# OVER and WINDOW > 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: OVER and WINDOW 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-clauses/over-window page-component-name: cloud-data-platform page-version: master page-component-version: master page-component-title: Cloud page-relative-src-path: sql/sql-clauses/over-window.adoc page-edit-url: https://github.com/redpanda-data/cloud-docs/edit/main/modules/reference/pages/sql/sql-clauses/over-window.adoc description: Window functions use the OVER and WINDOW clauses to define the set of rows over which the function operates. page-topic-type: reference page-git-created-date: "2026-05-26" page-git-modified-date: "2026-05-26" --- Window functions use a set of clauses to define the rows they operate over. Some of these clauses are mandatory and others are optional. ## [](#over-clause)OVER clause The `OVER` clause defines a window, or user-specified set of rows, within a query result set. It is mandatory for window functions and differentiates them from other SQL functions. ### [](#syntax)Syntax ```sql OVER (PARTITION BY rows1 ORDER BY rows2) ``` The `PARTITION BY` clause is a list of expressions interpreted in much the same way as the elements of a `GROUP BY` clause, except that they are always simple expressions and never the name or number of an output column. These expressions can also contain aggregate function calls, which are not allowed in a regular `GROUP BY` clause (windowing occurs after grouping and aggregation). `[ PARTITION BY expression [, …​] ]` (optional window partition) The `ORDER BY` clause used in the `OVER` clause is a list of expressions interpreted in much the same way as the elements of a statement-level `ORDER BY` clause, except that the expressions are always taken as simple expressions and never the name or number of an output column. `[ ORDER BY expression [ ASC | DESC | USING operator ] [ NULLS { FIRST | LAST } ] [, …​] ]` (optional window ordering) ## [](#window-clause)WINDOW clause The optional `WINDOW` clause defines one or more named window specifications, as a `window_name` and `window_definition` pair. ### [](#syntax-2)Syntax ```sql WINDOW window_name AS (window_definition) [, ...] ``` `window_name` is a name that can be referenced from `OVER` clauses or subsequent window definitions. Note the following: - The `window_definition` may use an `existing_window_name` to refer to a previous `window_definition` in the `WINDOW` clause, but the previous `window_definition` must not specify a frame clause. - The `window_definition` copies the `PARTITION BY` and `ORDER BY` clauses from the previous `window_definition`, but it cannot specify its own `PARTITION BY` clause. It can specify an `ORDER BY` clause if the previous `window_definition` does not have one. `[ existing_window_name ] [ PARTITION BY clause ] [ ORDER BY clause ] [ frame clause ]` (all arguments are optional) > 📝 **NOTE** > > A `window_definition` without arguments defines a window with all rows, without partition or ordering. The frame clause defines the window frame for window functions that depend on the frame (not all do). The window frame is a set of related rows for each row of the query (called the current row). - `{ RANGE | ROWS | GROUPS } frame_start [ frame_exclusion ]` - `{ RANGE | ROWS | GROUPS } BETWEEN frame_start AND frame_end [ frame_exclusion ]` > 📝 **NOTE** > > Redpanda SQL supports `ROWS` and `RANGE` frame modes. The `GROUPS` frame mode and `frame_exclusion` are not supported. Note the following: - `frame_start` and `frame_end` can be one of: `UNBOUNDED PRECEDING`, `offset PRECEDING`, `CURRENT ROW`, `offset FOLLOWING`, `UNBOUNDED FOLLOWING`. - If `frame_end` is omitted, it defaults to `CURRENT ROW`. The following restrictions apply: - `frame_start` cannot be `UNBOUNDED FOLLOWING`. - `frame_end` cannot be `UNBOUNDED PRECEDING`. - `frame_end` cannot appear earlier in the list of `frame_start` and `frame_end` options than the `frame_start` choice does. In `ROWS` mode, `CURRENT ROW` means that the frame starts or ends with the current row. The offset is an integer indicating that the frame starts or ends that many rows before or after the current row. > 📝 **NOTE** > > The `ROWS` mode can produce unpredictable results if the `ORDER BY` ordering does not order the rows uniquely. ## [](#examples)Examples For the examples in this section, create the `winsales` table: ```sql CREATE TABLE winsales( salesid int, dateid date, sellerid int, buyerid text, qty int, qty_shipped int); INSERT INTO winsales VALUES (30001, '8/2/2003', 3, 'b', 10, 10), (10001, '12/24/2003', 1, 'c', 10, 10), (10005, '12/24/2003', 1, 'a', 30, null), (40001, '1/9/2004', 4, 'a', 40, null), (10006, '1/18/2004', 1, 'c', 10, null), (20001, '2/12/2004', 2, 'b', 20, 20), (40005, '2/12/2004', 4, 'a', 10, 10), (20002, '2/16/2004', 2, 'c', 20, 20), (30003, '4/18/2004', 3, 'b', 15, null), (30004, '4/18/2004', 3, 'b', 20, null), (30007, '9/7/2004', 3, 'c', 30, null); ``` ### [](#over-clause-with-partition-by-and-order-by)OVER clause with PARTITION BY and ORDER BY This example uses the `OVER` clause with `PARTITION BY` and `ORDER BY`: ```sql SELECT *, SUM(qty) OVER (PARTITION BY sellerid) AS seller_qty FROM winsales ORDER BY sellerid, salesid; ``` The query returns: ```sql salesid | dateid | sellerid | buyerid | qty | qty_shipped | seller_qty ---------+------------+----------+---------+-----+-------------+------------ 10001 | 2003-12-24 | 1 | c | 10 | 10 | 50 10005 | 2003-12-24 | 1 | a | 30 | | 50 10006 | 2004-01-18 | 1 | c | 10 | | 50 20001 | 2004-02-12 | 2 | b | 20 | 20 | 40 20002 | 2004-02-16 | 2 | c | 20 | 20 | 40 30001 | 2003-08-02 | 3 | b | 10 | 10 | 75 30003 | 2004-04-18 | 3 | b | 15 | | 75 30004 | 2004-04-18 | 3 | b | 20 | | 75 30007 | 2004-09-07 | 3 | c | 30 | | 75 40001 | 2004-01-09 | 4 | a | 40 | | 50 40005 | 2004-02-12 | 4 | a | 10 | 10 | 50 (11 rows) ``` ### [](#over-clause-with-named-window)OVER clause with named window This example uses the `OVER` clause with a named window defined in the `WINDOW` clause: ```sql SELECT *, SUM(qty) OVER seller AS seller_qty FROM winsales WINDOW seller AS (PARTITION BY sellerid) ORDER BY sellerid, salesid; ``` The query returns: ```sql salesid | dateid | sellerid | buyerid | qty | qty_shipped | seller_qty ---------+------------+----------+---------+-----+-------------+------------ 10001 | 2003-12-24 | 1 | c | 10 | 10 | 50 10005 | 2003-12-24 | 1 | a | 30 | | 50 10006 | 2004-01-18 | 1 | c | 10 | | 50 20001 | 2004-02-12 | 2 | b | 20 | 20 | 40 20002 | 2004-02-16 | 2 | c | 20 | 20 | 40 30001 | 2003-08-02 | 3 | b | 10 | 10 | 75 30003 | 2004-04-18 | 3 | b | 15 | | 75 30004 | 2004-04-18 | 3 | b | 20 | | 75 30007 | 2004-09-07 | 3 | c | 30 | | 75 40001 | 2004-01-09 | 4 | a | 40 | | 50 40005 | 2004-02-12 | 4 | a | 10 | 10 | 50 (11 rows) ```