ColumnStore Distributed Aggregate Functions
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MariaDB ColumnStore supports the following aggregate functions, these can be used in the SELECT, HAVING, and ORDER BY clauses of the SQL statement.
Function | Description |
---|---|
AVG([DISTINCT] column) | Average value of a numeric (INT variations, NUMERIC, DECIMAL) column |
COUNT (*, [DISTINCT] column) | The number of rows returned by a query or grouping. All datatypes are supported |
MAX ([DISTINCT] column) | The maximum value of a column. All datatypes are supported. |
MIN ([DISTINCT] column) | The maximum value of a column. All datatypes are supported. |
STD(), STDDEV(), STDDEV_POP() | The population standard deviation of a numeric (INT variations, NUMERIC, DECIMAL) column |
STDDEV_SAMP() | The sample standard deviation of a numeric (INT variations, NUMERIC, DECIMAL) column |
SUM([DISTINCT] column) | The sum of a numeric (INT variations, NUMERIC, DECIMAL) column |
VARIANCE(), VAR_POP() | The population standard variance of a numeric (INT variations, NUMERIC, DECIMAL) column |
VAR_SAMP() | The population standard variance of a numeric (INT variations, NUMERIC, DECIMAL) column |
REGR_AVGX(ColumnY, ColumnX) | average of the independent variable (sum(ColumnX)/N), where N is number of rows processed by the query |
REGR_AVGY(ColumnY, ColumnX) | average of the dependent variable (sum(ColumnY)/N), where N is number of rows processed by the query |
REGR_COUNT(ColumnY, ColumnX) | The total number of input rows in which both column Y and column X are nonnull |
REGR_SLOPE(ColumnY, ColumnX) | The slope of the least-squares-fit linear equation determined by the (ColumnX, ColumnY) pairs |
REGR_INTERCEPT(ColumnY, ColumnX) | The y-intercept of the least-squares-fit linear equation determined by the (ColumnX, ColumnY) pairs |
REGR_R2(ColumnY, ColumnX) | square of the correlation coefficient. correlation coefficient is the regr_intercept(ColumnY, ColumnX) for linear model |
Note
- Regression functions (REGR_AVGX to REGR_R2) are supported for version 1.2.0 and higher
Example
An example group by query using aggregate functions is:
select year(o_orderdate) order_year, avg(o_totalprice) avg_totalprice, max(o_totalprice) max_totalprice, count(*) order_count from orders group by order_year order by order_year;
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