问题
I have a table with customers, users and revenue similar to below (in reality thousands of records):
Customer User Revenue
001 James 500
002 James 750
003 James 450
004 Sarah 100
005 Sarah 500
006 Sarah 150
007 Sarah 600
008 James 150
009 James 100
What I want to do is to return only the highest spending customers that make up 80% of the total revenue for the user.
To do this manually I would order James' customers by their revenue, work out the percentage of total and a running total percentage, then only return records up to the point that the running total hits 80%:
Customer User Revenue % of total Running Total %
002 James 750 0.38 0.38
001 James 500 0.26 0.64
003 James 450 0.23 0.87 <- Greater than 80%, last record
008 James 150 0.08 0.95
009 James 100 0.05 1.00
I've tried using a CTE but so far have come up blank. Is there any way to do this via a single query rather than manually in an Excel sheet?
回答1:
SQL Server 2012+ only
You could use windowed SUM:
WITH cte AS
(
SELECT *,
1.0 * Revenue/SUM(Revenue) OVER(PARTITION BY [User]) AS percentile,
1.0 * SUM(Revenue) OVER(PARTITION BY [User] ORDER BY [Revenue] DESC)
/SUM(Revenue) OVER(PARTITION BY [User]) AS running_percentile
FROM tab
)
SELECT *
FROM cte
WHERE running_percentile <= 0.8;
LiveDemo
SQL Server 2008:
WITH cte AS
(
SELECT *, ROW_NUMBER() OVER(PARTITION BY [User] ORDER BY Revenue DESC) AS rn
FROM t
), cte2 AS
(
SELECT c.Customer, c.[User], c.[Revenue]
,percentile = 1.0 * Revenue / NULLIF(c3.s,0)
,running_percentile = 1.0 * c2.s / NULLIF(c3.s,0)
FROM cte c
CROSS APPLY
(SELECT SUM(Revenue) AS s
FROM cte c2
WHERE c.[User] = c2.[User]
AND c2.rn <= c.rn) c2
CROSS APPLY
(SELECT SUM(Revenue) AS s
FROM cte c2
WHERE c.[User] = c2.[User]) AS c3
)
SELECT *
FROM cte2
WHERE running_percentile <= 0.8;
LiveDemo2
Output:
╔══════════╦═══════╦═════════╦════════════════╦════════════════════╗
║ Customer ║ User ║ Revenue ║ percentile ║ running_percentile ║
╠══════════╬═══════╬═════════╬════════════════╬════════════════════╣
║ 2 ║ James ║ 750 ║ 0,384615384615 ║ 0,384615384615 ║
║ 1 ║ James ║ 500 ║ 0,256410256410 ║ 0,641025641025 ║
║ 7 ║ Sarah ║ 600 ║ 0,444444444444 ║ 0,444444444444 ║
╚══════════╩═══════╩═════════╩════════════════╩════════════════════╝
EDIT 2:
That looks nearly there, the only niggle is it's missing the last row, the third row for James takes him over 0.80 but needs to be included.
WITH cte AS
(
SELECT *, ROW_NUMBER() OVER(PARTITION BY [User] ORDER BY Revenue DESC) AS rn
FROM t
), cte2 AS
(
SELECT c.Customer, c.[User], c.[Revenue]
,percentile = 1.0 * Revenue / NULLIF(c3.s,0)
,running_percentile = 1.0 * c2.s / NULLIF(c3.s,0)
FROM cte c
CROSS APPLY
(SELECT SUM(Revenue) AS s
FROM cte c2
WHERE c.[User] = c2.[User]
AND c2.rn <= c.rn) c2
CROSS APPLY
(SELECT SUM(Revenue) AS s
FROM cte c2
WHERE c.[User] = c2.[User]) AS c3
)
SELECT a.*
FROM cte2 a
CROSS APPLY (SELECT MIN(running_percentile) AS rp
FROM cte2
WHERE running_percentile >= 0.8
AND cte2.[User] = a.[User]) AS s
WHERE a.running_percentile <= s.rp;
LiveDemo3
Output:
╔══════════╦═══════╦═════════╦════════════════╦════════════════════╗
║ Customer ║ User ║ Revenue ║ percentile ║ running_percentile ║
╠══════════╬═══════╬═════════╬════════════════╬════════════════════╣
║ 2 ║ James ║ 750 ║ 0,384615384615 ║ 0,384615384615 ║
║ 1 ║ James ║ 500 ║ 0,256410256410 ║ 0,641025641025 ║
║ 3 ║ James ║ 450 ║ 0,230769230769 ║ 0,871794871794 ║
║ 7 ║ Sarah ║ 600 ║ 0,444444444444 ║ 0,444444444444 ║
║ 5 ║ Sarah ║ 500 ║ 0,370370370370 ║ 0,814814814814 ║
╚══════════╩═══════╩═════════╩════════════════╩════════════════════╝
Looks to be perfect, translated to my big table and returns what I need, spent a good 5 minutes working through it and still can't follow what you've done!
SQL Server 2008 does not support everything in OVER() clause, but ROW_NUMBER does.
First cte just calculate position within a group:
╔═══════════╦════════╦══════════╦════╗
║ Customer ║ User ║ Revenue ║ rn ║
╠═══════════╬════════╬══════════╬════╣
║ 2 ║ James ║ 750 ║ 1 ║
║ 1 ║ James ║ 500 ║ 2 ║
║ 3 ║ James ║ 450 ║ 3 ║
║ 8 ║ James ║ 150 ║ 4 ║
║ 9 ║ James ║ 100 ║ 5 ║
║ 7 ║ Sarah ║ 600 ║ 1 ║
║ 5 ║ Sarah ║ 500 ║ 2 ║
║ 6 ║ Sarah ║ 150 ║ 3 ║
║ 4 ║ Sarah ║ 100 ║ 4 ║
╚═══════════╩════════╩══════════╩════╝
Second cte:
c2subquery calculate running total based on rank fromROW_NUMBERc3calculate full sum per user
In final query s subquery finds the lowest running total that exceeds 80%.
EDIT 3:
Using ROW_NUMBER is actually redundant.
WITH cte AS
(
SELECT c.Customer, c.[User], c.[Revenue]
,percentile = 1.0 * Revenue / NULLIF(c3.s,0)
,running_percentile = 1.0 * c2.s / NULLIF(c3.s,0)
FROM t c
CROSS APPLY
(SELECT SUM(Revenue) AS s
FROM t c2
WHERE c.[User] = c2.[User]
AND c2.Revenue >= c.Revenue) c2
CROSS APPLY
(SELECT SUM(Revenue) AS s
FROM t c2
WHERE c.[User] = c2.[User]) AS c3
)
SELECT a.*
FROM cte a
CROSS APPLY (SELECT MIN(running_percentile) AS rp
FROM cte c2
WHERE running_percentile >= 0.8
AND c2.[User] = a.[User]) AS s
WHERE a.running_percentile <= s.rp
ORDER BY [User], Revenue DESC;
LiveDemo4
回答2:
In SQL Server 2012+, you would use the cumulative sum -- much more efficient. In SQL Server 2008, you can do this using a correlated subquery or cross apply:
select t.*,
sum(t.Revenue*1.0) / sum(t.Revenue) over (partition by user) as [% of Total],
sum(RunningRevenue*1.0) / sum(t.Revenue) over (partition by user) as [Running Total %]
from t cross apply
(select sum(Revenue) as RunningRevenue
from t t2
where t2.Revenue >= t.Revenue and t2.user = t.user
) t2;
Note: The *1.0 is just in case Revenue is stored as an integer. SQL Server does integer division, which would return 0 for both columns on almost all rows.
EDIT:
Add where user = 'James' if you want results only for James.
来源：https://stackoverflow.com/questions/36452626/selecting-a-subset-of-rows-that-exceed-a-percentage-of-total-values