Over partition by 2 columns SQL Server - sql

I took one of my previous exercises and added some complexity to it.
You can find my original problem under: select case with "over partition by"
The scenario: (using SQL Server 2012)
create table #testing (b varchar (20), a date, c int, e int)
insert into #testing (b,a,c,e)
values
('xf_1m','2015-03-02','1','3'),
('xf_3m','2015-03-02','2','5'),
('xf_5y','2015-03-02','4','2'),
('xf_10y','2015-03-02','3','6'),
('ay_10y','2015-03-02','7','2'),
('adfe_1m','2015-03-02','2','5'),
('xm_1m','2013-02-01','7','2'),
('xf_15y','2013-02-01','1','8'),
('xf_20y','2013-02-01','10','1')
After using this query:
select
b, a, c, e,
substring (b, 1, CHARINDEX ('_', b) - 1) rnc,
substring(b, CHARINDEX('_', b) + 1, LEN (b)) rnb,
case
when b like 'xf%' then --
(sum(c * e) over (partition by a )) end as sumProduct
into #testing2
from #testing
select
*,
case
when b like 'xf%' then --
(sum(c * e) over (partition by a )) end as sumProduct
into #testing3
from #testing2
select *
from #testing3
I am getting this:
Only that now I want to calculate the sumProduct partitioned by rnc and date (column a).
How to do this? I tried with group by, but i'm having troubles with the unequal number from the select and the number of items i'm grouping by.
So, I'd like to re-write somehow like this:
(sum(c * e) over (partition by a and partition by rnc )) as sumProduct

I'm not sure why you are using temporary tables, but you can partition by multiple columns just by including them in the partition by list:
select *,
(case when b like 'xf%'
then sum(c * e) over (partition by a, rnd )
end) as sumProduct
into #testing3
from #testing2;

Related

Perform loop and calculation on BigQuery Array type

My original data, B is an array of INT64:
And I want to calculate the difference between B[n+1] - B[n], hence result in a new table as follow:
I figured out I can somehow achieve this by using LOOP and IF condition:
DECLARE x INT64 DEFAULT 0;
LOOP
SET x = x + 1
IF(x < array_length(table.B))
THEN INSERT INTO newTable (SELECT A, B[OFFSET(x+1)] - B[OFFSET(x)]) from table
END IF;
END LOOP;
The problem is that the above idea doesn't work on each row of my data, cause I still need to loop through each row in my data table, but I can't find a way to integrate my scripting part into a normal query, where I can
SELECT A, [calculation script] from table
Can someone point me how can I do it? Or any better way to solve this problem?
Thank you.
Below actually works - BigQuery
select * replace(
array(select diff from (
select offset, lead(el) over(order by offset) - el as diff
from unnest(B) el with offset
) where not diff is null
order by offset
) as B
)
from `project.dataset.table` t
if to apply to sample data in your question - output is
You can use unnest() with offset for this purpose:
select id, a,
array_agg(b_el - prev_b_el order by n) as b_diffs
from (select t.*, b_el, lag(b_el) over (partition by t.id order by n) as prev_b_el
from t cross join
unnest(b) b_el with offset n
) t
where prev_b_el is not null
group by t.id, t.a

SQL List the percentage of names starting with A, B, C - Z from a column

I want to show the percentage of each alphabet of a name from a column.
ex. A = 20%, B = 30%, Z = 10% etc.
Names:
Apple
Ace
Benedict
Been
Broom
Car
Make
Safe
Thanksgiving
Zappers
You need LEFT() and COUNT() and GROUP BY to get the expected result:
Please find the sample execution:
CREATE TABLE TestTable (String VARCHAR (100));
INSERT INTO TestTable (String) VALUES
('Apple'),
('Ace'),
('Benedict'),
('Been'),
('Broom'),
('Car'),
('Make'),
('Safe'),
('Thanksgiving'),
('Zappers');
DECLARE #TCount AS INT = 0;
SELECT #TCount = COUNT(*) FROM TestTable;
SELECT LEFT(String, 1) AS FChar,
CONCAT(COUNT(LEFT(String, 1)) *100 / #TCount, '%') AS CharPercent
FROM TestTable
GROUP BY LEFT(String, 1)
ORDER BY LEFT(String, 1)
Working demo on db<>fiddle
You can use window functions. The correct logic is:
SELECT LEFT(name, 1) AS first_char,
COUNT(*) * 100.0 / SUM(COUNT(*)) OVER() AS pct
FROM t
GROUP BY LEFT(name, 1)
ORDER BY first_char;

Is there an equivalent of Excel's PERCENTRANK (column,value) in SQL?

Is there an equivalent of Excel's PERCENTRANK (column,value) in SQL? I think native SQL Server functions provide only percentiles from the same column, but am I missing something?
The problem is that I have two columns - A and B - and I need to use distribution of values from column A and then take values from another column and rank them against column A - how do values in B fit in distribution defined by column A (or, precisely: get CDF of column A at point defined by B).
Possible solutions:
Write UDF (they don't parallelize, do they?) - can you answer how could I efficiently structure such UDF?
Use SQL Server 2016 and integrate it with R (R code within SQL code)
Copy data to R, perform calculations, send back to server
Copy data to Excel and calculate it over there "manually", import results back to database
There are multiple columns with values and distributions I need to apply this strategy to, so I am looking for an efficient solution.
Edit - example:
column A column B result
10 16 0,20 =PERCENTRANK($A1:$A4, B1)
20 35 0,83 =PERCENTRANK($A1:$A4, B2)
30 10 0,00 =PERCENTRANK($A1:$A4, B3)
40 25 0,50 =PERCENTRANK($A1:$A4, B4)
This could serve as an approximate, not foolproof numerical solution with column being passed as a name:
CREATE FUNCTION [dbo].[PERCENTRANK_column](
#colname nvarchar(50)
)
RETURNS #resultingtable TABLE(
RowID int,
PercentRank float
)
AS
BEGIN
;WITH true_CDF AS (
SELECT
PERCENT_RANK() OVER (PARTITION BY 1 ORDER BY
CASE #colname
WHEN 'X' THEN X
WHEN 'Y' THEN Y
ELSE NULL
END
ASC) as PercentRank
,
CASE #colname
WHEN 'X' THEN X
WHEN 'Y' THEN Y
ELSE NULL
END AS selected_col
FROM dbo.MainTable
)
, selectColumn AS (
SELECT
m.RowID
,CASE #colname
WHEN 'X' THEN to_score_X
WHEN 'Y' THEN to_score_Y
ELSE NULL
END as to_score
FROM dbo.MainTable m
)
, added_Mins AS (
SELECT
B.RowID
, ABS(B.to_score - A.selected_col) as diff
, MIN(ABS(B.to_score - A.selected_col)) OVER (PARTITION BY 1) as lowest_difference
, A.PercentRank
FROM selectColumn B
CROSS JOIN true_CDF A
)
INSERT INTO #resultingtable
SELECT
RowID, PercentRank
FROM added_Mins
WHERE lowest_difference = diff
RETURN
END

Median depending on other variable in SQL

I want to calculate median conditionally, say separately for men and women in a sex variable as an example. I would like to use the modification of one of the following two alternative codes provided here http://sqlperformance.com/2012/08/t-sql-queries/median as the fastest method for calculating median.
Alternative 1
DECLARE #c BIGINT = (SELECT COUNT(*) FROM dbo.EvenRows);
SELECT AVG(1.0 * val)
FROM (
SELECT val FROM dbo.EvenRows
ORDER BY val
OFFSET (#c - 1) / 2 ROWS
FETCH NEXT 1 + (1 - #c % 2) ROWS ONLY
) AS x;
Alternative 2
SELECT #Median = AVG(1.0 * val)
FROM
(
SELECT o.val, rn = ROW_NUMBER() OVER (ORDER BY o.val), c.c
FROM dbo.EvenRows AS o
CROSS JOIN (SELECT c = COUNT(*) FROM dbo.EvenRows) AS c
) AS x
WHERE rn IN ((c + 1)/2, (c + 2)/2);
Where to put GROUP statement? Can someone advise me how to make a function with parameters MEDIAN(ColumnToCalculateMedian, ColumnContaingSex)

Simple way to calculate median with MySQL

What's the simplest (and hopefully not too slow) way to calculate the median with MySQL? I've used AVG(x) for finding the mean, but I'm having a hard time finding a simple way of calculating the median. For now, I'm returning all the rows to PHP, doing a sort, and then picking the middle row, but surely there must be some simple way of doing it in a single MySQL query.
Example data:
id | val
--------
1 4
2 7
3 2
4 2
5 9
6 8
7 3
Sorting on val gives 2 2 3 4 7 8 9, so the median should be 4, versus SELECT AVG(val) which == 5.
In MariaDB / MySQL:
SELECT AVG(dd.val) as median_val
FROM (
SELECT d.val, #rownum:=#rownum+1 as `row_number`, #total_rows:=#rownum
FROM data d, (SELECT #rownum:=0) r
WHERE d.val is NOT NULL
-- put some where clause here
ORDER BY d.val
) as dd
WHERE dd.row_number IN ( FLOOR((#total_rows+1)/2), FLOOR((#total_rows+2)/2) );
Steve Cohen points out, that after the first pass, #rownum will contain the total number of rows. This can be used to determine the median, so no second pass or join is needed.
Also AVG(dd.val) and dd.row_number IN(...) is used to correctly produce a median when there are an even number of records. Reasoning:
SELECT FLOOR((3+1)/2),FLOOR((3+2)/2); -- when total_rows is 3, avg rows 2 and 2
SELECT FLOOR((4+1)/2),FLOOR((4+2)/2); -- when total_rows is 4, avg rows 2 and 3
Finally, MariaDB 10.3.3+ contains a MEDIAN function
I just found another answer online in the comments:
For medians in almost any SQL:
SELECT x.val from data x, data y
GROUP BY x.val
HAVING SUM(SIGN(1-SIGN(y.val-x.val))) = (COUNT(*)+1)/2
Make sure your columns are well indexed and the index is used for filtering and sorting. Verify with the explain plans.
select count(*) from table --find the number of rows
Calculate the "median" row number. Maybe use: median_row = floor(count / 2).
Then pick it out of the list:
select val from table order by val asc limit median_row,1
This should return you one row with just the value you want.
I found the accepted solution didn't work on my MySQL install, returning an empty set, but this query worked for me in all situations that I tested it on:
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
Unfortunately, neither TheJacobTaylor's nor velcrow's answers return accurate results for current versions of MySQL.
Velcro's answer from above is close, but it does not calculate correctly for result sets with an even number of rows. Medians are defined as either 1) the middle number on odd numbered sets, or 2) the average of the two middle numbers on even number sets.
So, here's velcro's solution patched to handle both odd and even number sets:
SELECT AVG(middle_values) AS 'median' FROM (
SELECT t1.median_column AS 'middle_values' FROM
(
SELECT #row:=#row+1 as `row`, x.median_column
FROM median_table AS x, (SELECT #row:=0) AS r
WHERE 1
-- put some where clause here
ORDER BY x.median_column
) AS t1,
(
SELECT COUNT(*) as 'count'
FROM median_table x
WHERE 1
-- put same where clause here
) AS t2
-- the following condition will return 1 record for odd number sets, or 2 records for even number sets.
WHERE t1.row >= t2.count/2 and t1.row <= ((t2.count/2) +1)) AS t3;
To use this, follow these 3 easy steps:
Replace "median_table" (2 occurrences) in the above code with the name of your table
Replace "median_column" (3 occurrences) with the column name you'd like to find a median for
If you have a WHERE condition, replace "WHERE 1" (2 occurrences) with your where condition
I propose a faster way.
Get the row count:
SELECT CEIL(COUNT(*)/2) FROM data;
Then take the middle value in a sorted subquery:
SELECT max(val) FROM (SELECT val FROM data ORDER BY val limit #middlevalue) x;
I tested this with a 5x10e6 dataset of random numbers and it will find the median in under 10 seconds.
Install and use this mysql statistical functions: http://www.xarg.org/2012/07/statistical-functions-in-mysql/
After that, calculate median is easy:
SELECT median(val) FROM data;
A comment on this page in the MySQL documentation has the following suggestion:
-- (mostly) High Performance scaling MEDIAN function per group
-- Median defined in http://en.wikipedia.org/wiki/Median
--
-- by Peter Hlavac
-- 06.11.2008
--
-- Example Table:
DROP table if exists table_median;
CREATE TABLE table_median (id INTEGER(11),val INTEGER(11));
COMMIT;
INSERT INTO table_median (id, val) VALUES
(1, 7), (1, 4), (1, 5), (1, 1), (1, 8), (1, 3), (1, 6),
(2, 4),
(3, 5), (3, 2),
(4, 5), (4, 12), (4, 1), (4, 7);
-- Calculating the MEDIAN
SELECT #a := 0;
SELECT
id,
AVG(val) AS MEDIAN
FROM (
SELECT
id,
val
FROM (
SELECT
-- Create an index n for every id
#a := (#a + 1) mod o.c AS shifted_n,
IF(#a mod o.c=0, o.c, #a) AS n,
o.id,
o.val,
-- the number of elements for every id
o.c
FROM (
SELECT
t_o.id,
val,
c
FROM
table_median t_o INNER JOIN
(SELECT
id,
COUNT(1) AS c
FROM
table_median
GROUP BY
id
) t2
ON (t2.id = t_o.id)
ORDER BY
t_o.id,val
) o
) a
WHERE
IF(
-- if there is an even number of elements
-- take the lower and the upper median
-- and use AVG(lower,upper)
c MOD 2 = 0,
n = c DIV 2 OR n = (c DIV 2)+1,
-- if its an odd number of elements
-- take the first if its only one element
-- or take the one in the middle
IF(
c = 1,
n = 1,
n = c DIV 2 + 1
)
)
) a
GROUP BY
id;
-- Explanation:
-- The Statement creates a helper table like
--
-- n id val count
-- ----------------
-- 1, 1, 1, 7
-- 2, 1, 3, 7
-- 3, 1, 4, 7
-- 4, 1, 5, 7
-- 5, 1, 6, 7
-- 6, 1, 7, 7
-- 7, 1, 8, 7
--
-- 1, 2, 4, 1
-- 1, 3, 2, 2
-- 2, 3, 5, 2
--
-- 1, 4, 1, 4
-- 2, 4, 5, 4
-- 3, 4, 7, 4
-- 4, 4, 12, 4
-- from there we can select the n-th element on the position: count div 2 + 1
If MySQL has ROW_NUMBER, then the MEDIAN is (be inspired by this SQL Server query):
WITH Numbered AS
(
SELECT *, COUNT(*) OVER () AS Cnt,
ROW_NUMBER() OVER (ORDER BY val) AS RowNum
FROM yourtable
)
SELECT id, val
FROM Numbered
WHERE RowNum IN ((Cnt+1)/2, (Cnt+2)/2)
;
The IN is used in case you have an even number of entries.
If you want to find the median per group, then just PARTITION BY group in your OVER clauses.
Rob
Most of the solutions above work only for one field of the table, you might need to get the median (50th percentile) for many fields on the query.
I use this:
SELECT CAST(SUBSTRING_INDEX(SUBSTRING_INDEX(
GROUP_CONCAT(field_name ORDER BY field_name SEPARATOR ','),
',', 50/100 * COUNT(*) + 1), ',', -1) AS DECIMAL) AS `Median`
FROM table_name;
You can replace the "50" in example above to any percentile, is very efficient.
Just make sure you have enough memory for the GROUP_CONCAT, you can change it with:
SET group_concat_max_len = 10485760; #10MB max length
More details: http://web.performancerasta.com/metrics-tips-calculating-95th-99th-or-any-percentile-with-single-mysql-query/
I have this below code which I found on HackerRank and it is pretty simple and works in each and every case.
SELECT M.MEDIAN_COL FROM MEDIAN_TABLE M WHERE
(SELECT COUNT(MEDIAN_COL) FROM MEDIAN_TABLE WHERE MEDIAN_COL < M.MEDIAN_COL ) =
(SELECT COUNT(MEDIAN_COL) FROM MEDIAN_TABLE WHERE MEDIAN_COL > M.MEDIAN_COL );
You could use the user-defined function that's found here.
Building off of velcro's answer, for those of you having to do a median off of something that is grouped by another parameter:
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) r
ORDER BY grp_field, d.val
) as t1 JOIN (
SELECT grp_field, count(*) as total_rows
FROM data d
GROUP BY grp_field
) as t2
ON t1.grp_field = t2.grp_field
WHERE t1.row_number=floor(total_rows/2)+1;
Takes care about an odd value count - gives the avg of the two values in the middle in that case.
SELECT AVG(val) FROM
( SELECT x.id, x.val from data x, data y
GROUP BY x.id, x.val
HAVING SUM(SIGN(1-SIGN(IF(y.val-x.val=0 AND x.id != y.id, SIGN(x.id-y.id), y.val-x.val)))) IN (ROUND((COUNT(*))/2), ROUND((COUNT(*)+1)/2))
) sq
My code, efficient without tables or additional variables:
SELECT
((SUBSTRING_INDEX(SUBSTRING_INDEX(group_concat(val order by val), ',', floor(1+((count(val)-1) / 2))), ',', -1))
+
(SUBSTRING_INDEX(SUBSTRING_INDEX(group_concat(val order by val), ',', ceiling(1+((count(val)-1) / 2))), ',', -1)))/2
as median
FROM table;
Single query to archive the perfect median:
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
Optionally, you could also do this in a stored procedure:
DROP PROCEDURE IF EXISTS median;
DELIMITER //
CREATE PROCEDURE median (table_name VARCHAR(255), column_name VARCHAR(255), where_clause VARCHAR(255))
BEGIN
-- Set default parameters
IF where_clause IS NULL OR where_clause = '' THEN
SET where_clause = 1;
END IF;
-- Prepare statement
SET #sql = CONCAT(
"SELECT AVG(middle_values) AS 'median' FROM (
SELECT t1.", column_name, " AS 'middle_values' FROM
(
SELECT #row:=#row+1 as `row`, x.", column_name, "
FROM ", table_name," AS x, (SELECT #row:=0) AS r
WHERE ", where_clause, " ORDER BY x.", column_name, "
) AS t1,
(
SELECT COUNT(*) as 'count'
FROM ", table_name, " x
WHERE ", where_clause, "
) AS t2
-- the following condition will return 1 record for odd number sets, or 2 records for even number sets.
WHERE t1.row >= t2.count/2
AND t1.row <= ((t2.count/2)+1)) AS t3
");
-- Execute statement
PREPARE stmt FROM #sql;
EXECUTE stmt;
END//
DELIMITER ;
-- Sample usage:
-- median(table_name, column_name, where_condition);
CALL median('products', 'price', NULL);
My solution presented below works in just one query without creation of table, variable or even sub-query.
Plus, it allows you to get median for each group in group-by queries (this is what i needed !):
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`;
It works because of a smart use of group_concat and substring_index.
But, to allow big group_concat, you have to set group_concat_max_len to a higher value (1024 char by default).
You can set it like that (for current sql session) :
SET SESSION group_concat_max_len = 10000;
-- up to 4294967295 in 32-bits platform.
More infos for group_concat_max_len: https://dev.mysql.com/doc/refman/5.1/en/server-system-variables.html#sysvar_group_concat_max_len
Another riff on Velcrow's answer, but uses a single intermediate table and takes advantage of the variable used for row numbering to get the count, rather than performing an extra query to calculate it. Also starts the count so that the first row is row 0 to allow simply using Floor and Ceil to select the median row(s).
SELECT Avg(tmp.val) as median_val
FROM (SELECT inTab.val, #rows := #rows + 1 as rowNum
FROM data as inTab, (SELECT #rows := -1) as init
-- Replace with better where clause or delete
WHERE 2 > 1
ORDER BY inTab.val) as tmp
WHERE tmp.rowNum in (Floor(#rows / 2), Ceil(#rows / 2));
Knowing exact row count you can use this query:
SELECT <value> AS VAL FROM <table> ORDER BY VAL LIMIT 1 OFFSET <half>
Where <half> = ceiling(<size> / 2.0) - 1
SELECT
SUBSTRING_INDEX(
SUBSTRING_INDEX(
GROUP_CONCAT(field ORDER BY field),
',',
((
ROUND(
LENGTH(GROUP_CONCAT(field)) -
LENGTH(
REPLACE(
GROUP_CONCAT(field),
',',
''
)
)
) / 2) + 1
)),
',',
-1
)
FROM
table
The above seems to work for me.
I used a two query approach:
first one to get count, min, max and avg
second one (prepared statement) with a "LIMIT #count/2, 1" and "ORDER BY .." clauses to get the median value
These are wrapped in a function defn, so all values can be returned from one call.
If your ranges are static and your data does not change often, it might be more efficient to precompute/store these values and use the stored values instead of querying from scratch every time.
as i just needed a median AND percentile solution, I made a simple and quite flexible function based on the findings in this thread. I know that I am happy myself if I find "readymade" functions that are easy to include in my projects, so I decided to quickly share:
function mysql_percentile($table, $column, $where, $percentile = 0.5) {
$sql = "
SELECT `t1`.`".$column."` as `percentile` FROM (
SELECT #rownum:=#rownum+1 as `row_number`, `d`.`".$column."`
FROM `".$table."` `d`, (SELECT #rownum:=0) `r`
".$where."
ORDER BY `d`.`".$column."`
) as `t1`,
(
SELECT count(*) as `total_rows`
FROM `".$table."` `d`
".$where."
) as `t2`
WHERE 1
AND `t1`.`row_number`=floor(`total_rows` * ".$percentile.")+1;
";
$result = sql($sql, 1);
if (!empty($result)) {
return $result['percentile'];
} else {
return 0;
}
}
Usage is very easy, example from my current project:
...
$table = DBPRE."zip_".$slug;
$column = 'seconds';
$where = "WHERE `reached` = '1' AND `time` >= '".$start_time."'";
$reaching['median'] = mysql_percentile($table, $column, $where, 0.5);
$reaching['percentile25'] = mysql_percentile($table, $column, $where, 0.25);
$reaching['percentile75'] = mysql_percentile($table, $column, $where, 0.75);
...
Here is my way . Of course, you could put it into a procedure :-)
SET #median_counter = (SELECT FLOOR(COUNT(*)/2) - 1 AS `median_counter` FROM `data`);
SET #median = CONCAT('SELECT `val` FROM `data` ORDER BY `val` LIMIT ', #median_counter, ', 1');
PREPARE median FROM #median;
EXECUTE median;
You could avoid the variable #median_counter, if you substitude it:
SET #median = CONCAT( 'SELECT `val` FROM `data` ORDER BY `val` LIMIT ',
(SELECT FLOOR(COUNT(*)/2) - 1 AS `median_counter` FROM `data`),
', 1'
);
PREPARE median FROM #median;
EXECUTE median;
After reading all previous ones they didn't match with my actual requirement so I implemented my own one which doesn't need any procedure or complicate statements, just I GROUP_CONCAT all values from the column I wanted to obtain the MEDIAN and applying a COUNT DIV BY 2 I extract the value in from the middle of the list like the following query does :
(POS is the name of the column I want to get its median)
(query) SELECT
SUBSTRING_INDEX (
SUBSTRING_INDEX (
GROUP_CONCAT(pos ORDER BY CAST(pos AS SIGNED INTEGER) desc SEPARATOR ';')
, ';', COUNT(*)/2 )
, ';', -1 ) AS `pos_med`
FROM table_name
GROUP BY any_criterial
I hope this could be useful for someone in the way many of other comments were for me from this website.
Based on #bob's answer, this generalizes the query to have the ability to return multiple medians, grouped by some criteria.
Think, e.g., median sale price for used cars in a car lot, grouped by year-month.
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;
create table med(id integer);
insert into med(id) values(1);
insert into med(id) values(2);
insert into med(id) values(3);
insert into med(id) values(4);
insert into med(id) values(5);
insert into med(id) values(6);
select (MIN(count)+MAX(count))/2 from
(select case when (select count(*) from
med A where A.id<B.id)=(select count(*)/2 from med) OR
(select count(*) from med A where A.id>B.id)=(select count(*)/2
from med) then cast(B.id as float)end as count from med B) C;
?column?
----------
3.5
(1 row)
OR
select cast(avg(id) as float) from
(select t1.id from med t1 JOIN med t2 on t1.id!= t2.id
group by t1.id having ABS(SUM(SIGN(t1.id-t2.id)))=1) A;
Often, we may need to calculate Median not just for the whole table, but for aggregates with respect to our ID. In other words, calculate median for each ID in our table, where each ID has many records. (good performance and works in many SQL + fixes problem of even and odds, more about performance of different Median-methods 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;
Hope it helps
MySQL has supported window functions since version 8.0, you can use ROW_NUMBER or DENSE_RANK (DO NOT use RANK as it assigns the same rank to same values, like in sports ranking):
SELECT AVG(t1.val) AS median_val
FROM (SELECT val,
ROW_NUMBER() OVER(ORDER BY val) AS rownum
FROM data) t1,
(SELECT COUNT(*) AS num_records FROM data) t2
WHERE t1.row_num IN
(FLOOR((t2.num_records + 1) / 2),
FLOOR((t2.num_records + 2) / 2));
A simple way to calculate Median in 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;
The most simple and fast way to calculate median in mysql.
select x.col
from (select lat_n,
count(1) over (partition by 'A') as total_rows,
row_number() over (order by col asc) as rank_Order
from station ft) x
where x.rank_Order = round(x.total_rows / 2.0, 0)