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SQL(面试实战05)

1. 工作日各时段叫车量、等待接单时间和调度时间

用户打车记录表tb_get_car_record

iduidcityevent_timeend_timeorder_id
1107北京2021-09-20 11:00:002021-09-20 11:00:309017
2108北京2021-09-20 21:00:002021-09-20 21:00:409008
3108北京2021-09-20 18:59:302021-09-20 19:01:009018
4102北京2021-09-21 08:59:002021-09-21 09:01:009002
5106北京2021-09-21 17:58:002021-09-21 18:01:009006
6103北京2021-09-22 07:58:002021-09-22 08:01:009003
7104北京2021-09-23 07:59:002021-09-23 08:01:009004
8103北京2021-09-24 19:59:202021-09-24 20:01:009019
9101北京2021-09-24 08:28:102021-09-24 08:30:009011

(uid 用户ID, city-城市, event_time-打车时间, end_time-打车结束时间, order_id-订单号)

打车订单表tb_get_car_order

idorder_iduiddriver_idorder_timestart_timefinish_timemileagefaregrade
190171072132021-09-20 11:00:302021-09-20 11:02:102021-09-20 11:31:0011385
290081082042021-09-20 21:00:402021-09-20 21:03:002021-09-20 21:31:0013.2384
390181082142021-09-20 19:01:002021-09-20 19:04:502021-09-20 19:21:0014385
490021022022021-09-21 09:01:002021-09-21 09:06:002021-09-21 09:31:001041.55
590061062032021-09-21 18:01:002021-09-21 18:09:002021-09-21 18:31:00825.54
690071072032021-09-22 11:01:002021-09-22 11:07:002021-09-22 11:31:009.9305
790031032022021-09-22 08:01:002021-10-22 08:15:002021-10-22 08:31:001141.54
890041042022021-09-23 08:01:002021-09-23 08:13:002021-09-23 08:31:007.5224
990051052022021-09-23 10:01:002021-09-23 10:13:002021-09-23 10:31:009295
1090191032022021-09-24 20:01:002021-09-24 20:11:002021-09-24 20:51:0010394
1190111012112021-09-24 08:30:002021-09-24 08:31:002021-09-24 08:54:0010355

(order_id-订单号, uid-用户ID, driver_id-司机ID, order_time-接单时间, start_time-开始计费的上车时间, finish_time-订单完成时间, mileage-行驶里程数, fare-费用, grade-评分)

场景逻辑说明

  • 用户提交打车请求后,在用户打车记录表生成一条打车记录,订单号-order_id设为null
  • 当有司机接单时,在打车订单表生成一条订单,填充接单时间-**order_time 及其左边的字段,上车时间-****start_time及其右边的字段全部为null**,并把订单号-****order_id接单时间-*order_time*end_time-**打车结束时间)写入打车记录表;若一直无司机接单,超时或中途用户主动取消打车,则记录打车结束时间-**end_time
  • 若乘客上车前,乘客或司机点击取消订单,会将打车订单表对应订单的finish_time-****订单完成时间填充为取消时间,其余字段设为null
  • 当司机接上乘客时,填充订单表中该订单的**start_time-**上车时间
  • 当订单完成时填充订单完成时间、里程数、费用;评分设为null,在用户给司机打1~5星评价后填充。

问题:统计周一到周五各时段的叫车量、平均等待接单时间和平均调度时间。全部以event_time-开始打车时间为时段划分依据,平均等待接单时间和平均调度时间均保留1位小数,平均调度时间仅计算完成了的订单,结果按叫车量升序排序。

输出示例

示例数据的输出结果如下:

periodget_car_numavg_wait_timeavg_dispatch_time
工作时间10.51.7
休息时间10.72.3
晚高峰32.17.3
早高峰42.28.0

解释:订单9017打车开始于11点整,属于工作时间,等待时间30秒,调度时间为1分40秒,示例数据中工作时间打车订单就一个,平均等待时间0.5分钟,平均调度时间1.7分钟。

示例1
DROP TABLE IF EXISTS tb_get_car_record,tb_get_car_order;
CREATE TABLE tb_get_car_record (
    id INT PRIMARY KEY AUTO_INCREMENT COMMENT '自增ID',
    uid INT NOT NULL COMMENT '用户ID',
    city VARCHAR(10) NOT NULL COMMENT '城市',
    event_time datetime COMMENT '打车时间',
    end_time datetime COMMENT '打车结束时间',
    order_id INT COMMENT '订单号'
) CHARACTER SET utf8 COLLATE utf8_bin;

CREATE TABLE tb_get_car_order (
    id INT PRIMARY KEY AUTO_INCREMENT COMMENT '自增ID',
    order_id INT NOT NULL COMMENT '订单号',
    uid INT NOT NULL COMMENT '用户ID',
    driver_id INT NOT NULL COMMENT '司机ID',
    order_time datetime COMMENT '接单时间',
    start_time datetime COMMENT '开始计费的上车时间',
    finish_time datetime COMMENT '订单结束时间',
    mileage FLOAT COMMENT '行驶里程数',
    fare FLOAT COMMENT '费用',
    grade TINYINT COMMENT '评分'
) CHARACTER SET utf8 COLLATE utf8_bin;

INSERT INTO tb_get_car_record(uid, city, event_time, end_time, order_id) VALUES
 (107, '北京', '2021-09-20 11:00:00', '2021-09-20 11:00:30', 9017),
 (108, '北京', '2021-09-20 21:00:00', '2021-09-20 21:00:40', 9008),
 (108, '北京', '2021-09-20 18:59:30', '2021-09-20 19:01:00', 9018),
 (102, '北京', '2021-09-21 08:59:00', '2021-09-21 09:01:00', 9002),
 (106, '北京', '2021-09-21 17:58:00', '2021-09-21 18:01:00', 9006),
 (103, '北京', '2021-09-22 07:58:00', '2021-09-22 08:01:00', 9003),
 (104, '北京', '2021-09-23 07:59:00', '2021-09-23 08:01:00', 9004),
 (103, '北京', '2021-09-24 19:59:20', '2021-09-24 20:01:00', 9019),
 (101, '北京', '2021-09-24 08:28:10', '2021-09-24 08:30:00', 9011);

INSERT INTO tb_get_car_order(order_id, uid, driver_id, order_time, start_time, finish_time, mileage, fare, grade) VALUES
 (9017, 107, 213, '2021-09-20 11:00:30', '2021-09-20 11:02:10', '2021-09-20 11:31:00', 11, 38, 5),
 (9008, 108, 204, '2021-09-20 21:00:40', '2021-09-20 21:03:00', '2021-09-20 21:31:00', 13.2, 38, 4),
 (9018, 108, 214, '2021-09-20 19:01:00', '2021-09-20 19:04:50', '2021-09-20 19:21:00', 14, 38, 5),
 (9002, 102, 202, '2021-09-21 09:01:00', '2021-09-21 09:06:00', '2021-09-21 09:31:00', 10.0, 41.5, 5),
 (9006, 106, 203, '2021-09-21 18:01:00', '2021-09-21 18:09:00', '2021-09-21 18:31:00', 8.0, 25.5, 4),
 (9007, 107, 203, '2021-09-22 11:01:00', '2021-09-22 11:07:00', '2021-09-22 11:31:00', 9.9, 30, 5),
 (9003, 103, 202, '2021-09-22 08:01:00', '2021-09-22 08:15:00', '2021-09-22 08:31:00', 11.0, 41.5, 4),
 (9004, 104, 202, '2021-09-23 08:01:00', '2021-09-23 08:13:00', '2021-09-23 08:31:00', 7.5, 22, 4),
 (9005, 105, 202, '2021-09-23 10:01:00', '2021-09-23 10:13:00', '2021-09-23 10:31:00', 9, 29, 5),
 (9019, 103, 202, '2021-09-24 20:01:00', '2021-09-24 20:11:00', '2021-09-24 20:51:00', 10, 39, 4),
 (9011, 101, 211, '2021-09-24 08:30:00', '2021-09-24 08:31:00', '2021-09-24 08:54:00', 10, 35, 5);
输出:

工作时间|1|0.5|1.7
休息时间|1|0.7|2.3
晚高峰|3|2.1|7.3
早高峰|4|2.2|8.0

思路
统计周一到周五各时段的叫车量、平均等待接单时间和平均调度时间
(开始打车到司机接单为等待接单时间,从司机接单到上车为调度时间)
1.用户打车记录表tb_get_car_record 连接 打车订单表tb_get_car_order
from tb_get_car_order join tb_get_car_record using(order_id)
2.获取出车时间分类,订单id,等待接单时间、调度时间,
select 
	case 
	when date_format(event_time,"%H:%i:%s") between "07:00:00" and "08:59:59"    then "早高峰"
	when date_format(event_time,"%H:%i:%s")	between "09:00:00" and "16:59:59"    then "工作时间"
	when date_format(event_time,"%H:%i:%s") between "17:00:00" and "19:59:59"   then "晚高峰"
	else "休息时间"
	end 
	period,
	order_id,
	timestampdiff(second,event_time,end_time) wait_time,
	timestampdiff(second,order_time,start_time) dispatch_time
3.按照不同时段分组
group by period
4.获取 不同时段,叫车量,平均等待接单时间和平均调度时间
select 
	period,
	count(order_id) get_car_num,
	round(avg(wait_time)/60,1) avg_wait_time,
	round(avg(dispatch_time)/60,1) avg_dispatch_time
题解
select 
	period,
	count(order_id) get_car_num,
	round(avg(wait_time)/60,1) avg_wait_time,
	round(avg(dispatch_time)/60,1) avg_dispatch_time
from 
(
	select 
	case 
	when date_format(event_time,"%H:%i:%s")
    between "07:00:00" and "08:59:59"    then "早高峰"
	when date_format(event_time,"%H:%i:%s")	
    between "09:00:00" and "16:59:59"    then "工作时间"
	when date_format(event_time,"%H:%i:%s") 
    between "17:00:00" and "19:59:59"   then "晚高峰"
	else "休息时间"
	end 
	period,
	order_id,
	timestampdiff(second,event_time,end_time) wait_time,
	timestampdiff(second,order_time,start_time) dispatch_time
	from tb_get_car_order
	join tb_get_car_record using(order_id)
	where dayofweek(order_time) between 2 and 6
)t
group by period
order by get_car_num

2. 各城市最大同时等车人数

用户打车记录表tb_get_car_record

iduidcityevent_timeend_timeorder_id
1108北京2021-10-20 08:00:002021-10-20 08:00:409008
2118北京2021-10-20 08:00:102021-10-20 08:00:459018
3102北京2021-10-20 08:00:302021-10-20 08:00:509002
4106北京2021-10-20 08:05:412021-10-20 08:06:009006
5103北京2021-10-20 08:05:502021-10-20 08:07:109003
6104北京2021-10-20 08:01:012021-10-20 08:01:209004
7105北京2021-10-20 08:01:152021-10-20 08:01:309019
8101北京2021-10-20 08:28:102021-10-20 08:30:009011

(uid-用户ID, city-城市, event_time-打车时间, end_time-打车结束时间, order_id-订单号)

打车订单表tb_get_car_order

idorder_iduiddriver_idorder_timestart_timefinish_timemileagefaregrade
190081082042021-10-20 08:00:402021-10-20 08:03:002021-10-20 08:31:0013.2384
290181082142021-10-20 08:00:452021-10-20 08:04:502021-10-20 08:21:0014385
390021022022021-10-20 08:00:502021-10-20 08:06:002021-10-20 08:31:001041.55
490061062062021-10-20 08:06:002021-10-20 08:09:002021-10-20 08:31:00825.54
590031032032021-10-20 08:07:102021-10-20 08:15:002021-10-20 08:31:001141.54
690041042042021-10-20 08:01:202021-10-20 08:13:002021-10-20 08:31:007.5224
790191052052021-10-20 08:01:302021-10-20 08:11:002021-10-20 08:51:0010394
890111012112021-10-20 08:30:002021-10-20 08:31:002021-10-20 08:54:0010355

(order_id-订单号, uid-用户ID, driver_id-司机ID, order_time-接单时间, start_time-开始计费的上车时间, finish_time-订单完成时间, mileage-行驶里程数, fare-费用, grade-评分)

场景逻辑说明

  • 用户提交打车请求后,在用户打车记录表生成一条打车记录,订单号-order_id设为null
  • 当有司机接单时,在打车订单表生成一条订单,填充接单时间-order_time及其左边的字段,上车时间及其右边的字段全部为null,并把订单号和接单时间(打车结束时间)写入打车记录表;若一直无司机接单、超时或中途用户主动取消打车,则记录打车结束时间。
  • 若乘客上车前,乘客或司机点击取消订单,会将打车订单表对应订单的订单完成时间-finish_time填充为取消时间,其余字段设为null
  • 当司机接上乘客时,填充打车订单表中该订单的上车时间start_time
  • 当订单完成时填充订单完成时间、里程数、费用;评分设为null,在用户给司机打1~5星评价后填充。

问题:请统计各个城市在2021年10月期间,单日中最大的同时等车人数。

: 等车指从开始打车起,直到取消打车、取消等待或上车前的这段时间里用户的状态。

如果同一时刻有人停止等车,有人开始等车,等车人数记作先增加后减少。

结果按各城市最大等车人数升序排序,相同时按城市升序排序。

输出示例

示例结果如下

citymax_wait_uv
北京5

解释:由打车订单表可以得知北京2021年10月20日有8条打车记录,108号乘客从08:00:00等到08:03:00,118号乘客从08:00:10等到08:04:50…,由此得知08:02:00秒时刻,共有5人在等车。

示例1
DROP TABLE IF EXISTS tb_get_car_record,tb_get_car_order;
CREATE TABLE tb_get_car_record (
    id INT PRIMARY KEY AUTO_INCREMENT COMMENT '自增ID',
    uid INT NOT NULL COMMENT '用户ID',
    city VARCHAR(10) NOT NULL COMMENT '城市',
    event_time datetime COMMENT '打车时间',
    end_time datetime COMMENT '打车结束时间',
    order_id INT COMMENT '订单号'
) CHARACTER SET utf8 COLLATE utf8_bin;

CREATE TABLE tb_get_car_order (
    id INT PRIMARY KEY AUTO_INCREMENT COMMENT '自增ID',
    order_id INT NOT NULL COMMENT '订单号',
    uid INT NOT NULL COMMENT '用户ID',
    driver_id INT NOT NULL COMMENT '司机ID',
    order_time datetime COMMENT '接单时间',
    start_time datetime COMMENT '开始计费的上车时间',
    finish_time datetime COMMENT '订单结束时间',
    mileage FLOAT COMMENT '行驶里程数',
    fare FLOAT COMMENT '费用',
    grade TINYINT COMMENT '评分'
) CHARACTER SET utf8 COLLATE utf8_bin;

INSERT INTO tb_get_car_record(uid, city, event_time, end_time, order_id) VALUES
 (108, '北京', '2021-10-20 08:00:00', '2021-10-20 08:00:40', 9008),
 (108, '北京', '2021-10-20 08:00:10', '2021-10-20 08:00:45', 9018),
 (102, '北京', '2021-10-20 08:00:30', '2021-10-20 08:00:50', 9002),
 (106, '北京', '2021-10-20 08:05:41', '2021-10-20 08:06:00', 9006),
 (103, '北京', '2021-10-20 08:05:50', '2021-10-20 08:07:10', 9003),
 (104, '北京', '2021-10-20 08:01:01', '2021-10-20 08:01:20', 9004),
 (103, '北京', '2021-10-20 08:01:15', '2021-10-20 08:01:30', 9019),
 (101, '北京', '2021-10-20 08:28:10', '2021-10-20 08:30:00', 9011);

INSERT INTO tb_get_car_order(order_id, uid, driver_id, order_time, start_time, finish_time, mileage, fare, grade) VALUES
 (9008, 108, 204, '2021-10-20 08:00:40', '2021-10-20 08:03:00', '2021-10-20 08:31:00', 13.2, 38, 4),
 (9018, 108, 214, '2021-10-20 08:00:45', '2021-10-20 08:04:50', '2021-10-20 08:21:00', 14, 38, 5),
 (9002, 102, 202, '2021-10-20 08:00:50', '2021-10-20 08:06:00', '2021-10-20 08:31:00', 10.0, 41.5, 5),
 (9006, 106, 203, '2021-10-20 08:06:00', '2021-10-20 08:09:00', '2021-10-20 08:31:00', 8.0, 25.5, 4),
 (9003, 103, 202, '2021-10-20 08:07:10', '2021-10-20 08:15:00', '2021-10-20 08:31:00', 11.0, 41.5, 4),
 (9004, 104, 202, '2021-10-20 08:01:20', '2021-10-20 08:13:00', '2021-10-20 08:31:00', 7.5, 22, 4),
 (9019, 103, 202, '2021-10-20 08:01:30', '2021-10-20 08:11:00', '2021-10-20 08:51:00', 10, 39, 4),
 (9011, 101, 211, '2021-10-20 08:30:00', '2021-10-20 08:31:00', '2021-10-20 08:54:00', 10, 35, 5);
思路
请统计各个城市在202110月期间,单日中最大的同时等车人数。
方式一:
- 状态1:司机接单前取消,则没有生成order_id,这种情况 order_id IS NULL 记录end_time
- 状态2:司机接单后取消,则没有上车时间,start_time IS NULL 记录 finish_time
- 状态3:正常上车,记录start_time,start_time IS NOT NULL
 SELECT city,event_time uv_time,1 AS uv 
 FROM  tb_get_car_record #进入等车状态
		UNION ALL
SELECT city,end_time uv_time,-1 AS uv 
FROM  tb_get_car_record
WHERE order_id IS NULL #接单前取消
		UNION ALL
SELECT city,IFNULL(start_time,finish_time) uv_time,-1 AS uv 
FROM tb_get_car_order 
LEFT JOIN tb_get_car_record USING(order_id)#接单后取消或上车

方式二:
  SELECT city, event_time as at_time, 1 as wait_uv 
  FROM tb_get_car_record
        UNION ALL
  SELECT city,
  COALESCE(start_time, finish_time, end_time) as at_time, -1 as wait_uv
  FROM tb_get_car_record
  LEFT JOIN tb_get_car_order USING(order_id)
  
2.筛选时间窗:WHERE DATE_FORMAT(at_time, "%Y-%m") = "2021-10"
3.定义按城市和日期分区按时刻排序的窗口(先增加后减少,所以uv倒排):
 SUM(wait_uv) over(PARTITION BY city, DATE(at_time) ORDER BY at_time, wait_uv DESC) as current_max
4.计算当前最大等车人数:
SUM(wait_uv) over(wd_city_date) as current_max
5.按城市分组:
GROUP BY city
6.计算各城市最大等待人数:
MAX(current_max) as max_wait_uv
题解
方式一:
select 
	city,max(wait_uv)max_wait_uv
from 
(
	select city,date(time)days,sum(uv)over(partition by city,date(time) order by time,uv desc) wait_uv
	from 
	(	
        #进入等车状态
	SELECT city,event_time time,1 AS uv 
    FROM  tb_get_car_record 
		UNION ALL
	SELECT city,end_time time,-1 AS uv 
    FROM  tb_get_car_record 
    WHERE order_id IS NULL #接单前取消
		UNION ALL
	SELECT city,IFNULL(start_time,finish_time) uv_time,-1 AS uv
    FROM tb_get_car_order
    LEFT JOIN tb_get_car_record USING(order_id)#接单后取消或上车
	)t_city_wait
	where date_format(time,"%Y-%m")="2021-10"
)t_max_city_wait
group by city
order by max_wait_uv,city

方式二:
SELECT city, MAX(current_max) as max_wait_uv
FROM (
    SELECT city, SUM(wait_uv) 
    over(PARTITION BY city, DATE(at_time) ORDER BY at_time, wait_uv DESC) as current_max
    FROM (
        SELECT city, event_time as at_time, 1 as wait_uv 
        FROM tb_get_car_record
        UNION ALL
        SELECT city, COALESCE(start_time, finish_time, end_time) as at_time, -1 as wait_uv
        FROM tb_get_car_record
        LEFT JOIN tb_get_car_order USING(order_id)
    ) as t_uv_at_time
    WHERE DATE_FORMAT(at_time, "%Y-%m") = "2021-10"
 --   WINDOW wd_city_date as (PARTITION BY city, DATE(at_time) ORDER BY at_time, wait_uv DESC)
) as t_city_cur_max
GROUP BY city
ORDER BY max_wait_uv, city;


方式三:
WITH t1 AS(
    #每个城市等车瞬时UV
	SELECT city,
    SUM(uv)OVER(PARTITION BY city ORDER BY uv_time,uv DESC) AS uv_cnt 
    FROM (
    SELECT city,event_time uv_time,1 AS uv
    FROM  tb_get_car_record #进入等车状态
		UNION ALL
	SELECT city,end_time uv_time,-1 AS uv
    FROM  tb_get_car_record WHERE order_id IS NULL #接单前取消
		UNION ALL
	SELECT city,IFNULL(start_time,finish_time) uv_time,-1 AS uv 
    FROM tb_get_car_order
     LEFT JOIN tb_get_car_record USING(order_id)#接单后取消或上车
    )AS t WHERE DATE_FORMAT(uv_time,'%Y%m')='202110' #2021年10月
)
SELECT city,MAX(uv_cnt) max_wait_uv FROM t1 GROUP BY citY ORDER BY max_wait_uv,citY;#排序先按照uv升序,uv一样按照城市升序

拓展
coalesce(expression_1, expression_2, ...,expression_n)函数

在学习sql时,发现coalesce函数,和三则运算表达式有些类似,不过它又好像跟三则表达式有些不同,它跟java 的泛型也有些类似,参数个数可以动态传递,类似这样的用法在mysql函数中是很少见的。

语法
coalesce(expression_1, expression_2, ...,expression_n)依次参考各参数表达式,遇到非null值即停止并返回该值。如果所有的表达式都是空值,最终将返回一个空值。使用coalesce在于大部分包含空值的表达式最终将返回空值


select 
coalesce(null,null,1,2);

输出:
1

3. 某宝店铺的SPU数量

11月结束后,小牛同学需要对其在某宝的网店就11月份用户交易情况和产品情况进行分析以更好的经营小店。

已知产品情况表product_tb如下(其中,item_id指某款号的具体货号,style_id指款号,tag_price表示标签价格,inventory指库存量):

item_idstyle_idtag_priceinventory
A001A10020
A002A12030
A003A20015
B001B13018
B002B15022
B003B12510
B004B15512
C001C26025
C002C28018

请你统计每款的SPU(货号)数量,并按SPU数量降序排序,以上例子的输出结果如下:

style_idSPU_num
B4
A3
C2
示例1
drop table if exists product_tb;
CREATE TABLE product_tb(
item_id char(10) NOT NULL,
style_id char(10) NOT NULL,
tag_price int(10) NOT NULL,
inventory int(10) NOT NULL
);
INSERT INTO product_tb VALUES('A001', 'A', 100,  20);
INSERT INTO product_tb VALUES('A002', 'A', 120, 30);
INSERT INTO product_tb VALUES('A003', 'A', 200,  15);
INSERT INTO product_tb VALUES('B001', 'B', 130, 18);
INSERT INTO product_tb VALUES('B002', 'B', 150,  22);
INSERT INTO product_tb VALUES('B003', 'B', 125, 10);
INSERT INTO product_tb VALUES('B004', 'B', 155,  12);
INSERT INTO product_tb VALUES('C001', 'C', 260, 25);
INSERT INTO product_tb VALUES('C002', 'C', 280,  18);
输出

B|4
A|3
C|2

题解
select style_id,count(*) SPU_num
from product_tb
group by style_id
order by SPU_num desc

4.某宝店铺的实际销售额与客单价

11月结束后,小牛同学需要对其在某宝的网店就11月份用户交易情况和产品情况进行分析以更好的经营小店。

已知11月份销售数据表sales_tb如下(其中,sales_date表示销售日期,user_id指用户编号,item_id指货号,sales_num表示销售数量,sales_price表示结算金额):

sales_dateuser_iditem_idsales_numsales_price
2021-11-011A001190
2021-11-012A0022220
2021-11-012B0011120
2021-11-023C0012500
2021-11-024B0011120
2021-11-035C0011240
2021-11-036C0021270
2021-11-047A0031180
2021-11-048B0021140
2021-11-049B0011125
2021-11-0510B0031120
2021-11-0510B0041150
2021-11-0510A0031180
2021-11-0611B0031120
2021-11-0610B0041150

请你统计实际总销售额与客单价(人均付费,总收入/总用户数,结果保留两位小数),以上例子的输出结果如下:

sales_totalper_trans
2725247.73

示例1

drop table if exists sales_tb;
CREATE TABLE sales_tb(
sales_date date NOT NULL,
user_id int(10) NOT NULL,
item_id char(10) NOT NULL,
sales_num int(10) NOT NULL,
sales_price int(10) NOT NULL
);

INSERT INTO sales_tb VALUES('2021-11-1', 1, 'A001',  1, 90);
INSERT INTO sales_tb VALUES('2021-11-1', 2, 'A002',  2, 220);
INSERT INTO sales_tb VALUES('2021-11-1', 2, 'B001',  1, 120);
INSERT INTO sales_tb VALUES('2021-11-2', 3, 'C001',  2, 500);
INSERT INTO sales_tb VALUES('2021-11-2', 4, 'B001',  1, 120);
INSERT INTO sales_tb VALUES('2021-11-3', 5, 'C001',  1, 240);
INSERT INTO sales_tb VALUES('2021-11-3', 6, 'C002',  1, 270);
INSERT INTO sales_tb VALUES('2021-11-4', 7, 'A003',  1, 180);
INSERT INTO sales_tb VALUES('2021-11-4', 8, 'B002',  1, 140);
INSERT INTO sales_tb VALUES('2021-11-4', 9, 'B001',  1, 125);
INSERT INTO sales_tb VALUES('2021-11-5', 10, 'B003',  1, 120);
INSERT INTO sales_tb VALUES('2021-11-5', 10, 'B004',  1, 150);
INSERT INTO sales_tb VALUES('2021-11-5', 10, 'A003',  1, 180);
INSERT INTO sales_tb VALUES('2021-11-6', 11, 'B003',  1, 120);
INSERT INTO sales_tb VALUES('2021-11-6', 10, 'B004',  1, 150);
输出

2725|247.73

题解
select 
sum(sales_price)sales_total,
round(sum(sales_price)/count(distinct user_id),2)per_trans
from sales_tb
where month(sales_date)="11"

5. 某宝店铺折扣率

11月结束后,小牛同学需要对其在某宝的网店就11月份用户交易情况和产品情况进行分析以更好的经营小店。

已知产品情况表product_tb如下(其中,item_id指某款号的具体货号,style_id指款号,tag_price表示标签价格,inventory指库存量):

item_idstyle_idtag_priceinventory
A001A10020
A002A12030
A003A20015
B001B13018
B002B15022
B003B12510
B004B15512
C001C26025
C002C28018

11月份销售数据表sales_tb如下(其中,sales_date表示销售日期,user_id指用户编号,item_id指货号,sales_num表示销售数量,sales_price表示结算金额):

sales_dateuser_iditem_idsales_numsales_price
2021-11-011A001190
2021-11-012A0022220
2021-11-012B0011120
2021-11-023C0012500
2021-11-024B0011120
2021-11-035C0011240
2021-11-036C0021270
2021-11-047A0031180
2021-11-048B0021140
2021-11-049B0011125
2021-11-0510B0031120
2021-11-0510B0041150
2021-11-0510A0031180
2021-11-0611B0031120
2021-11-0610B0041150

请你统计折扣率(GMV/吊牌金额,GMV指的是成交金额),以上例子的输出结果如下(折扣率保留两位小数):

discount_rate(%)
93.97
示例1
drop table if exists product_tb;
CREATE TABLE product_tb(
item_id char(10) NOT NULL,
style_id char(10) NOT NULL,
tag_price int(10) NOT NULL,
inventory int(10) NOT NULL
);
INSERT INTO product_tb VALUES('A001', 'A', 100,  20);
INSERT INTO product_tb VALUES('A002', 'A', 120, 30);
INSERT INTO product_tb VALUES('A003', 'A', 200,  15);
INSERT INTO product_tb VALUES('B001', 'B', 130, 18);
INSERT INTO product_tb VALUES('B002', 'B', 150,  22);
INSERT INTO product_tb VALUES('B003', 'B', 125, 10);
INSERT INTO product_tb VALUES('B004', 'B', 155,  12);
INSERT INTO product_tb VALUES('C001', 'C', 260, 25);
INSERT INTO product_tb VALUES('C002', 'C', 280,  18);

drop table if exists sales_tb;
CREATE TABLE sales_tb(
sales_date date NOT NULL,
user_id int(10) NOT NULL,
item_id char(10) NOT NULL,
sales_num int(10) NOT NULL,
sales_price int(10) NOT NULL
);

INSERT INTO sales_tb VALUES('2021-11-1', 1, 'A001',  1, 90);
INSERT INTO sales_tb VALUES('2021-11-1', 2, 'A002',  2, 220);
INSERT INTO sales_tb VALUES('2021-11-1', 2, 'B001',  1, 120);
INSERT INTO sales_tb VALUES('2021-11-2', 3, 'C001',  2, 500);
INSERT INTO sales_tb VALUES('2021-11-2', 4, 'B001',  1, 120);
INSERT INTO sales_tb VALUES('2021-11-3', 5, 'C001',  1, 240);
INSERT INTO sales_tb VALUES('2021-11-3', 6, 'C002',  1, 270);
INSERT INTO sales_tb VALUES('2021-11-4', 7, 'A003',  1, 180);
INSERT INTO sales_tb VALUES('2021-11-4', 8, 'B002',  1, 140);
INSERT INTO sales_tb VALUES('2021-11-4', 9, 'B001',  1, 125);
INSERT INTO sales_tb VALUES('2021-11-5', 10, 'B003',  1, 120);
INSERT INTO sales_tb VALUES('2021-11-5', 10, 'B004',  1, 150);
INSERT INTO sales_tb VALUES('2021-11-5', 10, 'A003',  1, 180);
INSERT INTO sales_tb VALUES('2021-11-6', 11, 'B003',  1, 120);
INSERT INTO sales_tb VALUES('2021-11-6', 10, 'B004',  1, 150);
输出

93.97

题解
select round(sum(sales_price)/sum(sales_num*tag_price)*100,2) 'discount_rate(%)' 
from product_tb
join sales_tb
using(item_id)
;