使用Java Stream API高效分组与自定义映射JPA实体数据

public class RegistryEntity {
    private Long id;
    private String name;
    private String city;

    // 构造函数
    public RegistryEntity(Long id, String name, String city) {
        this.id = id;
        this.name = name;
        this.city = city;
    }

    // Getter方法
    public Long getId() { return id; }
    public String getName() { return name; }
    public String getCity() { return city; }

    // Setter方法 (根据需要添加)
    public void setId(Long id) { this.id = id; }
    public void setName(String name) { this.name = name; }
    public void setCity(String city) { this.city = city; }

    @Override
    public String toString() {
        return "RegistryEntity{" +
               "id=" + id +
               ", name='" + name + '\'' +
               ", city='" + city + '\'' +
               '}';
    }
}

{"New York":["John","Josh"],"Atlanta":["Paul", "Charles"],"Los Angeles":["Mark","Susan"]}

import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

public class DataProcessor {

    public Map<String, List<String>> findAllUsersGroupedByCity(List<RegistryEntity> items) {
        Map<String, List<String>> itemsGrouped = new HashMap<>();
        for (RegistryEntity s : items) {
            String city = s.getCity();
            String name = s.getName();

            // 如果城市已存在于Map中，则将姓名添加到对应的列表中
            if (itemsGrouped.containsKey(city)) {
                itemsGrouped.get(city).add(name);
            } else {
                // 如果城市不存在，则创建一个新的列表并放入Map
                List<String> namesForCity = new ArrayList<>();
                namesForCity.add(name);
                itemsGrouped.put(city, namesForCity);
            }
        }
        return itemsGrouped;
    }

    public static void main(String[] args) {
        List<RegistryEntity> entities = new ArrayList<>();
        entities.add(new RegistryEntity(1L, "John", "New York"));
        entities.add(new RegistryEntity(2L, "Paul", "Atlanta"));
        entities.add(new RegistryEntity(3L, "Mark", "Los Angeles"));
        entities.add(new RegistryEntity(4L, "Susan", "Los Angeles"));
        entities.add(new RegistryEntity(5L, "Josh", "New York"));
        entities.add(new RegistryEntity(6L, "Charles", "Atlanta"));

        DataProcessor processor = new DataProcessor();
        Map<String, List<String>> result = processor.findAllUsersGroupedByCity(entities);
        System.out.println(result);
        // 预期输出: {New York=[John, Josh], Atlanta=[Paul, Charles], Los Angeles=[Mark, Susan]}
    }
}

import java.util.List;
import java.util.Map;
import java.util.stream.Collectors;
import java.util.ArrayList; // 仅用于示例数据

public class StreamDataProcessor {

    public Map<String, List<String>> findAllUsersGroupedByCityStream(List<RegistryEntity> items) {
        return items.stream()
                    .collect(Collectors.groupingBy(
                        RegistryEntity::getCity, // 分组键：根据城市分组
                        Collectors.mapping(
                            RegistryEntity::getName, // 对每个分组内的实体，提取其姓名
                            Collectors.toList()      // 将提取出的姓名收集成一个列表
                        )
                    ));
    }

    public static void main(String[] args) {
        List<RegistryEntity> entities = new ArrayList<>();
        entities.add(new RegistryEntity(1L, "John", "New York"));
        entities.add(new RegistryEntity(2L, "Paul", "Atlanta"));
        entities.add(new RegistryEntity(3L, "Mark", "Los Angeles"));
        entities.add(new RegistryEntity(4L, "Susan", "Los Angeles"));
        entities.add(new RegistryEntity(5L, "Josh", "New York"));
        entities.add(new RegistryEntity(6L, "Charles", "Atlanta"));

        StreamDataProcessor processor = new StreamDataProcessor();
        Map<String, List<String>> result = processor.findAllUsersGroupedByCityStream(entities);
        System.out.println(result);
        // 预期输出: {New York=[John, Josh], Atlanta=[Paul, Charles], Los Angeles=[Mark, Susan]}
    }
}