来看看Java stream提供的分组 - groupingBy

一. 基本用法 - 接收一个参数

它接收一个函数作为参数，也就是说可以传lambda表达式进来。

    public static <T, K> Collector<T, ?, Map<K, List<T>>>
    groupingBy(Function<? super T, ? extends K> classifier) {
        return groupingBy(classifier, toList());
UserList.stream().collect(Collectors.groupingBy( 函数 ))，返回的是一个map，key为分组的值，value为list，包含组内的元素。
1. 简单类型分组
    @Test
    public void test01() {
        List<Integer> intList = Arrays.asList(1, 2, 3, 4, 5, 6, 7, 1, 2, 3);
        Map<Integer, List<Integer>> collect = intList.stream().collect(Collectors.groupingBy(e -> e%2));
        System.out.println(collect);
2. 对象，按一个属性分组
这里用到的User::getEducation，class名字+双冒号+方法名，等同于lambda表达式e -> e.getEduction()
    @Test
    public void test02() {
        List<User> userList = Arrays.asList(new User(0, "zhangsan", "zhangsan@qq.com", 20, "High School"),
                new User(1, "lisi", "lisi@qq.com", 20, "High School"),
                new User(2, "wangwu", "wangwu@qq.com", 20, "High School"),
                new User(3, "lilei", "lilei@qq.com", 25, "Graduate"),
                new User(4, "hanmeimei", "hanmeimei@qq.com", 26, "Graduate"),
                new User(5, "lucy", "lucy@qq.com", 25, "Graduate"));
        Map<String, List<User>> collect = userList.stream().collect(Collectors.groupingBy(User::getEducation));
        System.out.println(collect);
3. 对象，按多个属性分组
嵌套分组 (groupingBy 接收两个参数)
        Map<Integer, Map<String, List<User>>> collect =
                userList.stream().collect(Collectors.groupingBy(User::getAge, Collectors.groupingBy(User::getEducation)));
        System.out.println(collect.get(20).get("High School"));
4. 按整个对象分组
用User::new方法进行分组，它会调用构造方法public User(User user)，并依赖于hashcode和equals方法来判断对象是否相等，进而进行分组。如果有一些特殊的逻辑对对象进行分组，可以重写hashcode和equals方法。
Map<User, List<User>> collect = userList.stream().collect(Collectors.groupingBy(User::new));
    public User(User user) {
        this.id = user.id;
        this.name = user.name;
        this.email = user.email;
        this.age = user.age;
        this.education = user.education;
5. 处理null key
        Map<String, List<User>> collect = userList.stream().collect(Collectors.groupingBy(e -> {
            if (e.getEducation() == null || "".equals(e.getEducation())) {
                return "";
            return e.getEducation();
二. 接收两个参数 - 对groupingby结果集进一步处理
    public static <T, K, A, D>
    Collector<T, ?, Map<K, D>> groupingBy(Function<? super T, ? extends K> classifier,
                                          Collector<? super T, A, D> downstream) {
        return groupingBy(classifier, HashMap::new, downstream);
1. 计算平均值
        Map<String, Double> collect = 
                userList.stream().collect(Collectors.groupingBy(User::getEducation, Collectors.averagingInt(User::getAge)));
{High School=20.0, Graduate=25.333333333333332}
2. count
        Map<String, Long> collect =
                userList.stream().collect(Collectors.groupingBy(User::getEducation, Collectors.counting()));
{High School=3, Graduate=3}
3. 求和
        Map<String, Integer> collect =
                userList.stream().collect(Collectors.groupingBy(User::getEducation, Collectors.summingInt(User::getAge)));
{High School=60, Graduate=76}
三. 接收三个参数
添加了对结果Map的生成方式，默认是HashMap
    public static <T, K, D, A, M extends Map<K, D>>
    Collector<T, ?, M> groupingBy(Function<? super T, ? extends K> classifier,
                                  Supplier<M> mapFactory,
                                  Collector<? super T, A, D> downstream)
例，用TreeMap对key进行排序：
        Map<String, Set<String>> namesByEdu =
                userList.stream().collect(Collectors.groupingBy(User::getEducation, TreeMap::new, mapping(User::getName,Collectors.toSet())));