根据魔术贴的答案，对于那些必须根据另一个参数分组的东西做中位数的人来说

SELECT grp_field, t1。val FROM ( SELECT grp_field， @rownum:=IF(@s = grp_field， @rownum + 1,0) AS row_number， @s:=IF(@s = grp_field， @s, grp_field) AS sec, d.val FROM data d， (SELECT @rownum:=0， @s:=0 ORDER BY grp_field, d.val )作为t1 JOIN ( SELECT grp_field, count(*)为total_rows 数据d GROUP BY grp_field )为t2 在t1。Grp_field = t2.grp_field 在t1.row_number =地板(total_rows / 2) + 1;

一个简单的方法来计算中位数在MySQL

set @ct := (select count(1) from station);
set @row := 0;

select avg(a.val) as median from 
(select * from  table order by val) a
where (select @row := @row + 1)
between @ct/2.0 and @ct/2.0 +1;

如果这是MySQL，现在有窗口函数，你可以这样做(假设你想四舍五入到最接近的整数-否则只需将round替换为CEIL或FLOOR或其他什么)。下面的解决方案适用于表，无论表的行数是偶数还是奇数:

WITH CTE AS (
    SELECT val,
            ROW_NUMBER() OVER (ORDER BY val ASC) AS rn,
            COUNT(*) OVER () AS total_count
    FROM data
)
SELECT ROUND(AVG(val)) AS median
FROM CTE
WHERE
    rn BETWEEN
    total_count / 2.0 AND
    total_count / 2.0 + 1;

I think some of the more recent answers on this thread were already getting at this approach, but it also seemed like people were overthinking it, so consider this an improved version. Regardless of SQL flavor, there is no reason anyone should be writing a huge paragraph of code with multiple subqueries just to get the median in 2021. However, please note that the above query only works if you're asked to find the median for a continuous series. Of course, regardless of row number, sometimes people do make a distinction between what is referred to as the Discrete Median and what is referred to as the Interpolated Median for a continuous series.

如果你被要求为一个离散级数找到中位数，而表的行数是偶数，那么上面的解决方案就不适合你，你应该恢复使用其他解决方案之一，比如TheJacobTaylor的。

下面的第二个解决方案是对TheJacobTaylor的稍微修改的版本，其中我显式地声明了CROSS JOIN。这个方法也适用于行数为奇数的表，不管你是被要求求连续序列的中位数还是离散序列的中位数，但我特别会在被要求求离散序列的中位数时使用这个方法。否则，使用第一种解决方案。这样，您就永远不必考虑数据是包含“偶数”还是“奇数”个数的数据点。

SELECT x.val AS median
FROM data x
CROSS JOIN data y
GROUP BY x.val
HAVING SUM(SIGN(1 - SIGN(y.val - x.val))) = (COUNT(*) + 1) / 2;

最后，你可以在PostgreSQL中使用内置函数轻松做到这一点。这里有一个很好的解释，以及关于离散中位数和插值中位数的有效总结。

https://leafo.net/guides/postgresql-calculating-percentile.html#calculating-the-median

我下面提出的解决方案只需要一个查询，而不需要创建表、变量甚至子查询。 另外，它可以让你在组-查询(这是我需要的!)

SELECT `columnA`, 
SUBSTRING_INDEX(SUBSTRING_INDEX(GROUP_CONCAT(`columnB` ORDER BY `columnB`), ',', CEILING((COUNT(`columnB`)/2))), ',', -1) medianOfColumnB
FROM `tableC`
-- some where clause if you want
GROUP BY `columnA`;

它之所以能够工作，是因为巧妙地使用了group_concat和substring_index。

但是，为了允许大的group_concat，必须将group_concat_max_len设置为一个更高的值(默认为1024字符)。 你可以这样设置(对于当前的sql会话):

SET SESSION group_concat_max_len = 10000; 
-- up to 4294967295 in 32-bits platform.

有关group_concat_max_len的更多信息:https://dev.mysql.com/doc/refman/5.1/en/server-system-variables.html#sysvar_group_concat_max_len

我使用了两个查询方法:

第一个得到count, min, Max和avg 第二个语句(预处理语句)使用“LIMIT @count/ 2,1”和“ORDER BY ..”子句来获得中值

它们被包装在函数defn中，因此可以从一次调用中返回所有值。

如果您的范围是静态的，并且数据不经常更改，那么预先计算/存储这些值并使用存储的值，而不是每次都从头查询，可能会更有效。

归档完美中位数的单个查询:

SELECT 
COUNT(*) as total_rows, 
IF(count(*)%2 = 1, CAST(SUBSTRING_INDEX(SUBSTRING_INDEX( GROUP_CONCAT(val ORDER BY val SEPARATOR ','), ',', 50/100 * COUNT(*)), ',', -1) AS DECIMAL), ROUND((CAST(SUBSTRING_INDEX(SUBSTRING_INDEX( GROUP_CONCAT(val ORDER BY val SEPARATOR ','), ',', 50/100 * COUNT(*) + 1), ',', -1) AS DECIMAL) + CAST(SUBSTRING_INDEX(SUBSTRING_INDEX( GROUP_CONCAT(val ORDER BY val SEPARATOR ','), ',', 50/100 * COUNT(*)), ',', -1) AS DECIMAL)) / 2)) as median, 
AVG(val) as average 
FROM 
data