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The PARTITION BY clause groups rows into partitions, and the function is applied to each partition separately. If the PARTITION BY clause is omitted (such as with an empty OVER() clause), then the entire result set is treated as a single partition. [4] For this query, the average salary reported would be the average taken over all rows.
An example of a recursive query computing the factorial of numbers from 0 to 9 is the following: WITH recursive temp ( n , fact ) AS ( SELECT 0 , 1 -- Initial Subquery UNION ALL SELECT n + 1 , ( n + 1 ) * fact FROM temp WHERE n < 9 -- Recursive Subquery ) SELECT * FROM temp ;
Snowflake schema used by example query. The example schema shown to the right is a snowflaked version of the star schema example provided in the star schema article. The following example query is the snowflake schema equivalent of the star schema example code which returns the total number of television units sold by brand and by country for 1997.
SELECT * FROM (SELECT ROW_NUMBER OVER (ORDER BY sort_key ASC) AS row_number, columns FROM tablename) AS foo WHERE row_number <= 10 ROW_NUMBER can be non-deterministic : if sort_key is not unique, each time you run the query it is possible to get different row numbers assigned to any rows where sort_key is the same.
Correlated subqueries may appear elsewhere besides the WHERE clause; for example, this query uses a correlated subquery in the SELECT clause to print the entire list of employees alongside the average salary for each employee's department. Again, because the subquery is correlated with a column of the outer query, it must be re-executed for ...
Without an ORDER BY clause, the order of rows returned by an SQL query is undefined. The DISTINCT keyword [3] eliminates duplicate data. [4] The OFFSET clause specifies the number of rows to skip before starting to return data. The FETCH FIRST clause specifies the number of rows to return. Some SQL databases instead have non-standard ...
After the aggregating operation, HAVING is applied, filtering out the rows that don't match the specified conditions. Therefore, WHERE applies to data read from tables, and HAVING should only apply to aggregated data, which isn't known in the initial stage of a query. To view the present condition formed by the GROUP BY clause, the HAVING ...
In SQL the UNION clause combines the results of two SQL queries into a single table of all matching rows. The two queries must result in the same number of columns and compatible data types in order to unite. Any duplicate records are automatically removed unless UNION ALL is used.