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A hierarchical query is a type of SQL query that handles hierarchical model data. They are special cases of more general recursive fixpoint queries, which compute transitive closures . In standard SQL:1999 hierarchical queries are implemented by way of recursive common table expressions (CTEs).
DELETE requires a shared table lock; Triggers fire; DELETE can be used in the case of: database link; DELETE returns the number of records deleted; Transaction log - DELETE needs to read records, check constraints, update block, update indexes, and generate redo / undo. All of this takes time, hence it takes time much longer than with TRUNCATE
Data query language (DQL) is part of the base grouping of SQL sub-languages. These sub-languages are mainly categorized into four categories: a data query language (DQL), a data definition language (DDL), a data control language (DCL), and a data manipulation language (DML).
In computer programming, create, read, update, and delete (CRUD) are the four basic operations (actions) of persistent storage. [1] CRUD is also sometimes used to describe user interface conventions that facilitate viewing, searching, and changing information using computer-based forms and reports .
In SQL, the data manipulation language comprises the SQL-data change statements, [3] which modify stored data but not the schema or database objects. Manipulation of persistent database objects, e.g., tables or stored procedures, via the SQL schema statements, [3] rather than the data stored within them, is considered to be part of a separate data definition language (DDL).
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 ...
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".
Codd's steps for organizing database tables and their keys is called database normalization, which avoids certain hidden database design errors (delete anomalies or update anomalies). In real life the process of database normalization ends up breaking tables into a larger number of smaller tables.