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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.
Views take very little space to store; the database contains only the definition of a view, not a copy of all the data that it presents. Views structure data in a way that classes of users find natural and intuitive. [2] Just as a function (in programming) can provide abstraction, so can a database view. In another parallel with functions ...
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 alternatives, e.g. LIMIT, TOP or ROWNUM. The clauses of a query have a particular order of execution, [5] which is denoted by the number on the right ...
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]
In SQL, a window function or analytic function [1] is a function which uses values from one or multiple rows to return a value for each row. (This contrasts with an aggregate function, which returns a single value for multiple rows.) Window functions have an OVER clause; any function without an OVER clause is not a window function, but rather ...
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 ...
The CASE expression, for example, enables SQL to perform conditional branching within queries, providing a mechanism to return different values based on evaluated conditions. This logic can be particularly useful for data transformation during retrieval, especially in SELECT statements.
In SQL procedures, a cursor makes it possible to define a result set (a set of data rows) and perform complex logic on a row by row basis. By using the same mechanics, a SQL procedure can also define a result set and return it directly to the caller of the SQL procedure or to a client application.