java8中的聚合操作

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package lambda;  import java.util.Arrays; import java.util.List; import java.util.Map; import java.util.stream.Collectors;  public class LambdaMapReduce {     private static List<User> users = Arrays.asList(             new User(1, "张三", 12,User.Sex.MALE),              new User(2, "李四", 21, User.Sex.FEMALE),              new User(3,"王五", 32, User.Sex.MALE),              new User(4, "赵六", 32, User.Sex.FEMALE));      public static void main(String[] args) {         reduceAvg();         reduceSum();                   //与stream.reduce方法不同，Stream.collect修改现存的值，而不是每处理一个元素，创建一个新值         //获取所有男性用户的平均年龄         Averager averageCollect = users.parallelStream()                 .filter(p -> p.getGender() == User.Sex.MALE)                 .map(User::getAge)                 .collect(Averager::new, Averager::accept, Averager::combine);          System.out.println("Average age of male members: "                 + averageCollect.average());          //获取年龄大于12的用户列表         List<User> list = users.parallelStream().filter(p -> p.age > 12)                 .collect(Collectors.toList());         System.out.println(list);          //按性别统计用户数         Map<User.Sex, Integer> map = users.parallelStream().collect(                 Collectors.groupingBy(User::getGender,                         Collectors.summingInt(p -> 1)));         System.out.println(map);          //按性别获取用户名称         Map<User.Sex, List<String>> map2 = users.stream()                 .collect(                         Collectors.groupingBy(                                 User::getGender,                                 Collectors.mapping(User::getName,                                         Collectors.toList())));         System.out.println(map2);                  //按性别求年龄的总和         Map<User.Sex, Integer> map3 = users.stream().collect(                 Collectors.groupingBy(User::getGender,                         Collectors.reducing(0, User::getAge, Integer::sum)));          System.out.println(map3);                  //按性别求年龄的平均值         Map<User.Sex, Double> map4 = users.stream().collect(                 Collectors.groupingBy(User::getGender,                         Collectors.averagingInt(User::getAge)));         System.out.println(map4);      }      // 注意，reduce操作每处理一个元素总是创建一个新值，     // Stream.reduce适用于返回单个结果值的情况     //获取所有用户的平均年龄     private static void reduceAvg() {         // mapToInt的pipeline后面可以是average,max,min,count,sum         double avg = users.parallelStream().mapToInt(User::getAge)                  .average().getAsDouble();          System.out.println("reduceAvg User Age: " + avg);     }      //获取所有用户的年龄总和     private static void reduceSum() {         double sum = users.parallelStream().mapToInt(User::getAge)                 .reduce(0, (x, y) -> x + y); // 可以简写为.sum()          System.out.println("reduceSum User Age: " + sum);     } }
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