Aggregate functions

For details about the supported syntaxes of aggregate expressions, see Aggregate function calls.

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General-purpose aggregate functions

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array_agg

Returns an array from input values in which each value in the set is assigned to an array element. The ORDER BY clause is optional and specifies the order of rows processed in the aggregation, which determines the order of the elements in the result array.

array_agg ( expression [ ORDER BY [ sort_expression { ASC | DESC } ] ] ) -> output_array

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avg

Returns the average (arithmetic mean) of the selected values.

avg ( expression ) -> see description

Input types include smallint, int, bigint, numeric, real, and double precision.

Return type is numeric for integer inputs and double precision for float point inputs.

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bit_and

Returns the bitwise AND of all non-null input values or null if no non-null values are provided.

bit_and ( smallint, int, or bigint ) -> same as input type

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bit_or

Returns the bitwise OR of all non-null input values or null if no non-null values are provided.

bit_or ( smallint, int, or bigint ) -> same as input type

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bool_and

Returns true if all input values are true, otherwise false.

bool_and ( boolean ) -> boolean

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bool_or

Returns true if at least one input value is true, otherwise false.

bool_or ( boolean ) -> boolean

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count

Returns the number of non-null rows.

count ( expression ) -> bigint

The input can be of any supported data type.

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jsonb_agg

Aggregates values, including nulls, as a JSON array. The ORDER BY clause is optional and specifies the order of rows processed in the aggregation, which determines the order of the elements in the result array.

jsonb_agg ( any_element ) -> jsonb

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jsonb_object_agg

Aggregates name/value pairs as a JSON object.

jsonb_object_agg ( key "string" , value "any" ) -> jsonb

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max

Returns the maximum value in a set of values.

max ( expression ) -> same as input type

Input can be of any numeric, string, date/time, or interval type, or an array of these types.

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min

Returns the minimum value in a set of values.

min ( expression ) -> same as input type

Input can be of any numeric, string, date/time, or interval type, or an array of these types.

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string_agg

Combines non-null values into a string, separated by delimiter_string. The ORDER BY clause is optional and specifies the order of rows processed in the aggregation, which determines the order of the elements in the result array.

string_agg ( expression, delimiter_string ) -> output_string

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sum

Returns the sum of all input values.

sum ( expression )

Input types include smallint, int, bigint, numeric, real, and double precision.

Return type is bigint for smallint or int inputs, numeric for bigint inputs, otherwise the same as the input data type.

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first_value

Returns the first value in an ordered set of values.

first_value ( expression ORDER BY order_key ) -> same as input type

order_key is the column or expression used to determine the order of the values. It is required to make the result deterministic.

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last_value

Returns the last value in an ordered set of values.

last_value ( expression ORDER BY order_key ) -> same as input type

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Aggregate functions for statistics

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stddev_pop

Calculates the population standard deviation of the input values. Returns NULL if the input contains no non-null values.

stddev_pop ( expression ) -> output_value

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stddev_samp

Calculates the sample standard deviation of the input values. Returns NULL if the input contains fewer than two non-null values.

stddev_samp ( expression ) -> output_value

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var_pop

Calculates the population variance of the input values. Returns NULL if the input contains no non-null values.

var_pop ( expression ) -> output_value

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var_samp

Calculates the sample variance of the input values. Returns NULL if the input contains fewer than two non-null values.

var_samp ( expression ) -> output_value

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Ordered-set aggregate functions

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mode

Computes the mode, which is the most frequent value of the aggregated argument. If there are multiple equally-frequent values, it arbitrarily chooses the first one.

mode () WITHIN GROUP ( ORDER BY sort_expression anyelement ) -> same as sort_expression

sort_expression: Must be of a sortable type.

This example calculates the mode of the values in column1 from table1.

SELECT mode() WITHIN GROUP (ORDER BY column1) FROM table1;

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percentile_cont

Computes the continuous percentile, which is a value corresponding to the specified fraction within the ordered set of aggregated argument values. It can interpolate between adjacent input items if needed.

percentile_cont ( fraction double precision ) WITHIN GROUP ( ORDER BY sort_expression double precision ) -> double precision

fraction: The fraction value representing the desired percentile. It should be between 0 and 1.

This example calculates the median (50th percentile) of the values in column1 from table1.

SELECT percentile_cont(0.5) WITHIN GROUP (ORDER BY column1) FROM table1;

If NULL is provided, the function will not calculate a specific percentile and return NULL instead.

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percentile_disc

Computes the discrete percentile, which is the first value within the ordered set of aggregated argument values whose position in the ordering equals or exceeds the specified fraction.

percentile_disc ( fraction double precision ) WITHIN GROUP ( ORDER BY sort_expression anyelement ) -> same as sort_expression

fraction: The fraction value representing the desired percentile. It should be between 0 and 1.

sort_expression: Must be of a sortable type.

This example calculates the 75th percentile of the values in column1 from table1.

SELECT percentile_disc(0.75) WITHIN GROUP (ORDER BY column1) FROM table1;

If NULL is provided, the function will not calculate a specific percentile and return NULL instead.

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approx_percentile

Returns an approximate value of the specified percentile from a numeric column.

approx_percentile(DOUBLE percentile [, DOUBLE relative_error]) WITHIN GROUP (ORDER BY percentile_column) -> output_value

• percentile: The percentile to approximate. It should be between 0 and 1.
• relative_error: Optional. Specifies the maximum allowed error in the approximation. Defaults to 0.01 (1%).
• percentile_column: The column from which to calculate the percentile. Must be of a numeric type.

This example calculates the 50th percentile of a numeric column with the default relative error:

SELECT approx_percentile(0.5) WITHIN GROUP (ORDER BY column1) FROM table1;

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Grouping operation functions

Grouping operation functions are used in conjunction with grouping sets to distinguish result rows. The arguments to the grouping() function are not actually evaluated, but they must exactly match expressions given in the GROUP BY clause of the associated query level.

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grouping

Returns a bit mask indicating which GROUP BY expressions are not included in the current grouping set. Bits are assigned with the rightmost argument corresponding to the least-significant bit; each bit is 0 if the corresponding expression is included in the grouping criteria of the grouping set generating the current result row, and 1 if it is not included.

grouping ( group_by_expression(s) ) → integer

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Example

CREATE TABLE items_sold (brand varchar, size varchar, sales int);

INSERT INTO items_sold VALUES ('Foo', 'L', 10),('Foo', 'M', 20),('Bar', 'M', 15),('Bar', 'L', '5');

SELECT brand, size, sum(sales), grouping(brand), grouping(size), grouping(brand,size), count(DISTINCT sales)
FROM items_sold
GROUP BY GROUPING SETS ((brand), (size), ());
------RESULTS
Bar NULL 20 0 1 1 2
Foo NULL 30 0 1 1 2
NULL L 15 1 0 2 2
NULL M 35 1 0 2 2
NULL NULL 50 1 1 3 4