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SQL includes operators and functions for calculating values on stored values. SQL allows the use of expressions in the select list to project data, as in the following example, which returns a list of books that cost more than 100.00 with an additional sales_tax column containing a sales tax figure calculated at 6% of the price.
by adding a SQL window function to the SELECT-statement; ISO SQL:2008 introduced the FETCH FIRST clause. According to PostgreSQL v.9 documentation, an SQL window function "performs a calculation across a set of table rows that are somehow related to the current row", in a way similar to aggregate functions. [7]
A WHERE clause in SQL specifies that a SQL Data Manipulation Language (DML) statement should only affect rows that meet specified criteria. The criteria are expressed in the form of predicates. WHERE clauses are not mandatory clauses of SQL DML statements, but can be used to limit the number of rows affected by a SQL DML statement or returned ...
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 ...
The SQL equivalent of selection is the SELECT query statement with a WHERE clause. The projection operation (π) extracts only the specified attributes from a tuple or set of tuples. The join operation defined for relational databases is often referred to as a natural join (⋈).
Conversely, an inner join can result in disastrously slow performance or even a server crash when used in a large volume query in combination with database functions in an SQL Where clause. [2] [3] [4] A function in an SQL Where clause can result in the database ignoring relatively compact table indexes. The database may read and inner join the ...
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The attributes preceding the g are grouping attributes, which function like a "group by" clause in SQL. Then there are an arbitrary number of aggregation functions applied to individual attributes. The operation is applied to an arbitrary relation r. The grouping attributes are optional, and if they are not supplied, the aggregation functions ...