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SQL - V4.3.1

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    OVER clause

    Last Updated:2026-04-15 08:25:15  Updated
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    Purpose

    You can use this clause to define a window.

    A window is also called a frame. OceanBase Database supports two types of frame semantics: ROWS and RANGE. The former is based on a physical row offset, and the latter is based on a logical value offset.

    Functions applied to the OVER clause are analytic functions, also known as window functions in some databases. For more information about analytic functions, see Analytic functions.

    Syntax

     [query_partition_clause] [ order_by_clause [win_window]]
    
    win_window:
        {ROWS | RANGE} BETWEEN win_bouding AND win_bouding
      | {ROWS | RANGE} win_bouding
    
    win_bouding:
        CURRENT ROW
      | win_interval {PRECEDING | FOLLOWING}
    
    win_internal:
       expr | INTERVAL expr date_unit
    
    date_unit:
        DAY
      | DAY_HOUR
      | DAY_MICROSECOND
      | DAY_MINUTE
      | DAY_SECOND
      | HOUR
      | HOUR_MICROSECOND
      | HOUR_MINUTE
      | HOUR_SECOND
      | MICROSECOND
      | MINUTE
      | MINUTE_MICROSECOND
      | MINUTE_SECOND
      | MONTH
      | QUARTER
      | SECOND
      | SECOND_MICROSECOND
      | WEEK
      | YEAR
      | YEAR_MONTH
    

    Parameters

    Parameter
    Description
    ROWS Sorts rows by using the ORDER BY clause in a physical window, and takes data of the first and last N rows for calculation.
    RANGE The range of values corresponding to the current row in a logical window.
    CURRENT ROW Uses the current row as the boundary of the window.
    win_interval PRECEDING | FOLLOWING The boundary of the window.
    • win_interval: the number of rows of the boundary.
    • PRECEDING: uses the first N rows.
    • FOLLOWING: uses the last N rows.
    INTERVAL expr date_unit The interval of the window.
    • expr: the number of rows of the interval.
    • date_unit: the unit of expr.

    Examples

    Create a table named employees and insert data into it.

    obclient> CREATE TABLE employees (manager_id INT, last_name VARCHAR(50), hiredate VARCHAR(50), salary INT);
    INSERT INTO employees VALUES(100, 'Raphaely', '2017-07-01', 1700);
    INSERT INTO employees VALUES(100, 'De Haan', '2018-05-01',11000);      
    INSERT INTO employees VALUES(100, 'Errazuriz', '2017-07-21', 1400);
    INSERT INTO employees VALUES(100, 'Hartstein', '2019-05-01',14000);     
    INSERT INTO employees VALUES(100, 'Raphaely', '2017-07-22', 1700);
    INSERT INTO employees VALUES(100, 'Weiss', '2019-07-11',13500);     
    INSERT INTO employees VALUES(100, 'Russell', '2019-10-05', 13000);
    INSERT INTO employees VALUES(100, 'Partners', '2018-12-01',14000);     
    INSERT INTO employees VALUES(200, 'Ross', '2019-06-11',13500);     
    INSERT INTO employees VALUES(200, 'Bell', '2019-05-25', 13000);
    INSERT INTO employees VALUES(200, 'Part', '2018-08-11',14000);  
    COMMIT;
    

    Calculate the number of rows with unique values in the salary column.

    obclient> SELECT last_name, salary, APPROX_COUNT_DISTINCT(salary) OVER (ORDER BY hiredate) "Variance"
    FROM employees WHERE manager_id = 100 ORDER BY last_name, salary, "Variance";
    +-----------+--------+----------+
    | last_name | salary | Variance |
    +-----------+--------+----------+
    | De Haan   |  11000 |        3 |
    | Errazuriz |   1400 |        2 |
    | Hartstein |  14000 |        4 |
    | Partners  |  14000 |        4 |
    | Raphaely  |   1700 |        1 |
    | Raphaely  |   1700 |        2 |
    | Russell   |  13000 |        6 |
    | Weiss     |  13500 |        5 |
    +-----------+--------+----------+
    

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