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The following example of a SELECT query returns a list of expensive books. The query retrieves all rows from the Book table in which the price column contains a value greater than 100.00. The result is sorted in ascending order by title. The asterisk (*) in the select list indicates that all columns of the Book table should be included in the ...
The following example of a SELECT query returns a list of expensive books. The query retrieves all rows from the Book table in which the price column contains a value greater than 100.00. The result is sorted in ascending order by title. The asterisk (*) in the select list indicates that all columns of the Book table should be included in the ...
Query by Example (QBE) is a database query language for relational databases. It was devised by Moshé M. Zloof at IBM Research during the mid-1970s, in parallel to the development of SQL . [ 1 ] It is the first graphical query language, using visual tables where the user would enter commands, example elements and conditions.
In a SQL database query, a correlated subquery (also known as a synchronized subquery) is a subquery (a query nested inside another query) that uses values from the outer query. This can have major impact on performance because the correlated subquery might get recomputed every time for each row of the outer query is processed.
An ORDER BY clause in SQL specifies that a SQL SELECT statement returns a result set with the rows being sorted by the values of one or more columns. The sort criteria does not have to be included in the result set (restrictions apply for SELECT DISTINCT, GROUP BY, UNION [DISTINCT], EXCEPT [DISTINCT] and INTERSECT [DISTINCT].)
Set operations in SQL is a type of operations which allow the results of multiple queries to be combined into a single result set. [1] Set operators in SQL include UNION, INTERSECT, and EXCEPT, which mathematically correspond to the concepts of union, intersection and set difference.
If a query contains GROUP BY, rows from the tables are grouped and aggregated. 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.
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