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Java實(shí)現(xiàn)List分組的常見(jiàn)方法詳解

更新時(shí)間：2025年12月23日 08:33:15 作者：悟能不能悟

這篇文章主要為大家詳細(xì)介紹了使用Java實(shí)現(xiàn)List分組的幾個(gè)常見(jiàn)方法,文中的示例代碼講解詳細(xì),感興趣的小伙伴可以跟隨小編一起學(xué)習(xí)一下

1. 使用 Stream API (Java 8+ 推薦)

1.1 按屬性分組

// 按對(duì)象屬性分組
List<Person> people = Arrays.asList(
    new Person("Alice", "IT"),
    new Person("Bob", "HR"),
    new Person("Charlie", "IT")
);

Map<String, List<Person>> byDept = people.stream()
    .collect(Collectors.groupingBy(Person::getDepartment));

// 復(fù)雜分組：按多個(gè)條件分組
Map<String, Map<Integer, List<Person>>> byDeptAndAge = people.stream()
    .collect(Collectors.groupingBy(
        Person::getDepartment,
        Collectors.groupingBy(Person::getAge)
    ));

1.2 分組后處理

// 分組并計(jì)數(shù)
Map<String, Long> countByDept = people.stream()
    .collect(Collectors.groupingBy(
        Person::getDepartment,
        Collectors.counting()
    ));

// 分組并求和
Map<String, Integer> sumByDept = people.stream()
    .collect(Collectors.groupingBy(
        Person::getDepartment,
        Collectors.summingInt(Person::getSalary)
    ));

// 分組后獲取最大/最小值
Map<String, Optional<Person>> maxByDept = people.stream()
    .collect(Collectors.groupingBy(
        Person::getDepartment,
        Collectors.maxBy(Comparator.comparing(Person::getSalary))
    ));

2. 使用傳統(tǒng)循環(huán)

Map<String, List<Person>> byDept = new HashMap<>();

for (Person person : people) {
    String dept = person.getDepartment();
    byDept.computeIfAbsent(dept, k -> new ArrayList<>())
          .add(person);
}

3. 使用第三方庫(kù)

3.1 Apache Commons Collections

// 添加依賴
// implementation 'org.apache.commons:commons-collections4:4.4'

MultiValuedMap<String, Person> byDept = new ArrayListValuedHashMap<>();
for (Person person : people) {
    byDept.put(person.getDepartment(), person);
}

3.2 Google Guava

// 添加依賴
// implementation 'com.google.guava:guava:31.1-jre'

Multimap<String, Person> byDept = ArrayListMultimap.create();
for (Person person : people) {
    byDept.put(person.getDepartment(), person);
}

// 或者使用流式方式
ImmutableListMultimap<String, Person> grouped = Multimaps.index(
    people, Person::getDepartment
);

4. 完整示例

import java.util.*;
import java.util.stream.Collectors;

class Person {
    private String name;
    private String department;
    private int age;
    private int salary;
    
    // 構(gòu)造方法、getter、setter
    
    public static void main(String[] args) {
        List<Person> people = Arrays.asList(
            new Person("Alice", "IT", 25, 5000),
            new Person("Bob", "HR", 30, 4500),
            new Person("Charlie", "IT", 28, 5500),
            new Person("David", "HR", 35, 4800)
        );
        
        // 1. 按部門分組
        Map<String, List<Person>> byDept = people.stream()
            .collect(Collectors.groupingBy(Person::getDepartment));
        
        // 2. 按部門統(tǒng)計(jì)平均工資
        Map<String, Double> avgSalaryByDept = people.stream()
            .collect(Collectors.groupingBy(
                Person::getDepartment,
                Collectors.averagingDouble(Person::getSalary)
            ));
        
        // 3. 按年齡段分組
        Map<String, List<Person>> byAgeGroup = people.stream()
            .collect(Collectors.groupingBy(p -> {
                if (p.getAge() < 30) return "青年";
                else if (p.getAge() < 40) return "中年";
                else return "資深";
            }));
    }
}

5. 自定義分組邏輯

// 自定義分組器
Collector<Person, ?, Map<String, List<Person>>> customGrouping = 
    Collector.of(
        HashMap::new,  // 供應(yīng)者
        (map, person) -> {  // 累加器
            String key = person.getDepartment() + "-" + 
                        (person.getAge() / 10 * 10);  // 按10歲分段
            map.computeIfAbsent(key, k -> new ArrayList<>())
               .add(person);
        },
        (map1, map2) -> {  // 合并器（用于并行流）
            map2.forEach((key, value) -> 
                map1.merge(key, value, (list1, list2) -> {
                    list1.addAll(list2);
                    return list1;
                })
            );
            return map1;
        }
    );

Map<String, List<Person>> customGrouped = people.stream()
    .collect(customGrouping);