Aggregate/Analytic Functions¶
Aggregate function returns one result based on the group of rows. When the GROUP BY clause is included, a one-row aggregate result per group is returned. When the GROUP BY clause is omitted, a one-row aggregate result for all rows is returned. The HAVING clause is used to add a condition to the query which contains the GROUP BY clause.
Most aggregate functions can use DISTINCT, UNIQUE constraints. For the GROUP BY ... HAVING clause, see GROUP BY ... HAVING Clause.
Analytic function calculates the aggregate value based on the result of rows. The analytic function is different from the aggregate function since it can return one or more rows based on the groups specified by the query_partition_clause after the OVER clause (when this clause is omitted, all rows are regarded as a group).
The analytic function is used along with a new analytic clause, OVER, for the existing aggregate functions to allow a variety of statistics for a group of specific rows.
function_name ( [argument_list ] ) OVER (<analytic_clause>)
<analytic_clause>::=
[ <query_partition_clause> ] [ <order_by_clause> ]
<query_partition_clause>::=
PARTITION BY value_expr [, value_expr ]...
<order_by_clause>::=
ORDER BY { expr | position | column_alias } [ ASC | DESC ]
[, { expr | position | column_alias } [ ASC | DESC ] ] ...
- <query_partition_clause> : Groups based on one or more value_expr. It uses the PARTITION BY clause to partition the query result.
- <order_by_clause> : defines the data sorting method in the partition made by <query_partition_clause>. The result can be sorted with several keys. <When query_partition_clause> is omitted, the data is sorted within the overall result sets. Based on the sorting order, the function is applied to the column values of accumulated records, including the previous values.
The behavior of a query with the expression of ORDER BY/PARTITION BY clause which is used together after the OVER clause is as follows.
- ORDER BY/PARTITION BY <expression with non-constant> (ex: i, sin(i+1)): The expression is used to do ordering/partitioning.
- ORDER BY/PARTITION BY <constant> (ex: 1): Constant is considered as the column position of SELECT list.
- ORDER BY/PARTITION BY <constant expression> (ex: 1+0): Constant is ignored and it is not used to do ordering/partitioning.
AVG¶
-
AVG( [ DISTINCT | DISTINCTROW | UNIQUE | ALL ] expression )¶ The AVG function is used as an aggregate function or an analytic function. It calculates the arithmetic average of the value of an expression representing all rows. Only one expression is specified as a parameter. You can get the average without duplicates by using the DISTINCT or UNIQUE keyword in front of the expression or the average of all values by omitting the keyword or by using ALL.
Parameters: - expression -- Specifies an expression that returns a numeric value. An expression that returns a collection-type data is not allowed.
- ALL -- Calculates an average value for all data (default).
- DISTINCT,DISTINCTROW,UNIQUE -- Calculates an average value without duplicates.
Return type: DOUBLE
The following example shows how to retrieve the average number of gold medals that Korea won in Olympics in the demodb database.
SELECT AVG(gold)
FROM participant
WHERE nation_code = 'KOR';
avg(gold)
==========================
9.600000000000000e+00
The following example shows how to output the number of gold medals by year and the average number of accumulated gold medals in history, acquired whose nation_code starts with 'AU'.
SELECT host_year, nation_code, gold,
AVG(gold) OVER (PARTITION BY nation_code ORDER BY host_year) avg_gold
FROM participant WHERE nation_code like 'AU%';
host_year nation_code gold avg_gold
=======================================================================
1988 'AUS' 3 3.000000000000000e+00
1992 'AUS' 7 5.000000000000000e+00
1996 'AUS' 9 6.333333333333333e+00
2000 'AUS' 16 8.750000000000000e+00
2004 'AUS' 17 1.040000000000000e+01
1988 'AUT' 1 1.000000000000000e+00
1992 'AUT' 0 5.000000000000000e-01
1996 'AUT' 0 3.333333333333333e-01
2000 'AUT' 2 7.500000000000000e-01
2004 'AUT' 2 1.000000000000000e+00
The following example is removing the "ORDER BY host_year" clause under the OVER analysis clause from the above example. The avg_gold value is the average of gold medals for all years, so the value is identical for every year by nation_code.
SELECT host_year, nation_code, gold, AVG(gold) OVER (PARTITION BY nation_code) avg_gold
FROM participant WHERE nation_code LIKE 'AU%';
host_year nation_code gold avg_gold
==========================================================================
2004 'AUS' 17 1.040000000000000e+01
2000 'AUS' 16 1.040000000000000e+01
1996 'AUS' 9 1.040000000000000e+01
1992 'AUS' 7 1.040000000000000e+01
1988 'AUS' 3 1.040000000000000e+01
2004 'AUT' 2 1.000000000000000e+00
2000 'AUT' 2 1.000000000000000e+00
1996 'AUT' 0 1.000000000000000e+00
1992 'AUT' 0 1.000000000000000e+00
1988 'AUT' 1 1.000000000000000e+00
COUNT¶
-
COUNT(* | [ DISTINCT | DISTINCTROW | UNIQUE | ALL ] expression)¶ The COUNT function is used as an aggregate function or an analytic function. It returns the number of rows returned by a query. If an asterisk (*) is specified, the number of all rows satisfying the condition (including the rows with the NULL value) is returned. If the DISTINCT or UNIQUE keyword is specified in front of the expression, only the number of rows that have a unique value (excluding the rows with the NULL value) is returned after duplicates have been removed. Therefore, the value returned is always an integer and NULL is never returned.
Parameters: - expression -- Specifies an expression.
- ALL -- Gets the number of rows given in the expression (default).
- DISTINCT,DISTINCTROW,UNIQUE -- Gets the number of rows without duplicates.
Return type: INT
A column that has collection type and object domain (user-defined class) can also be specified in the expression.
The following example shows how to retrieve the number of Olympic Games that have a mascot in the demodb database.
SELECT COUNT(*)
FROM olympic
WHERE mascot IS NOT NULL;
count(*)
=============
9
The following example shows how to output the number of players whose nation_code is 'AUT' in demodb by accumulating the number of events when the event is changed. The last row shows the number of all players.
SELECT nation_code, event, name, COUNT(*) OVER (ORDER BY event) co
FROM athlete WHERE nation_code='AUT';
nation_code event name co
===============================================================================
'AUT' 'Athletics' 'Kiesl Theresia' 2
'AUT' 'Athletics' 'Graf Stephanie' 2
'AUT' 'Equestrian' 'Boor Boris' 6
'AUT' 'Equestrian' 'Fruhmann Thomas' 6
'AUT' 'Equestrian' 'Munzner Joerg' 6
'AUT' 'Equestrian' 'Simon Hugo' 6
'AUT' 'Judo' 'Heill Claudia' 9
'AUT' 'Judo' 'Seisenbacher Peter' 9
'AUT' 'Judo' 'Hartl Roswitha' 9
'AUT' 'Rowing' 'Jonke Arnold' 11
'AUT' 'Rowing' 'Zerbst Christoph' 11
'AUT' 'Sailing' 'Hagara Roman' 15
'AUT' 'Sailing' 'Steinacher Hans Peter' 15
'AUT' 'Sailing' 'Sieber Christoph' 15
'AUT' 'Sailing' 'Geritzer Andreas' 15
'AUT' 'Shooting' 'Waibel Wolfram Jr.' 17
'AUT' 'Shooting' 'Planer Christian' 17
'AUT' 'Swimming' 'Rogan Markus' 18
DENSE_RANK¶
-
DENSE_RANK() OVER ( [partition_by_clause] [order_by_clause] )¶ DENSE_RANK function is used as an analytic function only. The rank of the value in the column value group made by the PARTITION BY clause is calculated and output as INTEGER. Even when there is the same rank, 1 is added to the next rank value. For example, when there are three rows of Rank 13, the next rank is 14, not 16. On the contrary, the
RANK()function calculates the next rank by adding the number of same ranks.Return type: INT
The following example shows output of the number of Olympic gold medals of each country and the rank of the countries by year: The number of the same rank is ignored and the next rank is calculated by adding 1 to the rank.
SELECT host_year, nation_code, gold,
DENSE_RANK() OVER (PARTITION BY host_year ORDER BY gold DESC) AS d_rank
FROM participant;
host_year nation_code gold d_rank
=============================================================
1988 'URS' 55 1
1988 'GDR' 37 2
1988 'USA' 36 3
1988 'KOR' 12 4
1988 'HUN' 11 5
1988 'FRG' 11 5
1988 'BUL' 10 6
1988 'ROU' 7 7
1988 'ITA' 6 8
1988 'FRA' 6 8
1988 'KEN' 5 9
1988 'GBR' 5 9
1988 'CHN' 5 9
...
1988 'CHI' 0 14
1988 'ARG' 0 14
1988 'JAM' 0 14
1988 'SUI' 0 14
1988 'SWE' 0 14
1992 'EUN' 45 1
1992 'USA' 37 2
1992 'GER' 33 3
...
2000 'RSA' 0 15
2000 'NGR' 0 15
2000 'JAM' 0 15
2000 'BRA' 0 15
2004 'USA' 36 1
2004 'CHN' 32 2
2004 'RUS' 27 3
2004 'AUS' 17 4
2004 'JPN' 16 5
2004 'GER' 13 6
2004 'FRA' 11 7
2004 'ITA' 10 8
2004 'UKR' 9 9
2004 'CUB' 9 9
2004 'GBR' 9 9
2004 'KOR' 9 9
...
2004 'EST' 0 17
2004 'SLO' 0 17
2004 'SCG' 0 17
2004 'FIN' 0 17
2004 'POR' 0 17
2004 'MEX' 0 17
2004 'LAT' 0 17
2004 'PRK' 0 17
GROUP_CONCAT¶
-
GROUP_CONCAT([DISTINCT] {col | expression} [ORDER BY {col | unsigned_int} [ASC | DESC]] [SEPARATOR str_val])¶ The GROUP_CONCAT function is used as an aggregate function only. It connects the values that are not NULL in the group and returns the character string in the VARCHAR type. If there are no rows of query result or there are only NULL values, NULL will be returned.
Parameters: - expression -- Column or expression returning numerical values or character strings
- str_val -- Character string to use as a separator
- DISTINCT -- Removes duplicate values from the result.
- ORDERBY -- Specifies the order of result values.
- SEPARATOR -- Specifies the separator to divide the result values. If it is omitted, the default character, comma (,) will be used as a separator.
Return type: STRING
The maximum size of the return value follows the configuration of the system parameter, group_concat_max_len. The default is 1024 bytes, the minimum value is 4 bytes and the maximum value is 33,554,432 bytes. If it exceeds the maximum value, NULL will be returned.
To remove the duplicate values, use the DISTINCT clause. The default separator for the group result values is comma (,). To represent the separator explicitly, add the character string to use as a separator in the SEPARATOR clause and after that. If you want to remove separators, enter empty strings after the SEPARATOR clause.
If the non-character string type is passed to the result character string, an error will be returned.
To use the GROUP_CONCAT function, you must meet the following conditions.
- Only one expression (or a column) is allowed for an input parameter.
- Sorting with ORDER BY is available only in the expression used as a parameter.
- The character string used as a separator allows not only character string type but also allows other types.
SELECT GROUP_CONCAT(s_name) FROM code;
group_concat(s_name)
======================
'X,W,M,B,S,G'
SELECT GROUP_CONCAT(s_name ORDER BY s_name SEPARATOR ':') FROM code;
group_concat(s_name order by s_name separator ':')
======================
'B:G:M:S:W:X'
CREATE TABLE t(i int);
INSERT INTO t VALUES (4),(2),(3),(6),(1),(5);
SELECT GROUP_CONCAT(i*2+1 ORDER BY 1 SEPARATOR '') FROM t;
group_concat(i*2+1 order by 1 separator '')
======================
'35791113'
LAG¶
-
LAG(expression[, offset[, default]]) OVER ( [partition_by_clause] [order_by_clause] )¶ LAG is an analytic function that returns the expression value from a previous row, before offset that comes before the current row. It can be used to access several rows simultaneously without making any self join.
Parameters: - expression -- a column or an expression that returns a number or a string
- offset -- an integer which indicates the offset position. If not specified, the default is 1
- default -- a value to return when an expression value before offset is NULL. If a default value is not specified, NULL is returned
Return type: NUMBER or STRING
The following example shows how to sort employee numbers and output the previous employee number on the same row:
CREATE TABLE t_emp (name VARCHAR(10), empno INT);
INSERT INTO t_emp VALUES
('Amie', 11011),
('Jane', 13077),
('Lora', 12045),
('James', 12006),
('Peter', 14006),
('Tom', 12786),
('Ralph', 23518),
('David', 55);
SELECT name, empno, LAG (empno, 1) OVER (ORDER BY empno) prev_empno
FROM t_emp;
name empno prev_empno
================================================
'David' 55 NULL
'Amie' 11011 55
'James' 12006 11011
'Lora' 12045 12006
'Tom' 12786 12045
'Jane' 13077 12786
'Peter' 14006 13077
'Ralph' 23518 14006
On the contrary, LEAD() function returns the expression value from a subsequent row, after offset that follows the current row.
LEAD¶
-
LEAD(expression, offset, default) OVER ( [partition_by_clause] [order_by_clause] )¶ LEAD is an analytic function that returns the expression value from a subsequent row, after offset that follows the current row. It can be used to access several rows simultaneously without making any self join.
Parameters: - expression -- 숫자 또는 문자열을 반환하는 칼럼 또는 연산식
- offset -- 오프셋 위치를 나타내는 정수. 생략 시 기본값 1
- default -- 현재 위치에서 offset 이전에 위치한 expression 값이 NULL인 경우 출력하는 값. 기본값 NULL
Return type: NUMBER or STRING
The following example shows how to sort employee numbers and output the next employee number on the same row:
CREATE TABLE t_emp (name VARCHAR(10), empno INT); INSERT INTO t_emp VALUES ('Amie', 11011), ('Jane', 13077), ('Lora', 12045), ('James', 12006), ('Peter', 14006), ('Tom', 12786), ('Ralph', 23518), ('David', 55); SELECT name, empno, LEAD (empno,1) OVER (ORDER BY empno) next_empno FROM t_emp; name empno next_empno ================================================ 'David' 55 11011 'Amie' 11011 12006 'James' 12006 12045 'Lora' 12045 12786 'Tom' 12786 13077 'Jane' 13077 14006 'Peter' 14006 23518 'Ralph' 23518 NULL
The following example shows how to output the title of the previous row and the title of the next row along with the title of the current row on the tbl_board table:
CREATE TABLE tbl_board (num INT, title VARCHAR(50));
INSERT INTO tbl_board VALUES
(1, 'title 1'), (2, 'title 2'), (3, 'title 3'), (4, 'title 4'), (5, 'title 5'), (6, 'title 6'), (7, 'title 7');
SELECT num, title,
LEAD (title,1,'no next page') OVER (ORDER BY num) next_title,
LAG (title,1,'no previous page') OVER (ORDER BY num) prev_title
FROM tbl_board;
num title next_title prev_title
===============================================================================
1 'title 1' 'title 2' NULL
2 'title 2' 'title 3' 'title 1'
3 'title 3' 'title 4' 'title 2'
4 'title 4' 'title 5' 'title 3'
5 'title 5' 'title 6' 'title 4'
6 'title 6' 'title 7' 'title 5'
7 'title 7' NULL 'title 6'
The following example shows how to output the title of the previous row and the title of the next row along with the title of a specified row on the tbl_board table. If a WHERE condition is enclosed in parentheses, the values of next_title and prev_title are NULL as only one row is selected but the previous row and the subsequent row.
SELECT * FROM
(
SELECT num, title,
LEAD (title,1,'no next page') OVER (ORDER BY num) next_title,
LAG (title,1,'no previous page') OVER (ORDER BY num) prev_title
FROM tbl_board
)
WHERE num=5;
num title next_title prev_title
===============================================================================
5 'title 5' 'title 6' 'title 4'
MAX¶
-
MAX( [ DISTINCT | DISTINCTROW | UNIQUE | ALL ] expression )¶ The MAX function is used as an aggregate function or an analytic function. It gets the greatest value of expressions of all rows. Only one expression is specified.
Parameters: - expression -- Specifies an expression that returns a numeric or string value. An expression that returns a collection-type data is not allowed.
- ALL -- Gets the maximum value for all data (default).
- DISTINCT,DISTINCTROW,UNIQUE -- Gets the maximum value without duplicates.
Return type: same type as that the expression
For expressions that return character strings, the string that appears later in alphabetical order becomes the maximum value; for those that return numbers, the greatest value becomes the maximum value.
The following example shows how to retrieve the maximum number of gold (gold) medals that Korea won in the Olympics in the demodb database.
SELECT MAX(gold) FROM participant WHERE nation_code = 'KOR';
max(gold)
=============
12
The following example shows how to output the number of gold medals by year and the maximum number of gold medals in history, acquired by the country whose nation_code code starts with 'AU'.
SELECT host_year, nation_code, gold,
MAX(gold) OVER (PARTITION BY nation_code) mx_gold
FROM participant WHERE nation_code like 'AU%' ORDER BY nation_code, host_year;
host_year nation_code gold mx_gold
=============================================================
1988 'AUS' 3 17
1992 'AUS' 7 17
1996 'AUS' 9 17
2000 'AUS' 16 17
2004 'AUS' 17 17
1988 'AUT' 1 2
1992 'AUT' 0 2
1996 'AUT' 0 2
2000 'AUT' 2 2
2004 'AUT' 2 2
MIN¶
-
MIN( [ DISTINCT | DISTINCTROW | UNIQUE | ALL ] expression )¶ The MIN function is used as an aggregate function or an analytic function. It gets the smallest value of expressions of all rows. Only one expression is specified. For expressions that return character strings, the string that appears earlier in alphabetical order becomes the minimum value; for those that return numbers, the smallest value becomes the minimum value.
Parameters: - expression -- Specifies an expression that returns a numeric or string value. A collection expression cannot be specified.
- ALL -- Gets the minimum value for all data (default).
- DISTINCT,DISTINCTROW,UNIQUE -- Gets the maximum value without duplicates.
Return type: same type as that the expression
The following example shows how to retrieve the minimum number of gold (gold) medals that Korea won in the Olympics in the demodb database.
SELECT MIN(gold) FROM participant WHERE nation_code = 'KOR';
min(gold)
=============
7
The following example shows how to output the number of gold medals by year and the maximum number of gold medals in history, acquired by the country whose nation_code code starts with 'AU'.
SELECT host_year, nation_code, gold,
MIN(gold) OVER (PARTITION BY nation_code) mn_gold
FROM participant WHERE nation_code like 'AU%' ORDER BY nation_code, host_year;
host_year nation_code gold mn_gold
=============================================================
1988 'AUS' 3 3
1992 'AUS' 7 3
1996 'AUS' 9 3
2000 'AUS' 16 3
2004 'AUS' 17 3
1988 'AUT' 1 0
1992 'AUT' 0 0
1996 'AUT' 0 0
2000 'AUT' 2 0
2004 'AUT' 2 0
NTILE¶
-
NTILE(expression) OVER ([partition_by_clause] [order_by_clause])¶ - NTILE is an analytic function. It divides an ordered data set into a number of buckets indicated by the input parameter value and assigns the appropriate bucket number to each row. The buckets are numbered 1. In other words, the NTILE function creates an equi-height histogram. The return value is an integer. This function equally divides the number of rows by the given number of buckets and assigns the bucket number to each bucket. That is, every bucket has the same number of rows.
Parameters: expression -- the number of buckets. It specifies a certain expression which returns a number value. Return type: INT
NTILE function equally divides the number of rows by the given number of buckets and assigns the bucket number to each bucket. That is, NTILE function creates an equi-height histogram. The number of rows in the buckets can differ by at most 1. The remainder values (the remainder number of rows divided by buckets number) are distributed one for each bucket, starting with #1 Bucket.
On the contrary, WIDTH_BUCKET() function equally divides the range by the given number of buckets and assigns the bucket number to each bucket. That is, every interval (bucket) has the identical size.
The following example divides rows into five buckets of eight customers based on their dates of birth. Because the total number of rows is not divisible by the number of buckets, the first three buckets have two rows and the remaining groups have one row each.
CREATE TABLE t_customer(name VARCHAR(10), birthdate DATE);
INSERT INTO t_customer VALUES
('Amie', date'1978-03-18'),
('Jane', date'1983-05-12'),
('Lora', date'1987-03-26'),
('James', date'1948-12-28'),
('Peter', date'1988-10-25'),
('Tom', date'1980-07-28'),
('Ralph', date'1995-03-17'),
('David', date'1986-07-28');
SELECT name, birthdate, NTILE(5) OVER (ORDER BY birthdate) age_group
FROM t_customer;
name birthdate age_group
===============================================
'James' 12/28/1948 1
'Amie' 03/18/1978 1
'Tom' 07/28/1980 2
'Jane' 05/12/1983 2
'David' 07/28/1986 3
'Lora' 03/26/1987 3
'Peter' 10/25/1988 4
'Ralph' 03/17/1995 5
The following example divides eight students into five buckets that have the identical number of rows in the order of score and outputs in the order of the name. As the score column of the t_score table has eight rows, the remaining three rows are assigned to buckets from #1 Bucket. The first three buckets have one more row than the remaining groups. The NTILE function equally divides the grade based on the number of rows, regardless the range of the score.
CREATE TABLE t_score(name VARCHAR(10), score INT);
INSERT INTO t_score VALUES
('Amie', 60),
('Jane', 80),
('Lora', 60),
('James', 75),
('Peter', 70),
('Tom', 30),
('Ralph', 99),
('David', 55);
SELECT name, score, NTILE(5) OVER (ORDER BY score DESC) grade
FROM t_score
ORDER BY name;
name score grade
================================================
'Ralph' 99 1
'Jane' 80 1
'James' 75 2
'Peter' 70 2
'Amie' 60 3
'Lora' 60 3
'David' 55 4
'Tom' 30 5
RANK¶
-
RANK() OVER ( [partition_by_clause] [order_by_clause] )¶ RANK function is used as an analytic function only. The rank of the value in the column value group made by the PARTITION BY clause is calculated and output as INTEGER. When there is another identical rank, the next rank is the number adding the number of the same ranks. For example, when there are three rows of Rank 13, the next rank is 16, not 14. On the contrary, the
DENSE_RANK()function calculates the next rank by adding 1 to the rank.rtype: INT
The following example shows output of the number of Olympic gold medals of each country and the rank of the countries by year. The next rank of the same rank is calculated by adding the number of the same ranks.
SELECT host_year, nation_code, gold,
RANK() OVER (PARTITION BY host_year ORDER BY gold DESC) AS g_rank
FROM participant;
host_year nation_code gold g_rank
=============================================================
1988 'URS' 55 1
1988 'GDR' 37 2
1988 'USA' 36 3
1988 'KOR' 12 4
1988 'HUN' 11 5
1988 'FRG' 11 5
1988 'BUL' 10 7
1988 'ROU' 7 8
1988 'ITA' 6 9
1988 'FRA' 6 9
1988 'KEN' 5 11
1988 'GBR' 5 11
1988 'CHN' 5 11
...
1988 'CHI' 0 32
1988 'ARG' 0 32
1988 'JAM' 0 32
1988 'SUI' 0 32
1988 'SWE' 0 32
1992 'EUN' 45 1
1992 'USA' 37 2
1992 'GER' 33 3
...
2000 'RSA' 0 52
2000 'NGR' 0 52
2000 'JAM' 0 52
2000 'BRA' 0 52
2004 'USA' 36 1
2004 'CHN' 32 2
2004 'RUS' 27 3
2004 'AUS' 17 4
2004 'JPN' 16 5
2004 'GER' 13 6
2004 'FRA' 11 7
2004 'ITA' 10 8
2004 'UKR' 9 9
2004 'CUB' 9 9
2004 'GBR' 9 9
2004 'KOR' 9 9
...
2004 'EST' 0 57
2004 'SLO' 0 57
2004 'SCG' 0 57
2004 'FIN' 0 57
2004 'POR' 0 57
2004 'MEX' 0 57
2004 'LAT' 0 57
2004 'PRK' 0 57
ROW_NUMBER¶
-
ROW_NUMBER() OVER ( [partition_by_clause] [order_by_clause] )¶ ROW_NUMBER function is used as an analytic function only. The rank of a row is one plus the number of distinct ranks that come before the row in question by using the PARTITION BY clause and outputs as INTEGER.
Return type: INT
The following example shows output of the serial number according to the number of Olympic gold medals of each country by year. If the number of gold medals is the same, the sorting follows the alphabetic order of the nation_code.
SELECT host_year, nation_code, gold,
ROW_NUMBER() OVER (PARTITION BY host_year ORDER BY gold DESC) AS r_num
FROM participant;
host_year nation_code gold r_num
=============================================================
1988 'URS' 55 1
1988 'GDR' 37 2
1988 'USA' 36 3
1988 'KOR' 12 4
1988 'FRG' 11 5
1988 'HUN' 11 6
1988 'BUL' 10 7
1988 'ROU' 7 8
1988 'FRA' 6 9
1988 'ITA' 6 10
1988 'CHN' 5 11
...
1988 'YEM' 0 152
1988 'YMD' 0 153
1988 'ZAI' 0 154
1988 'ZAM' 0 155
1988 'ZIM' 0 156
1992 'EUN' 45 1
1992 'USA' 37 2
1992 'GER' 33 3
...
2000 'VIN' 0 194
2000 'YEM' 0 195
2000 'ZAM' 0 196
2000 'ZIM' 0 197
2004 'USA' 36 1
2004 'CHN' 32 2
2004 'RUS' 27 3
2004 'AUS' 17 4
2004 'JPN' 16 5
2004 'GER' 13 6
2004 'FRA' 11 7
2004 'ITA' 10 8
2004 'CUB' 9 9
2004 'GBR' 9 10
2004 'KOR' 9 11
...
2004 'UGA' 0 195
2004 'URU' 0 196
2004 'VAN' 0 197
2004 'VEN' 0 198
2004 'VIE' 0 199
2004 'VIN' 0 200
2004 'YEM' 0 201
2004 'ZAM' 0 202
STDDEV, STDDEV_POP¶
-
STDDEV( [ DISTINCT | DISTINCTROW | UNIQUE | ALL] expression )¶
-
STDDEV_POP( [ DISTINCT | DISTINCTROW | UNIQUE | ALL] expression )¶ The functions STDDEV and STDDEV_POP are used interchangeably and they are used as an aggregate function or an analytic function. They return a standard variance of the values calculated for all rows. The STDDEV_POP function is a standard of the SQL:1999. Only one expression is specified as a parameter. If the DISTINCT or UNIQUE keyword is inserted before the expression, they calculate the sample standard variance after deleting duplicates; if keyword is omitted or ALL, they it calculate the sample standard variance for all values.
Parameters: - expression -- Specifies an expression that returns a numeric value.
- ALL -- Calculates the standard variance for all data (default).
- DISTINCT,DISTINCTROW,UNIQUE -- Calculates the standard variance without duplicates.
Return type: DOUBLE
The return value is the same with the square root of its variance (the return value of VAR_POP() and it is a DOUBLE type. If there are no rows that can be used for calculating a result, NULL is returned.
The following is a formula that is applied to the function.
Note
In CUBRID 2008 R3.1 or earlier, the STDDEV function worked the same as the STDDEV_SAMP().
The following example shows how to output the population standard variance of all students for all subjects.
CREATE TABLE student (name VARCHAR(32), subjects_id INT, score DOUBLE);
INSERT INTO student VALUES
('Jane',1, 78), ('Jane',2, 50), ('Jane',3, 60),
('Bruce', 1, 63), ('Bruce', 2, 50), ('Bruce', 3, 80),
('Lee', 1, 85), ('Lee', 2, 88), ('Lee', 3, 93),
('Wane', 1, 32), ('Wane', 2, 42), ('Wane', 3, 99),
('Sara', 1, 17), ('Sara', 2, 55), ('Sara', 3, 43);
SELECT STDDEV_POP(score) FROM student;
stddev_pop(score)
==========================
2.329711474744362e+01
The following example shows how to output the score and population standard variance of all students by subject (subjects_id).
SELECT subjects_id, name, score, STDDEV_POP(score) OVER(PARTITION BY subjects_id) std_pop
FROM student
ORDER BY subjects_id, name;
subjects_id name score std_pop
=======================================================================================
1 'Bruce' 6.300000000000000e+01 2.632869157402243e+01
1 'Jane' 7.800000000000000e+01 2.632869157402243e+01
1 'Lee' 8.500000000000000e+01 2.632869157402243e+01
1 'Sara' 1.700000000000000e+01 2.632869157402243e+01
1 'Wane' 3.200000000000000e+01 2.632869157402243e+01
2 'Bruce' 5.000000000000000e+01 1.604992211819110e+01
2 'Jane' 5.000000000000000e+01 1.604992211819110e+01
2 'Lee' 8.800000000000000e+01 1.604992211819110e+01
2 'Sara' 5.500000000000000e+01 1.604992211819110e+01
2 'Wane' 4.200000000000000e+01 1.604992211819110e+01
3 'Bruce' 8.000000000000000e+01 2.085185843036539e+01
3 'Jane' 6.000000000000000e+01 2.085185843036539e+01
3 'Lee' 9.300000000000000e+01 2.085185843036539e+01
3 'Sara' 4.300000000000000e+01 2.085185843036539e+01
3 'Wane' 9.900000000000000e+01 2.085185843036539e+01
STDDEV_SAMP¶
-
STDDEV_SAMP( [ DISTINCT | DISTINCTROW | UNIQUE | ALL] expression )¶ The STDDEV_SAMP function is used as an aggregate function or an analytic function. It calculates the sample standard variance. Only one expression is specified as a parameter. If the DISTINCT or UNIQUE keyword is inserted before the expression, it calculates the sample standard variance after deleting duplicates; if a keyword is omitted or ALL, it calculates the sample standard variance for all values.
Parameters: - expression -- An expression that returns a numeric value
- ALL -- Used to calculate the standard variance for all values. It is the default value.
- DISTINCT,DISTINCTROW,UNIQUE -- Used to calculate the standard variance for the unique values without duplicates.
Return type: DOUBLE
The return value is the same as the square root of its sample variance (VAR_SAMP()) and it is a DOUBLE type. If there are no rows that can be used for calculating a result, NULL is returned.
The following are the formulas applied to the function.
The following example shows how to output the sample standard variance of all students for all subjects.
CREATE TABLE student (name VARCHAR(32), subjects_id INT, score DOUBLE);
INSERT INTO student VALUES
('Jane',1, 78), ('Jane',2, 50), ('Jane',3, 60),
('Bruce', 1, 63), ('Bruce', 2, 50), ('Bruce', 3, 80),
('Lee', 1, 85), ('Lee', 2, 88), ('Lee', 3, 93),
('Wane', 1, 32), ('Wane', 2, 42), ('Wane', 3, 99),
('Sara', 1, 17), ('Sara', 2, 55), ('Sara', 3, 43);
SELECT STDDEV_SAMP(score) FROM student;
stddev_samp(score)
==========================
2.411480477888654e+01
The following example shows how to output the sample standard variance of all students for all subjects.
SELECT subjects_id, name, score, STDDEV_SAMP(score) OVER(PARTITION BY subjects_id) std_samp
FROM student
ORDER BY subjects_id, name;
subjects_id name score std_samp
=======================================================================================
1 'Bruce' 6.300000000000000e+01 2.943637205907005e+01
1 'Jane' 7.800000000000000e+01 2.943637205907005e+01
1 'Lee' 8.500000000000000e+01 2.943637205907005e+01
1 'Sara' 1.700000000000000e+01 2.943637205907005e+01
1 'Wane' 3.200000000000000e+01 2.943637205907005e+01
2 'Bruce' 5.000000000000000e+01 1.794435844492636e+01
2 'Jane' 5.000000000000000e+01 1.794435844492636e+01
2 'Lee' 8.800000000000000e+01 1.794435844492636e+01
2 'Sara' 5.500000000000000e+01 1.794435844492636e+01
2 'Wane' 4.200000000000000e+01 1.794435844492636e+01
3 'Bruce' 8.000000000000000e+01 2.331308645374953e+01
3 'Jane' 6.000000000000000e+01 2.331308645374953e+01
3 'Lee' 9.300000000000000e+01 2.331308645374953e+01
3 'Sara' 4.300000000000000e+01 2.331308645374953e+01
3 'Wane' 9.900000000000000e+01 2.331308645374953e+01
SUM¶
-
SUM( [ DISTINCT | DISTINCTROW | UNIQUE | ALL ] expression )¶ The SUM function is used as an aggregate function or an analytic function. It returns the sum of expressions of all rows. Only one expression is specified as a parameter. You can get the sum without duplicates by inserting the DISTINCT or UNIQUE keyword in front of the expression, or get the sum of all values by omitting the keyword or by using ALL.
Parameters: - expression -- Specifies an expression that returns a numeric value.
- ALL -- Gets the sum for all data (default).
- DISTINCT,DISTINCTROW,UNIQUE -- Gets the sum of unique values without duplicates
Return type: same type as that the expression
The following is an example that outputs the top 10 countries and the total number of gold medals based on the sum of gold medals won in the Olympic Games in demodb.
SELECT nation_code, SUM(gold)
FROM participant
GROUP BY nation_code
ORDER BY SUM(gold) DESC
LIMIT 10;
=== <Result of SELECT Command in Line 1> ===
nation_code sum(gold)
===================================
'USA' 190
'CHN' 97
'RUS' 85
'GER' 79
'URS' 55
'FRA' 53
'AUS' 52
'ITA' 48
'KOR' 48
'EUN' 45
The following example shows how to output the number of gold medals by year and the average sum of the accumulated gold medals to the year acquired by the country whose nation_code code starts with 'AU' in demodb.
SELECT host_year, nation_code, gold,
SUM(gold) OVER (PARTITION BY nation_code ORDER BY host_year) sum_gold
FROM participant
WHERE nation_code LIKE 'AU%';
host_year nation_code gold sum_gold
=============================================================
1988 'AUS' 3 3
1992 'AUS' 7 10
1996 'AUS' 9 19
2000 'AUS' 16 35
2004 'AUS' 17 52
1988 'AUT' 1 1
1992 'AUT' 0 1
1996 'AUT' 0 1
2000 'AUT' 2 3
2004 'AUT' 2 5
The following example is removing the "ORDER BY host_year" clause under the OVER analysis clause from the above example. The avg_gold value is the average of gold medals for all years, so the value is identical for every year by nation_code.
SELECT host_year, nation_code, gold, SUM(gold) OVER (PARTITION BY nation_code) sum_gold
FROM participant
WHERE nation_code LIKE 'AU%';
host_year nation_code gold sum_gold
=============================================================
2004 'AUS' 17 52
2000 'AUS' 16 52
1996 'AUS' 9 52
1992 'AUS' 7 52
1988 'AUS' 3 52
2004 'AUT' 2 5
2000 'AUT' 2 5
1996 'AUT' 0 5
1992 'AUT' 0 5
1988 'AUT' 1 5
VARIANCE, VAR_POP¶
-
VAR_POP( [ DISTINCT | UNIQUE | ALL] expression )¶
-
VARIANCE( [ DISTINCT | UNIQUE | ALL] expression )¶ The functions VARPOP and VARIANCE are used interchangeably and they are used as an aggregate function or an analytic function. They return a variance of expression values for all rows. Only one expression is specified as a parameter. If the DISTINCT or UNIQUE keyword is inserted before the expression, they calculate the population variance after deleting duplicates; if the keyword is omitted or ALL, they calculate the sample population variance for all values.
Parameters: - expression -- Specifies an expression that returns a numeric value.
- ALL -- Gets the variance for all values (default).
- DISTINCT,DISTINCTROW,UNIQUE -- Gets the variance of unique values without duplicates.
Return type: DOUBLE
The return value is a DOUBLE type. If there are no rows that can be used for calculating a result, NULL will be returned.
The following is a formula that is applied to the function.
Note
In CUBRID 2008 R3.1 or earlier, the VARIANCE function worked the same as the VAR_SAMP().
The following example shows how to output the population variance of all students for all subjects
CREATE TABLE student (name VARCHAR(32), subjects_id INT, score DOUBLE);
INSERT INTO student VALUES
('Jane',1, 78), ('Jane',2, 50), ('Jane',3, 60),
('Bruce', 1, 63), ('Bruce', 2, 50), ('Bruce', 3, 80),
('Lee', 1, 85), ('Lee', 2, 88), ('Lee', 3, 93),
('Wane', 1, 32), ('Wane', 2, 42), ('Wane', 3, 99),
('Sara', 1, 17), ('Sara', 2, 55), ('Sara', 3, 43);
SELECT VAR_POP(score) FROM student;
var_pop(score)
==========================
5.427555555555550e+02
The following example shows how to output the score and population variance of all students by subject (subjects_id).
SELECT subjects_id, name, score, VAR_POP(score) OVER(PARTITION BY subjects_id) v_pop
FROM student
ORDER BY subjects_id, name;
subjects_id name score v_pop
=======================================================================================
1 'Bruce' 6.300000000000000e+01 6.931999999999998e+02
1 'Jane' 7.800000000000000e+01 6.931999999999998e+02
1 'Lee' 8.500000000000000e+01 6.931999999999998e+02
1 'Sara' 1.700000000000000e+01 6.931999999999998e+02
1 'Wane' 3.200000000000000e+01 6.931999999999998e+02
2 'Bruce' 5.000000000000000e+01 2.575999999999999e+02
2 'Jane' 5.000000000000000e+01 2.575999999999999e+02
2 'Lee' 8.800000000000000e+01 2.575999999999999e+02
2 'Sara' 5.500000000000000e+01 2.575999999999999e+02
2 'Wane' 4.200000000000000e+01 2.575999999999999e+02
3 'Bruce' 8.000000000000000e+01 4.348000000000002e+02
3 'Jane' 6.000000000000000e+01 4.348000000000002e+02
3 'Lee' 9.300000000000000e+01 4.348000000000002e+02
3 'Sara' 4.300000000000000e+01 4.348000000000002e+02
3 'Wane' 9.900000000000000e+01 4.348000000000002e+02
VAR_SAMP¶
-
VAR_SAMP( [ DISTINCT | UNIQUE | ALL] expression )¶ The VAR_SAMP function is used as an aggregate function or an analytic function. It returns the sample variance. The denominator is the number of all rows - 1. Only one expression is specified as a parameter. If the DISTINCT or UNIQUE keyword is inserted before the expression, it calculates the sample variance after deleting duplicates and if the keyword is omitted or ALL, it calculates the sample variance for all values.
Parameters: - expression -- Specifies one expression to return the numeric.
- ALL -- Is used to calculate the sample variance of unique values without duplicates. It is the default value.
- DISTINCT,DISTINCTROW,UNIQUE -- Is used to calculate the sample variance for the unique values without duplicates.
Return type: DOUBLE
The return value is a DOUBLE type. If there are no rows that can be used for calculating a result, NULL is returned.
The following are the formulas applied to the function.
The following example shows how to output the sample variance of all students for all subjects.
CREATE TABLE student (name VARCHAR(32), subjects_id INT, score DOUBLE);
INSERT INTO student VALUES
('Jane',1, 78),
('Jane',2, 50),
('Jane',3, 60),
('Bruce', 1, 63),
('Bruce', 2, 50),
('Bruce', 3, 80),
('Lee', 1, 85),
('Lee', 2, 88),
('Lee', 3, 93),
('Wane', 1, 32),
('Wane', 2, 42),
('Wane', 3, 99),
('Sara', 1, 17),
('Sara', 2, 55),
('Sara', 3, 43);
SELECT VAR_SAMP(score) FROM student;
var_samp(score)
==========================
5.815238095238092e+02
The following example shows how to output the score and sample variance of all students by subject (subjects_id).
SELECT subjects_id, name, score, VAR_SAMP(score) OVER(PARTITION BY subjects_id) v_samp
FROM student
ORDER BY subjects_id, name;
subjects_id name score v_samp
=======================================================================================
1 'Bruce' 6.300000000000000e+01 8.665000000000000e+02
1 'Jane' 7.800000000000000e+01 8.665000000000000e+02
1 'Lee' 8.500000000000000e+01 8.665000000000000e+02
1 'Sara' 1.700000000000000e+01 8.665000000000000e+02
1 'Wane' 3.200000000000000e+01 8.665000000000000e+02
2 'Bruce' 5.000000000000000e+01 3.220000000000000e+02
2 'Jane' 5.000000000000000e+01 3.220000000000000e+02
2 'Lee' 8.800000000000000e+01 3.220000000000000e+02
2 'Sara' 5.500000000000000e+01 3.220000000000000e+02
2 'Wane' 4.200000000000000e+01 3.220000000000000e+02
3 'Bruce' 8.000000000000000e+01 5.435000000000000e+02
3 'Jane' 6.000000000000000e+01 5.435000000000000e+02
3 'Lee' 9.300000000000000e+01 5.435000000000000e+02
3 'Sara' 4.300000000000000e+01 5.435000000000000e+02
3 'Wane' 9.900000000000000e+01 5.435000000000000e+02