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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 .
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 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).
A query includes a list of columns to include in the final result, normally immediately following the SELECT keyword. An asterisk ("*") can be used to specify that the query should return all columns of all the queried tables. SELECT is the most complex statement in SQL, with optional keywords and clauses that include:
R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.
It supports complex analytics query operators, such as calculated columns, searching and filtering on rows, group by-aggregates and joins. [ 25 ] The engine service exposes a relational data model : At the top level ( cluster ) there is a collection of databases, each database contains a collection of tables and stored functions.
[4]: 114 A DataFrame is a 2-dimensional data structure of rows and columns, similar to a spreadsheet, and analogous to a Python dictionary mapping column names (keys) to Series (values), with each Series sharing an index. [4]: 115 DataFrames can be concatenated together or "merged" on columns or indices in a manner similar to joins in SQL.