SQL经典面试题

发布于:2024-07-03 ⋅ 阅读:(15) ⋅ 点赞:(0)



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

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)

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)

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

-- 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)

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)

-- 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