Java中的stream流分组示例详解

 // 按 department 字段分组
        Map<String, List<User>> groupedByDept = users.stream()
            .collect(Collectors.groupingBy(User::getDepartment));

Map<String, List<User>> grouped = users.stream()
    .collect(Collectors.groupingBy(
        user -> user.getDepartment() + "-" + user.getJobTitle()
    ));

Map<Map.Entry<String, String>, List<User>> grouped = users.stream()
    .collect(Collectors.groupingBy(
        user -> Map.entry(user.getDepartment(), user.getJobTitle())
    ));

// 定义一个记录类作为分组 key
record DeptJobKey(String department, String jobTitle) {}
Map<DeptJobKey, List<User>> grouped = users.stream()
    .collect(Collectors.groupingBy(
        user -> new DeptJobKey(user.getDepartment(), user.getJobTitle())
    ));

Map<String, Long> countByDept = users.stream()
    .collect(Collectors.groupingBy(
        User::getDepartment,
        Collectors.counting()  // 统计每个部门的用户数
    ));

Map<String, List<String>> namesByDept = users.stream()
    .collect(Collectors.groupingBy(
        User::getDepartment,
        Collectors.mapping(User::getName, Collectors.toList()) // 只提取 name 字段
    ));

Map<String, Optional<Integer>> maxAgeByDept = users.stream()
    .collect(Collectors.groupingBy(
        User::getDepartment,
        Collectors.mapping(User::getAge, Collectors.maxBy(Comparator.naturalOrder()))
    ));
// 或者更直观地使用 Collectors.maxBy / averagingInt 等
//或者使用 Collectors.summarizingInt 做综合统计
Map<String, IntSummaryStatistics> ageStatsByDept = users.stream()
    .collect(Collectors.groupingBy(
        User::getDepartment,
        Collectors.summarizingInt(User::getAge)  // 统计年龄：count, sum, min, max, avg
    ));

Map<String, List<User>> collect = javaList.stream().collect(Collectors.groupingBy(user -> {
            String id = user.getId();
            return (StringUtils.isEmpty(id)) ? "empty" : "notEmpty"; // 如果为 null，返回empty,不为空notEmpty
        }));