Master Student Geographic Aggregation in Java with Nested Maps

Problem: Student Geographic Information Report

The task is to group a list of students by province, city, and district, then produce statistics such as the number of students per province, the city with the most students, and similar aggregations.

Define a simple Student class with fields for name, province, city, and district.

public class Student {
    String name;
    String province;
    String city;
    String district;

    public Student(String name, String province, String city, String district) {
        this.name = name;
        this.province = province;
        this.city = city;
        this.district = district;
    }
}

Use a three‑level nested Map<String, Map<String, Map<String, List<Student>>>> to store the hierarchy.

Map<String, Map<String, Map<String, List<Student>>>> geoMap = new HashMap<>();
for (Student s : students) {
    geoMap.computeIfAbsent(s.province, k -> new HashMap<>())
          .computeIfAbsent(s.city, k -> new HashMap<>())
          .computeIfAbsent(s.district, k -> new ArrayList<>())
          .add(s);
}

Example statistic: count students per province.

for (Map.Entry<String, Map<String, Map<String, List<Student>>>> provinceEntry : geoMap.entrySet()) {
    int total = 0;
    for (Map<String, List<Student>> cityMap : provinceEntry.getValue().values()) {
        for (List<Student> districtList : cityMap.values()) {
            total += districtList.size();
        }
    }
    System.out.println(provinceEntry.getKey() + " 省学生总数：" + total);
}

Find the city with the most students.

String maxCity = "";
int maxCount = 0;
for (Map<String, Map<String, List<Student>>> cityMap : geoMap.values()) {
    for (Map.Entry<String, Map<String, List<Student>>> cityEntry : cityMap.entrySet()) {
        int count = 0;
        for (List<Student> districtList : cityEntry.getValue().values()) {
            count += districtList.size();
        }
        if (count > maxCount) {
            maxCount = count;
            maxCity = cityEntry.getKey();
        }
    }
}
System.out.println("学生最多的城市是：" + maxCity + "，人数：" + maxCount);

The same pattern can be applied to real‑world scenarios such as order statistics for delivery services, sales distribution for e‑commerce, or enrollment analysis for education systems.