如何解决SQL-使用条件对列中的值进行计数并按
我有一个包含动物及其疫苗日期的以下数据集。我试图通过sql计算每条记录中在过去90、180和365天宠物所接种的疫苗数量。我可以在Excel中解决这个问题。将下表粘贴到Excel单元格A1中，并将以下公式COUNTIFS(C:C,"<"&C2,C:C,">="&C2-90,A:A,A2)放在单元格D2中。您可以分别将90调整为180和365。
Animal Visit_ID Vaccine_Date Count_90 Count_180 Count_365
Cat 1 7/22/2017 0 0 0
Cat 2 8/1/2017 1 1 1
Cat 3 8/14/2017 2 2 2
Cat 4 8/23/2017 3 3 3
Cat 5 9/11/2017 4 4 4
Cat 6 9/30/2017 5 5 5
Cat 7 10/11/2017 6 6 6
Cat 8 10/23/2017 6 7 7
Cat 9 10/31/2017 6 8 8
Cat 10 11/6/2017 7 9 9
Cat 11 11/17/2017 7 10 10
Cat 12 11/29/2017 7 11 11
Cat 13 12/11/2017 7 12 12
Cat 14 12/25/2017 8 13 13
Cat 15 1/2/2018 8 14 14
Cat 16 1/29/2018 7 13 15
Cat 17 2/22/2018 5 12 16
Cat 18 3/9/2018 5 13 17
Cat 19 3/21/2018 5 13 18
Cat 20 4/13/2018 4 12 19
Cat 21 5/21/2018 4 9 20
Cat 22 8/27/2018 0 4 17
Cat 23 9/18/2018 1 3 17
Cat 24 10/3/2018 2 4 17
Cat 25 12/19/2018 1 3 11
Cat 26 12/22/2018 2 4 12
Cat 27 1/6/2019 2 5 11
Cat 28 1/30/2019 3 6 11
Cat 29 3/10/2019 4 6 10
Cat 30 3/26/2019 3 6 10
Cat 31 4/17/2019 3 6 10
Cat 32 5/13/2019 3 7 11
Cat 33 5/18/2019 4 8 12
Cat 34 5/25/2019 5 9 12
Cat 35 6/17/2019 5 10 13
Cat 36 7/2/2019 5 9 14
Cat 37 7/12/2019 6 9 15
Cat 38 8/2/2019 6 9 16
Cat 39 8/15/2019 6 10 17
Cat 40 8/27/2019 5 11 18
Cat 41 9/9/2019 6 11 18
Cat 42 9/17/2019 6 12 19
Cat 43 9/26/2019 7 12 19
Cat 44 10/9/2019 7 13 19
Cat 45 10/19/2019 7 13 20
Cat 46 11/12/2019 7 13 21
Cat 47 11/15/2019 7 13 22
Cat 48 11/26/2019 7 13 23
Cat 49 12/20/2019 6 13 23
Cat 50 12/31/2019 6 13 23
Cat 51 2/14/2020 3 11 22
Cat 52 3/8/2020 3 10 23
Cat 53 4/6/2020 2 9 22
Cat 54 5/5/2020 3 8 22
Cat 55 5/23/2020 3 7 21
Cat 56 6/18/2020 3 6 20
Cat 57 6/30/2020 4 6 21
Cat 58 7/16/2020 4 7 20
Cat 59 7/22/2020 5 8 21
Dog 1 3/8/2018 0:00 0 0 0
Dog 2 4/18/2019 0:00 0 0 0
Dog 3 7/1/2019 0:00 1 1 1
Dog 4 12/12/2019 0:00 0 1 2
Dog 5 12/23/2019 0:00 1 2 3
但是，当我尝试使用以下代码通过sql完成此操作时，它只是查看上一行并进行添加。它似乎并没有像上面的Excel公式那样在每个疫苗日期上倒数，而且我不确定如何将窗口函数集成到过去以90,180,365个间隔为基础对动物划分的疫苗日期进行计数的过程中。
select
qry3.Animal,qry3.Vaccine_Date,(case when qry3.Count_90 = 0 then 0 else row_number() over (partition by qry3.Animal,qry3.Count_90_2 order by qry3.animal_rank) - 1 end) as Admit_90,(case when qry3.Count_180 = 0 then 0 else row_number() over (partition by qry3.Animal,qry3.Count_180_2 order by qry3.animal_rank) - 1 end) as Admit_180,(case when qry3.Count_365 = 0 then 0 else row_number() over (partition by qry3.Animal,qry3.Count_365_2 order by qry3.animal_rank) - 1 end) as Admit_365
from
(
select
qry2.Animal,qry2.Vaccine_Date,qry2.animal_rank,qry2.Count_90,qry2.Count_180,qry2.Count_365,sum(case when qry2.Count_90 = 0 then 1 else 0 end) over(partition by qry2.Animal order by qry2.animal_rank rows between unbounded preceding and current row) as Count_90_2,sum(case when qry2.Count_180 = 0 then 1 else 0 end) over(partition by qry2.Animal order by qry2.animal_rank rows between unbounded preceding and current row) as Count_180_2,sum(case when qry2.Count_365 = 0 then 1 else 0 end) over(partition by qry2.Animal order by qry2.animal_rank rows between unbounded preceding and current row) as Count_365_2
from
(
select
qry1.Animal,qry1.Vaccine_Date,qry1.animal_Rank,case when qry1.Vaccine_Date-qry1.PrevIoUs_Vaccine_Date < 90 then 1 else 0 end as Count_90,case when qry1.Vaccine_Date-qry1.PrevIoUs_Vaccine_Date < 180 then 1 else 0 end as Count_180,case when qry1.Vaccine_Date-qry1.PrevIoUs_Vaccine_Date < 365 then 1 else 0 end as Count_365
from
(
select
a.Animal,a.Vaccine_Date,b.Vaccine_Date as PrevIoUs_Vaccine_Date,row_number() over (partition by null order by A.Animal,a.Vaccine_Date) as animal_Rank
from Animal_Vaccine a
left join Animal_Vaccine b on a.Visit_ID = b.Visit_ID - 1
) as qry1
) as qry2
) as qry3
以下是sql的结果（再次尝试模仿顶部的excel公式）：
Animal Vaccine_Date Count_90 Count_180 Count_365
Cat 7/22/2017 0:00 0 0 0
Cat 8/1/2017 0:00 1 1 1
Cat 8/14/2017 0:00 2 2 2
Cat 8/23/2017 0:00 3 3 3
Cat 9/11/2017 0:00 4 4 4
Cat 9/30/2017 0:00 5 5 5
Cat 10/11/2017 0:00 6 6 6
Cat 10/23/2017 0:00 7 7 7
Cat 10/31/2017 0:00 8 8 8
Cat 11/6/2017 0:00 9 9 9
Cat 11/17/2017 0:00 10 10 10
Cat 11/29/2017 0:00 11 11 11
Cat 12/11/2017 0:00 12 12 12
Cat 12/25/2017 0:00 13 13 13
Cat 1/2/2018 0:00 14 14 14
Cat 1/29/2018 0:00 15 15 15
Cat 2/22/2018 0:00 16 16 16
Cat 3/9/2018 0:00 17 17 17
Cat 3/21/2018 0:00 18 18 18
Cat 4/13/2018 0:00 19 19 19
Cat 5/21/2018 0:00 20 20 20
Cat 8/27/2018 0:00 21 21 21
Cat 9/18/2018 0:00 22 22 22
Cat 10/3/2018 0:00 23 23 23
Cat 12/19/2018 0:00 24 24 24
Cat 12/22/2018 0:00 25 25 25
Cat 1/6/2019 0:00 26 26 26
Cat 1/30/2019 0:00 27 27 27
Cat 3/10/2019 0:00 28 28 28
Cat 3/26/2019 0:00 29 29 29
Cat 4/17/2019 0:00 30 30 30
Cat 5/13/2019 0:00 31 31 31
Cat 5/18/2019 0:00 32 32 32
Cat 5/25/2019 0:00 33 33 33
Cat 6/17/2019 0:00 34 34 34
Cat 7/2/2019 0:00 35 35 35
Cat 7/12/2019 0:00 36 36 36
Cat 8/2/2019 0:00 37 37 37
Cat 8/15/2019 0:00 38 38 38
Cat 8/27/2019 0:00 39 39 39
Cat 9/9/2019 0:00 40 40 40
Cat 9/17/2019 0:00 41 41 41
Cat 9/26/2019 0:00 42 42 42
Cat 10/9/2019 0:00 43 43 43
Cat 10/19/2019 0:00 44 44 44
Cat 11/12/2019 0:00 45 45 45
Cat 11/15/2019 0:00 46 46 46
Cat 11/26/2019 0:00 47 47 47
Cat 12/20/2019 0:00 48 48 48
Cat 12/31/2019 0:00 49 49 49
Cat 2/14/2020 0:00 50 50 50
Cat 3/8/2020 0:00 51 51 51
Cat 4/6/2020 0:00 52 52 52
Cat 5/5/2020 0:00 53 53 53
Cat 5/23/2020 0:00 54 54 54
Cat 6/18/2020 0:00 55 55 55
Cat 6/30/2020 0:00 56 56 56
Cat 7/16/2020 0:00 57 57 57
Cat 7/22/2020 0:00 58 58 58
Dog 3/8/2018 0:00 0 0 0
Dog 4/18/2019 0:00 0 0 0
Dog 7/1/2019 0:00 1 1 1
Dog 12/12/2019 0:00 0 2 2
Dog 12/23/2019 0:00 1 3 3
解决方法
我能够通过在动物身上和疫苗日期之间重新加入表来解决此问题，然后计算不同的visit_id。我完全使它复杂化了，但是当我喜欢它们时，将可以使用窗口功能！
select
a.Animal,a.Vaccine_Date,a.visit_id,count(distinct b.visit_id) - 1 as Count_90 --minus 1 so it as to not count itself,count(distinct c.visit_id) - 1 as Count_180 --minus 1 so it as to not count itself,count(distinct d.visit_id) - 1 as Count_365 --minus 1 so it as to not count itself
from Animal_Vaccine a
left join Animal_Vaccine b on a.Animal = b.Animal and b.Vaccine_date between a.Vaccine_Date - 90 and a.Vaccine_Date
left join Animal_Vaccine c on a.Animal = c.Animal and c.Vaccine_date between a.Vaccine_Date - 180 and a.Vaccine_Date
left join Animal_Vaccine d on a.Animal = d.Animal and d.Vaccine_date between a.Vaccine_Date - 365 and a.Vaccine_Date
group by 1,2,3
;
只要每个值的行数很少，您的方法就可以了。但是，如果每个值的行数增加，CPU将会爆炸，您的DBA会给您打电话：-）
但是，假设animal / visit_id是唯一的，则您的查询查询可以简化为单个产品联接，而不是三个产品联接：
select
a.Animal,count(case when b.Vaccine_date between a.Vaccine_Date - 90 and a.Vaccine_Date then b.visit_id end) as Count_90,count(case when b.Vaccine_date between a.Vaccine_Date - 180 and a.Vaccine_Date then b.visit_id end) as Count_180,count(b.visit_id) as Count_365
from vt a
left join vt b
on a.Animal = b.Animal
and b.Vaccine_date between a.Vaccine_Date - 365 and a.Vaccine_Date - 1 -- don't include current row
group by 1,3
如果Animal是主索引，则可以提高性能（否则也可以使用该索引创建挥发表）。
根据每只动物的行数和日期范围，最好使用EXPAND简单地创建缺失的日期，然后可以使用ROWS代替RANGE：
select animal,Visit_ID,Vaccine_date
-- EXPAND ON returned one row per day with repeated data,the CASE effectily NULLs the added rows,count(case when valid_from = Vaccine_date then 1 end) over (partition by animal order by Vaccine_date rows between 90 preceding and 1 preceding),count(case when valid_from = Vaccine_date then 1 end) over (partition by animal order by Vaccine_date rows between 180 preceding and 1 preceding),count(case when valid_from = Vaccine_date then 1 end) over (partition by animal order by Vaccine_date rows between 365 preceding and 1 preceding)
from
( -- create the missing dates to get 1 row per animal/day
select animal,begin(pd) as Vaccine_date,valid_from
from
(
select animal,cast(Vaccine_date as date) as valid_from -- seems to be a Timestamp
-- get the next row's Vaccine_date for EXPAND ON in following step
/* -- LAG/LEAD not supported in TD 15.10,lead(Vaccine_date,1,Vaccine_date+1)
over (partition by animal
order by Vaccine_date) as valid_to
*/ -- workaround for LEAD,coalesce(min(Vaccine_date)
over (partition by animal
order by Vaccine_date
rows between 1 following and 1 following),Vaccine_date +1) as valid_to -- replace the last row's NULL with a valid end date
from vt
) as prepare_data
expand on period(valid_from,valid_to) as pd
) as expand_data
-- now remove the added dates again
qualify valid_from = Vaccine_date
这假设每只动物每天只有一行，否则在EXPAND ON期间会收到错误消息。然后必须在准备步骤中汇总数据。
,不幸的是，Teradata不支持范围窗口框架，因此您无法使用窗口功能执行所需的操作。 dnoeth建议使用左连接和条件聚合的解决方案提供了一种有效的解决方法。
但是，我想知道几个相关的子查询是否会表现更好，因为它根本不需要外部聚合：
select
v.*,(select count(*) from vt v1 where v1.animal = v.animal and v1.vaccine_date >= v.vaccine_date - 90 and v1.vaccine_date < v.vaccine_date) count_90,(select count(*) from vt v1 where v1.animal = v.animal and v1.vaccine_date >= v.vaccine_date - 180 and v1.vaccine_date < v.vaccine_date) count_180,(select count(*) from vt v1 where v1.animal = v.animal and v1.vaccine_date >= v.vaccine_date - 365 and v1.vaccine_date < v.vaccine_date) count_365
from vt v
对于此查询，请确保您在(animal,vaccine_date)上具有索引。
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