Aggregate Functions
Aggregate Functions
sum(expression)
Description: Sum of expression across all input values
Return type:
Generally, same as the argument data type. In the following cases, type conversion occurs:
- BIGINT for SMALLINT or INT arguments
- NUMBER for BIGINT arguments
- DOUBLE PRECISION for floating-point arguments
Example:
postgres=# SELECT SUM(ss_ext_tax) FROM tpcds.STORE_SALES; sum -------------- 213267594.69 (1 row)
max(expression)
Description: maximum value of expression across all input values
Argument types: any array, numeric, string, or date/time type
Return type: same as the argument type
Example:
postgres=# SELECT MAX(inv_quantity_on_hand) FROM tpcds.inventory;
min(expression)
Description: minimum value of expression across all input values
Argument types: any array, numeric, string, or date/time type
Return type: same as the argument type
Example:
postgres=# SELECT MIN(inv_quantity_on_hand) FROM tpcds.inventory; min ----- 0 (1 row)
avg(expression)
Description: Average (arithmetic mean) of all input values
Return type:
NUMBER for any integer-type argument.
DOUBLE PRECISION for a floating-point argument,
otherwise the same as the argument data type.
Example:
postgres=# SELECT AVG(inv_quantity_on_hand) FROM tpcds.inventory; avg ---------------------- 500.0387129084044604 (1 row)
count(expression)
Description: number of input rows for which the value of expression is not null
Return type: bigint
Example:
postgres=# SELECT COUNT(inv_quantity_on_hand) FROM tpcds.inventory; count ---------- 11158087 (1 row)
count(*)
Description: number of input rows
Return type: bigint
Example:
postgres=# SELECT COUNT(*) FROM tpcds.inventory; count ---------- 11745000 (1 row)
median(expression) [over (query partition clause)]
Description: Returns the median of an expression. NULL will be ignored by the median function during calculation. The DISTINCT keyword can be used to exclude duplicate records in an expression. The data type of the input expression can be numeric (including integer, double, and bigint) or interval. For other data types, the median cannot be calculated.
Return type: double or interval
Example:
select median(id) from (values(1), (2), (3), (4), (null)) test(id); median -------- 2.5 (1 row)
array_agg(expression)
Description: input values, including nulls, concatenated into an array
Return type: array of the argument type
Example:
postgres=# SELECT ARRAY_AGG(sr_fee) FROM tpcds.store_returns WHERE sr_customer_sk = 2; array_agg --------------- {22.18,63.21} (1 row)
string_agg(expression, delimiter)
Description: input values concatenated into a string, separated by delimiter
Return type: same as the argument type
Example:
postgres=# SELECT string_agg(sr_item_sk, ',') FROM tpcds.store_returns where sr_item_sk < 3; string_agg --------------------------------------------------------------------------------- ------------------------------ 1,2,1,2,2,1,1,2,2,1,2,1,2,1,1,1,2,1,1,1,1,1,2,1,1,1,1,1,2,2,1,1,1,1,1,1,1,1,1,2, 2,1,1,1,1,1,1,2,2,1,1,2,1,1,1 (1 row)
listagg(expression [, delimiter]) WITHIN GROUP(ORDER BY order-list)
Description: aggregation column data sorted according to the mode specified by WITHIN GROUP, and concatenated to a string using the specified delimiter
- expression: Mandatory. It specifies an aggregation column name or a column-based, valid expression. It does not support the DISTINCT keyword and the VARIADIC parameter.
- delimiter: Optional. It specifies a delimiter, which can be a string constant or a deterministic expression based on a group of columns. The default value is empty.
- order-list: Mandatory. It specifies the sorting mode in a group.
Return type: text
Example:
The aggregation column is of the text character set type.
postgres=# SELECT deptno, listagg(ename, ',') WITHIN GROUP(ORDER BY ename) AS employees FROM emp GROUP BY deptno; deptno | employees --------+-------------------------------------- 10 | CLARK,KING,MILLER 20 | ADAMS,FORD,JONES,SCOTT,SMITH 30 | ALLEN,BLAKE,JAMES,MARTIN,TURNER,WARD (3 rows)
The aggregation column is of the integer type.
postgres=# SELECT deptno, listagg(mgrno, ',') WITHIN GROUP(ORDER BY mgrno NULLS FIRST) AS mgrnos FROM emp GROUP BY deptno; deptno | mgrnos --------+------------------------------- 10 | 7782,7839 20 | 7566,7566,7788,7839,7902 30 | 7698,7698,7698,7698,7698,7839 (3 rows)
The aggregation column is of the floating point type.
postgres=# SELECT job, listagg(bonus, '($); ') WITHIN GROUP(ORDER BY bonus DESC) || '($)' AS bonus FROM emp GROUP BY job; job | bonus ------------+------------------------------------------------- CLERK | 10234.21($); 2000.80($); 1100.00($); 1000.22($) PRESIDENT | 23011.88($) ANALYST | 2002.12($); 1001.01($) MANAGER | 10000.01($); 2399.50($); 999.10($) SALESMAN | 1000.01($); 899.00($); 99.99($); 9.00($) (5 rows)
The aggregation column is of the time type.
postgres=# SELECT deptno, listagg(hiredate, ', ') WITHIN GROUP(ORDER BY hiredate DESC) AS hiredates FROM emp GROUP BY deptno; deptno | hiredates --------+------------------------------------------------------------------------------------------------------------------------------ 10 | 1982-01-23 00:00:00, 1981-11-17 00:00:00, 1981-06-09 00:00:00 20 | 2001-04-02 00:00:00, 1999-12-17 00:00:00, 1987-05-23 00:00:00, 1987-04-19 00:00:00, 1981-12-03 00:00:00 30 | 2015-02-20 00:00:00, 2010-02-22 00:00:00, 1997-09-28 00:00:00, 1981-12-03 00:00:00, 1981-09-08 00:00:00, 1981-05-01 00:00:00 (3 rows)
The aggregation column is of the time interval type.
postgres=# SELECT deptno, listagg(vacationTime, '; ') WITHIN GROUP(ORDER BY vacationTime DESC) AS vacationTime FROM emp GROUP BY deptno; deptno | vacationtime --------+------------------------------------------------------------------------------------ 10 | 1 year 30 days; 40 days; 10 days 20 | 70 days; 36 days; 9 days; 5 days 30 | 1 year 1 mon; 2 mons 10 days; 30 days; 12 days 12:00:00; 4 days 06:00:00; 24:00:00 (3 rows)
By default, the delimiter is empty.
postgres=# SELECT deptno, listagg(job) WITHIN GROUP(ORDER BY job) AS jobs FROM emp GROUP BY deptno; deptno | jobs --------+---------------------------------------------- 10 | CLERKMANAGERPRESIDENT 20 | ANALYSTANALYSTCLERKCLERKMANAGER 30 | CLERKMANAGERSALESMANSALESMANSALESMANSALESMAN (3 rows)
When listagg is used as a window function, the OVER clause does not support the window sorting of ORDER BY, and the listagg column is an ordered aggregation of the corresponding groups.
postgres=# SELECT deptno, mgrno, bonus, listagg(ename,'; ') WITHIN GROUP(ORDER BY hiredate) OVER(PARTITION BY deptno) AS employees FROM emp; deptno | mgrno | bonus | employees --------+-------+----------+------------------------------------------- 10 | 7839 | 10000.01 | CLARK; KING; MILLER 10 | | 23011.88 | CLARK; KING; MILLER 10 | 7782 | 10234.21 | CLARK; KING; MILLER 20 | 7566 | 2002.12 | FORD; SCOTT; ADAMS; SMITH; JONES 20 | 7566 | 1001.01 | FORD; SCOTT; ADAMS; SMITH; JONES 20 | 7788 | 1100.00 | FORD; SCOTT; ADAMS; SMITH; JONES 20 | 7902 | 2000.80 | FORD; SCOTT; ADAMS; SMITH; JONES 20 | 7839 | 999.10 | FORD; SCOTT; ADAMS; SMITH; JONES 30 | 7839 | 2399.50 | BLAKE; TURNER; JAMES; MARTIN; WARD; ALLEN 30 | 7698 | 9.00 | BLAKE; TURNER; JAMES; MARTIN; WARD; ALLEN 30 | 7698 | 1000.22 | BLAKE; TURNER; JAMES; MARTIN; WARD; ALLEN 30 | 7698 | 99.99 | BLAKE; TURNER; JAMES; MARTIN; WARD; ALLEN 30 | 7698 | 1000.01 | BLAKE; TURNER; JAMES; MARTIN; WARD; ALLEN 30 | 7698 | 899.00 | BLAKE; TURNER; JAMES; MARTIN; WARD; ALLEN (14 rows)
covar_pop(Y, X)
Description: overall covariance
Return type: double precision
Example:
postgres=# SELECT COVAR_POP(sr_fee, sr_net_loss) FROM tpcds.store_returns WHERE sr_customer_sk < 1000; covar_pop ------------------ 829.749627587403 (1 row)
covar_samp(Y, X)
Description: sample covariance
Return type: double precision
Example:
postgres=# SELECT COVAR_SAMP(sr_fee, sr_net_loss) FROM tpcds.store_returns WHERE sr_customer_sk < 1000; covar_samp ------------------ 830.052235037289 (1 row)
stddev_pop(expression)
Description: overall standard difference
Return type: double precision for floating-point arguments, otherwise numeric
Example:
postgres=# SELECT STDDEV_POP(inv_quantity_on_hand) FROM tpcds.inventory WHERE inv_warehouse_sk = 1; stddev_pop ------------------ 289.224294957556 (1 row)
stddev_samp(expression)
Description: sample standard deviation of the input values
Return type: double precision for floating-point arguments, otherwise numeric
Example:
postgres=# SELECT STDDEV_SAMP(inv_quantity_on_hand) FROM tpcds.inventory WHERE inv_warehouse_sk = 1; stddev_samp ------------------ 289.224359757315 (1 row)
var_pop(expression)
Description: population variance of the input values (square of the population standard deviation)
Return type: double precision for floating-point arguments, otherwise numeric
Example:
postgres=# SELECT VAR_POP(inv_quantity_on_hand) FROM tpcds.inventory WHERE inv_warehouse_sk = 1; var_pop -------------------- 83650.692793695475 (1 row)
var_samp(expression)
Description: sample variance of the input values (square of the sample standard deviation)
Return type: double precision for floating-point arguments, otherwise numeric
Example:
postgres=# SELECT VAR_SAMP(inv_quantity_on_hand) FROM tpcds.inventory WHERE inv_warehouse_sk = 1; var_samp -------------------- 83650.730277028768 (1 row)
bit_and(expression)
Description: the bitwise AND of all non-null input values, or null if none
Return type: same as the argument type
Example:
postgres=# SELECT BIT_AND(inv_quantity_on_hand) FROM tpcds.inventory WHERE inv_warehouse_sk = 1; bit_and --------- 0 (1 row)
bit_or(expression)
Description: the bitwise OR of all non-null input values, or null if none
Return type: same as the argument type
Example:
postgres=# SELECT BIT_OR(inv_quantity_on_hand) FROM tpcds.inventory WHERE inv_warehouse_sk = 1; bit_or -------- 1023 (1 row)
bool_and(expression)
Description: Its value is true if all input values are true, otherwise false.
Return type: bool
Example:
postgres=# SELECT bool_and(100 <2500); bool_and ---------- t (1 row)
bool_or(expression)
Description: Its value is true if at least one input value is true, otherwise false.
Return type: bool
Example:
postgres=# SELECT bool_or(100 <2500); bool_or ---------- t (1 row)
corr(Y, X)
Description: correlation coefficient
Return type: double precision
Example:
postgres=# SELECT CORR(sr_fee, sr_net_loss) FROM tpcds.store_returns WHERE sr_customer_sk < 1000; corr ------------------- .0381383624904186 (1 row)
every(expression)
Description: equivalent to bool_and
Return type: bool
Example:
postgres=# SELECT every(100 <2500); every ------- t (1 row)
regr_avgx(Y, X)
Description: average of the independent variable (sum(X)/N)
Return type: double precision
Example:
postgres=# SELECT REGR_AVGX(sr_fee, sr_net_loss) FROM tpcds.store_returns WHERE sr_customer_sk < 1000; regr_avgx ------------------ 578.606576740795 (1 row)
regr_avgy(Y, X)
Description: average of the dependent variable (sum(Y)/N)
Return type: double precision
Example:
postgres=# SELECT REGR_AVGY(sr_fee, sr_net_loss) FROM tpcds.store_returns WHERE sr_customer_sk < 1000; regr_avgy ------------------ 50.0136711629602 (1 row)
regr_count(Y, X)
Description: number of input rows in which both expressions are non-null
Return type: bigint
Example:
postgres=# SELECT REGR_COUNT(sr_fee, sr_net_loss) FROM tpcds.store_returns WHERE sr_customer_sk < 1000; regr_count ------------ 2743 (1 row)
regr_intercept(Y, X)
Description: y-intercept of the least-squares-fit linear equation determined by the (X, Y) pairs
Return type: double precision
Example:
postgres=# SELECT REGR_INTERCEPT(sr_fee, sr_net_loss) FROM tpcds.store_returns WHERE sr_customer_sk < 1000; regr_intercept ------------------ 49.2040847848607 (1 row)
regr_r2(Y, X)
Description: square of the correlation coefficient
Return type: double precision
Example:
postgres=# SELECT REGR_R2(sr_fee, sr_net_loss) FROM tpcds.store_returns WHERE sr_customer_sk < 1000; regr_r2 -------------------- .00145453469345058 (1 row)
regr_slope(Y, X)
Description: slope of the least-squares-fit linear equation determined by the (X, Y) pairs
Return type: double precision
Example:
postgres=# SELECT REGR_SLOPE(sr_fee, sr_net_loss) FROM tpcds.store_returns WHERE sr_customer_sk < 1000; regr_slope -------------------- .00139920009665259 (1 row)
regr_sxx(Y, X)
Description: **sum(X^2) - sum(X)^2/N **(sum of squares of the independent variables)
Return type: double precision
Example:
postgres=# SELECT REGR_SXX(sr_fee, sr_net_loss) FROM tpcds.store_returns WHERE sr_customer_sk < 1000; regr_sxx ------------------ 1626645991.46135 (1 row)
regr_sxy(Y, X)
Description: sum(X*Y) - sum(X) * sum(Y)/N (“sum of products” of independent times dependent variable)
Return type: double precision
Example:
postgres=# SELECT REGR_SXY(sr_fee, sr_net_loss) FROM tpcds.store_returns WHERE sr_customer_sk < 1000; regr_sxy ------------------ 2276003.22847225 (1 row)
regr_syy(Y, X)
Description: sum(Y^2) - sum(Y)^2/N (“sum of squares” of the dependent variable)
Return type: double precision
Example:
postgres=# SELECT REGR_SYY(sr_fee, sr_net_loss) FROM tpcds.store_returns WHERE sr_customer_sk < 1000; regr_syy ----------------- 2189417.6547314 (1 row)
stddev(expression)
Description: alias of stddev_samp
Return type: double precision for floating-point arguments, otherwise numeric
Example:
postgres=# SELECT STDDEV(inv_quantity_on_hand) FROM tpcds.inventory WHERE inv_warehouse_sk = 1; stddev ------------------ 289.224359757315 (1 row)
variance(expexpression,ression)
Description: alias of var_samp
Return type: double precision for floating-point arguments, otherwise numeric
Example:
postgres=# SELECT VARIANCE(inv_quantity_on_hand) FROM tpcds.inventory WHERE inv_warehouse_sk = 1; variance -------------------- 83650.730277028768 (1 row)
checksum(expression)
Description: Returns the CHECKSUM value of all input values. This function can be used to check whether the data in the tables is the same before and after the backup, restoration, or migration of the openGauss database (databases other than openGauss are not supported). Before and after database backup, database restoration, or data migration, you need to manually run SQL commands to obtain the execution results. Compare the obtained execution results to check whether the data in the tables before and after the backup or migration is the same.
NOTE:
- For large tables, the execution of CHECKSUM function may take a long time.
- If the CHECKSUM values of two tables are different, it indicates that the contents of the two tables are different. Using the hash function in the CHECKSUM function may incur conflicts. There is low possibility that two tables with different contents may have the same CHECKSUM value. The same problem may occur when CHECKSUM is used for columns.
- If the time type is timestamp, timestamptz, or smalldatetime, ensure that the time zone settings are the same when calculating the CHECKSUM value.
- If the CHECKSUM value of a column is calculated and the column type can be changed to TEXT by default, set expression to the column name.
- If the CHECKSUM value of a column is calculated and the column type cannot be converted to TEXT by default, set expression to Column name::TEXT.
- If the CHECKSUM value of all columns is calculated, set expression to Table name::TEXT.
The following types of data can be converted into TEXT types by default: char, name, int8, int2, int1, int4, raw, pg_node_tree, float4, float8, bpchar, varchar, nvarchar2, date, timestamp, timestamptz, numeric, and smalldatetime. Other types need to be forcibly converted to TEXT.
Return type: numeric
Example:
The following shows the CHECKSUM value of a column that can be converted to the TEXT type by default:
postgres=# SELECT CHECKSUM(inv_quantity_on_hand) FROM tpcds.inventory; checksum ------------------- 24417258945265247 (1 row)
The following shows the CHECKSUM value of a column that cannot be converted to the TEXT type by default. Note that the CHECKSUM parameter is set to Column name::TEXT.
postgres=# SELECT CHECKSUM(inv_quantity_on_hand::TEXT) FROM tpcds.inventory; checksum ------------------- 24417258945265247 (1 row)
The following shows the CHECKSUM value of all columns in a table. Note that the CHECKSUM parameter is set to Table name::TEXT. The table name is not modified by its schema.
postgres=# SELECT CHECKSUM(inventory::TEXT) FROM tpcds.inventory; checksum ------------------- 25223696246875800 (1 row)
mode() within group (order by value anyelement)
Description: value with the highest occurrence frequency in a column. If multiple values have the same frequency, the smallest value is returned. The sorting mode is the same as the default sorting mode of the column type. value is an input parameter and can be of any type.
Return type: same as the input parameter type
Example:
postgres=# select mode() within group (order by value) from (values(1, 'a'), (2, 'b'), (2, 'c')) v(value, tag); mode ------ 2 (1 row) postgres=# select mode() within group (order by tag) from (values(1, 'a'), (2, 'b'), (2, 'c')) v(value, tag); mode ------ a (1 row)