DECLARE @Obs int
DECLARE @RowAsc table
(
ID      INT IDENTITY,
Observation  FLOAT
)
INSERT INTO @RowAsc
SELECT Observations FROM MyTable
ORDER BY 1 
SELECT @Obs=COUNT(*)/2 FROM @RowAsc
SELECT Observation AS Median FROM @RowAsc WHERE ID=@Obs

在我的解决方案表中是一个只有分数列的学生表，我正在计算分数的中位数，这个解决方案是基于SQL server 2019的

with total_c as ( --Total_c CTE counts total number of rows in a table
    select count(*) as n from student
),
even as ( --Even CTE extract two middle rows if the number of rows are even
    select marks from student 
    order by marks 
    offset (select n from total_c)/2 -1 rows
    fetch next 2 rows only
),
odd as ( --Odd CTE extract middle row if the number of rows are odd
    select marks from student 
    order by marks 
    offset (select n + 1 from total_c)/2 -1 rows
    fetch next 1 rows only
    )
--Case statement helps to select odd or even CTE based on number of rows
select                                                        
case when n%2 = 0 then (select avg(cast(marks as float)) from even)
    else (select marks from odd)
end as med_marks
from total_c

对于大规模数据集，您可以尝试以下GIST:

https://gist.github.com/chrisknoll/1b38761ce8c5016ec5b2

它通过聚合您在集合中找到的不同值(例如年龄或出生年份等)来工作，并使用SQL窗口函数来定位您在查询中指定的任何百分比位置。

with t1 as (select *, row_number() over(order by ordqty) as rn,
count(*) over() as rc from ord_line)
select rn,* from t1 where rn in((rc+1)/2, (rc+2)/2);

它将计算偶数和奇数的中位数。

Ord_line是一个表 Ordqty是一个列

使用COUNT聚合， 首先可以计算有多少行，并存储在一个名为@cnt的变量中。然后 你可以计算OFFSET-FETCH过滤器的参数来指定，基于数量排序， 要跳过多少行(偏移值)和筛选多少行(获取值)。

行数 跳过是(@cnt - 1) / 2。很明显，对于奇数，这个计算是正确的，因为 首先对单个中间值减去1，然后再除以2。

这也适用于偶数计数，因为表达式中使用的除法是 整数除法;所以，当一个偶数减去1时，你得到的是一个奇数。

When dividing that odd value by 2, the fraction part of the result (.5) is truncated. The number of rows to fetch is 2 - (@cnt % 2). The idea is that when the count is odd the result of the modulo operation is 1, and you need to fetch 1 row. When the count is even the result of the modulo operation is 0, and you need to fetch 2 rows. By subtracting the 1 or 0 result of the modulo operation from 2, you get the desired 1 or 2, respectively. Finally, to compute the median quantity, take the one or two result quantities, and apply an average after converting the input integer value to a numeric one as follows:

DECLARE @cnt AS INT = (SELECT COUNT(*) FROM [Sales].[production].[stocks]);
SELECT AVG(1.0 * quantity) AS median
FROM ( SELECT quantity
FROM [Sales].[production].[stocks]
ORDER BY quantity
OFFSET (@cnt - 1) / 2 ROWS FETCH NEXT 2 - @cnt % 2 ROWS ONLY ) AS D;

在UDF中，写:

 Select Top 1 medianSortColumn from Table T
  Where (Select Count(*) from Table
         Where MedianSortColumn <
           (Select Count(*) From Table) / 2)
  Order By medianSortColumn