Java8 - Stream API

版权声明：转载请注明出处 https://blog.csdn.net/u013837825/article/details/87191393

Java8 - Stream API

总览

1.介绍

• Stream创建 -> 中间操作 -> 终止操作

流一旦使用终止操作，就不能再进行中间操作

• Java8 特性
• 与 函数式接口 配合使用

参考Java8 - Lambda表达式

• 与 Optional 配合使用
• 惰性求值

多个中间操作可以连接起来形成一个流水线，除非流水 线上触发终止操作，否则中间操作不会执行任何的处理!而在终止操作时一次性全部处理，称为“惰性求值”。

2.Stream 的创建

2.1 使用 Collection 集合进行创建

default Stream stream() {return StreamSupport.stream(spliterator(), false);}

default Stream parallelStream() {return StreamSupport.stream(spliterator(), true);}

        Collection<Integer> collection = new ArrayList<Integer>();
        collection.add(1);
        collection.add(2);
        collection.add(3);
        collection.add(4);

        // 串行流
        Stream<Integer> stream1 = collection.stream();
        // 并行流
        Stream<Integer> stream2 = collection.parallelStream();

2.2 使用数组进行创建

public static Stream stream(T[] array)

public static Stream stream(T[] array, int startInclusive, int endExclusive)

public static IntStream stream(int[] array) …

public static LongStream stream(long[] array) …

public static DoubleStream stream(double[] array) …

        Integer[] array = new Integer[]{1, 2, 3, 4};
        Stream<Integer> stream1 = Arrays.stream(array);

2.3 Stream 的静态方法 of()

public static Stream of(T… values)

        Stream<Integer> stream1 = Stream.of(1, 2, 3, 4);

2.4 创建无限流 ’迭代‘ 或 ’生成‘

public static Stream iterate(final T seed, final UnaryOperator f)

public static Stream generate(Supplier s)

        Stream<Integer> stream1 = Stream.iterate(1, (t) -> t + 2);

        Stream<Double> stream1 = Stream.generate(() -> new Random().nextInt(100));

2.5 其他

public static Stream concat(Stream<? extends T> a, Stream<? extends T> b)

3.Stream 的中间操作

3.1 筛选 filter

Stream filter(Predicate<? super T> predicate);

        Stream<Student> stream2 = stream1.filter((t) -> {
            if (t.getAge() >= 18) {
                return true;
            }
            return false;
        });

3.2 切片 limit skip

Stream limit(long maxSize);
截取前N个元素

Stream skip(long n);
忽略前N个元素

3.3 去重 distinct

Stream distinct();

以对象的 hashCode() 和 equals() 来判定是否是同一个元素

3.4 映射 map flatMap

Stream map(Function<? super T, ? extends R> mapper);

IntStream mapToInt(ToIntFunction<? super T> mapper);

LongStream mapToLong(ToLongFunction<? super T> mapper);

DoubleStream mapToDouble(ToDoubleFunction<? super T> mapper);

Stream flatMap(Function<? super T, ? extends Stream<? extends R>> mapper);

…

        Stream<Student> stream2 = stream1.map((o) -> {
            if (o.getName().contains("敏感词汇")) {
                o.setName(o.getName().replaceAll("敏感词汇","*"));
            }
            return o;
        });

        Stream<String> stream2 = stream1.map(Student::getName);

对比 flatMap 和 map 的区别: flatMap会将结果拼装成一个整体

    public void test7() {
        List<String> list = Arrays.asList("hello", "world", "gq");

        Stream<Stream<Character>> stream
                = list.stream().map(StreamAPIOperrateDemo::stringToCharacter);
        Stream<Character> stream2
                = list.stream().flatMap(StreamAPIOperrateDemo::stringToCharacter);

        stream.forEach((sm) -> sm.forEach(System.out::print));
        //

        System.out.println();
        stream2.forEach(System.out::print);
        //
    }

    private static Stream<Character> stringToCharacter(String string) {
        List<Character> characterList = new ArrayList<>();
        char[] chars = string.toCharArray();
        for (Character ch : chars) {
            characterList.add(ch);
        }
        return characterList.stream();
    }

3.5 排序 sorted

Stream sorted();

前提：T 实现 Comparable 接口

Stream sorted(Comparator<? super T> comparator);

        //Stream<Student> stream2 = stream1.sorted();
        //Stream<Student> stream2 = stream1.sorted(new StudentComparator());

        //Stream<Student> stream2 = stream1.sorted((s1, s2) -> s1.getAge() - s2.getAge());

        Stream<Student> stream2 = stream1.sorted((s1, s2) -> Integer.compare(s1.getAge(),s2.getAge()));

        // 推荐
        Stream<Student> stream3 = stream1.sorted(Comparator.comparingInt(Student::getAge));

4.Stream 的终止操作

4.1 匹配 allMatch anyMatch noneMatch

boolean allMatch(Predicate<? super T> predicate);

检查是否匹配所有元素

boolean anyMatch(Predicate<? super T> predicate);

检查是否至少匹配一个元素

boolean noneMatch(Predicate<? super T> predicate);

检查是否没有匹配的元素

4.2 查找 findFirst findAny count max min

Optional findFirst();

返回第一个元素

Optional findAny();

返回当前流中的任意元素

long count();

返回流中元素的总个数

Optional max(Comparator<? super T> comparator);

返回流中最大值

Optional<Integer> maxAge = stream1.distinct().map(Student::getAge).max(Integer::compare);

Optional min(Comparator<? super T> comparator);

返回流中最小值

4.3 归约 reduce

T reduce(T identity, BinaryOperator accumulator);

        List<Integer> list = Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9, 10);
        Integer sum = list.stream().reduce(0, (x, y) -> x + y);
        System.out.println(sum);

Optional reduce(BinaryOperator accumulator);

U reduce(U identity, BiFunction<U, ? super T, U> accumulator, BinaryOperator combiner);

        List<String> list = Arrays.asList("June", "Kmde", "Kang", "Zhan", "Gui");
        Optional<String> result = list.stream().reduce((x, y) -> x + "_" + y);
        System.out.println(result.get());

Integer sum = stream1.distinct().map(Student::getAge).reduce(0, (x, y) -> x + y);

Optional<Integer> sum = stream1.distinct().map(Student::getAge).reduce(Integer::sum);

4.4 搜集 collect

R collect(Supplier supplier,
BiConsumer<R, ? super T> accumulator,
BiConsumer<R, R> combiner);

<R, A> R collect(Collector<? super T, A, R> collector);

可以借助Collectors工具类进行构建Collector对象；

4.4.1 转化

可以转化成List、Set、Map …

List<String> names = stream1.map(Student::getName).collect(Collectors.toList());

Set<String> names = stream1.map(Student::getName).collect(Collectors.toSet());

Set<String> names = stream1.map(Student::getName).collect(Collectors.toCollection(HashSet::new));

Map<Integer, String> names = stream1.distinct().collect(Collectors.toMap(Student::getId, Student::getName));

4.4.2 汇总数据

汇总 总量、总数值、平均值、最大最小值…

Long count = stream1.collect(Collectors.counting());

Double sum = stream1.collect(Collectors.summingDouble(Student::getHeight));

Double avg = stream1.collect(Collectors.averagingDouble(Student::getHeight));

Optional<Student> optionalStudent = stream1.collect(Collectors.maxBy(Comparator.comparingDouble(Student::getHeight)));

// 汇总统计
        DoubleSummaryStatistics sum = stream1.collect(Collectors.summarizingDouble(Student::getHeight));

        System.out.println(sum.getCount());
        System.out.println(sum.getSum());
        System.out.println(sum.getAverage());
        System.out.println(sum.getMax());
        System.out.println(sum.getMin());

4.4.3 分组

        Map<Integer, List<Student>> stuMap = stream1.collect(Collectors.groupingBy(Student::getAge));
        stuMap.forEach((key, value) -> {
            System.out.println("age:" + key);
            value.forEach(System.out::println);
        });

        // ----

        Map<Integer, Map<String, List<Student>>> stuMap = stream1.collect(Collectors.groupingBy(Student::getAge, Collectors.groupingBy(t -> {
            if (t.getHeight() >= 1.80) {
                return "挺高";
            } else if (t.getHeight() <= 1.60) {
                return "偏矮";
            } else {
                return "正常";
            }
        })));

        stuMap.forEach((key, value) -> {
            System.out.println("age:" + key);

            value.forEach((k, v) -> {
                System.out.println("height" + k);
                v.forEach(System.out::println);
            });

        });

4.4.4 分片

        Map<Boolean, List<Student>> booleanListMap = stream1.collect(Collectors.partitioningBy(t -> t.getAge() >= 18));
        booleanListMap.forEach((key, value) -> {
            System.out.println("age:" + key);
            value.forEach(System.out::println);
        });

4.4.5 连接 join

String names = stream1.map(Student::getName).collect(Collectors.joining(",", "<Start>", "<End>"));

---

开源中国博客