java8-3-LambdaMapReduce例子
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("age > 12: ");
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("sex -> num");
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("sex -> name");
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("sex -> ageSum");
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("sex -> ageAvg");
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);
}
}
class User{
public int id;
public String name;
public int age;
public Sex gender;
public User(int id, String name, int age, Sex gender) {
this.id=id;
this.name=name;
this.age=age;
this.gender=gender;
}
public int getId() {
return id;
}
public void setId(int id) {
this.id = id;
}
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
public int getAge() {
return age;
}
public void setAge(int age) {
this.age = age;
}
public enum Sex{
FEMALE,
MALE;
}
public Sex getGender() {
return gender;
}
public void setGender(Sex gender) {
this.gender = gender;
}
}
class Averager implements IntConsumer
{
private int total = 0;
private int count = 0;
public double average() {
return count > 0 ? ((double) total)/count : 0;
}
public void accept(int i) { total += i; count++; }
public void combine(Averager other) {
total += other.total;
count += other.count;
}
}
