto the given origin (inclusive) and bound (exclusive).

Implementation Note:This method is implemented to be equivalent to ints(Long.MAX_VALUE, randomNumberOrigin, randomNumberBound).

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Задача: вычислить сумму 5 различных псевдослучайных чисел от 1 до 20.

new Random().ints(1, 20+1).distinct().limit(5).sum();new Random().ints(1, 20+1).parallel().distinct().limit(5).sum();

# VM version: JDK 9-ea, VM 9-ea+130Benchmark Mode Cnt Score Error UnitsrndSum avgt 30 0.318 ± 0.003 us/oprndSumPar avgt 30 7.793 ± 0.026 us/op

JDK-8154387 Parallel unordered Stream.limit() tries to collect 128 elements even if limit is less

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parallel().skip()IntStream.range(0, 100_000_000) 104.5±4.4 ms .skip(99_000_000) .sum();

IntStream.range(0, 100_000_000) ? .parallel() .skip(99_000_000) .sum();

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parallel().skip()API Note:While skip() is generally a cheap operation on sequential stream pipelines, it can be quite expensive on ordered parallel pipelines, especially for large values of n, since skip(n) is constrained to skip not just any n elements, but the first n elements in the encounter order.

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parallel().skip()IntStream.range(0, 100_000_000) 104.5±4.4 ms .skip(99_000_000) .sum();

IntStream.range(0, 100_000_000) 1.4±0.2 ms .parallel() (74.6×) .skip(99_000_000) .sum();

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parallel(): trySplit() (SIZED+SUBSIZED)

0..99_999_999

0..49_999_999 50_000_000..99_999_999

75_000_000..99_999_999

50_000_000..74_999_999

…………

25_000_000..49_999_999

……

0..24_999_999

……

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parallel().skip()(SIZED+SUBSIZED)

0..99_999_999

0..49_999_999 50_000_000..99_999_999

75_000_000..99_999_99950_000_000..74_999_999

……

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class Node { private String name; private List<Node> children;

public Node(String name, Node... children) { this.name = name; this.children = Arrays.asList(children); }

@Override public String toString() { return name; }

public Stream<Node> allNodes() { return …? }}

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class Node { private String name; private List<Node> children;

...

@Override public String toString() { return name; }

public Stream<Node> allNodes() { return children.isEmpty() ? Stream.of(this) : Stream.concat( Stream.of(this), children.stream().flatMap(Node::allNodes)); }}

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flatMap()Stream<Integer> a = ...;Stream<Integer> b = ...;Stream<Integer> c = ...;Stream<Integer> d = ...;Stream<Integer> res = Stream.concat( Stream.concat(Stream.concat(a, b), c), d);

Stream<Integer> res = Stream.of(a, b, c, d) .flatMap(Function.identity());

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flatMap() – декартово произведениеList<List<String>> input = asList(asList("a", "b", "c"), asList("x", "y"), asList("1", "2", "3"));

Supplier<Stream<String>> s = input.stream() .<Supplier<Stream<String>>>map(list -> list::stream) .reduce((sup1, sup2) -> () -> sup1.get() .flatMap(e1 -> sup2.get().map(e2 -> e1+e2))) .orElse(() -> Stream.of(""));

s.get().forEach(System.out::println);>> ax1>> ax2>> …>> cy3

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flatMap() parallel?Stream.of(list1, list2).parallel() .flatMap(List::stream).forEach(item -> {...});

list1

Item1Item2Item3

…Item1000

list2

Item1Item2Item3

…Item1000

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flatMap() parallel?Stream.of(list1, list2).parallel() .flatMap(l -> l.stream().parallel()).forEach(item -> {...});

list1

Item1Item2Item3

…Item1000

list2

Item1Item2Item3

…Item1000

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concat()-то лучше!Stream.concat(list1.stream().parallel(), list2.stream().parallel()).forEach(item -> {});

list1

Item1Item2

…Item500

Item501Item502

…Item1000

list2

Item1Item2

…Item500

Item501Item502

…Item1000

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flatMap() и short-circuitingprivate IntStream stream() {

if (!flatMap) {

return IntStream.rangeClosed(0, 1_000_000_000);

} else {

return IntStream.of(1_000_000_000)

.flatMap(x -> IntStream.rangeClosed(0, x));

}

}

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flatMap() и short-circuiting@Benchmarkpublic boolean hasGreaterThan2() { return stream().anyMatch(x -> x > 2);}

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flatMap() и short-circuiting@Benchmarkpublic boolean hasGreaterThan2() { return stream().anyMatch(x -> x > 2);}

# VM version: JDK 1.8.0_101, VM 25.101-b13Benchmark (flatMap) Mode Score Error UnitshasGreaterThan2 false avgt 0.040 ± 0.001 μs/ophasGreaterThan2 true avgt 980489.972 ± 12335.916 μs/op

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flatMap() и tryAdvance()flatMap = false;Spliterator<Integer> spliterator = stream().spliterator();spliterator.tryAdvance(System.out::println);>> 0

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flatMap() и tryAdvance()flatMap = true;Spliterator<Integer> spliterator = stream().spliterator();spliterator.tryAdvance(System.out::println);

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java.lang.OutOfMemoryError: Java heap space at java.util.stream.SpinedBuffer.ensureCapacity at java.util.stream.SpinedBuffer.increaseCapacity at java.util.stream.SpinedBuffer.accept at java.util.stream.IntPipeline$4$1.accept at java.util.stream.IntPipeline$7$1.lambda$accept$198 at java.util.stream.IntPipeline$7$1$$Lambda$7/1831932724.accept at java.util.stream.Streams$RangeIntSpliterator.forEachRemaining at java.util.stream.IntPipeline$Head.forEach at java.util.stream.IntPipeline$7$1.accept at java.util.stream.Streams$IntStreamBuilderImpl.tryAdvance at java.util.Spliterator$OfInt.tryAdvance ... at java.util.stream.StreamSpliterators$WrappingSpliterator.tryAdvance at by.jetconf.streamsamples.FlatMapTryAdvance.main

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flatMap() и tryAdvance()flatMap = true;Spliterator<Integer> spliterator = stream().spliterator();spliterator.tryAdvance(System.out::println);

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flatMap() и concat()flatMap = true;

stream().sum();

stream().findFirst(); // non-short-circuit

IntStream.concat(stream(), IntStream.of(1)).sum();

IntStream.concat(stream(), IntStream.of(1)).findFirst();

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Exception in thread "main" java.lang.OutOfMemoryError: Java heap space at java.util.stream.SpinedBuffer$OfInt.newArray at java.util.stream.SpinedBuffer$OfInt.newArray at java.util.stream.SpinedBuffer$OfPrimitive.ensureCapacity at java.util.stream.SpinedBuffer$OfPrimitive.increaseCapacity at java.util.stream.SpinedBuffer$OfPrimitive.preAccept at java.util.stream.SpinedBuffer$OfInt.accept ... at java.util.stream.Streams$ConcatSpliterator$OfInt.tryAdvance at java.util.stream.IntPipeline.forEachWithCancel at java.util.stream.AbstractPipeline.copyIntoWithCancel at java.util.stream.AbstractPipeline.copyInto at java.util.stream.AbstractPipeline.wrapAndCopyInto at java.util.stream.FindOps$FindOp.evaluateSequential at java.util.stream.AbstractPipeline.evaluate at java.util.stream.IntPipeline.findFirst at by.jetconf.streamsamples.ConcatFlat.main

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class Node { private String name; private List<Node> children;

...

@Override public String toString() { return name; }

public Stream<Node> allNodes() { return children.isEmpty() ? Stream.of(this) : Stream.concat( Stream.of(this), children.stream().flatMap(Node::allNodes)); }}

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Root

Child

n0 n1 n2 n3 n999999…

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root.allNodes().count()

root.allNodes().anyMatch(n -> false)

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count 29.4 ± 2.0 ms 80 001 KB/op

anyMatch 70.0 ± 6.0 ms 84 196 KB/op

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// with concatpublic Stream<Node> allNodes() { return children.isEmpty() ? Stream.of(this) : Stream.concat( Stream.of(this), children.stream().flatMap(Node::allNodes));}

// without concatpublic Stream<Node> allNodes() { return children.isEmpty() ? Stream.of(this) : Stream.of(Stream.of(this), children.stream().flatMap(Node::allNodes)) .flatMap(Function.identity());}

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count (concat) 29.4 ± 2.0 ms 80 001 KB/op (flatMap) 32.6 ± 2.0 ms 80 001 KB/op

anyMatch (concat) 70.0 ± 6.0 ms 84 196 KB/op (flatMap) 31.0 ± 2.3 ms 80 001 KB/op

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// with concatpublic Stream<Node> allNodes() { return children.isEmpty() ? Stream.of(this) : Stream.concat( Stream.of(this), children.stream().flatMap(Node::allNodes));}

// without concatpublic Stream<Node> allNodes() { return children.isEmpty() ? Stream.of(this) : Stream.of(Stream.of(this), children.stream().flatMap(Node::allNodes)) .flatMap(Function.identity());}

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import one.util.streamex.StreamEx;

public Stream<Node> allNodes() { return StreamEx.ofTree(this, n -> n.children.isEmpty() ? null : StreamEx.of(n.children));}

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count (concat) 29.4 ± 2.0 ms 80 001 KB/op (flatMap) 32.6 ± 2.0 ms 80 001 KB/op (StreamEx) 12.4 ± 0.2 ms 0.5 KB/op

anyMatch (concat) 70.0 ± 6.0 ms 84 196 KB/op (flatMap) 31.0 ± 2.3 ms 80 001 KB/op (StreamEx) 19.3 ± 0.3 ms 0.5 KB/op

Stream и Iterator

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iterator()

Верните цикл for()!

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for vs forEach()for forEach()

Появился Java 1.5 Java 1.8

Нормальная отладка

Короткие стектрейсы

Checked exceptions

Изменяемые переменные

Досрочный выход по break

Параллелизм (всё равно не нужен)

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iterator()

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iterator()Stream<String> s = Stream.of("a", "b", "c");for(String str : (Iterable<String>)s::iterator) { System.out.println(str);}

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iterator()Stream<String> s = Stream.of("a", "b", "c");for(String str : (Iterable<String>)s::iterator) { System.out.println(str);}

// Joshua Bloch approvesfor(String str : StreamEx.of("a", "b", "c")) { System.out.println(str);}

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iterator()

IntStream s = IntStream.of(1_000_000_000) .flatMap(x -> IntStream.range(0, x));for(int i : (Iterable<Integer>)s::iterator) { System.out.println(i);}

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Exception in thread "main" java.lang.OutOfMemoryError: Java heap space at j.u.s.SpinedBuffer$OfInt.newArray at j.u.s.SpinedBuffer$OfInt.newArray at j.u.s.SpinedBuffer$OfPrimitive.ensureCapacity at j.u.s.SpinedBuffer$OfPrimitive.increaseCapacity at j.u.s.SpinedBuffer$OfPrimitive.preAccept at j.u.s.SpinedBuffer$OfInt.accept at j.u.s.IntPipeline$7$1.lambda$accept$198 ... at j.u.s.StreamSpliterators$AbstractWrappingSpliterator.fillBuffer at j.u.s.StreamSpliterators$AbstractWrappingSpliterator.doAdvance at j.u.s.StreamSpliterators$IntWrappingSpliterator.tryAdvance at j.u.Spliterators$2Adapter.hasNext at by.jetconf.streamsamples.IterableWorkaround.main

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Map<String, String> userPasswords = Files.lines(Paths.get("/etc/passwd")) .map(str -> str.split(":")) .collect(toMap(arr -> arr[0], arr -> arr[1]));

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Map<String, String> userPasswords = Files.lines(Paths.get("/etc/passwd")) .map(str -> str.split(":")) .collect(toMap(arr -> arr[0], arr -> arr[1]));

such stream

WOWmuch fluent

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Map<String, String> userPasswords;try (Stream<String> stream = Files.lines(Paths.get("/etc/passwd"))) { userPasswords = stream.map(str -> str.split(":")) .collect(toMap(arr -> arr[0], arr -> arr[1]));}

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Map<String, String> userPasswords;try (Stream<String> stream = Files.lines(Paths.get("/etc/passwd"))) { userPasswords = stream.map(str -> str.split(":")) .collect(toMap(arr -> arr[0], arr -> arr[1]));}

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http://stackoverflow.com/questions/34753078/

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Терминальные операции

Нормальные (с внутренним обходом):

forEach()collect()reduce()

findFirst()count()toArray()

…

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Терминальные операции

Нормальные (с внутренним обходом):

forEach()collect()reduce()

findFirst()count()toArray()

…

Причудливые(с внешним обходом):

iterator()spliterator()

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Use flatMapto save the Stream!

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flatMap<R> Stream<R> flatMap( Function<? super T,? extends Stream<? extends R>> 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 closed after its contents have been placed into this stream. (If a mapped stream is null an empty stream is used, instead.)

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Map<String, String> userPasswords = Stream.of(Files.lines(Paths.get("/etc/passwd"))) .flatMap(Function.identity()) .map(str -> str.split(":")) .collect(toMap(arr -> arr[0], arr -> arr[1]));

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Files.lines(Paths.get("/etc/passwd")) .spliterator().tryAdvance(...);// вычитываем одну строку, файл не закрываем

Stream.of(Files.lines(Paths.get("/etc/passwd"))) .flatMap(s -> s) .spliterator().tryAdvance(...);// вычитываем весь файл в память, файл закрываем

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Files.lines(Paths.get("/etc/passwd")) .spliterator().tryAdvance(...);// вычитываем одну строку, файл не закрываем

Stream.of(Files.lines(Paths.get("/etc/passwd"))) .flatMap(s -> s) .spliterator().tryAdvance(...);// вычитываем весь файл в память, файл закрываем

http://stackoverflow.com/a/32767282/4856258 (небуферизующий flatMap)

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There’s no way to save the Stream

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Спасибо за внимание

https://twitter.com/tagir_valeev

https://github.com/amaembo

https://habrahabr.ru/users/lany