题解 | #各城市最大同时等车人数#
各城市最大同时等车人数
http://www.nowcoder.com/practice/f301eccab83c42ab8dab80f28a1eef98
总代码
with t1 as (
SELECT city,type
,rank() over(partition by city order by event_time,type desc) as 'rnk'
from (
SELECT city,event_time,1 as 'type' from tb_get_car_record
union all
SELECT city
,( case when start_time is null then finish_time
when order_id is null then end_time
else start_time end
) as 'event_time'
,-1 as 'type'
from tb_get_car_record as A
left join tb_get_car_order as B
using(order_id)
) as temp
where date_format(event_time,'%Y-%m') = '2021-10'
)
select city
,max(num) as 'max_wait_uv'
from (
select city,type
,( select sum(type)
from t1 as B where B.city = A.city
and B.rnk <= A.rnk
) as 'num'
from t1 as A
) as t2
group by city order by max_wait_uv
思路分析
1.构造临时表
- 遇到同时在线问题,基本都是把开始时间和结束时间单独取出后使用union all进行合并(union 会去重)
- 并新增列(如命名为type)分别赋值为1,-1以区分人数加减
- 若要求如【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】,则需在新增一列排序,以方便计算人数(如果后面计算人数只是用时间来比较而不是用序号,遇到同个时间点有加有减则会计算错误)
本题中的开始时间比较容易:为用户开始打车时间即event_time
结束时间:
- 若司机接单后取消订单则为,finish_time
- 若用户自己取消则为,end_time
- 若司机成功接单则为,start_time
代码及该部分结果(图中为了便于理解rnk作用还select了event_time)如下
with t1 as (
SELECT city,type
,rank() over(partition by city order by event_time,type desc) as 'rnk'
from (
SELECT city,event_time,1 as 'type' from tb_get_car_record
union all
SELECT city
,( case when start_time is null then finish_time
when order_id is null then end_time
else start_time end
) as 'event_time'
,-1 as 'type'
from tb_get_car_record as A
left join tb_get_car_order as B
using(order_id)
) as temp
where date_format(event_time,'%Y-%m') = '2021-10'
)
select * from t1
2.计算人数
有了临时表后接下来就容易了,只需要进行分组计算(把小于当前行的序号的type进行累计求和)即可
select city,max(num) as 'max_wait_uv'
from (
select city,type
,( select sum(type) from t1 as B
where B.city = A.city and B.rnk <= A.rnk
) as 'num'
from t1 as A
) as t2
group by city order by max_wait_uv