Collectors.groupingBy根据一个或多个属性对集合中的项目进行分组

数据准备：

  1. @Data
  2. public class Product {
  3.     private Long id;
  4.     private Integer num;
  5.     private BigDecimal price;
  6.     private String name;
  7.     private String category;
  9.     public Product() {
  10.     }
  12.     public Product(Long id, Integer num, BigDecimal price, String name, String category) {
  13.         this.id = id;
  14.         this.num = num;
  15.         this.price = price;
  16.         this.name = name;
  17.         this.category = category;
  18.     }
  20. }

分组

按照类目分组：

  1. Map<String, List<Product>> prodMap= prodList.stream().collect(Collectors.groupingBy(Product::getCategory));
  3. //{"啤酒":[{"category":"啤酒","id":4,"name":"青岛啤酒","num":3,"price":10},{"category":"啤酒","id":5,"name":"百威啤酒","num":10,"price":15}],"零食":[{"category":"零食","id":1,"name":"面包","num":1,"price":15.5},{"category":"零食","id":2,"name":"饼干","num":2,"price":20},{"category":"零食","id":3,"name":"月饼","num":3,"price":30}]}

按照几个属性拼接分组：

  1. Map<String, List<Product>> prodMap = prodList.stream().collect(Collectors.groupingBy(item -> item.getCategory() + "_" + item.getName()));
  3. //{"零食_月饼":[{"category":"零食","id":3,"name":"月饼","num":3,"price":30}],"零食_面包":[{"category":"零食","id":1,"name":"面包","num":1,"price":15.5}],"啤酒_百威啤酒":[{"category":"啤酒","id":5,"name":"百威啤酒","num":10,"price":15}],"啤酒_青岛啤酒":[{"category":"啤酒","id":4,"name":"青岛啤酒","num":3,"price":10}],"零食_饼干":[{"category":"零食","id":2,"name":"饼干","num":2,"price":20}]}

根据不同条件分组

  1. Map<String, List<Product>> prodMap= prodList.stream().collect(Collectors.groupingBy(item -> {
  2.     if(item.getNum() < 3) {
  3.         return "3";
  4.     }else {
  5.         return "other";
  6.     }
  7. }));
  9. //{"other":[{"category":"零食","id":3,"name":"月饼","num":3,"price":30},{"category":"啤酒","id":4,"name":"青岛啤酒","num":3,"price":10},{"category":"啤酒","id":5,"name":"百威啤酒","num":10,"price":15}],"3":[{"category":"零食","id":1,"name":"面包","num":1,"price":15.5},{"category":"零食","id":2,"name":"饼干","num":2,"price":20}]}

多级分组

要实现多级分组，我们可以使用一个由双参数版本的Collectors.groupingBy工厂方法创 建的收集器，它除了普通的分类函数之外，还可以接受collector类型的第二个参数。那么要进 行二级分组的话，我们可以把一个内层groupingBy传递给外层groupingBy，并定义一个为流 中项目分类的二级标准。

  1. Map<String, Map<String, List<Product>>> prodMap= prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.groupingBy(item -> {
  2.     if(item.getNum() < 3) {
  3.         return "3";
  4.     }else {
  5.         return "other";
  6.     }
  7. })));
  8. //{"啤酒":{"other":[{"category":"啤酒","id":4,"name":"青岛啤酒","num":3,"price":10},{"category":"啤酒","id":5,"name":"百威啤酒","num":10,"price":15}]},"零食":{"other":[{"category":"零食","id":3,"name":"月饼","num":3,"price":30}],"3":[{"category":"零食","id":1,"name":"面包","num":1,"price":15.5},{"category":"零食","id":2,"name":"饼干","num":2,"price":20}]}}

按子组收集数据

求总数
  1. Map<String, Long> prodMap = prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.counting()));
  3. //{"啤酒":2,"零食":3}

求和
  1. Map<String, Integer> prodMap = prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.summingInt(Product::getNum)));
  3. //{"啤酒":13,"零食":6}

排序
  1. Map<String, Integer> prodMap = prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.summingInt(Product::getNum)));
  3. prodMap.entrySet().stream().sorted(Map.Entry.<String, Integer>comparingByValue().reversed())
  4.          .forEachOrdered(System.out::println);
  6. //{"啤酒":13,"零食":6}

把收集器的结果转换为另一种类型
  1. Map<String, Product> prodMap = prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.collectingAndThen(Collectors.maxBy(Comparator.comparingInt(Product::getNum)), Optional::get)));
  3. //{"啤酒":{"category":"啤酒","id":5,"name":"百威啤酒","num":10,"price":15},"零食":{"category":"零食","id":3,"name":"月饼","num":3,"price":30}}

联合其他收集器
  1. Map<String, Set<String>> prodMap = prodList.stream().collect(Collectors.groupingBy(Product::getCategory, Collectors.mapping(Product::getName, Collectors.toSet())));
  3. //{"啤酒":["青岛啤酒","百威啤酒"],"零食":["面包","饼干","月饼"]}

案例：

  1. import java.math.BigDecimal;
  2. import java.sql.Timestamp;
  4. public class Student {
  5.     private String name;
  6.     private Integer age;
  7.     private String score;
  8.     private Integer gender;
  9.     private BigDecimal height;
  10.     private Timestamp startTime;
  11.     private Timestamp endTime;
  13.     public String getName() {
  14.         return name;
  15.     }
  17.     public void setName(String name) {
  18.         this.name = name;
  19.     }
  21.     public Integer getAge() {
  22.         return age;
  23.     }
  25.     public void setAge(Integer age) {
  26.         this.age = age;
  27.     }
  29.     public String getScore() {
  30.         return score;
  31.     }
  33.     public void setScore(String score) {
  34.         this.score = score;
  35.     }
  37.     public Integer getGender() {
  38.         return gender;
  39.     }
  41.     public void setGender(Integer gender) {
  42.         this.gender = gender;
  43.     }
  45.     public BigDecimal getHeight() {
  46.         return height;
  47.     }
  49.     public void setHeight(BigDecimal height) {
  50.         this.height = height;
  51.     }
  53.     public Timestamp getStartTime() {
  54.         return startTime;
  55.     }
  57.     public void setStartTime(Timestamp startTime) {
  58.         this.startTime = startTime;
  59.     }
  61.     public Timestamp getEndTime() {
  62.         return endTime;
  63.     }
  65.     public void setEndTime(Timestamp endTime) {
  66.         this.endTime = endTime;
  67.     }
  69.     public Student(String name, Integer age) {
  70.         this.name = name;
  71.         this.age = age;
  72.     }
  74.     public Student(String name, Integer age, String score) {
  75.         this.name = name;
  76.         this.age = age;
  77.         this.score = score;
  78.     }
  80.     public Student(String name, Integer age, String score, Integer gender) {
  81.         this.name = name;
  82.         this.age = age;
  83.         this.score = score;
  84.         this.gender = gender;
  85.     }
  87.     public Student(String name, Integer age, String score, Integer gender, BigDecimal height) {
  88.         this.name = name;
  89.         this.age = age;
  90.         this.score = score;
  91.         this.gender = gender;
  92.         this.height = height;
  93.     }
  95.     public Student(String name, Integer age, String score, Integer gender, BigDecimal height, Timestamp startTime, Timestamp endTime) {
  96.         this.name = name;
  97.         this.age = age;
  98.         this.score = score;
  99.         this.gender = gender;
  100.         this.height = height;
  101.         this.startTime = startTime;
  102.         this.endTime = endTime;
  103.     }
  105.     @Override
  106.     public String toString() {
  107.         return "Student{" +
  108.                 "name='" + name + '\'' +
  109.                 ", age=" + age +
  110.                 ", score='" + score + '\'' +
  111.                 ", gender=" + gender +
  112.                 ", height=" + height +
  113.                 ", startTime=" + startTime +
  114.                 ", endTime=" + endTime +
  115.                 '}';
  116.     }
  117. }
  1. import org.apache.commons.lang3.StringUtils;
  3. import javax.swing.tree.TreeModel;
  4. import java.io.Serializable;
  5. import java.math.BigDecimal;
  6. import java.sql.Timestamp;
  7. import java.time.LocalDateTime;
  8. import java.util.*;
  9. import java.util.function.BinaryOperator;
  10. import java.util.function.Function;
  11. import java.util.stream.Collectors;
  12. import java.util.stream.Stream;
  14. import static java.util.stream.Collectors.counting;
  15. import static java.util.stream.Collectors.toCollection;
  17. public class groupingBy {
  18.     public static void main(String[] args) {
  21.         ArrayList<Student> list = new ArrayList<>();
  22.         list.add(new Student("王一", 21, "11", 1, new BigDecimal("193.0"), Timestamp.valueOf(LocalDateTime.now()), Timestamp.valueOf(LocalDateTime.now().plusMinutes(15L))));
  23.         list.add(new Student("郑二", 22, "22", 0, new BigDecimal("171.0"), Timestamp.valueOf(LocalDateTime.now()), Timestamp.valueOf(LocalDateTime.now().plusHours(16L))));
  24.         list.add(new Student("张三", 23, "33", 1, new BigDecimal("180.1"), Timestamp.valueOf(LocalDateTime.now()), Timestamp.valueOf(LocalDateTime.now().plusSeconds(500L))));
  25.         list.add(new Student("李四", 24, "44", 0, new BigDecimal("183.2"), Timestamp.valueOf(LocalDateTime.now()), Timestamp.valueOf(LocalDateTime.now().plusMinutes(18L))));
  26.         list.add(new Student("赵五", 25, "55", 1, new BigDecimal("178.3"), Timestamp.valueOf(LocalDateTime.now()), Timestamp.valueOf(LocalDateTime.now().plusMinutes(13L))));
  27.         list.add(new Student("韩六", 26, "88", 0, new BigDecimal("169.4"), Timestamp.valueOf(LocalDateTime.now()), Timestamp.valueOf(LocalDateTime.now().plusMinutes(1L))));
  28.         list.add(new Student("田七", 27, "77", 1, new BigDecimal("173.5"), Timestamp.valueOf(LocalDateTime.now()), Timestamp.valueOf(LocalDateTime.now().plusMinutes(17L))));
  29.         list.add(new Student("卢八", 28, "88", 0, new BigDecimal("159.6"), Timestamp.valueOf(LocalDateTime.now()), Timestamp.valueOf(LocalDateTime.now().plusMinutes(1L))));
  30. //        list.add(new Student("钱九", 29, null, 1, new BigDecimal("180.1")));
  31. //        list.add(new Student("魏十", null, "99", null, null));
  32. //        list.add(new Student("肖十一", null, "", null, null));
  33. //        list.add(new Student("柘十二", null, null, null, null));
  35.         //1根据性别进行分组
  36.         //1.1 为null的数据不需要，直接过滤
  37.         Map<Integer, List<Student>> collect = list.stream()
  38.                 .filter(a -> a.getGender() != null)
  39.                 .collect(Collectors.groupingBy(Student::getGender));
  40.         //1.2 需要保留为null的数据
  41.         Map<? extends Serializable, List<Student>> collect1 = list.stream()
  42.                 .collect(Collectors.groupingBy(a -> {
  43.                     if (a.getGender() == null) {
  44.                         return "null";
  45.                     }
  46.                     return a.getGender();
  47.                 }));
  49.         //2根据性别分组后，再根据分数分组，>=60:A <60:B 为null的数据保留
  50.         Map<? extends Serializable, Map<String, List<Student>>> collect2 = list.stream().collect(Collectors.groupingBy(a -> {
  51.             if (a.getGender() == null) {
  52.                 return "null";
  53.             }
  54.             return a.getGender();
  55.         }, Collectors.groupingBy(b -> {
  56.             String score = b.getScore();
  57.             if (score == null) {
  58.                 return "B";
  59.             } else {
  60.                 return score.compareTo("60") >= 0 ? "A" : "B";
  61.             }
  62.         })));
  64.         //3按照gender和height分组，TreeMap默认按key升序 TreeMap key不能为null
  65.         TreeMap<String, List<Student>> collect3 = list.stream().collect(Collectors.groupingBy(a -> {
  66.                     if (a.getGender() == null || a.getHeight() == null) {
  67.                         return "null";
  68.                     }
  69.                     return a.getGender() + "->" + a.getHeight();
  70.                 }
  71.                 , TreeMap::new
  72.                 , Collectors.toList()));
  75.         //统计gender为1和0的人数
  76.         Map<? extends Serializable, Long> collect4 = list.stream()
  77.                 .collect(Collectors.groupingBy(a -> {
  78.                             if (a.getGender() == null) {
  79.                                 return "mix";
  80.                             }
  81.                             return a.getGender();
  82.                         }
  83.                         , counting()));
  84.         //按gender分组后，统计60为分界的人数
  85.         Map<String, Map<String, Long>> collect5 = list.stream().collect(
  86.                 Collectors.groupingBy(//gender分组
  87.                         a -> {
  88.                             if (a.getGender() == null) {
  89.                                 return "null";//gender为null
  90.                             }
  91.                             return a.getGender() == 1 ? "M" : "F";
  92.                         }
  93.                         , Collectors.groupingBy(//60为分界
  94.                                 b -> {
  95.                                     String score = b.getScore();
  96.                                     if (score == null) {
  97.                                         return "null";
  98.                                     } else {
  99.                                         return score.compareTo("60") >= 0 ? "A" : "B";
  100.                                     }
  101.                                 }
  102.                                 , counting()//统计
  103.                         )
  104.                 ));
  105.         //统计60分界的男女各多少
  106.         Map<String, Map<Integer, Long>> collect6 = list.stream()
  107.                 .filter(a -> StringUtils.isNoneBlank(a.getScore()))//过滤score为""和null的数据
  108.                 .filter(b -> b.getGender() != null)//过滤gender为null的数据
  109.                 .collect(
  110.                         Collectors.groupingBy(
  111.                                 c -> c.getScore().compareTo("60") >= 0 ? "G" : "B",//以60分组
  112.                                 Collectors.groupingBy(
  113.                                         Student::getGender,//以gender分组
  114.                                         counting()//统计
  115.                                 )
  116.                         )
  117.                 );
  119.         //统计男女各年龄之和
  120.         Map<Integer, Integer> collect7 = list.stream()
  121.                 .filter(a -> a.getAge() != null || a.getGender() != null)
  122.                 .collect(Collectors.groupingBy(Student::getGender,
  123.                         Collectors.summingInt(Student::getAge)));
  125.         //分组元素存储在自定义集合
  126.         Map<Integer, TreeSet<Integer>> collect8 = list.stream()
  127.                 .filter(a -> a.getGender() != null)
  128.                 .collect(Collectors.groupingBy(Student::getGender,
  129.                         Collectors.mapping(Student::getAge, toCollection(TreeSet::new))));
  131.         //计算男女中最高的分数
  132.         Map<Integer, Student> collect9 = list.stream().filter(a -> a.getGender() != null)
  133.                 .collect(Collectors.groupingBy(
  134.                                 Student::getGender, Collectors.collectingAndThen(Collectors.maxBy(Comparator.comparing(Student::getScore)), Optional::get)
  135.                         )
  136.                 );
  137.         //计算男女中最低的分数
  138.         Map<Integer, Student> collect10 = list.stream().filter(a -> a.getGender() != null)
  139.                 .collect(Collectors.toMap(Student::getGender, Function.identity(), BinaryOperator.minBy(Comparator.comparing(Student::getScore)))
  140.                 );
  143.         // //计算男女中最高的分数 分数相同去用时最短
  144.         Map<Integer, Student> collect11 = list.stream().filter(a -> a.getGender() != null)
  145.                 .collect(Collectors.toMap(
  146.                                 Student::getGender,//性别
  147.                                 Function.identity(),//t->t
  148.                                 BinaryOperator.maxBy(
  149.                                         Comparator.comparing(Student::getScore)//分数比较
  150.                                                 .thenComparing(b -> b.getEndTime().getTime() - b.getStartTime().getTime()//分数相同，按时间比较
  151.                                                         , Comparator.reverseOrder()))//外层用的max，故此处排序取反
  152.                         )
  153.                 );
  156.         //相同的存放在list中
  157.         TreeMap<Integer, Student> collect12 = list.stream().filter(a -> a.getGender() != null)
  158.                 .collect(Collectors.toMap(
  159.                                 Student::getGender,
  160.                                 Function.identity(),
  161.                                 BinaryOperator.maxBy(
  162.                                         Comparator.comparing(Student::getScore)
  163.                                                 .thenComparing(b -> b.getEndTime().getTime() - b.getStartTime().getTime()
  164.                                                         , Comparator.reverseOrder())
  166.                                 ),
  167.                                 TreeMap::new
  168.                         )
  169.                 );
  170.         HashMap<Integer, List<Student>> hashMap = new HashMap<>();
  171.         collect12.forEach((k, v) -> {
  172.             Map<Integer, ArrayList<Student>> listMap = list.stream()
  173.                     .filter(a ->
  174.                             k.equals(a.getGender())
  175.                                     && v.getScore().equals(a.getScore())
  176.                                     && (a.getEndTime().getTime() - a.getStartTime().getTime()) == (v.getEndTime().getTime() - v.getStartTime().getTime())
  177.                     )
  178.                     .collect(Collectors.toMap(
  179.                             Student::getGender,
  180.                             t -> {
  181.                                 List<Student> students = Collections.singletonList(t);
  182.                                 return new ArrayList<>(students);
  183.                             },
  184.                             (v1, v2) -> {
  185.                                 v2.addAll(v1);
  186.                                 return v2;
  187.                             })
  188.                     );
  189.             hashMap.putAll(listMap);
  190.         });
  193.         //分数最高用时最短
  194.         Optional<Student> max = list.stream().max(Comparator
  195.                 .comparing(Student::getScore)
  196.                 .thenComparing(a -> a.getEndTime().getTime() - a.getStartTime().getTime(),
  197.                         Comparator.reverseOrder())
  198.         );
  199.         Student student = max.isPresent() ? max.get() : null;
  201.         //最大值 分数 用时
  202.         Student student1 = list.stream().max(Comparator
  203.                 .comparing(Student::getScore)
  204.                 .thenComparing(a -> a.getEndTime().getTime() - a.getStartTime().getTime(),
  205.                         Comparator.reverseOrder())
  206.         ).orElse(null);
  209.         //男女各组的平均分数
  210.         Map<Integer, Double> collect13 = list.stream()
  211.                 .filter(a -> a.getGender() != null)
  212.                 .filter(b -> StringUtils.isNoneBlank(b.getScore()))
  213.                 .collect(Collectors.groupingBy(Student::getGender,
  214.                         Collectors.averagingDouble(a -> Double.parseDouble(a.getScore()))));
  215.     }
  216. }