Sql 标记每个用户达到的金额阈值

故事： 两个条件：

我需要计算用户花费的时间 20美元、50美元和100美元，以其注册日期为准

如果某人的首次购买价格>100美元，则 3个阈值的天数相同

我能够得到标记阈值的逻辑，但我被用户的第一次购买超过一个或两个阈值所困扰

目标： 我需要计算它们达到20美元、50美元和100美元所需的天数

当前查询： 我可能不得不改变整个逻辑来满足第二个条件，但是的，我被卡住了。以下代码正确地标记正在达到的阈值

select
    user_id, register_date
    ,total
    ,order_date
    ,cumulative_sum
    ,threshold
    ,case 
        when threshold+LAG(threshold,1,0) over (partition by user_id order by order_date)=1 then 1
        when threshold+LAG(threshold,1,0) over (partition by user_id order by order_date)=3 then 2
        when threshold+LAG(threshold,1,0) over (partition by user_id order by order_date)=5 then 3
        else 0 end as flag
from (
    select
        user_id, register_date
        ,total
        ,order_date
        ,cumulative_sum
        ,case 
            When cumulative_sum>=100 then 3 
            When cumulative_sum>=50 then 2 
            When cumulative_sum>=20 then 1 else 0 end as threshold
    from (
        select 
            user_id, register_date
            ,(price*quantity) as total
            ,order_date 
            ,SUM(price*quantity) over (partition by user_id order by order_date asc) as cumulative_sum
        from #t1
    ) as base1
) as base2

数据：

CREATE TABLE #t1 (user_id int, price int, quantity int, order_date datetime,register_date datetime)
insert into #t1 values
(1,10,1,'2019-01-01 00:00:00.000','2019-01-01 00:00:00.000'),
(1,15,1,'2019-01-02 00:00:00.000','2019-01-01 00:00:00.000'),
(1,30,1,'2019-01-03 00:00:00.000','2019-01-01 00:00:00.000'),
(1,100,1,'2019-01-04 00:00:00.000','2019-01-01 00:00:00.000'),
(2,60,1,'2019-01-02 00:00:00.000','2019-01-01 00:00:00.000'),
(3,150,1,'2019-01-03 00:00:00.000','2019-01-01 00:00:00.000'),
(4,10,1,'2019-01-04 00:00:00.000','2019-01-01 00:00:00.000'),
(4,20,1,'2019-01-05 00:00:00.000','2019-01-01 00:00:00.000'),
(4,50,2,'2019-01-06 00:00:00.000','2019-01-01 00:00:00.000')

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只需使用条件聚合和

datediff（）

：

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“我卡住了”不是一个问题描述。引用的代码是做什么的？为什么这是错误的或不足以达到要求的结果？对不起，伙计们，我刚才编辑的问题遗漏了一个重要的部分。对不起，我遗漏了一个重要的因素，我只是在数据中添加了另一列，表示注册日期。达到阈值的天数基于登记日期。我的错@罗杰斯坦伯格。这并没有实质性地改变逻辑。

select user_id,
       datediff(day, min(register_date),
                min(case when cumulative_sum >= 20 then order_date end)
               ) as days_to_20,
       datediff(day, min(register_date),
                min(case when cumulative_sum >= 50 then order_date end)
               ) as days_to_50,
       datediff(day, min(register_date),
                min(case when cumulative_sum >= 100 then order_date end)
               ) as days_to_100
from (select t.*,
             sum(price * quantity) over (partition by user_id order by order_date asc) as cumulative_sum
      from #t1 t
     ) t
group by user_id;