根据如下订单表orders
的字段和类型,按要求写出满足条件的SQL语句:
order_id | user_id | product_id | paid_time | is_refunded |
---|---|---|---|---|
1001 | 123 | A | 2023-10-24 11:14:07 | 0 |
1002 | 123 | B | 2023-10-25 18:03:24 | 0 |
1003 | 234 | C | 2023-11-11 00:03:32 | 1 |
1004 | 456 | D | 2023-11-11 01:10:01 | 0 |
1005 | 234 | A | 2023-12-20 16:09:50 | 1 |
1006 | 456 | B | 2023-12-21 17:24:12 | 0 |
1007 | 123 | A | 2023-12-31 15:20:21 | 0 |
1008 | 234 | C | 2023-12-31 19:13:30 | 0 |
字段说明:
- order_id:订单ID,String类型
- user_id:用户ID,String类型
- product_id:商品ID,String类型
- paid_time:付款时间,String类型
- is_refunded:是否退款,1表示退款,0表示未退款,Bigint类型
1、数据准备
sql
create table orders (
order_id string,
user_id string,
product_id string,
paid_time string,
is_refunded bigint
);
insert into orders values
('1001', '123', 'A', '2023-10-24 11:14:07', 0),
('1002', '123', 'B', '2023-10-25 18:03:24', 0),
('1003', '234', 'C', '2023-11-11 00:03:32', 1),
('1004', '456', 'D', '2023-11-11 01:10:01', 0),
('1005', '234', 'A', '2023-12-20 16:09:50', 1),
('1006', '456', 'B', '2023-12-21 17:24:12', 0),
('1007', '123', 'A', '2023-12-31 15:20:21', 0),
('1008', '234', 'C', '2023-12-31 19:13:30', 0);
select * from orders order by order_id;
2、题目描述与题解
1) 查询购买过每种商品的总人数(不限时间、退款与否)
sql
select product_id,count(distinct user_id) cnt from orders group by product_id
结果如下:
product_id | cnt |
---|---|
A | 2 |
D | 1 |
B | 2 |
C | 1 |
2) 查询2023-11-01及之后购买过商品C超过1次的用户(不限退款与否)
sql
select user_id,count(1) cnt
from orders where substr(paid_time, 0, 11) >= '2023-11-01' and product_id='C'
group by user_id having cnt>1
结果如下:
user_id | cnt |
---|---|
234 | 2 |
3) 查询2023-11-01及之后每天的总订单数和退款率
sql
-- 方式1
select substr(paid_time, 0, 11) dt,count(order_id) nums,count(case when is_refunded=1 then is_refunded end)/count(is_refunded) refund_rate
from orders where substr(paid_time, 0, 11) >= '2023-11-01'
group by substr(paid_time, 0, 11)
-- 方式2
select substr(paid_time, 0, 11) dt,count(order_id) nums,count(case when is_refunded=1 then 1 end)/count(is_refunded) refund_rate
from orders where substr(paid_time, 0, 11) >= '2023-11-01'
group by substr(paid_time, 0, 11)
-- 方式3(注意:if(is_refunded='1',1)不能正确计算)
select substr(paid_time, 0, 11) dt,count(order_id) nums,count(if(is_refunded=1, is_refunded))/count(is_refunded) refund_rate
from orders where substr(paid_time, 0, 11) >= '2023-11-01'
group by substr(paid_time, 0, 11)
结果如下:
dt | nums | refund_rate |
---|---|---|
2023-11-11 | 2 | 0.5 |
2023-12-31 | 2 | 0.0 |
2023-12-20 | 1 | 1.0 |
2023-12-21 | 1 | 0.0 |
4) 查询日退款率前3的商品及对应退款率(不限时间)
sql
select substr(paid_time, 0, 11) dt,count(if(is_refunded=1, is_refunded))/count(is_refunded) refund_rate
from orders group by substr(paid_time, 0, 11) order by refund_rate desc limit 3
结果如下:
dt | refund_rate |
---|---|
2023-12-20 | 1.0 |
2023-11-11 | 0.5 |
2023-10-24 | 0.0 |
5) 查询每个用户购买每种商品的最后一次未退款的记录(结果仅包含表中字段)
sql
-- 方式1
select order_id,user_id,product_id,paid_time,is_refunded from (
select *,row_number() over(partition by user_id,product_id order by paid_time desc) rk
from orders where is_refunded=0
) t where t.rk=1
-- 方式2
select order_id,user_id,product_id,paid_time,is_refunded from (
select *,first_value(paid_time) over(partition by user_id,product_id order by paid_time desc) last_paid_time
from orders where is_refunded=0
) t where t.paid_time=t.last_paid_time
结果如下:
order_id | user_id | product_id | paid_time | is_refunded |
---|---|---|---|---|
1008 | 234 | C | 2023-12-31 19:13:30 | 0 |
1006 | 456 | B | 2023-12-21 17:24:12 | 0 |
1004 | 456 | D | 2023-11-11 01:10:01 | 0 |
1007 | 123 | A | 2023-12-31 15:20:21 | 0 |
1002 | 123 | B | 2023-10-25 18:03:24 | 0 |
以上SQL若存在错误或者大家有更好的方案,欢迎交流和指正