This section describes group (aggregate) functions that operate on sets of values.

**Table 12.25 Aggregate (GROUP BY) Functions**

Name | Description |
---|---|

`AVG()` |
Return the average value of the argument |

`BIT_AND()` |
Return bitwise AND |

`BIT_OR()` |
Return bitwise OR |

`BIT_XOR()` |
Return bitwise XOR |

`COUNT()` |
Return a count of the number of rows returned |

`COUNT(DISTINCT)` |
Return the count of a number of different values |

`GROUP_CONCAT()` |
Return a concatenated string |

`JSON_ARRAYAGG()` |
Return result set as a single JSON array |

`JSON_OBJECTAGG()` |
Return result set as a single JSON object |

`MAX()` |
Return the maximum value |

`MIN()` |
Return the minimum value |

`STD()` |
Return the population standard deviation |

`STDDEV()` |
Return the population standard deviation |

`STDDEV_POP()` |
Return the population standard deviation |

`STDDEV_SAMP()` |
Return the sample standard deviation |

`SUM()` |
Return the sum |

`VAR_POP()` |
Return the population standard variance |

`VAR_SAMP()` |
Return the sample variance |

`VARIANCE()` |
Return the population standard variance |

Unless otherwise stated, group functions ignore
`NULL`

values.

If you use a group function in a statement containing no
`GROUP BY`

clause, it is equivalent to grouping
on all rows. For more information, see
Section 12.19.3, “MySQL Handling of GROUP BY”.

Most aggregate functions can be used as window functions. Those
that can be used this way are signified in their syntax
description by
`[`

,
representing an optional * over_clause*]

`OVER`

clause.
*is described in Section 12.20.2, “Window Function Concepts and Syntax”, which also includes other information about window function usage.*

`over_clause`

For numeric arguments, the variance and standard deviation
functions return a `DOUBLE`

value.
The `SUM()`

and
`AVG()`

functions return a
`DECIMAL`

value for exact-value
arguments (integer or `DECIMAL`

),
and a `DOUBLE`

value for
approximate-value arguments
(`FLOAT`

or
`DOUBLE`

).

The `SUM()`

and
`AVG()`

aggregate functions do not
work with temporal values. (They convert the values to numbers,
losing everything after the first nonnumeric character.) To work
around this problem, convert to numeric units, perform the
aggregate operation, and convert back to a temporal value.
Examples:

`SELECT SEC_TO_TIME(SUM(TIME_TO_SEC(`*time_col*))) FROM *tbl_name*;
SELECT FROM_DAYS(SUM(TO_DAYS(*date_col*))) FROM *tbl_name*;

Functions such as `SUM()`

or
`AVG()`

that expect a numeric
argument cast the argument to a number if necessary. For
`SET`

or
`ENUM`

values, the cast operation
causes the underlying numeric value to be used.

The `BIT_AND()`

,
`BIT_OR()`

, and
`BIT_XOR()`

aggregate functions
perform bit operations. Prior to MySQL 8.0, bit functions and
operators required `BIGINT`

(64-bit
integer) arguments and returned
`BIGINT`

values, so they had a
maximum range of 64 bits.
Non-`BIGINT`

arguments were
converted to `BIGINT`

prior to
performing the operation and truncation could occur.

In MySQL 8.0, bit functions and operators permit binary string
type arguments (`BINARY`

,
`VARBINARY`

, and the
`BLOB`

types) and return a value of
like type, which enables them to take arguments and produce
return values larger than 64 bits. For discussion about argument
evaluation and result types for bit operations, see the
introductory discussion in Section 12.12, “Bit Functions and Operators”.

`AVG([DISTINCT]`

) [`expr`

]`over_clause`

Returns the average value of

. The`expr`

`DISTINCT`

option can be used to return the average of the distinct values of.`expr`

If there are no matching rows,

`AVG()`

returns`NULL`

.This function executes as a window function if

is present.`over_clause`

is as described in Section 12.20.2, “Window Function Concepts and Syntax”; it cannot be used with`over_clause`

`DISTINCT`

.`mysql> SELECT student_name, AVG(test_score) FROM student GROUP BY student_name;`

Returns the bitwise

`AND`

of all bits in.`expr`

The result type depends on whether the function argument values are evaluated as binary strings or numbers:

Binary-string evaluation occurs when the argument values have a binary string type, and the argument is not a hexadecimal literal, bit literal, or

`NULL`

literal. Numeric evaluation occurs otherwise, with argument value conversion to unsigned 64-bit integers as necessary.Binary-string evaluation produces a binary string of the same length as the argument values. If argument values have unequal lengths, an

`ER_INVALID_BITWISE_OPERANDS_SIZE`

error occurs. If the argument size exceeds 511 bytes, an`ER_INVALID_BITWISE_AGGREGATE_OPERANDS_SIZE`

error occurs. Numeric evaluation produces an unsigned 64-bit integer.

If there are no matching rows,

`BIT_AND()`

returns a neutral value (all bits set to 1) having the same length as the argument values.`NULL`

values do not affect the result unless all values are`NULL`

. In that case, the result is a neutral value having the same length as the argument values.For more information discussion about argument evaluation and result types, see the introductory discussion in Section 12.12, “Bit Functions and Operators”.

As of MySQL 8.0.12, this function executes as a window function if

is present.`over_clause`

is as described in Section 12.20.2, “Window Function Concepts and Syntax”.`over_clause`

Returns the bitwise

`OR`

of all bits in.`expr`

The result type depends on whether the function argument values are evaluated as binary strings or numbers:

Binary-string evaluation occurs when the argument values have a binary string type, and the argument is not a hexadecimal literal, bit literal, or

`NULL`

literal. Numeric evaluation occurs otherwise, with argument value conversion to unsigned 64-bit integers as necessary.Binary-string evaluation produces a binary string of the same length as the argument values. If argument values have unequal lengths, an

`ER_INVALID_BITWISE_OPERANDS_SIZE`

error occurs. If the argument size exceeds 511 bytes, an`ER_INVALID_BITWISE_AGGREGATE_OPERANDS_SIZE`

error occurs. Numeric evaluation produces an unsigned 64-bit integer.

If there are no matching rows,

`BIT_OR()`

returns a neutral value (all bits set to 0) having the same length as the argument values.`NULL`

values do not affect the result unless all values are`NULL`

. In that case, the result is a neutral value having the same length as the argument values.For more information discussion about argument evaluation and result types, see the introductory discussion in Section 12.12, “Bit Functions and Operators”.

As of MySQL 8.0.12, this function executes as a window function if

is present.`over_clause`

is as described in Section 12.20.2, “Window Function Concepts and Syntax”.`over_clause`

Returns the bitwise

`XOR`

of all bits in.`expr`

The result type depends on whether the function argument values are evaluated as binary strings or numbers:

Binary-string evaluation occurs when the argument values have a binary string type, and the argument is not a hexadecimal literal, bit literal, or

`NULL`

literal. Numeric evaluation occurs otherwise, with argument value conversion to unsigned 64-bit integers as necessary.Binary-string evaluation produces a binary string of the same length as the argument values. If argument values have unequal lengths, an

`ER_INVALID_BITWISE_OPERANDS_SIZE`

error occurs. If the argument size exceeds 511 bytes, an`ER_INVALID_BITWISE_AGGREGATE_OPERANDS_SIZE`

error occurs. Numeric evaluation produces an unsigned 64-bit integer.

If there are no matching rows,

`BIT_XOR()`

returns a neutral value (all bits set to 0) having the same length as the argument values.`NULL`

values do not affect the result unless all values are`NULL`

. In that case, the result is a neutral value having the same length as the argument values.For more information discussion about argument evaluation and result types, see the introductory discussion in Section 12.12, “Bit Functions and Operators”.

As of MySQL 8.0.12, this function executes as a window function if

is present.`over_clause`

is as described in Section 12.20.2, “Window Function Concepts and Syntax”.`over_clause`

Returns a count of the number of non-

`NULL`

values ofin the rows retrieved by a`expr`

`SELECT`

statement. The result is a`BIGINT`

value.If there are no matching rows,

`COUNT()`

returns`0`

.This function executes as a window function if

is present.`over_clause`

is as described in Section 12.20.2, “Window Function Concepts and Syntax”.`over_clause`

`mysql> SELECT student.student_name,COUNT(*) FROM student,course WHERE student.student_id=course.student_id GROUP BY student_name;`

`COUNT(*)`

is somewhat different in that it returns a count of the number of rows retrieved, whether or not they contain`NULL`

values.For transactional storage engines such as

`InnoDB`

, storing an exact row count is problematic. Multiple transactions may be occurring at the same time, each of which may affect the count.`InnoDB`

does not keep an internal count of rows in a table because concurrent transactions might “see” different numbers of rows at the same time. Consequently,`SELECT COUNT(*)`

statements only count rows visible to the current transaction.As of MySQL 8.0.13,

`SELECT COUNT(*) FROM`

query performance for`tbl_name`

`InnoDB`

tables is optimized for single-threaded workloads if there are no extra clauses such as`WHERE`

or`GROUP BY`

.`InnoDB`

processes`SELECT COUNT(*)`

statements by traversing the smallest available secondary index unless an index or optimizer hint directs the optimizer to use a different index. If a secondary index is not present,`InnoDB`

processes`SELECT COUNT(*)`

statements by scanning the clustered index.Processing

`SELECT COUNT(*)`

statements takes some time if index records are not entirely in the buffer pool. For a faster count, create a counter table and let your application update it according to the inserts and deletes it does. However, this method may not scale well in situations where thousands of concurrent transactions are initiating updates to the same counter table. If an approximate row count is sufficient, use`SHOW TABLE STATUS`

.`InnoDB`

handles`SELECT COUNT(*)`

and`SELECT COUNT(1)`

operations in the same way. There is no performance difference.For

`MyISAM`

tables,`COUNT(*)`

is optimized to return very quickly if the`SELECT`

retrieves from one table, no other columns are retrieved, and there is no`WHERE`

clause. For example:`mysql> SELECT COUNT(*) FROM student;`

This optimization only applies to

`MyISAM`

tables, because an exact row count is stored for this storage engine and can be accessed very quickly.`COUNT(1)`

is only subject to the same optimization if the first column is defined as`NOT NULL`

.`COUNT(DISTINCT`

,[`expr`

...])`expr`

Returns a count of the number of rows with different non-

`NULL`

values.`expr`

If there are no matching rows,

`COUNT(DISTINCT)`

returns`0`

.`mysql> SELECT COUNT(DISTINCT results) FROM student;`

In MySQL, you can obtain the number of distinct expression combinations that do not contain

`NULL`

by giving a list of expressions. In standard SQL, you would have to do a concatenation of all expressions inside`COUNT(DISTINCT ...)`

.This function returns a string result with the concatenated non-

`NULL`

values from a group. It returns`NULL`

if there are no non-`NULL`

values. The full syntax is as follows:`GROUP_CONCAT([DISTINCT]`

*expr*[,*expr*...] [ORDER BY {*unsigned_integer*|*col_name*|*expr*} [ASC | DESC] [,*col_name*...]] [SEPARATOR*str_val*])`mysql> SELECT student_name, GROUP_CONCAT(test_score) FROM student GROUP BY student_name;`

Or:

`mysql> SELECT student_name, GROUP_CONCAT(DISTINCT test_score ORDER BY test_score DESC SEPARATOR ' ') FROM student GROUP BY student_name;`

In MySQL, you can get the concatenated values of expression combinations. To eliminate duplicate values, use the

`DISTINCT`

clause. To sort values in the result, use the`ORDER BY`

clause. To sort in reverse order, add the`DESC`

(descending) keyword to the name of the column you are sorting by in the`ORDER BY`

clause. The default is ascending order; this may be specified explicitly using the`ASC`

keyword. The default separator between values in a group is comma (`,`

). To specify a separator explicitly, use`SEPARATOR`

followed by the string literal value that should be inserted between group values. To eliminate the separator altogether, specify`SEPARATOR ''`

.The result is truncated to the maximum length that is given by the

`group_concat_max_len`

system variable, which has a default value of 1024. The value can be set higher, although the effective maximum length of the return value is constrained by the value of`max_allowed_packet`

. The syntax to change the value of`group_concat_max_len`

at runtime is as follows, whereis an unsigned integer:`val`

`SET [GLOBAL | SESSION] group_concat_max_len =`

*val*;The return value is a nonbinary or binary string, depending on whether the arguments are nonbinary or binary strings. The result type is

`TEXT`

or`BLOB`

unless`group_concat_max_len`

is less than or equal to 512, in which case the result type is`VARCHAR`

or`VARBINARY`

.See also

`CONCAT()`

and`CONCAT_WS()`

: Section 12.5, “String Functions”.Aggregates a result set as a single

`JSON`

array whose elements consist of the rows. The order of elements in this array is undefined. The function acts on a column or an expression that evaluates to a single value. Returns`NULL`

if the result contains no rows, or in the event of an error.`mysql> SELECT o_id, attribute, value FROM t3; +------+-----------+-------+ | o_id | attribute | value | +------+-----------+-------+ | 2 | color | red | | 2 | fabric | silk | | 3 | color | green | | 3 | shape | square| +------+-----------+-------+ 4 rows in set (0.00 sec) mysql> SELECT o_id, JSON_ARRAYAGG(attribute) AS attributes > FROM t3 GROUP BY o_id; +------+---------------------+ | o_id | attributes | +------+---------------------+ | 2 | ["color", "fabric"] | | 3 | ["color", "shape"] | +------+---------------------+ 2 rows in set (0.00 sec)`

Takes two column names or expressions as arguments, the first of these being used as a key and the second as a value, and returns a JSON object containing key-value pairs. Returns

`NULL`

if the result contains no rows, or in the event of an error. An error occurs if any key name is`NULL`

or the number of arguments is not equal to 2.`mysql> SELECT o_id, attribute, value FROM t3; +------+-----------+-------+ | o_id | attribute | value | +------+-----------+-------+ | 2 | color | red | | 2 | fabric | silk | | 3 | color | green | | 3 | shape | square| +------+-----------+-------+ 4 rows in set (0.00 sec) mysql> SELECT o_id, JSON_OBJECTAGG(attribute, value) FROM t3 GROUP BY o_id; +------+----------------------------------------+ | o_id | JSON_OBJECTAGG(attribute, name) | +------+----------------------------------------+ | 2 | {"color": "red", "fabric": "silk"} | | 3 | {"color": "green", "shape": "square"} | +------+----------------------------------------+ 1 row in set (0.00 sec)`

`MAX([DISTINCT]`

) [`expr`

]`over_clause`

Returns the maximum value of

.`expr`

`MAX()`

may take a string argument; in such cases, it returns the maximum string value. See Section 8.3.1, “How MySQL Uses Indexes”. The`DISTINCT`

keyword can be used to find the maximum of the distinct values of, however, this produces the same result as omitting`expr`

`DISTINCT`

.If there are no matching rows,

`MAX()`

returns`NULL`

.This function executes as a window function if

is present.`over_clause`

is as described in Section 12.20.2, “Window Function Concepts and Syntax”; it cannot be used with`over_clause`

`DISTINCT`

.`mysql> SELECT student_name, MIN(test_score), MAX(test_score) FROM student GROUP BY student_name;`

For

`MAX()`

, MySQL currently compares`ENUM`

and`SET`

columns by their string value rather than by the string's relative position in the set. This differs from how`ORDER BY`

compares them.`MIN([DISTINCT]`

) [`expr`

]`over_clause`

Returns the minimum value of

.`expr`

`MIN()`

may take a string argument; in such cases, it returns the minimum string value. See Section 8.3.1, “How MySQL Uses Indexes”. The`DISTINCT`

keyword can be used to find the minimum of the distinct values of, however, this produces the same result as omitting`expr`

`DISTINCT`

.If there are no matching rows,

`MIN()`

returns`NULL`

.This function executes as a window function if

is present.`over_clause`

is as described in Section 12.20.2, “Window Function Concepts and Syntax”; it cannot be used with`over_clause`

`DISTINCT`

.`mysql> SELECT student_name, MIN(test_score), MAX(test_score) FROM student GROUP BY student_name;`

For

`MIN()`

, MySQL currently compares`ENUM`

and`SET`

columns by their string value rather than by the string's relative position in the set. This differs from how`ORDER BY`

compares them.Returns the population standard deviation of

.`expr`

`STD()`

is a synonym for the standard SQL function`STDDEV_POP()`

, provided as a MySQL extension.If there are no matching rows,

`STD()`

returns`NULL`

.This function executes as a window function if

is present.`over_clause`

is as described in Section 12.20.2, “Window Function Concepts and Syntax”.`over_clause`

Returns the population standard deviation of

.`expr`

`STDDEV()`

is a synonym for the standard SQL function`STDDEV_POP()`

, provided for compatibility with Oracle.If there are no matching rows,

`STDDEV()`

returns`NULL`

.This function executes as a window function if

is present.`over_clause`

is as described in Section 12.20.2, “Window Function Concepts and Syntax”.`over_clause`

`STDDEV_POP(`

) [`expr`

]`over_clause`

Returns the population standard deviation of

(the square root of`expr`

`VAR_POP()`

). You can also use`STD()`

or`STDDEV()`

, which are equivalent but not standard SQL.If there are no matching rows,

`STDDEV_POP()`

returns`NULL`

.is present.`over_clause`

is as described in Section 12.20.2, “Window Function Concepts and Syntax”.`over_clause`

`STDDEV_SAMP(`

) [`expr`

]`over_clause`

Returns the sample standard deviation of

(the square root of`expr`

`VAR_SAMP()`

.If there are no matching rows,

`STDDEV_SAMP()`

returns`NULL`

.is present.`over_clause`

is as described in Section 12.20.2, “Window Function Concepts and Syntax”.`over_clause`

`SUM([DISTINCT]`

) [`expr`

]`over_clause`

Returns the sum of

. If the return set has no rows,`expr`

`SUM()`

returns`NULL`

. The`DISTINCT`

keyword can be used to sum only the distinct values of.`expr`

If there are no matching rows,

`SUM()`

returns`NULL`

.is present.`over_clause`

is as described in Section 12.20.2, “Window Function Concepts and Syntax”; it cannot be used with`over_clause`

`DISTINCT`

.Returns the population standard variance of

. It considers rows as the whole population, not as a sample, so it has the number of rows as the denominator. You can also use`expr`

`VARIANCE()`

, which is equivalent but is not standard SQL.If there are no matching rows,

`VAR_POP()`

returns`NULL`

.is present.`over_clause`

is as described in Section 12.20.2, “Window Function Concepts and Syntax”.`over_clause`

Returns the sample variance of

. That is, the denominator is the number of rows minus one.`expr`

If there are no matching rows,

`VAR_SAMP()`

returns`NULL`

.is present.`over_clause`

is as described in Section 12.20.2, “Window Function Concepts and Syntax”.`over_clause`

Returns the population standard variance of

.`expr`

`VARIANCE()`

is a synonym for the standard SQL function`VAR_POP()`

, provided as a MySQL extension.If there are no matching rows,

`VARIANCE()`

returns`NULL`

.is present.`over_clause`

is as described in Section 12.20.2, “Window Function Concepts and Syntax”.`over_clause`

SELECT COUNT( IF(x=1, 1, NULL) ) AS c;

SELECT SUM( IF(x=1, 1, 0) ) AS c;

SELECT COUNT(x=1 OR NULL) AS c;

The above 3 statements are equivalent. Though the last is not immediately obvious how its working. The condition x=1 is evaluated as TRUE or FALSE. If it is TRUE, then the lazy evaluation of the OR means that it exits and runs COUNT(TRUE). When x=1 is FALSE, you get FALSE OR NULL, which evaluates to NULL, so you get COUNT(NULL). This means you only COUNT the lines where x=1.

It is also worth noting that in all cases above you can have any condition e.g. x>1, x IN (1,2,3), (x=1 AND y=2)

i.e. COUNT( (x=1 AND y=2) OR NULL ) as c

Variance() and Var_pop() return the Variance. The variance of a random variable or distribution is the mean of the squared deviation of that variable from its mean.

Coefficient of Variation must be calcuated by STDDEV_POP(x)/Avg(x), as far as I know there is not a built in function.

http://en.wikipedia.org/wiki/Coefficient_of_variation

http://en.wikipedia.org/wiki/Variance

FIRST Aggregate Function MySQL equivalent is MIN

MIN returns the lowest number for numeric fields

MIN returns the first line in the GROUP BY Clause base on Sort Order for non numeric fields

http://www.websitefactors.co.uk/mysql/2011/07/mysql-limit-the-values-in-the-group_concat-function/

--------------------------------------------

SELECT

B.Year_Enter,

B.Month_Enter,

B.MonthName_Enter,

@IT_Open := @IT_Open + B.IT AS IT_Open,

@CS_Open := @CS_Open + B.CS AS CS_Open

FROM

(SELECT

A.Year_Enter,

A.Month_Enter,

A.MonthName_Enter,

SUM(IF(A.Month_Enter <> A.Month_Close, A.IT, 0)) AS IT,

SUM(IF(A.Month_Enter <> A.Month_Close, A.CS, 0)) AS CS

FROM

(SELECT

YEAR(I.Date_Entered) AS Year_Enter,

MONTH(I.Date_Entered) AS Month_Enter,

MONTHNAME(I.Date_Entered) AS MonthName_Enter,

IFNULL(MONTH(I.Closed_Date),0) AS Month_Close,

IFNULL(MONTHNAME(I.Closed_Date),'') AS MonthName_Close,

SUM(IF(U.Department = 'IT',1,0)) AS IT,

SUM(IF(U.Department = 'CS',1,0)) AS CS

FROM

Incident I,

User U

WHERE

I.Initiated_By = U.userLogin

GROUP BY

YEAR(I.Date_Entered),

MONTH(I.Date_Entered),

MONTHNAME(I.Date_Entered),

MONTH(I.Closed_Date),

MONTHNAME(I.Closed_Date)

ORDER BY

YEAR(I.Date_Entered),

MONTH(I.Date_Entered),

MONTH(I.Closed_Date)) A

GROUP BY

A.Year_Enter,

A.Month_Enter) B,

(SELECT

@IT_Open := 0,

@CS_Open := 0

FROM DUAL) C

First it runs a query to count the (non-null) values and saves the count in variable @N_VALS.

Then it runs a query containing a subquery:

- Inner query (named SQ1): from the values, selects the median value (if the number of values is odd) or the two middle values. During the selection, stores the value(s) selected in variables @MID1 and @MID2, leaving @MID1 null or @MID1<=@MID2. To accomplish this the values are ordered using an index or sort. The full scan required by some approaches, after the ordering, to assign a sequence number to every row is avoided. By using the LIMIT keyword, we can proceed directly to (at worst) a scan over half the values (also required where sequence numbers are assigned) to fetch the median value or the two middle values. We use LIMIT with OFFSET to identify the one or two values we need by position in the ordered list of values.

- Outer query: Uses @N_VALS, @MID1 and @MID2 to calculate median.

SET @TABLE =

/* Your table (or schema.table) > */ 'the_table_specification';

SET @COLUMN =

/* Your column > */ 'the_column_name';

#

SET @MEDIAN_QUERY1 = CONCAT('SELECT COUNT(', @COLUMN,') FROM ', @TABLE,' INTO @N_VALS');

PREPARE MEDIAN_PREPARED1 FROM @MEDIAN_QUERY1;

EXECUTE MEDIAN_PREPARED1;

DEALLOCATE PREPARE MEDIAN_PREPARED1;

SET @ODD = @N_VALS%2;

SET @MEDIAN_QUERY2 = CONCAT('SELECT CAST(IF(@ODD, @MID2, (@MID1+@MID2)/2) AS CHAR) AS `MEDIAN(', @COLUMN, ')` FROM (SELECT @MID1:=@MID2, @MID2:=', @COLUMN, ' FROM ',

@TABLE, ' WHERE ', @COLUMN, ' IS NOT NULL ORDER BY ', @COLUMN, ' LIMIT ', 2-@ODD, ' OFFSET ', @N_VALS DIV 2 - 1*(@N_VALS>'0') + @ODD,') SQ1 LIMIT 1');

PREPARE MEDIAN_PREPARED2 FROM @MEDIAN_QUERY2;

EXECUTE MEDIAN_PREPARED2;

DEALLOCATE PREPARE MEDIAN_PREPARED2;

http://mahmudahsan.wordpress.com/2008/08/27/mysql-the-group_concat-function/

http://www.qubed.ro

SELECT GROUP_CONCAT(`t`.`id`) FROM

(SELECT `id` FROM `table` LIMIT 5) `t`

Great function but 1) Cannot run in stored function so must be procedure. 2) You forgot to ad " INTO @SomeOutputVariable" in the final line I believe...

Here is a corrected version...

-- ------------------------------------------------------------------------------------

-- Dynamic SQL not permitted in stored functions, thus using a stored procedure instead.

-- Median procedure => MEDIAN(Using Column,From Table,InOut Result)

--

-- Use by...

-- CALL MEDIAN('YourColumn','YourTable',@res);

-- SELECT @res AS MEDIAN;

-- ------------------------------------------------------------------------------------

DELIMITER $$

DROP PROCEDURE IF EXISTS `MEDIAN`$$

CREATE DEFINER=`root`@`localhost` PROCEDURE `MEDIAN`(UsingCol varchar(64),FromTbl varchar(64),INOUT res decimal(50,5))

BEGIN

SET @ires = 0;

SET @TABLE = FromTbl;

/* Your table (or schema.table) > 'the_table_specification';*/

SET @COLUMN = UsingCol;

/* Your column > 'the_column_name'; */

#

SET @MEDIAN_QUERY1 = CONCAT('SELECT COUNT(', @COLUMN,') FROM ', @TABLE,' INTO @N_VALS');

PREPARE MEDIAN_PREPARED1 FROM @MEDIAN_QUERY1;

EXECUTE MEDIAN_PREPARED1;

DEALLOCATE PREPARE MEDIAN_PREPARED1;

SET @ODD = @N_VALS%2;

SET @MEDIAN_QUERY2 = CONCAT('SELECT CAST(IF(@ODD, @MID2, (@MID1+@MID2)/2) AS CHAR) AS `MEDIAN(', @COLUMN, ')` FROM (SELECT @MID1:=@MID2, @MID2:=', @COLUMN, ' FROM ',

@TABLE, ' WHERE ', @COLUMN, ' IS NOT NULL ORDER BY ', @COLUMN, ' LIMIT ', 2-@ODD, ' OFFSET ', @N_VALS DIV 2 - 1*(@N_VALS>'0') + @ODD,') SQ1 LIMIT 1 INTO @ires');

PREPARE MEDIAN_PREPARED2 FROM @MEDIAN_QUERY2;

EXECUTE MEDIAN_PREPARED2;

DEALLOCATE PREPARE MEDIAN_PREPARED2;

SET res = @ires;

END;

$$

DELIMITER ;

--- Now for the rest...

Just a few samples without needing to learn C / C++ or get a separate compiler outside MySQL

-- ------------------------------------------

-- Faculty function FACULTY(x) => x!

-- input Max value = 65, min value = 0

-- ------------------------------------------

DELIMITER $$

DROP FUNCTION IF EXISTS `FACULTY`$$

CREATE DEFINER=`root`@`localhost` FUNCTION `FACULTY`(x tinyint(3) UNSIGNED) RETURNS bigint(20) UNSIGNED

BEGIN

IF x = 1 OR x = 0 THEN

SET @res = 1;

ELSE

SET @res = 1;

SET @i = x;

WHILE @i >= 1 DO

SET @res = (@res * @i);

SET @i = @i - 1;

END WHILE;

END IF;

RETURN @res;

END;

$$

DELIMITER ;

-- ------------------------------------------

-- Combination function COMBINATIONS(x,y) => x!/y!/(x-y)!

-- input Max value = 65, min value = 0

-- ------------------------------------------

DELIMITER $$

DROP FUNCTION IF EXISTS `COMBINATIONS`$$

CREATE DEFINER=`root`@`localhost` FUNCTION `COMBINATIONS`(x tinyint(3) UNSIGNED,y tinyint(3) UNSIGNED) RETURNS bigint(20) UNSIGNED

BEGIN

IF (x < y) THEN

SET @res = 0;

ELSEIF (x = y) OR (x = 0) OR (y = 0) THEN

SET @res = 1;

ELSE

SET @varX = FACULTY(x);

SET @varY = FACULTY(y);

SET @varZ = FACULTY(x-y);

SET @res = (@varX / @varY / @varZ);

END IF;

RETURN @res;

END;

$$

DELIMITER ;