JDK8 新特性-Stream

List 转Map

list.stream().collect(Collectors.toMap(SkiiSchedulePlanReportVO::getManagerId, i -> i, (a1, a2) -> a1));

求平均值

List.stream.collect(Collectors.averaginDouble(Double::doubleValue));

filter筛选

List<Integer> integerList = Arrays.asList(1, 1, 2, 3, 4, 5);
Stream<Integer> stream = integerList.stream().filter(i -> i > 3);

distinct去除重复元素

List<Integer> integerList = Arrays.asList(1, 1, 2, 3, 4, 5); 
Stream<Integer> stream = integerList.stream().distinct();

limit返回指定流个数

List<Integer> integerList = Arrays.asList(1, 1, 2, 3, 4, 5); 
Stream<Integer> stream = integerList.stream().limit(3);

skip跳过流中的元素

List<Integer> integerList = Arrays.asList(1, 1, 2, 3, 4, 5); 
Stream<Integer> stream = integerList.stream().skip(2);

元素匹配

提供了三种匹配方式

• allMatch匹配所有

  List<Integer> integerList = Arrays.asList(1, 2, 3, 4, 5);
  if (integerList.stream().allMatch(i -> i > 3)) {     System.out.println("值都大于3"); }

  通过allMatch方法实现

• anyMatch匹配其中一个

  List<Integer> integerList = Arrays.asList(1, 2, 3, 4, 5); 
  if (integerList.stream().anyMatch(i -> i > 3)) { System.out.println("存在大于3的值"); }

存在大于3的值则打印，java8中通过anyMatch方法实现这个功能

• noneMatch全部不匹配

  List<Integer> integerList = Arrays.asList(1, 2, 3, 4, 5); 
  if (integerList.stream().noneMatch(i -> i > 3)) { System.out.println("值都小于3"); }

  查找

• findFirst查找第一个

  List<Integer> integerList = Arrays.asList(1, 2, 3, 4, 5); 
  Optional<Integer> result = integerList.stream().filter(i -> i > 3).findFirst();

• findAny随机查找一个

  List<Integer> integerList = Arrays.asList(1, 2, 3, 4, 5); 
  Optional<Integer> result = integerList.stream().filter(i -> i > 3).findAny();

  求和

• 通过summingInt

  int sum = menu.stream().collect(summingInt(Dish::getCalories));

• 通过reduce

  int sum = integerList.stream().reduce(0, Integer::sum);

• 通过sum

  int sum = menu.stream().mapToInt(Dish::getCalories).sum();

reduce接受两个参数，一个初始值这里是0，一个BinaryOperator accumulator 来将两个元素结合起来产生一个新值， 另外reduce方法还有一个没有初始化值的重载方法

获取流中最小最大值

OptionalInt min = menu.stream().mapToInt(Dish::getCalories).min();
OptionalInt max = menu.stream().mapToInt(Dish::getCalories).max();

通过summarizingInt同时求总和、平均值、最大值、最小值

IntSummaryStatistics intSummaryStatistics = menu.stream().collect(summarizingInt(Dish::getCalories));
double average = intSummaryStatistics.getAverage();  //获取平均值
int min = intSummaryStatistics.getMin();  //获取最小值
int max = intSummaryStatistics.getMax();  //获取最大值
long sum = intSummaryStatistics.getSum();  //获取总和

返回集合

List<String> strings = menu.stream().map(Dish::getName).collect(toList());
Set<String> sets = menu.stream().map(Dish::getName).collect(toSet());

通过joining拼接流中的元素

String result = menu.stream().map(Dish::getName).collect(Collectors.joining(", "));

进阶通过groupingBy进行分组

Map<Type, List<Dish>> result = dishList.stream().collect(groupingBy(Dish::getType));

在collect方法中传入groupingBy进行分组，其中groupingBy的方法参数为分类函数。还可以通过嵌套使用groupingBy进行多级分类

Map<Type, List<Dish>> result = menu.stream().collect(groupingBy(Dish::getType,
        groupingBy(dish -> {
            if (dish.getCalories() <= 400) return CaloricLevel.DIET;
                else if (dish.getCalories() <= 700) return CaloricLevel.NORMAL;
                else return CaloricLevel.FAT;
        })));