The New Relational Database Dictionary by C. J. Date
Author:C. J. Date
Language: eng
Format: mobi, epub
ISBN: 9781491951736
Publisher: O’Reilly Media, Inc.
Published: 2016-01-14T16:00:00+00:00
table 1. SQL analog of either a relation or a relvar, as the context demands. Here are some of the major differences between tables in SQL and their relational counterparts: (a) SQL tables can contain duplicate rows; (b) SQL tables can contain nulls; (c) SQL tables have a left to right ordering to their columns; (d) SQL tables can have two or more columns with the same name; (e) SQL tables can have what are, in effect, columns with no name at all; (f) SQL tables—even ones in the database—can contain pointers; (g) SQL tables have no types. 2. More generally, a picture of a relation (on paper, for example). See also cell; column; row. Note: A confusion between relations and such tabular pictures probably accounts for the popular misconception that relations are “flat” or two-dimensional (see flat relation). While it’s obviously true that those pictures are two-dimensional, relations in general aren’t; rather, a relation of degree n is n-dimensional (q.v.), in the sense that its tuples correspond to points in some n-dimensional space (one dimension for each attribute of the relation in question).
table alias See alias.
TABLE_DEE and TABLE_DUM Two relation constants, preferably built in. TABLE_DEE is the unique relation with no attributes and exactly one tuple (necessarily the empty tuple); TABLE_DUM is the unique relation with no attributes and no tuples at all. They can be interpreted as TRUE (or yes) and FALSE (or no), respectively. (More precisely, the relation predicate for TABLE_DEE is any 0-place predicate that evaluates to TRUE, and the relation predicate for TABLE_DUM is any 0-place predicate that evaluates to FALSE.) Note: The names are perhaps not very well chosen, since TABLE_DEE and TABLE_DUM are precisely the two relations for which the popular understanding of a relation as a table most obviously breaks down.
table subquery See subquery.
tables and views / tables or views Phrases frequently appearing in SQL contexts that strongly suggest that views are somehow different from tables. But the whole point about views is that, in SQL terms, they are tables—just as, in mathematics, the whole point about a set that’s (e.g.) the union or intersection of two sets is that it is itself a set. In other words, views are supposed to “look and feel” just like base tables to the user (The Principle of Interchangeability, q.v., translated into SQL terms).
target (Assignment) See assignment.
target key See foreign key.
target relvar 1. (IND) For the general meaning, see inclusion dependency. In the foreign key context in particular, the term is sometimes used as a synonym for referenced relvar, q.v. 2. (Assignment) The relvar being updated in a relational assignment operation.
target tuple Term sometimes used in the foreign key context as a synonym for referenced tuple, q.v.
target type (Without inheritance) 1. Let S be a selector for type T; then the target type for an invocation of S is T. 2. In the CAST invocation CAST_AS_T (...), the target type is T.
tautology A predicate whose every possible invocation is guaranteed to yield TRUE, regardless of what arguments are substituted for its parameters.
Download
The New Relational Database Dictionary by C. J. Date.epub
This site does not store any files on its server. We only index and link to content provided by other sites. Please contact the content providers to delete copyright contents if any and email us, we'll remove relevant links or contents immediately.
AI & Machine Learning | Bioinformatics |
Computer Simulation | Cybernetics |
Human-Computer Interaction | Information Theory |
Robotics | Systems Analysis & Design |
Algorithms of the Intelligent Web by Haralambos Marmanis;Dmitry Babenko(8293)
Test-Driven Development with Java by Alan Mellor(6666)
Data Augmentation with Python by Duc Haba(6570)
Principles of Data Fabric by Sonia Mezzetta(6330)
Learn Blender Simulations the Right Way by Stephen Pearson(6215)
Microservices with Spring Boot 3 and Spring Cloud by Magnus Larsson(6090)
Hadoop in Practice by Alex Holmes(5958)
Jquery UI in Action : Master the concepts Of Jquery UI: A Step By Step Approach by ANMOL GOYAL(5806)
RPA Solution Architect's Handbook by Sachin Sahgal(5483)
Big Data Analysis with Python by Ivan Marin(5331)
The Infinite Retina by Robert Scoble Irena Cronin(5183)
Life 3.0: Being Human in the Age of Artificial Intelligence by Tegmark Max(5140)
Pretrain Vision and Large Language Models in Python by Emily Webber(4294)
Infrastructure as Code for Beginners by Russ McKendrick(4053)
Functional Programming in JavaScript by Mantyla Dan(4037)
The Age of Surveillance Capitalism by Shoshana Zuboff(3943)
WordPress Plugin Development Cookbook by Yannick Lefebvre(3766)
Embracing Microservices Design by Ovais Mehboob Ahmed Khan Nabil Siddiqui and Timothy Oleson(3570)
Applied Machine Learning for Healthcare and Life Sciences Using AWS by Ujjwal Ratan(3543)
