为多个层次组优化 SUM OVER PARTITION BY
我有一张如下表:
Region Country Manufacturer Brand Period Spend
R1 C1 M1 B1 2016 5
R1 C1 M1 B1 2017 10
R1 C1 M1 B1 2017 20
R1 C1 M1 B2 2016 15
R1 C1 M1 B3 2017 20
R1 C2 M1 B1 2017 5
R1 C2 M2 B4 2017 25
R1 C2 M2 B5 2017 30
R2 C3 M1 B1 2017 35
R2 C3 M2 B4 2017 40
R2 C3 M2 B5 2017 45
我需要在不同的组中找到 SUM([Spend]
如下:
I need to find SUM([Spend]
over different groups as follow:
- 整个表中所有行的总支出
- 每个区域 的总支出
- 每个地区和国家组的总支出
- 每个地区、国家/地区和广告客户组的总支出
- Total Spend over all the rows in the whole table
- Total Spend for each Region
- Total Spend for each Region and Country group
- Total Spend for each Region, Country and Advertiser group
所以我在下面写了这个查询:
So I wrote this query below:
SELECT
[Period]
,[Region]
,[Country]
,[Manufacturer]
,[Brand]
,SUM([Spend]) OVER (PARTITION BY [Period]) AS [SumOfSpendWorld]
,SUM([Spend]) OVER (PARTITION BY [Period], [Region]) AS [SumOfSpendRegion]
,SUM([Spend]) OVER (PARTITION BY [Period], [Region], [Country]) AS [SumOfSpendCountry]
,SUM([Spend]) OVER (PARTITION BY [Period], [Region], [Country], [Manufacturer]) AS [SumOfSpendManufacturer]
FROM myTable
但是对于只有 450K 行的表,该查询需要 15 分钟以上的时间.我想知道是否有任何方法可以优化此性能.预先感谢您的回答/建议!
But that query takes >15 minutes for a table of just 450K rows. I'd like to know if there is any way to optimize this performance. Thank you in advanced for your answers/suggestions!
推荐答案
你对问题的描述向我暗示了分组集
:
Your description of the problem suggests grouping sets
to me:
SELECT YEAR([Period]) AS [Period], [Region], [Country], [Manufacturer],
SUM([Spend])
GROUP BY GROUPING SETS ( (YEAR([Period]),
(YEAR([Period]), [Region]),
(YEAR([Period]), [Region], [Country]),
(YEAR([Period]), [Region], [Country], [Manufacturer])
);
我不知道这是否会更快,但它似乎更符合您的问题.
I don't know if this will be faster, but it certainly seems more aligned with your question.
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