在SQL日常开发中,条件判断是不可或缺的基础技能。CASE WHEN作为SQL中灵活的条件表达式,在逻辑判断、行转列、多条件分组统计等场景下都极为实用。接下来快速梳理其两种核心写法,并介绍几个最常用的实战案例。
一、简单CASE WHEN函数
CASE SCORE WHEN 'A' THEN '优' ELSE '不及格' END # 使用 IF 函数进行替换 IF(SCORE = 'A', '优', '不及格')
THEN后的值与ELSE后的值类型必须一致,否则会引发错误。
例如:
CASE SCORE WHEN ‘A’ THEN ‘优’ ELSE 0 END 中,‘优’和0数据类型不匹配,将导致如下错误:
[Err] ORA-00932: 数据类型不一致: 应为 CHAR, 但却获得 NUMBER
简单CASE WHEN函数仅适用于简单的业务需求,而CASE WHEN条件表达式写法则更加灵活强大。
二、CASE WHEN条件表达式函数
类似JAVA中的IF ELSE语句。
语法格式:
CASE WHEN condition THEN result [WHEN...THEN...] ELSE result END
SQL示例:
CASE
WHEN SCORE = 'A' THEN '优'
WHEN SCORE = 'B' THEN '良'
WHEN SCORE = 'C' THEN '中'
ELSE '不及格' END
# 等同于
CASE score
WHEN 'A' THEN '优'
WHEN 'B' THEN '良'
WHEN 'C' THEN '中'
ELSE '不及格' END
condition是一个返回布尔类型的表达式。
如果表达式结果为true,则整个函数返回对应result的值;
如果所有表达式均为false,则返回ELSE后的result值;若省略ELSE子句,则返回NULL。
三、常用场景
前言
students表结构(DDL)
-- auto-generated definition
create table students
(
stu_code varchar(10) null,
stu_name varchar(10) null,
stu_sex int null,
stu_score int null
);
students表数据(DML)
# 其中stu_sex字段,0表示男生,1表示女生。
INSERT INTO students (stu_code, stu_name, stu_sex, stu_score) VALUES ('xm', '小明', 0, 88);
INSERT INTO students (stu_code, stu_name, stu_sex, stu_score) VALUES ('xl', '夏磊', 0, 55);
INSERT INTO students (stu_code, stu_name, stu_sex, stu_score) VALUES ('xf', '晓峰', 0, 45);
INSERT INTO students (stu_code, stu_name, stu_sex, stu_score) VALUES ('xh', '小红', 1, 89);
INSERT INTO students (stu_code, stu_name, stu_sex, stu_score) VALUES ('xn', '小妮', 1, 77);
INSERT INTO students (stu_code, stu_name, stu_sex, stu_score) VALUES ('xy', '小一', 1, 99);
INSERT INTO students (stu_code, stu_name, stu_sex, stu_score) VALUES ('xs', '小时', 1, 45);
energy_test表结构(DDL)
-- auto-generated definition
create table energy_test
(
e_code varchar(2) null,
e_value decimal(5, 2) null,
e_type int null
);
energy_test表数据(DML)
# 其中,E_TYPE表示能耗类型,0表示水耗,1表示电耗,2表示热耗
INSERT INTO energy_test (e_code, e_value, e_type) VALUES ('北京', 28.50, 0);
INSERT INTO energy_test (e_code, e_value, e_type) VALUES ('北京', 23.50, 1);
INSERT INTO energy_test (e_code, e_value, e_type) VALUES ('北京', 28.12, 2);
INSERT INTO energy_test (e_code, e_value, e_type) VALUES ('北京', 12.30, 0);
INSERT INTO energy_test (e_code, e_value, e_type) VALUES ('北京', 15.46, 1);
INSERT INTO energy_test (e_code, e_value, e_type) VALUES ('上海', 18.88, 0);
INSERT INTO energy_test (e_code, e_value, e_type) VALUES ('上海', 16.66, 1);
INSERT INTO energy_test (e_code, e_value, e_type) VALUES ('上海', 19.99, 0);
INSERT INTO energy_test (e_code, e_value, e_type) VALUES ('上海', 10.05, 0);
p_price表结构(DDL)
-- auto-generated definition
create table p_price
(
p_price decimal(5, 2) null comment '价格',
p_level int null comment '等级',
p_limit int null comment '阈值'
) comment '电能耗单价表';
p_price表数据(DML)
INSERT INTO test.p_price (p_price, p_level, p_limit) VALUES (1.20, 0, 10); INSERT INTO test.p_price (p_price, p_level, p_limit) VALUES (1.70, 1, 30); INSERT INTO test.p_price (p_price, p_level, p_limit) VALUES (2.50, 2, 50);
user_col_comments表结构(DDL)
-- auto-generated definition
create table user_col_comments
(
column_name varchar(50) null comment '列名',
comment varchar(100) null comment '列的备注'
);
user_col_comments表数据(DML)
INSERT INTO test.user_col_comments (column_name, comment) VALUES ('SHI_SHI_CODE', '设施编号');
INSERT INTO test.user_col_comments (column_name, comment) VALUES ('SHUI_HAO', '水耗');
INSERT INTO test.user_col_comments (column_name, comment) VALUES ('RE_HAO', '热耗');
INSERT INTO test.user_col_comments (column_name, comment) VALUES ('YAN_HAO', '盐耗');
INSERT INTO test.user_col_comments (column_name, comment) VALUES ('OTHER', '其他');
场景1:不同状态展示为不同的值
现有分数score,要求:score<60显示“不及格”,score>=60显示“及格”,score>=80显示“优秀”。

# 有分数score,score<60返回不及格,score>=60返回及格,score>=80返回优秀
SELECT
stu_name,
(CASE WHEN stu_score < 60 THEN '不及格'
WHEN stu_score >= 60 AND stu_score < 80 THEN '及格'
WHEN stu_score >= 80 THEN '优秀'
ELSE '异常' END) AS REMARK
FROM students;
注意:若需判断score是否为NULL,切勿写成WHEN score = NULL THEN ‘缺席考试’,这是错误用法。正确写法如下:
CASE WHEN score IS NULL THEN '缺席考试' ELSE '正常' END
场景2:统计不同状态下的值
老师需要统计班级中男生和女生的人数,以及男生中及格人数和女生中及格人数,要求使用一条SQL输出。其中stu_sex字段,0表示男生,1表示女生。

SELECT sum(CASE WHEN STU_SEX = 0 THEN 1 ELSE 0 END) AS MALE_COUNT, sum(CASE WHEN STU_SEX = 1 THEN 1 ELSE 0 END) AS FEMALE_COUNT, sum(CASE WHEN STU_SCORE >= 60 AND STU_SEX = 0 THEN 1 ELSE 0 END) AS MALE_PASS, sum(CASE WHEN STU_SCORE >= 60 AND STU_SEX = 1 THEN 1 ELSE 0 END) AS FEMALE_PASS FROM students;
输出结果如下:

注意事项:
此处使用 SUM 而非 COUNT。
THEN 1 ELSE 0 的位置不可随意更改,否则会造成统计错误,例如:
sum(CASE WHEN stu_sex = 0 THEN '1' ELSE '0' END) AS '男性', 改变了 sum(CASE WHEN stu_sex = 0 THEN '0' ELSE '1' END) AS '女性':
字符 ‘0’ 与数值 0 在SUM函数中效果相同,但建议保持数值类型以避免隐式转换问题。
场景3:配合聚合函数做统计
现需统计各个城市的水耗、电耗、热耗总量,使用一条SQL语句输出。能耗表中E_TYPE含义:0水耗,1电耗,2热耗。

select e_code,
sum(case when e_type = 0 then e_value else 0 end) as '水耗',
sum(case when e_type = 1 then e_value else 0 end) as '电耗',
sum(case when e_type = 2 then e_value else 0 end) as '热耗'
from energy_test
group by e_code;
输出结果如下:

场景4:CASE WHEN中使用子查询
根据城市用电量计算用电成本。假设电价分三档,根据能耗值匹配对应价格:当能耗值≤10时,使用P_LEVEL=0的价格;能耗值在10~30之间时,使用P_LEVEL=1的价格,依此类推。

energy_test 表中我修改了e_type为1的两条数据的e_value。

select e_code, e_value,
(CASE WHEN e_value <= (SELECT p_limit FROM p_price WHERE p_level = 0)
THEN (SELECT p_price FROM p_price WHERE p_level = 0)
WHEN e_value > (SELECT p_limit FROM p_price WHERE p_level = 0) AND e_value <= (SELECT p_limit FROM p_price WHERE p_level = 1)
THEN (SELECT P_PRICE FROM p_price WHERE P_LEVEL = 1)
WHEN e_value > (SELECT p_limit FROM p_price WHERE p_level = 1) AND e_value <= (SELECT p_limit FROM p_price WHERE p_level = 2)
THEN (SELECT p_price FROM p_price WHERE P_LEVEL = 2) end ) as price
from energy_test
where e_type = 1;
输出结果如下:

场景5:经典行转列,结合max聚合函数
行转列时,SUM在此场景中并非必须,但SELECT后必须包含聚合函数,不能直接省略。也可以使用MAX或MIN代替。

select
max(case when column_name = 'SHI_SHI_CODE' then comment else ''end) as SHI_SHI_CODE_COMMENT,
max(case when column_name = 'SHUI_HAO' then comment else ''end) as SHUI_HAO_COMMENT,
max(case when column_name = 'RE_HAO' then comment else ''end) as RE_HAO_COMMENT,
max(case when column_name = 'YAN_HAO' then comment else ''end) as YAN_HAO_COMMENT,
max(case when column_name = 'OTHER' then comment else '' end) as OTHER_COMMENT
from user_col_comments;
输出结果如下:

