我使用下表的解决方案在MySQL:

CREATE TABLE transactions (
  transaction_id int , user_id int , merchant_name varchar(255), transaction_date date , amount int
);

INSERT INTO transactions (transaction_id, user_id, merchant_name, transaction_date, amount)  
VALUES (1, 1 ,'abc', '2015-08-17', 100),(2, 2, 'ced', '2015-2-17', 100),(3, 1, 'def', '2015-2-16', 121),
(4, 1 ,'ced', '2015-3-17', 110),(5, 1, 'ced', '2015-3-17', 150),(6, 2 ,'abc', '2015-4-17', 130), 
(7, 3 ,'ced', '2015-12-17', 10),(8, 3 ,'abc', '2015-8-17', 100),(9, 2 ,'abc', '2015-12-17', 140),(10, 1,'abc', '2015-9-17', 100),
(11, 1 ,'abc', '2015-08-17', 121),(12, 2 ,'ced', '2015-12-23', 130),(13, 1 ,'def', '2015-12-23', 13),(3, 4, 'abc', '2015-2-16', 120),(3, 4, 'def', '2015-2-16', 121),(3, 4, 'ced', '2015-2-16', 121);

计算“金额”列的中位数:

WITH Numbered AS 
(
SELECT *, COUNT(*) OVER () AS TotatRecords,
    ROW_NUMBER() OVER (ORDER BY amount) AS RowNum
FROM transactions
)
SELECT Avg(amount)
FROM Numbered
WHERE RowNum IN ( FLOOR((TotatRecords+1)/2), FLOOR((TotatRecords+2)/2) )
;

TotalRecords = 16 and Median = 120.5000

此查询将适用于两种情况，即偶数和奇数记录。

通常，我们不仅需要为整个表计算Median，还需要为与ID相关的聚合计算Median。换句话说，计算表中每个ID的中位数，其中每个ID有许多记录。(良好的性能和工作在许多SQL +修复偶数和赔率的问题，更多关于不同的中值方法的性能https://sqlperformance.com/2012/08/t-sql-queries/median)

SELECT our_id, AVG(1.0 * our_val) as Median
FROM
( SELECT our_id, our_val, 
  COUNT(*) OVER (PARTITION BY our_id) AS cnt,
  ROW_NUMBER() OVER (PARTITION BY our_id ORDER BY our_val) AS rn
  FROM our_table
) AS x
WHERE rn IN ((cnt + 1)/2, (cnt + 2)/2) GROUP BY our_id;

希望能有所帮助

我发现接受的解决方案在我的MySQL安装上不起作用，返回一个空集，但这个查询在我测试的所有情况下都适用:

SELECT x.val from data x, data y
GROUP BY x.val
HAVING SUM(SIGN(1-SIGN(y.val-x.val)))/COUNT(*) > .5
LIMIT 1

让我们创建一个名为numbers的示例表

这个答案是针对mysql数据库的

在postgres Sql中，它简单地使用per_cont函数

创建表数字( num INT, 频率整数 ）;

在数字表中插入值

插入数字 (7) 0 (1, 1), (2、3), (1) 3 (9,1), (1, 1), (2、3), (1) 3 (9,1);

——select * from numbers

作为递归num_frequency (num,frequency, i) （ 选择num,频率,1 从数字 UNION ALL 选择num,频率,i + 1 从num_frequency num_frequency的地方。I < num_frequency.frequency ）

select * (max(当numbers=lower_limit时，则num else null end)/2 +max(当数字=upper_limit时，则num else null end)/2)作为中位数 从( select *, total_number % 2, 情况下 当total_number%2=0时，total_number/2 Else (total_number+1)/2 end as lower_limit， 情况下 当total_number%2=0时，total_number/2+1 其他(total_number + 1) / 2 结束为upper_limit

从( Select *，max(numbers) over() as total_number from ( Select num,row_number() over(按num排序) 作为num_frequency中的数字 b) b) b)

基于@bob的回答，这将查询泛化为能够返回多个中位数，并按某些标准分组。

想想，例如，一个车场二手车的中位数销售价格，按年-月分组。

SELECT 
    period, 
    AVG(middle_values) AS 'median' 
FROM (
    SELECT t1.sale_price AS 'middle_values', t1.row_num, t1.period, t2.count
    FROM (
        SELECT 
            @last_period:=@period AS 'last_period',
            @period:=DATE_FORMAT(sale_date, '%Y-%m') AS 'period',
            IF (@period<>@last_period, @row:=1, @row:=@row+1) as `row_num`, 
            x.sale_price
          FROM listings AS x, (SELECT @row:=0) AS r
          WHERE 1
            -- where criteria goes here
          ORDER BY DATE_FORMAT(sale_date, '%Y%m'), x.sale_price
        ) AS t1
    LEFT JOIN (  
          SELECT COUNT(*) as 'count', DATE_FORMAT(sale_date, '%Y-%m') AS 'period'
          FROM listings x
          WHERE 1
            -- same where criteria goes here
          GROUP BY DATE_FORMAT(sale_date, '%Y%m')
        ) AS t2
        ON t1.period = t2.period
    ) AS t3
WHERE 
    row_num >= (count/2) 
    AND row_num <= ((count/2) + 1)
GROUP BY t3.period
ORDER BY t3.period;

你可以使用这里的用户定义函数。