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电脑基础 · 2023年3月27日

[进阶] list 过滤 stream 的lambda进阶操作, 这一篇就够了

目录

1. list转化map基本操作

id最常用方式: 

-> 01  key-value值形式:

-> 02 id-> 对象本身

-> 03 id-> 对象本身的 lambda写法

->04  解决冲突的key

2. list计算操作

3. list转化泛型操作

4. List转成map的进阶操作

 ->4.1  有实体类的进阶操作(常用)

--->准备工作01 :  基础数据(User实体类)

--->4.1.1:  (1对1关系) 分组: 用户名-> 用户实体类对象User(String->T)

 --->4.1.2  (1对1关系) 用户名 -> 电话号(String-> String)

--->4.1.301:  (1对多) 分组01: 根据年龄分组  Integer-> List 

--->4.1.302:  (1对多) 分组01: 根据年龄分组  Integer-> List 方法二

--->4.1.4:  (1对多) 分组 根据年龄分出 年龄-> 用户 Integer -> List

-> 4.2 没有实体类的进阶操作

[待续未完....时间有限]

-> 5. 总结: 4整个的main方法

-> 5..1 不啰嗦 直接上代码

1. list转化map基本操作

id最常用方式: 

-> 01  key-value值形式:

Map<Integer,String>map = list.stream().collect(Collectors.toMap(User::getId,User::getRealName))

-> 02 id-> 对象本身

 Map<Integer,User> userMap3 = list.stream().collect(Collectors.toMap(User::getId, Function.identity()));

-> 03 id-> 对象本身的 lambda写法

Map<Integer,User> userMap2 = userList.stream().collect(Collectors.toMap(User::getId,User->User));

->04  解决冲突的key

Map<Integer,User> userMap4 = userList.stream().collect(Collectors.toMap(User::getId, Function.identity(),(key1,key2)->key2));

2. list计算操作

List<Long> testList = new ArrayList<>(Collections.nCopies(5, 0L));
        testList.set(0,1L);
        testList.set(1,2L);
        testList.set(2,3L);
        testList.set(3,4L);
        testList.set(4,5L);
        System.out.println("sum1 is " + testList.stream().reduce(0L, (a, b) -> a + b));
        // reduce根据初始值（参数1）和累积函数（参数2）依次对数据流进行操作，第一个值与初始值送入累积函数，后面计算结果和下一个数据流依次送入累积函数。
        System.out.println("sum2 is " + testList.stream().reduce(0L, Long::sum));
        System.out.println("sum3 is " + testList.stream().collect(Collectors.summingLong(Long::longValue)));
        // Collectors.summingLong()将流中所有元素视为Long类型，并计算所有元素的总和
        System.out.println("sum4 is " + testList.stream().mapToLong(Long::longValue).sum());
        System.out.println("***********************");
        List<Person> testList1 = new ArrayList<>(Collections.nCopies(5, new Person(1)));
        System.out.println("class sum1 is " + testList1.stream().map(e -> e.getAge()).reduce(0, (a,b) -> a + b));
        System.out.println("class sum2 is " + testList1.stream().map(e -> e.getAge()).reduce(0, Integer::sum));
        System.out.println("class sum3 is " + testList1.stream().collect(Collectors.summingInt(Person::getAge)));
        System.out.println("class sum4 is " + testList1.stream().map(e -> e.getAge()).mapToInt(Integer::intValue).sum());

3. list转化泛型操作

            List<User> list = userMapper.selectUserMessage(null);
            List<UserRespDTO> collect = list.stream().map(dto-> {
                UserRespDTO userRespDTO = new UserRespDTO();
                BeanUtils.copyProperties(dto, respDTO);
                return userRespDTO;
            }).collect(Collectors.toList());

4. List转成map的进阶操作

 ->4.1  有实体类的进阶操作(常用)

--->准备工作01 :  基础数据(User实体类)

import com.fasterxml.jackson.annotation.JsonFormat;
import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;
import lombok.experimental.Accessors;
import java.util.Date;
/**
 * 模拟用户实体类对象
 *
 * @author pzy
 * @version 0.1.0
 */
@Data
@NoArgsConstructor
@AllArgsConstructor
@Accessors(chain = true)
public class User {
    private String username;
    private Integer age;
    private String telephone;
    @JsonFormat(pattern = "yyyy-MM-dd HH:mm:ss", timezone = "GMT+8")
    private Date createTime;
}

---> 准备工作02: 

//1. 创建基础数据
        List<User> list = new ArrayList<>();
        User user1 = new User("张三", 33, "13345678913", new Date());
        User user2 = new User("李四", 44, "13345678914", new Date());
        User user3 = new User("王五", 55, "13345678915", new Date());
        User user4 = new User("李六", 55, "13345678916", new Date());
        list.add(user1);
        list.add(user2);
        list.add(user3);
        list.add(user4);

--->4.1.1:  (1对1关系) 分组: 用户名-> 用户实体类对象User(String->T)

Map<String, User> map1 = list.stream().collect(Collectors.toMap(User::getUsername, each -> each, (value1, value2) -> value1));
        System.out.println(JSON.toJSONString(map1));

 //{"李四":{"age":44,"createTime":1679536527360,"telephone":"13345678914","username":"李四"},"张三":{"age":33,"createTime":1679536527360,"telephone":"13345678913","username":"张三"},"李六":{"age":55,"createTime":1679536527360,"telephone":"13345678916","username":"李六"},"王五":{"age":55,"createTime":1679536527360,"telephone":"13345678915","username":"王五"}}

 --->4.1.2  (1对1关系) 用户名 -> 电话号(String-> String)

  Map<String,String> map2 =  list.stream().collect(Collectors.toMap(User::getUsername,User::getTelephone,(value1, value2) -> value1));
        System.out.println(JSON.toJSONString(map2));

//{"李四":"13345678914","张三":"13345678913","李六":"13345678916","王五":"13345678915"}

--->4.1.301:  (1对多) 分组01: 根据年龄分组  Integer-> List<T> 

Map<Integer, List<User>> map301 = list.stream().collect(Collectors.groupingBy(User::getAge));
        System.out.println(JSON.toJSONString(map301));
//{33:[{"age":33,"createTime":1679536527360,"telephone":"13345678913","username":"张三"}],55:[{"age":55,"createTime":1679536527360,"telephone":"13345678915","username":"王五"},{"age":55,"createTime":1679536527360,"telephone":"13345678916","username":"李六"}],44:[{"age":44,"createTime":1679536527360,"telephone":"13345678914","username":"李四"}]}

--->4.1.302:  (1对多) 分组01: 根据年龄分组  Integer-> List<T> 方法二

Map<Integer,List<User>> map302 =  list.stream().collect(Collectors.toMap(User::getAge, Collections::singletonList,(value1, value2) -> {
            List<User> union = new ArrayList<>(value1);
            union.addAll(value2);
            return union;
        }));
        System.out.println(JSON.toJSONString(map302));
//{33:[{"age":33,"createTime":1679536527360,"telephone":"13345678913","username":"张三"}],55:[{"age":55,"createTime":1679536527360,"telephone":"13345678915","username":"王五"},{"age":55,"createTime":1679536527360,"telephone":"13345678916","username":"李六"}],44:[{"age":44,"createTime":1679536527360,"telephone":"13345678914","username":"李四"}]}

--->4.1.4:  (1对多) 分组 根据年龄分出 年龄-> 用户 Integer -> List<String>

业务: 想查看每个年龄下都有谁(姓名即可)

Map<Integer,List<String>> map4 = list.stream().collect(Collectors.toMap(User::getAge,each->Collections.singletonList(each.getUsername()),(value1, value2) -> {
            List<String> usernameList = new ArrayList<>(value1);
            usernameList.addAll(value2);
            return usernameList;
        }));
        System.out.println(JSON.toJSONString(map4));
//{33:["张三"],55:["王五","李六"],44:["李四"]}

-> 4.2 没有实体类的进阶操作

[待续未完....时间有限]

-> 5. 总结: 4整个的main方法

-> 5..1 不啰嗦 直接上代码

 public static void main(String[] args) {
        //1. 创建基础数据
        List<User> list = new ArrayList<>();
        User user1 = new User("张三", 33, "13345678913", new Date());
        User user2 = new User("李四", 44, "13345678914", new Date());
        User user3 = new User("王五", 55, "13345678915", new Date());
        User user4 = new User("李六", 55, "13345678916", new Date());
        list.add(user1);
        list.add(user2);
        list.add(user3);
        list.add(user4);
        /*1. (1对1关系) 分组:  用户名-> 用户实体类对象User*/
        Map<String, User> map1 = list.stream().collect(Collectors.toMap(User::getUsername, each -> each, (value1, value2) -> value1));
        System.out.println(JSON.toJSONString(map1));
        //{"李四":{"age":44,"createTime":1679536527360,"telephone":"13345678914","username":"李四"},"张三":{"age":33,"createTime":1679536527360,"telephone":"13345678913","username":"张三"},"李六":{"age":55,"createTime":1679536527360,"telephone":"13345678916","username":"李六"},"王五":{"age":55,"createTime":1679536527360,"telephone":"13345678915","username":"王五"}}
        /*2. (1对1关系) 用户名 -> 电话号 */
        Map<String,String> map2 =  list.stream().collect(Collectors.toMap(User::getUsername,User::getTelephone,(value1, value2) -> value1));
        System.out.println(JSON.toJSONString(map2));
        //{"李四":"13345678914","张三":"13345678913","李六":"13345678916","王五":"13345678915"}
        /*301. (1对多关系) 分组01:  根据年龄分组  目的: 将年龄相等的进行分组 年龄->用户实体类 */
        Map<Integer, List<User>> map301 = list.stream().collect(Collectors.groupingBy(User::getAge));
        System.out.println(JSON.toJSONString(map301));
        //{33:[{"age":33,"createTime":1679536527360,"telephone":"13345678913","username":"张三"}],55:[{"age":55,"createTime":1679536527360,"telephone":"13345678915","username":"王五"},{"age":55,"createTime":1679536527360,"telephone":"13345678916","username":"李六"}],44:[{"age":44,"createTime":1679536527360,"telephone":"13345678914","username":"李四"}]}
        /*302. (1对多关系) 分组02:  根据年龄分组  目的: 将年龄相等的进行分组 年龄->用户实体类 */
        Map<Integer,List<User>> map302 =  list.stream().collect(Collectors.toMap(User::getAge, Collections::singletonList,(value1, value2) -> {
            List<User> union = new ArrayList<>(value1);
            union.addAll(value2);
            return union;
        }));
        System.out.println(JSON.toJSONString(map302));
        //{33:[{"age":33,"createTime":1679536527360,"telephone":"13345678913","username":"张三"}],55:[{"age":55,"createTime":1679536527360,"telephone":"13345678915","username":"王五"},{"age":55,"createTime":1679536527360,"telephone":"13345678916","username":"李六"}],44:[{"age":44,"createTime":1679536527360,"telephone":"13345678914","username":"李四"}]}
        /*4. (1对多关系) 分组 根据年龄分出 年龄-> 用户 业务: 想查看每个年龄下都有谁(姓名即可)*/
        Map<Integer,List<String>> map4 = list.stream().collect(Collectors.toMap(User::getAge,each->Collections.singletonList(each.getUsername()),(value1, value2) -> {
            List<String> usernameList = new ArrayList<>(value1);
            usernameList.addAll(value2);
            return usernameList;
        }));
        System.out.println(JSON.toJSONString(map4));
        //{33:["张三"],55:["王五","李六"],44:["李四"]}
    }

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