# DISTINCT > For the complete documentation index, see [llms.txt](https://docs.redpanda.com/llms.txt). Component-specific: [cloud-data-platform-full.txt](https://docs.redpanda.com/cloud-data-platform-full.txt) --- title: DISTINCT latest-operator-version: v26.1.4 latest-console-tag: v3.7.3 latest-connect-version: 4.93.0 latest-redpanda-tag: v26.1.9 docname: sql/sql-functions/aggregate-functions/distinct page-component-name: cloud-data-platform page-version: master page-component-version: master page-component-title: Cloud page-relative-src-path: sql/sql-functions/aggregate-functions/distinct.adoc page-edit-url: https://github.com/redpanda-data/cloud-docs/edit/main/modules/reference/pages/sql/sql-functions/aggregate-functions/distinct.adoc description: When using aggregation functions, they can contain the DISTINCT keyword. page-topic-type: reference page-git-created-date: "2026-05-26" page-git-modified-date: "2026-05-26" --- When using aggregation functions, they can contain the `DISTINCT` keyword. It acts as a qualifier for them, to ensure that only unique values are being processed. Syntax: ```sql aggregation function (DISTINCT expression [clause] ...) ... ``` `DISTINCT` keyword can be combined with the following aggregate functions: - `avg()` - `count()` - `max()` - `min()` - `sum()` All functions listed in this section operate on the same input and return types, that are supported by their counterparts without any qualifiers. They can be grouped without any limitations, provided that they utilise a single `DISTINCT` keyword. ## [](#examples)Examples This section focuses on a few examples that showcase sample usage of these concepts. They are based on creation of the following tables: ```sql CREATE TABLE customer ( customer_id int, cust_name text ); INSERT INTO customer (customer_id, cust_name) VALUES (11112, 'Alex'), (11113, 'Aaron'), (11114, 'Alice'), (11115, 'Nina'), (11116, 'Rosy'), (11117, 'Martha'), (11118, 'John'); CREATE TABLE rental ( rental_id int, rental_date timestamp, return_date timestamp, car text, customer_id int, total_price int ); INSERT INTO rental (rental_id, rental_date, return_date, car, customer_id, total_price) VALUES (8557411, '2022-04-02 09:10:19', '2022-04-10 10:15:05', 'Audi', 11112, 1400), (8557421, '2022-04-06 07:00:30', '2022-04-19 07:10:19', 'BMW', 11115, 2000), (8557451, '2022-04-19 08:00:20', '2022-04-24 08:05:00', 'Cadillac', 11112, 1000), (8557311, '2022-05-11 09:15:28', '2022-05-18 09:00:18', 'Audi', 11115, 1500), (8557321, '2022-05-20 10:12:22', '2022-05-28 10:08:48', 'Audi', 11113, 1500), (8557351, '2022-06-10 12:18:09', '2022-06-20 18:12:23', 'Cadillac', 11114, 1200), (8557221, '2022-06-17 14:02:02', '2022-06-20 14:17:02', 'Chevrolet', 11112, 1300), (8557251, '2022-07-12 05:19:49', '2022-07-19 07:15:28', 'Chevrolet', 11116, 1400), (8557231, '2022-08-09 09:29:08', '2022-08-24 09:30:58', 'Cadillac', 11114, 2000), (8557291, '2022-08-18 15:15:20', '2022-09-01 15:30:19', 'BMW', 11117, 3000); ``` The created tables: ```sql SELECT * FROM customer; +-------------+-----------+ | customer_id | cust_name | +-------------+-----------+ | 11112 | Alex | | 11113 | Aaron | | 11114 | Alice | | 11115 | Nina | | 11116 | Rosy | | 11117 | Martha | | 11118 | John | +-------------+-----------+ SELECT * FROM rental; +------------+---------------------+---------------------+-----------+---------------+-------------+ | rental_id | rental_date | return_date | car | customer_id | total_price | +------------+---------------------+---------------------+-----------+---------------+-------------+ | 8557411 | 2022-04-02 09:10:19 | 2022-04-10 10:15:05 | Audi | 11112 | 1400 | | 8557421 | 2022-04-06 07:00:30 | 2022-04-19 07:10:19 | BMW | 11115 | 2000 | | 8557451 | 2022-04-19 08:00:20 | 2022-04-24 08:05:00 | Cadillac | 11112 | 1000 | | 8557311 | 2022-05-11 09:15:28 | 2022-05-18 09:00:18 | Audi | 11115 | 1500 | | 8557321 | 2022-05-20 10:12:22 | 2022-05-28 10:08:48 | Audi | 11113 | 1500 | | 8557351 | 2022-06-10 12:18:09 | 2022-06-20 18:12:23 | Cadillac | 11114 | 1200 | | 8557221 | 2022-06-17 14:02:02 | 2022-06-20 14:17:02 | Chevrolet | 11112 | 1300 | | 8557251 | 2022-07-12 05:19:49 | 2022-07-19 07:15:28 | Chevrolet | 11116 | 1400 | | 8557231 | 2022-08-09 09:29:08 | 2022-08-24 09:30:58 | Cadillac | 11114 | 2000 | | 8557291 | 2022-08-18 15:15:20 | 2022-09-01 15:30:19 | BMW | 11117 | 3000 | +------------+---------------------+---------------------+-----------+---------------+-------------+ ``` ### [](#distinct-combined-with-count-function)`DISTINCT` combined with `count` function The following example uses `DISTINCT` qualifier combined with `count()` function to calculate the number of unique car brands in rentals: ```sql SELECT COUNT (DISTINCT car) AS number_of_car_brands FROM rental; ``` This returns the following output: ```sql +----------------------+ | number_of_car_brands | +----------------------+ | 4 | +----------------------+ ``` This example uses the `DISTINCT` qualifier combined with `count()` function to calculate the number of rentals by each customer: ```sql SELECT c.cust_name AS customer_name, COUNT (DISTINCT r.rental_id) AS rental_count FROM rental r JOIN customer c ON r.customer_id = c.customer_id GROUP BY c.cust_name; ``` This calculates the `rental_count` by each `customer_name`: ```sql +----------------+--------------+ | customer_name | rental_count | +----------------+--------------+ | Nina | 2 | | Aaron | 1 | | Alice | 2 | | Martha | 1 | | Alex | 3 | | Rosy | 1 | +----------------+--------------+ ``` ### [](#distinct-combined-with-max-function)`DISTINCT` combined with `max()` function The following example uses `DISTINCT` qualifier combined with `max()` function to find maximum single spending per each customer, dropping any repeated transactions: ```sql SELECT c.cust_name AS customer_name, MAX (DISTINCT r.total_price) AS max_spending FROM rental r JOIN customer c ON r.customer_id = c.customer_id GROUP BY c.cust_name; ``` The query returns: ```sql +---------------+--------------+ | customer_name | max_spending | +---------------+--------------+ | Martha | 3000 | | Rosy | 1400 | | Alex | 1400 | | Alice | 2000 | | Nina | 2000 | | Aaron | 1500 | +---------------+--------------+ ``` ### [](#distinct-combined-with-sum-function)`DISTINCT` combined with `sum()` function The following example compares the sum of unique revenues versus the sum of all revenues in rental data: ```sql SELECT SUM (DISTINCT r.total_price) AS unique_revenue, SUM (r.total_price) AS total_revenue FROM rental r; ``` The query returns: ```sql +----------------+---------------+ | unique_revenue | total_revenue | +----------------+---------------+ | 11400 | 16300 | +----------------+---------------+ ``` The result may help to understand what is the impact of repeating transactions on total revenue. ## [](#limitations)Limitations There is one use case that is not currently supported: - Aggregation functions with `DISTINCT` keyword used as an argument of an expression, for example, SELECT 1 + COUNT(DISTINCT col) FROM table