Aggregate Functions

Aggregate functions compute a single result from a set of input rows. They are typically used with the GROUP BY clause in SELECT statements, but can also be used without GROUP BY to aggregate over all rows. When used in a SELECT with non-aggregate columns and no GROUP BY, the result is a single row.

All standard aggregate functions ignore NULL values (except count(*)). If every input value is NULL, the aggregate returns NULL, with the exception of count() (which returns 0) and total() (which returns 0.0).

Function Reference

Detailed Descriptions and Examples

The examples below use the following table:

CREATE TABLE sales (
    id INTEGER PRIMARY KEY,
    region TEXT,
    product TEXT,
    amount REAL,
    quantity INTEGER
);

INSERT INTO sales VALUES
    (1, 'North', 'Widget', 100.00, 5),
    (2, 'North', 'Gadget', 250.00, 2),
    (3, 'South', 'Widget', 150.00, 8),
    (4, 'South', 'Gadget', NULL, 3),
    (5, 'North', 'Widget', 200.00, NULL),
    (6, 'South', 'Widget', 175.00, 6);

avg(X)

avg(X)

Returns the average of all non-NULL values of X as a REAL (floating-point) number. Returns NULL if all values are NULL.

Return type: REAL

SELECT avg(amount) FROM sales;
-- 175.0 (sum of non-NULL amounts / count of non-NULL amounts = 875.0 / 5)

SELECT region, avg(amount) AS avg_amount
FROM sales
GROUP BY region;

count(X) and count(*)

count(X)
count(*)

count(X) returns the number of rows where X is not NULL. count(*) returns the total number of rows in the group, including rows with NULL values.

Return type: INTEGER

SELECT count(*) FROM sales;
-- 6 (all rows)

SELECT count(amount) FROM sales;
-- 5 (excludes the row where amount is NULL)

SELECT region, count(*) AS total_rows, count(amount) AS rows_with_amount
FROM sales
GROUP BY region;

group_concat(X) and group_concat(X, Y)

group_concat(X)
group_concat(X, Y)

Concatenates all non-NULL values of X into a single string. The default separator is a comma (,). When Y is provided, it is used as the separator instead.

Return type: TEXT

SELECT group_concat(product) FROM sales;
-- 'Widget,Gadget,Widget,Gadget,Widget,Widget'

SELECT group_concat(DISTINCT product) FROM sales;
-- 'Widget,Gadget'

SELECT region, group_concat(product, ' | ') AS products
FROM sales
GROUP BY region;

string_agg(X, Y)

string_agg(X, Y)

Alias for group_concat(X, Y). Provided for compatibility with PostgreSQL.

Return type: TEXT

SELECT region, string_agg(product, ', ') AS products
FROM sales
GROUP BY region;

max(X) and min(X)

max(X)
min(X)

max(X) returns the maximum non-NULL value of X. min(X) returns the minimum non-NULL value of X. Values are compared using the standard SQLite comparison rules. Returns NULL if all values are NULL.

Return type: Same as the input type

SELECT max(amount), min(amount) FROM sales;
-- max: 250.0, min: 100.0

SELECT region, max(amount) AS highest, min(amount) AS lowest
FROM sales
GROUP BY region;

sum(X) and total(X)

sum(X)
total(X)

Both functions return the sum of all non-NULL values of X. They differ in return type and behavior when all values are NULL.

Return type:

• sum(X): INTEGER if all non-NULL inputs are integers and no overflow occurs, otherwise REAL. Returns NULL if all values are NULL.
• total(X): Always REAL. Returns 0.0 if all values are NULL.

SELECT sum(amount), total(amount) FROM sales;
-- sum: 875.0, total: 875.0

SELECT sum(quantity), total(quantity) FROM sales;
-- sum: 24, total: 24.0

Difference between sum() and total()

The key difference appears when all values in the group are NULL:

CREATE TABLE empty_amounts (val REAL);
INSERT INTO empty_amounts VALUES (NULL), (NULL);

SELECT sum(val) FROM empty_amounts;
-- NULL

SELECT total(val) FROM empty_amounts;
-- 0.0

This makes total() convenient when you need a numeric result even for empty or all-NULL groups:

SELECT
    region,
    sum(amount) AS sum_amount,
    total(amount) AS total_amount
FROM sales
GROUP BY region;

-- total() is useful in arithmetic to avoid NULL propagation
SELECT total(amount) * 1.1 AS with_tax FROM sales;
-- 962.5

-- sum() with all NULLs would produce NULL, making the multiplication NULL too

Using Aggregates with GROUP BY

The GROUP BY clause partitions rows into groups. Each aggregate function is computed independently for each group.

SELECT
    region,
    product,
    count(*) AS order_count,
    sum(amount) AS total_sales,
    avg(amount) AS avg_sale,
    min(amount) AS min_sale,
    max(amount) AS max_sale
FROM sales
GROUP BY region, product;

Filtering Groups with HAVING

The HAVING clause filters groups after aggregation. Use WHERE to filter rows before aggregation and HAVING to filter groups after.

SELECT region, sum(amount) AS total_sales
FROM sales
WHERE amount IS NOT NULL
GROUP BY region
HAVING sum(amount) > 400;

Aggregates with DISTINCT

The DISTINCT keyword causes the aggregate to consider only unique non-NULL values.

SELECT count(product) FROM sales;
-- 6 (all non-NULL product values)

SELECT count(DISTINCT product) FROM sales;
-- 2 (only 'Widget' and 'Gadget')

SELECT group_concat(DISTINCT product) FROM sales;
-- 'Widget,Gadget'

Aggregates as Window Functions

All standard aggregate functions can be used as window functions. When used with an OVER clause, the function computes a running or partitioned result without collapsing rows.

SELECT
    id,
    region,
    amount,
    sum(amount) OVER (PARTITION BY region ORDER BY id) AS running_total,
    count(*) OVER (PARTITION BY region) AS region_count
FROM sales
ORDER BY region, id;

Ordered-Set Aggregates (WITHIN GROUP)

Ordered-set aggregates compute a result over the values of an ORDER BY expression, sorted within each group:

mode() WITHIN GROUP (ORDER BY sort_expr)
percentile_cont(fraction) WITHIN GROUP (ORDER BY sort_expr)
percentile_disc(fraction) WITHIN GROUP (ORDER BY sort_expr)

The ORDER BY expression is the value being aggregated. For the percentile functions, the argument before WITHIN GROUP is the percentile fraction. NULL values of the ORDER BY expression are ignored; if there are no non-NULL values, the result is NULL.

mode()

mode() WITHIN GROUP (ORDER BY X)

Returns the most frequent value of X. If several values are equally frequent, the smallest is returned. Works with any type and returns the value in its original type.

Return type: same as X

SELECT mode() WITHIN GROUP (ORDER BY product) FROM sales;
-- 'Widget' (the most frequent product)

SELECT region, mode() WITHIN GROUP (ORDER BY product) AS top_product
FROM sales
GROUP BY region;

percentile_cont(fraction) and percentile_disc(fraction)

percentile_cont(fraction) WITHIN GROUP (ORDER BY X)
percentile_disc(fraction) WITHIN GROUP (ORDER BY X)

Compute the fraction-th percentile of X, where fraction is between 0.0 and 1.0:

• percentile_cont returns a continuous, interpolated value (always REAL).
• percentile_disc returns the actual element at the discrete percentile position, in its original type.

Return type: REAL for percentile_cont; same as X for percentile_disc

-- Median, interpolated vs. an actual data point
SELECT percentile_cont(0.5) WITHIN GROUP (ORDER BY amount) FROM sales;  -- 175.0
SELECT percentile_disc(0.5) WITHIN GROUP (ORDER BY amount) FROM sales;  -- 175.0

-- Quartiles per region
SELECT region,
       percentile_cont(0.25) WITHIN GROUP (ORDER BY amount) AS q1,
       percentile_cont(0.75) WITHIN GROUP (ORDER BY amount) AS q3
FROM sales
WHERE amount IS NOT NULL
GROUP BY region;

The fraction must be a constant with respect to the rows being aggregated — a literal, a constant expression, or a parameter. It cannot reference the columns being aggregated, and an out-of-range constant fraction is reported regardless of how many rows match:

SELECT percentile_cont(2.0) WITHIN GROUP (ORDER BY amount) FROM sales;
-- Error: percentile value 2 is not between 0 and 1

Collation

Text values are ordered using the applicable collation — an explicit COLLATE on the ORDER BY expression, the column's declared collation, or BINARY by default — consistent with ORDER BY.

Notes and limitations

• A single ORDER BY expression is required. Multiple expressions, DESC, and NULLS FIRST/LAST inside WITHIN GROUP are not yet supported.
• A subquery as the fraction argument is not currently supported.
• These aggregates work with GROUP BY, FILTER (WHERE ...), HAVING, subqueries, CTEs, joins, and attached databases.
• The percentile extension also provides non-standard two-argument forms, percentile_cont(Y, P) and percentile_disc(Y, P) (see Extension Aggregate Functions). The WITHIN GROUP forms above are the SQL-standard versions and require no extension.

Turso Extension: array_agg(X)

array_agg(X)

Collects all values of X (including NULLs) into an array. Returns NULL if the group is empty.

Return type: BLOB (array)

SELECT array_agg(name) FROM users;
-- ["Alice","Bob","Charlie"]

SELECT department, array_agg(name) FROM employees GROUP BY department;

-- Control ordering with a subquery
SELECT array_agg(name) FROM (SELECT name FROM users ORDER BY name);

-- Combine with array_length
SELECT array_length(array_agg(name)) FROM users;
-- 3

For more array functions, see Array Functions.

Turso Extension: stddev(X)

stddev(X)

Returns the population standard deviation of all non-NULL values of X. Returns NULL if there are no non-NULL values.

Return type: REAL

SELECT stddev(amount) FROM sales;

SELECT region, avg(amount) AS mean, stddev(amount) AS std_dev
FROM sales
GROUP BY region;

Extension Aggregate Functions

The following aggregate functions are available through the percentile extension. Load it before use.

median(X)

median(X)

Returns the median (middle value) of all non-NULL values of X.

Return type: REAL

SELECT median(amount) FROM sales;
-- 175.0

SELECT region, median(amount) AS median_amount
FROM sales
GROUP BY region;

percentile(Y, P)

percentile(Y, P)

Returns the P-th percentile of all non-NULL values of Y. Uses linear interpolation between adjacent values.

Return type: REAL

SELECT percentile(amount, 50) FROM sales;   -- 50th percentile (median)
SELECT percentile(amount, 90) FROM sales;   -- 90th percentile
SELECT percentile(amount, 25) FROM sales;   -- 25th percentile (Q1)

percentile_cont(Y, P) and percentile_disc(Y, P)

percentile_cont(Y, P)
percentile_disc(Y, P)

These two-argument forms are a convenience provided by the percentile extension. The SQL-standard spelling — percentile_cont(P) WITHIN GROUP (ORDER BY Y) — is built in and needs no extension; see Ordered-Set Aggregates above. percentile_cont uses a continuous (interpolated) distribution, while percentile_disc returns a discrete input value.

Return type: REAL

-- Continuous percentile (interpolates between values)
SELECT percentile_cont(amount, 0.5) FROM sales;

-- Discrete percentile (returns an actual input value)
SELECT percentile_disc(amount, 0.5) FROM sales;

See Also

• Scalar Functions for per-row functions
• Expressions for operator syntax, CAST, CASE, and subqueries
• SELECT for GROUP BY, HAVING, and window function syntax