携程笔试题3--2020-09-08

题目:在很多预测模型中,往往需要用到同一行为的不同周期汇总值作为特征。比如近1/7/15/30/60天购买笔数和金额。因此,怎么用简洁的sql获取这些特征是作为一个分析师必须要掌握的技能。

输入描述:

订单表edw_htl_order:

orderid  bint  comment (订单id)

userid  bigint comment(订单id)

orderdate string comment (下单日期) 

amount double comment(订单金额)

输出结果:用户id,近一天的订单数,近一天的订单金额,近七天订单数,近七天订单金额,近15天订单数,近15天订单金额

说明:为了兼容各sql引擎,我们简化约定近n天判断如下:

近1天:【‘2020-07-15’,‘2020-07-16’】

近7天:【‘2020-07-09’,‘2020-07-16’】

近15天:【‘2020-07-01’,‘2020-07-16’】

样例输入:

 

 

 样例输出:

 输入代码:

 1 select e1.userid,e1.cnt_1d,e1.amt_1d,e2.cnt_7d,e2.amt_7d,e3.cnt_15d,e3.amt_15d
 2 from (select userid, count(orderdate) cnt_1d, sum(amount) amt_1d
 3      from edw_htl_order
 4      where orderdate between '2020-07-15' and '2020-07-16'
 5      group by userid) as e1
 6 inner join 
 7     (select userid, count(orderdate) cnt_7d, sum(amount) amt_7d
 8          from edw_htl_order
 9          where orderdate between '2020-07-09' and '2020-07-16'
10          group by userid) as e2 on e1.userid = e2.userid
11 inner join 
12     (select userid, count(orderdate) cnt_15d, sum(amount) amt_15d
13          from edw_htl_order
14          where orderdate between '2020-07-01' and '2020-07-16'
15          group by userid) as e3 on e2.userid = e3.userid;

输出结果:

原文地址:https://www.cnblogs.com/xiaodangdang/p/13637485.html