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The SQL SELECT statement returns a result set of rows, from one or more tables. [1] [2] A SELECT statement retrieves zero or more rows from one or more database tables or database views. In most applications, SELECT is the most commonly used data manipulation language (DML) command.
The derived table is sometimes referred to as an inline view or a subselect. In the following example, the SQL statement involves a join from the initial "Book" table to the derived table "sales". This derived table captures associated book sales information using the ISBN to join to the "Book" table.
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].)
SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd [12] in the early 1970s. [13] This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San ...
Behind the scenes, it is this statement that is actually executed. A suitably comprehensive front-end can minimize the burden on the user to remember the finer details of SQL, and it is easier and more productive for end-users (and even programmers) to select tables and columns by selecting them rather than typing in their names.
A common table expression, or CTE, (in SQL) is a temporary named result set, derived from a simple query and defined within the execution scope of a SELECT, INSERT, UPDATE, or DELETE statement. CTEs can be thought of as alternatives to derived tables , views, and inline user-defined functions.
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.
The "implicit join notation" simply lists the tables for joining, in the FROM clause of the SELECT statement, using commas to separate them. Thus it specifies a cross join, and the WHERE clause may apply additional filter-predicates (which function comparably to the join-predicates in the explicit notation).