Java8 stream流之分组 groupingBy 的使用
作者:互联网
众所周知,使用stream流可以让我们的代码看上去很简洁,现在我们实战使用一下stream的分组与分区。
准备用到的数据类
public class Student{
//年级
private String grade;
//班级
private String classNumber;
//姓名
private String name;
//年龄
private int age;
//地址
private String address;
//数学成绩
private int mathScores;
//语文成绩
private int chainessScores;
}
添加数据
Student student1 = new Student("701","张三",16,"北京",78,90);
Student student2 = new Student("700","李四",17,"北京",78,90);
Student student3 = new Student("703","王五",16,"上海",78,90);
Student student4 = new Student("701","赵六",16,"上海",78,90);
Student student5 = new Student("700","钱七",18,"",78,90);
Student student6 = new Student("701","老八",17,"",78,90);
//这是一个高二年级的成绩单
List<Student> students = Stream.of(student1,student2,student3,student4,student5,student6).collect(Collectors.toList());
按照班级分组
Map<String, List<Student>> collect = students.stream().collect(Collectors.groupingBy(Student::getClassNumber));
System.out.println(JSON.toJSONString(collect));
//{"700":[{"age":17,"chainessScores":90,"classNumber":"700","mathScores":78,"name":"李四"},{"age":18,"chainessScores":90,"classNumber":"700","mathScores":78,"name":"钱七"}],
//"701":[{"age":16,"chainessScores":90,"classNumber":"701","mathScores":78,"name":"张三"},{"age":16,"chainessScores":90,"classNumber":"701","mathScores":78,"name":"赵六"},{"age":17,"chainessScores":90,"classNumber":"701","mathScores":78,"name":"老八"}],
//"703":[{"age":16,"chainessScores":90,"classNumber":"703","mathScores":78,"name":"王五"}]}
按照班级分组得到每个班级的同学姓名
Map<String, List<String>> collect = students.stream().collect(Collectors.groupingBy(Student::getClassNumber, Collectors.mapping(Student::getName, Collectors.toList())));
System.out.println(JSON.toJSONString(collect));
//{"700":["李四","钱七"],"701":["张三","赵六","老八"],"703":["王五"]}
统计每个班级人数
Map<String, Long> collect = students.stream().collect(Collectors.groupingBy(Student::getClassNumber, Collectors.counting()));
System.out.println(JSON.toJSONString(collect));
//{"700":2,"701":3,"703":1}
求每个班级的数学平均成绩
Map<String, Double> collect = students.stream().collect(Collectors.groupingBy(Student::getClassNumber, Collectors.averagingDouble(Student::getMathScores)));
System.out.println(JSON.toJSONString(collect));
//{"700":65.0,"701":61.0,"703":82.0}
按班级分组求每个同学的总成绩
Map<String, Map<String, Integer>> collect = students.stream().collect(Collectors.groupingBy(Student::getClassNumber, Collectors.toMap(Student::getName, student -> student.getMathScores() + student.getChainessScores())));
System.out.println(JSON.toJSONString(collect));
//{"700":{"钱七":150,"李四":160},"701":{"张三":168,"老八":148,"赵六":137},"703":{"王五":172}}
嵌套分组,先按班级分组,再按年龄分组
Map<String, Map<Integer, List<Student>>> collect = students.stream().collect(Collectors.groupingBy(Student::getClassNumber, Collectors.groupingBy(Student::getAge)));
分组后得到一个线程安全的ConcurrentMap
ConcurrentMap<String, List<Student>> collect = students.stream().collect(Collectors.groupingByConcurrent(Student::getClassNumber));
加上排序来一波
根据年龄分组并小到大排序,TreeMap默认为按照key升序
TreeMap<Integer, List<String>> collect = students.stream().collect(Collectors.groupingBy(Student::getAge, TreeMap::new, Collectors.mapping(Student::getName, Collectors.toList())));
System.out.println(JSON.toJSONString(collect));
//{16:["张三","王五","赵六"],17:["李四","老八"],18:["钱七"]}
根据年龄分组并大到小排序,因为TreeMap默认为按照key升序,所以排完顺序再反转一下就OK了
TreeMap<Integer, List<String>> collect = students.stream().collect(Collectors.groupingBy(Student::getAge, TreeMap::new, Collectors.mapping(Student::getName, Collectors.toList())));
Map<Integer, List<String>> collect2 = collect.descendingMap();
System.out.println(JSON.toJSONString(collect2));
//{18:["钱七"],17:["李四","老八"],16:["张三","王五","赵六"]}
标签:groupingBy,Collectors,流之,collect,Student,90,stream,78 来源: https://blog.csdn.net/sugelachao/article/details/117736155