很快,我将不得不准备一件商品价格清单。粒度为1天,在有商品销售的日子里,我将平均价格以获取当天的平均价格。有时候会没有销售,因此我很适合通过拉前一次和下一次销售来使用足够的近似值,并且在它们之间的每一天,其价格都从一个线性变化到另一个线性变化。
想象原始数据是:
Item Date Price
Bread 2000-01-01 10
Bread 2000-01-02 9.5
Bread 2000-01-04 9.1
Sugar 2000-01-01 100
Sugar 2000-01-11 150
我可以到这里:
Item Date Price
Bread 2000-01-01 10
Bread 2000-01-02 9.5
Bread 2000-01-03 NULL
Bread 2000-01-04 9.1
Sugar 2000-01-01 100
Sugar 2000-01-02 NULL
Sugar 2000-01-03 NULL
Sugar 2000-01-04 NULL
Sugar 2000-01-05 NULL
Sugar 2000-01-06 NULL
Sugar 2000-01-07 NULL
Sugar 2000-01-08 NULL
Sugar 2000-01-09 NULL
Sugar 2000-01-10 NULL
Sugar 2000-01-11 150
我想去的地方是:
Item Date Price
Bread 2000-01-01 10
Bread 2000-01-02 9.5
Bread 2000-01-03 9.3 --being 9.5 + ((9.1 - 9.5 / 2) * 1)
Bread 2000-01-04 9.1
Sugar 2000-01-01 100
Sugar 2000-01-02 105 --being 100 + (150 - 100 / 10) * 1)
Sugar 2000-01-03 110 --being 100 + (150 - 100 / 10) * 2)
Sugar 2000-01-04 115
Sugar 2000-01-05 120
Sugar 2000-01-06 125
Sugar 2000-01-07 130
Sugar 2000-01-08 135
Sugar 2000-01-09 140
Sugar 2000-01-10 145 --being 100 + (150 - 100 / 10) * 9)
Sugar 2000-01-11 150
到目前为止,我尝试了什么?仅思考;我打算做类似的事情:
但是,我想知道是否有一种更简单的方法,因为我有数百万个项目日,而且感觉好像效率不高。
我发现了很多这样的问题示例,其中逐行涂抹了最后一行或下一行的数据以填补空白,但我不记得看到这种情况在尝试某种过渡。也许可以通过向前涂抹,复制最新值以及向后涂抹的方式双重应用该技术:
Item Date DateFwd DateBak PriceF PriceB
Bread 2000-01-01 2000-01-01 2000-01-01 10 10
Bread 2000-01-02 2000-01-02 2000-01-02 9.5 9.5
Bread 2000-01-03 2000-01-02 2000-01-04 9.5 9.1
Bread 2000-01-04 2000-01-04 2000-01-04 9.1 9.1
Sugar 2000-01-01 2000-01-01 2000-01-01 100 100
Sugar 2000-01-02 2000-01-01 2000-01-11 100 150
Sugar 2000-01-03 2000-01-01 2000-01-11 100 150
Sugar 2000-01-04 2000-01-01 2000-01-11 100 150
Sugar 2000-01-05 2000-01-01 2000-01-11 100 150
Sugar 2000-01-06 2000-01-01 2000-01-11 100 150
Sugar 2000-01-07 2000-01-01 2000-01-11 100 150
Sugar 2000-01-08 2000-01-01 2000-01-11 100 150
Sugar 2000-01-09 2000-01-01 2000-01-11 100 150
Sugar 2000-01-10 2000-01-01 2000-01-11 100 150
Sugar 2000-01-11 2000-01-11 2000-01-11 150 150
这些可能会为公式提供必要的数据
(preceding_price + ((next_price - preceding_price)/gap_distance) * gap_progress)
:
?
这是我知道可以获取的数据的DDL(与日历表连接的原始数据)
CREATE TABLE Data
([I] varchar(5), [D] date, [P] DECIMAL(10,5))
;
INSERT Data
([I], [D], [P])
VALUES
('Bread', '2000-01-01', 10),
('Bread', '2000-01-02', 9.5),
('Bread', '2000-01-04', 9.1),
('Sugar', '2000-01-01', 100),
('Sugar', '2000-01-11', 150);
CREATE TABLE Cal([D] DATE);
INSERT Cal VALUES
('2000-01-01'),
('2000-01-02'),
('2000-01-03'),
('2000-01-04'),
('2000-01-05'),
('2000-01-06'),
('2000-01-07'),
('2000-01-08'),
('2000-01-09'),
('2000-01-10'),
('2000-01-11');
SELECT d.i as [item], c.d as [date], d.p as [price] FROM
cal c LEFT JOIN data d ON c.d = d.d
答案 0 :(得分:4)
您可以使用OUTER APPLY
以不为空的价格获取上一行和下一行:
select
d.item,
d.date,
case when d.price is null then
prev.price + ( (next.price - prev.price) /
datediff(day, prev.date, next.date) *
datediff(day, prev.date, d.date)
)
else
d.price
end as price
from data d
outer apply
(
select top(1) *
from data d2
where d2.item = d.item and d2.date < d.date and d2.price is not null
order by d2.date desc
) prev
outer apply
(
select top(1) *
from data d2
where d2.item = d.item and d2.date > d.date and d2.price is not null
order by d2.date
) next;
上个月的演示:http://rextester.com/QBL7472
更新:这可能很慢。也许在子查询的where子句中添加and d.price is null
可以帮助DBMS在价格不为null时不必实际上寻找其他记录。只需查看说明计划,看看是否有帮助。
答案 1 :(得分:1)
我会将您的公式100 + (150 - 100 / 10) * 9)
等放入标量UDF中,并在持久化的计算列中使用。
答案 2 :(得分:1)
更容易一次性生成那些缺失的缺口和价格
所以我从您的原始原始数据开始
CREATE TABLE t
([I] varchar(5), [D] date, [P] DECIMAL(10,2))
;
INSERT INTO t
([I], [D], [P])
VALUES
('Bread', '2000-01-01 00:00:00', '10'),
('Bread', '2000-01-02 00:00:00', '9.5'),
('Bread', '2000-01-04 00:00:00', '9.1'),
('Sugar', '2000-01-01 00:00:00', '100'),
('Sugar', '2000-01-11 00:00:00', '150');
; with
-- number is a tally table. here i use recursive cte to generate 100 numbers
number as
(
select n = 0
union all
select n = n + 1
from number
where n < 99
),
-- a cte to get the Price of next date and also day diff
cte as
(
select *,
nextP = lead(P) over(partition by I order by D),
cnt = datediff(day, D, lead(D) over(partition by I order by D)) - 1
from t
)
select I,
D = dateadd(day, n, D),
P = coalesce(c.P + (c.nextP - c.P) / ( cnt + 1) * n, c.P)
from cte c
cross join number n
where n.n <= isnull(c.cnt, 0)
drop table t
答案 3 :(得分:1)
这将适用于sql-server-2012 + 测试表:
DECLARE @t table
(Item char(5), Date date, Price decimal(9,1))
INSERT @t values
('Bread','2000-01-01', 10),
('Bread','2000-01-02', 9.5),
('Bread','2000-01-04', 9.1),
('Sugar','2000-01-01', 100),
('Sugar','2000-01-11', 150)
查询
;WITH CTE as
(
SELECT
Item, Date, Price,
lead(price) over(partition by Item order by Date) nextprice,
lead(Date) over(partition by Item order by Date) nextDate
FROM @t
), N(N) as
(
SELECT 1 FROM(VALUES(1),(1),(1),(1),(1),(1),(1),(1),(1),(1))M(N)
), tally(N) as
(
SELECT ROW_NUMBER()OVER(ORDER BY N.N)FROM N,N a,N b,N c,N d,N e,N f
)
SELECT
dateadd(d, coalesce(r, 0), Date) Date,
Item,
CAST(price + coalesce((nextprice-price) * r
/ datediff(d, date, nextdate), 0) as decimal(10,1)) Price
FROM CTE
OUTER APPLY
(
SELECT top(coalesce(datediff(d, date, nextdate), 0))
row_number() over (order by (select 1))-1 r
FROM N
) z
ORDER BY item, date
结果:
Date Item Price
2000-01-01 Bread 10.0
2000-01-02 Bread 9.5
2000-01-03 Bread 9.3
2000-01-04 Bread 9.1
2000-01-01 Sugar 100.0
2000-01-02 Sugar 105.0
2000-01-03 Sugar 110.0
2000-01-04 Sugar 115.0
2000-01-05 Sugar 120.0
2000-01-06 Sugar 125.0
2000-01-07 Sugar 130.0
2000-01-08 Sugar 135.0
2000-01-09 Sugar 140.0
2000-01-10 Sugar 145.0
2000-01-11 Sugar 150.0