docs/source/user-guide/sql/aggregate_functions.md

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# Aggregate Functions

Aggregate functions operate on a set of values to compute a single result.

## General Functions

- [array_agg](#array_agg)
- [avg](#avg)
- [bit_and](#bit_and)
- [bit_or](#bit_or)
- [bit_xor](#bit_xor)
- [bool_and](#bool_and)
- [bool_or](#bool_or)
- [count](#count)
- [first_value](#first_value)
- [grouping](#grouping)
- [last_value](#last_value)
- [max](#max)
- [mean](#mean)
- [median](#median)
- [min](#min)
- [string_agg](#string_agg)
- [sum](#sum)
- [var](#var)
- [var_pop](#var_pop)
- [var_population](#var_population)
- [var_samp](#var_samp)
- [var_sample](#var_sample)

### `array_agg`

Returns an array created from the expression elements. If ordering is required, elements are inserted in the specified order.

```
array_agg(expression [ORDER BY expression])
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT array_agg(column_name ORDER BY other_column) FROM table_name;
+-----------------------------------------------+
| array_agg(column_name ORDER BY other_column)  |
+-----------------------------------------------+
| [element1, element2, element3]                |
+-----------------------------------------------+
```

### `avg`

Returns the average of numeric values in the specified column.

```
avg(expression)
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT avg(column_name) FROM table_name;
+---------------------------+
| avg(column_name)           |
+---------------------------+
| 42.75                      |
+---------------------------+
```

#### Aliases

- mean

### `bit_and`

Computes the bitwise AND of all non-null input values.

```
bit_and(expression)
```

#### Arguments

- **expression**: Integer expression to operate on. Can be a constant, column, or function, and any combination of operators.

### `bit_or`

Computes the bitwise OR of all non-null input values.

```
bit_or(expression)
```

#### Arguments

- **expression**: Integer expression to operate on. Can be a constant, column, or function, and any combination of operators.

### `bit_xor`

Computes the bitwise exclusive OR of all non-null input values.

```
bit_xor(expression)
```

#### Arguments

- **expression**: Integer expression to operate on. Can be a constant, column, or function, and any combination of operators.

### `bool_and`

Returns true if all non-null input values are true, otherwise false.

```
bool_and(expression)
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT bool_and(column_name) FROM table_name;
+----------------------------+
| bool_and(column_name)       |
+----------------------------+
| true                        |
+----------------------------+
```

### `bool_or`

Returns true if all non-null input values are true, otherwise false.

```
bool_and(expression)
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT bool_and(column_name) FROM table_name;
+----------------------------+
| bool_and(column_name)       |
+----------------------------+
| true                        |
+----------------------------+
```

### `count`

Returns the number of non-null values in the specified column. To include null values in the total count, use `count(*)`.

```
count(expression)
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT count(column_name) FROM table_name;
+-----------------------+
| count(column_name)     |
+-----------------------+
| 100                   |
+-----------------------+

> SELECT count(*) FROM table_name;
+------------------+
| count(*)         |
+------------------+
| 120              |
+------------------+
```

### `first_value`

Returns the first element in an aggregation group according to the requested ordering. If no ordering is given, returns an arbitrary element from the group.

```
first_value(expression [ORDER BY expression])
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT first_value(column_name ORDER BY other_column) FROM table_name;
+-----------------------------------------------+
| first_value(column_name ORDER BY other_column)|
+-----------------------------------------------+
| first_element                                 |
+-----------------------------------------------+
```

### `grouping`

Returns 1 if the data is aggregated across the specified column, or 0 if it is not aggregated in the result set.

```
grouping(expression)
```

#### Arguments

- **expression**: Expression to evaluate whether data is aggregated across the specified column. Can be a constant, column, or function.

#### Example

```sql
> SELECT column_name, GROUPING(column_name) AS group_column
  FROM table_name
  GROUP BY GROUPING SETS ((column_name), ());
+-------------+-------------+
| column_name | group_column |
+-------------+-------------+
| value1      | 0           |
| value2      | 0           |
| NULL        | 1           |
+-------------+-------------+
```

### `last_value`

Returns the last element in an aggregation group according to the requested ordering. If no ordering is given, returns an arbitrary element from the group.

```
last_value(expression [ORDER BY expression])
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT last_value(column_name ORDER BY other_column) FROM table_name;
+-----------------------------------------------+
| last_value(column_name ORDER BY other_column) |
+-----------------------------------------------+
| last_element                                  |
+-----------------------------------------------+
```

### `max`

Returns the maximum value in the specified column.

```
max(expression)
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT max(column_name) FROM table_name;
+----------------------+
| max(column_name)      |
+----------------------+
| 150                  |
+----------------------+
```

### `mean`

_Alias of [avg](#avg)._

### `median`

Returns the median value in the specified column.

```
median(expression)
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT median(column_name) FROM table_name;
+----------------------+
| median(column_name)   |
+----------------------+
| 45.5                 |
+----------------------+
```

### `min`

Returns the minimum value in the specified column.

```
min(expression)
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT min(column_name) FROM table_name;
+----------------------+
| min(column_name)      |
+----------------------+
| 12                   |
+----------------------+
```

### `string_agg`

Concatenates the values of string expressions and places separator values between them.

```
string_agg(expression, delimiter)
```

#### Arguments

- **expression**: The string expression to concatenate. Can be a column or any valid string expression.
- **delimiter**: A literal string used as a separator between the concatenated values.

#### Example

```sql
> SELECT string_agg(name, ', ') AS names_list
  FROM employee;
+--------------------------+
| names_list               |
+--------------------------+
| Alice, Bob, Charlie      |
+--------------------------+
```

### `sum`

Returns the sum of all values in the specified column.

```
sum(expression)
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT sum(column_name) FROM table_name;
+-----------------------+
| sum(column_name)       |
+-----------------------+
| 12345                 |
+-----------------------+
```

### `var`

Returns the statistical sample variance of a set of numbers.

```
var(expression)
```

#### Arguments

- **expression**: Numeric expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Aliases

- var_sample
- var_samp

### `var_pop`

Returns the statistical population variance of a set of numbers.

```
var_pop(expression)
```

#### Arguments

- **expression**: Numeric expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Aliases

- var_population

### `var_population`

_Alias of [var_pop](#var_pop)._

### `var_samp`

_Alias of [var](#var)._

### `var_sample`

_Alias of [var](#var)._

## Statistical Functions

- [corr](#corr)
- [covar](#covar)
- [covar_pop](#covar_pop)
- [covar_samp](#covar_samp)
- [nth_value](#nth_value)
- [regr_avgx](#regr_avgx)
- [regr_avgy](#regr_avgy)
- [regr_count](#regr_count)
- [regr_intercept](#regr_intercept)
- [regr_r2](#regr_r2)
- [regr_slope](#regr_slope)
- [regr_sxx](#regr_sxx)
- [regr_sxy](#regr_sxy)
- [regr_syy](#regr_syy)
- [stddev](#stddev)
- [stddev_pop](#stddev_pop)
- [stddev_samp](#stddev_samp)

### `corr`

Returns the coefficient of correlation between two numeric values.

```
corr(expression1, expression2)
```

#### Arguments

- **expression1**: First expression to operate on. Can be a constant, column, or function, and any combination of operators.
- **expression2**: Second expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT corr(column1, column2) FROM table_name;
+--------------------------------+
| corr(column1, column2)         |
+--------------------------------+
| 0.85                           |
+--------------------------------+
```

### `covar`

_Alias of [covar_samp](#covar_samp)._

### `covar_pop`

Returns the sample covariance of a set of number pairs.

```
covar_samp(expression1, expression2)
```

#### Arguments

- **expression1**: First expression to operate on. Can be a constant, column, or function, and any combination of operators.
- **expression2**: Second expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT covar_samp(column1, column2) FROM table_name;
+-----------------------------------+
| covar_samp(column1, column2)      |
+-----------------------------------+
| 8.25                              |
+-----------------------------------+
```

### `covar_samp`

Returns the sample covariance of a set of number pairs.

```
covar_samp(expression1, expression2)
```

#### Arguments

- **expression1**: First expression to operate on. Can be a constant, column, or function, and any combination of operators.
- **expression2**: Second expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT covar_samp(column1, column2) FROM table_name;
+-----------------------------------+
| covar_samp(column1, column2)      |
+-----------------------------------+
| 8.25                              |
+-----------------------------------+
```

#### Aliases

- covar

### `nth_value`

Returns the nth value in a group of values.

```
nth_value(expression, n ORDER BY expression)
```

#### Arguments

- **expression**: The column or expression to retrieve the nth value from.
- **n**: The position (nth) of the value to retrieve, based on the ordering.

#### Example

```sql
> SELECT dept_id, salary, NTH_VALUE(salary, 2) OVER (PARTITION BY dept_id ORDER BY salary ASC) AS second_salary_by_dept
  FROM employee;
+---------+--------+-------------------------+
| dept_id | salary | second_salary_by_dept   |
+---------+--------+-------------------------+
| 1       | 30000  | NULL                    |
| 1       | 40000  | 40000                   |
| 1       | 50000  | 40000                   |
| 2       | 35000  | NULL                    |
| 2       | 45000  | 45000                   |
+---------+--------+-------------------------+
```

### `regr_avgx`

Computes the average of the independent variable (input) expression_x for the non-null paired data points.

```
regr_avgx(expression_y, expression_x)
```

#### Arguments

- **expression_y**: Dependent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.
- **expression_x**: Independent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.

### `regr_avgy`

Computes the average of the dependent variable (output) expression_y for the non-null paired data points.

```
regr_avgy(expression_y, expression_x)
```

#### Arguments

- **expression_y**: Dependent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.
- **expression_x**: Independent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.

### `regr_count`

Counts the number of non-null paired data points.

```
regr_count(expression_y, expression_x)
```

#### Arguments

- **expression_y**: Dependent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.
- **expression_x**: Independent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.

### `regr_intercept`

Computes the y-intercept of the linear regression line. For the equation (y = kx + b), this function returns b.

```
regr_intercept(expression_y, expression_x)
```

#### Arguments

- **expression_y**: Dependent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.
- **expression_x**: Independent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.

### `regr_r2`

Computes the square of the correlation coefficient between the independent and dependent variables.

```
regr_r2(expression_y, expression_x)
```

#### Arguments

- **expression_y**: Dependent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.
- **expression_x**: Independent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.

### `regr_slope`

Returns the slope of the linear regression line for non-null pairs in aggregate columns. Given input column Y and X: regr_slope(Y, X) returns the slope (k in Y = k\*X + b) using minimal RSS fitting.

```
regr_slope(expression_y, expression_x)
```

#### Arguments

- **expression_y**: Dependent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.
- **expression_x**: Independent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.

### `regr_sxx`

Computes the sum of squares of the independent variable.

```
regr_sxx(expression_y, expression_x)
```

#### Arguments

- **expression_y**: Dependent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.
- **expression_x**: Independent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.

### `regr_sxy`

Computes the sum of products of paired data points.

```
regr_sxy(expression_y, expression_x)
```

#### Arguments

- **expression_y**: Dependent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.
- **expression_x**: Independent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.

### `regr_syy`

Computes the sum of squares of the dependent variable.

```
regr_syy(expression_y, expression_x)
```

#### Arguments

- **expression_y**: Dependent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.
- **expression_x**: Independent variable expression to operate on. Can be a constant, column, or function, and any combination of operators.

### `stddev`

Returns the standard deviation of a set of numbers.

```
stddev(expression)
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT stddev(column_name) FROM table_name;
+----------------------+
| stddev(column_name)   |
+----------------------+
| 12.34                |
+----------------------+
```

#### Aliases

- stddev_samp

### `stddev_pop`

Returns the population standard deviation of a set of numbers.

```
stddev_pop(expression)
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT stddev_pop(column_name) FROM table_name;
+--------------------------+
| stddev_pop(column_name)   |
+--------------------------+
| 10.56                    |
+--------------------------+
```

### `stddev_samp`

_Alias of [stddev](#stddev)._

## Approximate Functions

- [approx_distinct](#approx_distinct)
- [approx_median](#approx_median)
- [approx_percentile_cont](#approx_percentile_cont)
- [approx_percentile_cont_with_weight](#approx_percentile_cont_with_weight)

### `approx_distinct`

Returns the approximate number of distinct input values calculated using the HyperLogLog algorithm.

```
approx_distinct(expression)
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT approx_distinct(column_name) FROM table_name;
+-----------------------------------+
| approx_distinct(column_name)      |
+-----------------------------------+
| 42                                |
+-----------------------------------+
```

### `approx_median`

Returns the approximate median (50th percentile) of input values. It is an alias of `approx_percentile_cont(x, 0.5)`.

```
approx_median(expression)
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.

#### Example

```sql
> SELECT approx_median(column_name) FROM table_name;
+-----------------------------------+
| approx_median(column_name)        |
+-----------------------------------+
| 23.5                              |
+-----------------------------------+
```

### `approx_percentile_cont`

Returns the approximate percentile of input values using the t-digest algorithm.

```
approx_percentile_cont(expression, percentile, centroids)
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.
- **percentile**: Percentile to compute. Must be a float value between 0 and 1 (inclusive).
- **centroids**: Number of centroids to use in the t-digest algorithm. _Default is 100_. A higher number results in more accurate approximation but requires more memory.

#### Example

```sql
> SELECT approx_percentile_cont(column_name, 0.75, 100) FROM table_name;
+-------------------------------------------------+
| approx_percentile_cont(column_name, 0.75, 100)  |
+-------------------------------------------------+
| 65.0                                            |
+-------------------------------------------------+
```

### `approx_percentile_cont_with_weight`

Returns the weighted approximate percentile of input values using the t-digest algorithm.

```
approx_percentile_cont_with_weight(expression, weight, percentile)
```

#### Arguments

- **expression**: The expression to operate on. Can be a constant, column, or function, and any combination of operators.
- **weight**: Expression to use as weight. Can be a constant, column, or function, and any combination of arithmetic operators.
- **percentile**: Percentile to compute. Must be a float value between 0 and 1 (inclusive).

#### Example

```sql
> SELECT approx_percentile_cont_with_weight(column_name, weight_column, 0.90) FROM table_name;
+----------------------------------------------------------------------+
| approx_percentile_cont_with_weight(column_name, weight_column, 0.90) |
+----------------------------------------------------------------------+
| 78.5                                                                 |
+----------------------------------------------------------------------+
```