我想去一个
lapsed_date
这是指给定时间内有12周(即84天)以上
ID
之间:
1)
onboarded_at
和当前日期(如果没有
applied_at
存在)-这意味着如果超过84天,现在就失效了
2)
船上的
和闽(
应用于
)(如果有)
3)每个连续
应用于
4)最大值(max)
应用于
)
current_date
-这意味着如果超过84天,现在就失效了。
如果有多个他失效的实例,那么我们只显示最近的失效日期。
我的尝试在大多数情况下都有效,但并非所有情况下都有效。你能协助使它普遍工作吗?
样本集:
CREATE TABLE #t
(
id VARCHAR(10),
rank INTEGER,
onboarded_at DATE,
applied_at DATE
);
INSERT INTO #t VALUES
('A',1,'20180101','20180402'),
('A',2,'20180101','20180403'),
('A',3,'20180101','20180504'),
('B',1,'20180201','20180801'),
('C',1,'20180301','20180401'),
('C',2,'20180301','20180501'),
('C',3,'20180301','20180901'),
('D',1,'20180401',null)
最佳尝试:
SELECT onb.id,
onb.rank,
onb.onboarded_at,
onb.applied_at,
onb.lapsed_now,
CASE WHEN lapsed_now = 1 OR lapsed_previous = 1
THEN 1
ELSE 0
END lapsed_ever,
CASE WHEN lapsed_now = 1
THEN DATEADD(DAY, 84, lapsed_now_date)
ELSE min_applied_at_add_84
END lapsed_date
FROM
(SELECT *,
CASE
WHEN DATEDIFF(DAY, onboarded_at, MIN(ISNULL(applied_at, onboarded_at)) over (PARTITION BY id)) >= 84
THEN 1
WHEN DATEDIFF(DAY, MAX(applied_at) OVER (PARTITION BY id), GETDATE()) >= 84
THEN 1
ELSE 0
END lapsed_now,
CASE
WHEN MAX(DATEDIFF(DAY, onboarded_at, ISNULL(applied_at, GETDATE()))) OVER (PARTITION BY id) >= 84
THEN 1
ELSE 0
END lapsed_previous,
MAX(applied_at) OVER (PARTITION BY id) lapsed_now_date,
DATEADD(DAY, 84, MIN(CASE WHEN applied_at IS NULL THEN onboarded_at ELSE applied_at END) OVER (PARTITION BY id)) min_applied_at_add_84
FROM #t
) onb
当前解决方案:
id rank onboarded_at applied_at lapsed_now lapsed_ever lapsed_date
A 1 2018-01-01 2018-04-02 1 1 2018-07-27
A 2 2018-01-01 2018-04-03 1 1 2018-07-27
A 3 2018-01-01 2018-05-04 1 1 2018-07-27
B 2 2018-02-01 2018-08-01 1 1 2018-10-24
C 1 2018-03-01 2018-04-01 0 1 2018-06-24
C 2 2018-03-01 2018-05-01 0 1 2018-06-24
C 3 2018-03-01 2018-09-01 0 1 2018-06-24
D 1 2018-04-01 null 1 1 2018-06-24
预期解决方案:
id rank onboarded_at applied_at lapsed_now lapsed_ever lapsed_date
A 1 2018-01-01 2018-04-02 1 1 2018-07-27 (not max lapsed date)
A 2 2018-01-01 2018-04-03 1 1 2018-07-27
A 3 2018-01-01 2018-05-04 1 1 2018-07-27 (May 4 + 84)
B 1 2018-02-01 2018-08-01 0 1 2018-04-26 (Feb 1 + 84)
C 1 2018-03-01 2018-04-01 0 1 2018-07-24
C 2 2018-03-01 2018-05-01 0 1 2018-07-24 (May 1 + 84)
C 3 2018-03-01 2018-09-01 0 1 2018-07-24
D 1 2018-04-01 null 1 1 2018-06-24