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Set operations in SQL is a type of operations which allow the results of multiple queries to be combined into a single result set. [ 1 ] Set operators in SQL include UNION , INTERSECT , and EXCEPT , which mathematically correspond to the concepts of union , intersection and set difference .
Database normalization is the process of structuring a relational database 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 .
The nested set model is a technique for representing nested set collections (also known as trees or hierarchies) in relational databases. It is based on Nested Intervals, that "are immune to hierarchy reorganization problem, and allow answering ancestor path hierarchical queries algorithmically — without accessing the stored hierarchy relation".
Slony-I is an asynchronous master-slave replication system for the PostgreSQL DBMS, providing support for cascading and failover. Asynchronous means that when a database transaction has been committed to the master server, it is not yet guaranteed to be available in slaves. Cascading means that replicas can be created (and updated) via other ...
Some database implementations adopted the term upsert (a portmanteau of update and insert) to a database statement, or combination of statements, that inserts a record to a table in a database if the record does not exist or, if the record already exists, updates the existing record. This synonym is used in PostgreSQL (v9.5+) [2] and SQLite (v3 ...
The ORDER BY clause identifies which columns to use to sort the resulting data, and in which direction to sort them (ascending or descending). Without an ORDER BY clause, the order of rows returned by an SQL query is undefined. The DISTINCT keyword [5] eliminates duplicate data. [6] The following example of a SELECT query returns a list of ...
Data cleansing may also involve harmonization (or normalization) of data, which is the process of bringing together data of "varying file formats, naming conventions, and columns", [2] and transforming it into one cohesive data set; a simple example is the expansion of abbreviations ("st, rd, etc." to "street, road, etcetera").
A data set representing a single item Column: Attribute or field: A labeled element of a tuple, e.g. "Address" or "Date of birth" Table: Relation or Base relvar: A set of tuples sharing the same attributes; a set of columns and rows View or result set: Derived relvar: Any set of tuples; a data report from the RDBMS in response to a query