JAVA8 Collector接口

Collector接口如下

public interface Collector<T, A, R> {
    Supplier<A> supplier();
    BiConsumer<A, T> accumulator();
    BinaryOperator<A> combiner();
    Function<A, R> finisher();
    Set<Characteristics> characteristics();
}

<T,A,R> 的意義:

T是供應源 A是累加器 R是組合器

一、例子一：

自己寫 toList() 的實現

public class ToCollectionList<T> implements Collector<T, List<T>, List<T>>{
    @Override
    //供應源--建立新的結果容器
    public Supplier<List<T>> supplier() {
        return ArrayList::new;
    }
    @Override
    //累加器--將元素添加到結果容器中
    public BiConsumer<List<T>, T> accumulator() {
        return List::add;
    }
    @Override
    //組合器--合并兩個結果容器
    public BinaryOperator<List<T>> combiner() {
        return (listA, listB) -> {
            listA.addAll(listB);
            return listA;
        };
    }
    @Override
    //恒等函數--對結果容器應用轉換
    public Function<List<T>, List<T>> finisher() {
        return Function.identity();
    }
    @Override
    //返回不可變Characteristics,定義收集器的行為，尤其是是否進行并行歸約
    public Set<Characteristics> characteristics() {
        return Collections.unmodifiableSet(EnumSet.of(Characteristics.IDENTITY_FINISH, Characteristics.CONCURRENT));
    }
}

二、例子二：

比自帶partitioningBy 性能更強的 分區實現（質數）

public class FuckPrime implements Collector<Integer, Map<Boolean, List<Integer>>, Map<Boolean, List<Integer>>> {

    @Override
    public Supplier<Map<Boolean, List<Integer>>> supplier() {
        return () -> new HashMap<Boolean, List<Integer>>() {

            private static final long serialVersionUID = -2542842140223455161L;

            {
                put(true, new ArrayList<Integer>());
                put(false, new ArrayList<Integer>());
            }
        };
    }

    @Override
    public BiConsumer<Map<Boolean, List<Integer>>, Integer> accumulator() {
        return (Map<Boolean, List<Integer>> map, Integer can) -> {
            map.get(isPrime(map.get(true), can)).add(can);
        };
    }

    @Override
    public BinaryOperator<Map<Boolean, List<Integer>>> combiner() {
        return (Map<Boolean, List<Integer>> map1, Map<Boolean, List<Integer>> map2) -> {
            map1.get(true).addAll(map2.get(true));
            map1.get(false).addAll(map2.get(false));
            return map1;
        };
    }

    @Override
    public Function<Map<Boolean, List<Integer>>, Map<Boolean, List<Integer>>> finisher() {
        return Function.identity();
    }

    @Override
    public Set<java.util.stream.Collector.Characteristics> characteristics() {
        return Collections.unmodifiableSet(EnumSet.of(Characteristics.IDENTITY_FINISH));
    }

    private static boolean isPrime(List<Integer> list, int can) {
        int canRoot = (int) Math.sqrt((double) can);
        return takeWhile(list, i -> i <= canRoot).stream().noneMatch(p -> can % p == 0);
    }

    private static boolean isPrime2(int num) {
        int num2 = (int) Math.sqrt((double) num);
        return IntStream.rangeClosed(2, num2).noneMatch(t -> num % t == 0);
    }

    private static <T> List<T> takeWhile(List<T> list, Predicate<T> p) {
        int i = 0;
        for (T t : list) {
            if (!p.test(t)) {
                return list.subList(0, i);
            }
            i++;
        }
        return list;
    }

    public static Map<Boolean, List<Integer>> getPrime(int n) {
        return IntStream.rangeClosed(2, n).boxed().collect(new FuckPrime());
    }

    public static Map<Boolean, List<Integer>> getPrime2(int n) {
        return IntStream.rangeClosed(2, n).boxed().collect(Collectors.partitioningBy(i -> isPrime2(i)));
    }

    public static void main(String[] args) {
        Long s = System.nanoTime();
        for (int i = 0; i <= 10; i++) {
            getPrime(1_000_000);
        }
        Long e = System.nanoTime();
        System.out.println("自寫方法耗時：" + (e - s) / 1_000_000 + "ms");

        Long s2 = System.nanoTime();
        for (int i = 0; i <= 10; i++) {
            getPrime2(1_000_000);
        }
        Long e2 = System.nanoTime();
        System.out.println("Stream分區方法耗時：" + (e2 - s2) / 1_000_000 + "ms");
    }
}

10次1000000內搜索結果：

自寫方法耗時：3015ms
Stream分區方法耗時：4785ms