In my opinion, one of the best things that happened to Planet MySQL lately, is Explain Extended, a blog by Alex Bolenok (also known as Quassnoi on Stackoverflow).

I never had the pleasure of meeting Alex in person, but his articles are always interesting and of high quality, and the SQL wizardry he pulls off is downright inspiring. I really feel humbled by the creativity of some of his solutions and his apparent experience with multiple RDBMS products.

Alex' most recent post is about aggregation, and finding a top 3 based on the aggregate:

In …

I just read SQL: Ranking without self join, in which Shlomi Noach shares a nice MySQL-specific trick based on user-defined variables to compute rankings.

Shlomi's trick reminds me somewhat of the trick I came across little over a year ago to caclulate percentiles. At that time, several people pointed out to me too that using user-defined variables in this way can be unreliable.The problem with user-defined variablesSo what is the problem exaclty? Well, whenever a query assigns to a variable, and that same variable is read in another part of the query, you're on thin ice. That's because the …

After stepping off of the GROUP_CONCAT() solution for calculating quantiles I figured it would be nice to find a better way to calculate the median too.
Solution
I previously wrote on how to calculate the median using GROUP_CONCAT(), but I think that this is a better way:

SELECT     AVG(length) AS median                 -- take the average of left and right median
,          MIN(length) AS left_median            -- 
,          MAX(length) AS right_median           --
,          @l          AS left_median_position   --
,          @r          AS right_median_position  --
FROM (
     SELECT     @n, length                       -- @n is just here to …

Are you getting fed up yet with my posts on calculating percentiles? Well, I'm sorry but I'm not quite finished.

Here's a simple, fast method to calculate the specified number of quantiles:

-- set the number of quantiles, for exmple:
--   quartiles: 4
--   deciles: 10
--   percentiles: 100

SET @quantiles:=4;  -- select quartiles

-- calculate all quantiles
-- 
--
SELECT     amount                     AS metric
,          @n DIV (@c DIV @quantiles) AS quantile
,          @n                         AS N
FROM       sakila.payment
CROSS JOIN (
            SELECT @n:=0                           -- rownumber
            ,      @c:=COUNT(*) …

My previous post on calculating percentiles with MySQL generated some comments and good discussion. In particular, I got some very interesting comments from Vladimir.

Basically, Vladimir was doubtful whether the GROUP_CONCAT() solution would be optimal in comparison to a JOIN. His proposal is to solve it like this:

SELECT   SUM(g1.r) sr
,        g2.length l
,        SUM(g1.r)/(SELECT COUNT(*) FROM film) p
FROM    (SELECT COUNT(*) r, length FROM film GROUP BY length) g1
JOIN    (SELECT COUNT(*) r, length FROM film GROUP BY length) g2
ON       g1.length < g2.length
GROUP BY g2.length
HAVING p > 0.9
ORDER BY p
LIMIT 1

First, this query sets up two identical subqueries in …

Yesterday, I was on the freenode ##pentaho irc channel when Andres Chaves asked me how to calculate the Nth percentile in MySQL. He saw a solution somewhere using subqueries, but wasn't too happy about it.

A while ago I wrote about calulating the median in MySQL, and it turns out the Nth percentile can be calculated using a similar, single-pass approach, not relying on subqueries, UDFs, or user-defined variables.
The percentile....
So, what is a percentile exactly? Here's what the wikipedia says:

A percentile is the value of a variable below which a certain percent of observations fall. So the 20th percentile is the value (or score) below which 20 …