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In relational algebra, a rename is a unary operation written as / where: . R is a relation; a and b are attribute names; b is an attribute of R; The result is identical to R except that the b attribute in all tuples is renamed to a. [1]
In database theory, relational algebra is a theory that uses algebraic structures for modeling ... A rename ρ) is a unary ... Consider tables Car and Boat which list ...
In SQL, you can alias tables and columns. A table alias is called a correlation name, according to the SQL standard. [1] A programmer can use an alias to temporarily assign another name to a table or column for the duration of the current SELECT query. Assigning an alias does not actually rename the column or table.
Queries made against the relational database, and the derived relvars in the database are expressed in a relational calculus or a relational algebra. In his original relational algebra, Codd introduced eight relational operators in two groups of four operators each. The first four operators were based on the traditional mathematical set operations:
[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 selected columns from both tables before reducing the number of rows using the filter that depends on a calculated value, resulting in a relatively enormous amount of inefficient processing.
Database normalization is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model .
A view can be defined by an expression using the operators of the relational algebra or the relational calculus. Such an expression operates on one or more relations and when evaluated yields another relation. The result is sometimes referred to as a "derived" relation when the operands are relations assigned to database variables.
Query rewriting is a typically automatic transformation that takes a set of database tables, views, and/or queries, usually indices, often gathered data and query statistics, and other metadata, and yields a set of different queries, which produce the same results but execute with better performance (for example, faster, or with lower memory use). [1]