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A database dump contains a record of the table structure and/or the data from a database and is usually in the form of a list of SQL statements ("SQL dump"). A database dump is most often used for backing up a database so that its contents can be restored in the event of data loss.
A derived table is the use of referencing an SQL subquery in a FROM clause. Essentially, the derived table is a subquery that can be selected from or joined to. The derived table functionality allows the user to reference the subquery as a table. The derived table is sometimes referred to as an inline view or a subselect.
MySQL (/ ˌ m aɪ ˌ ɛ s ˌ k juː ˈ ɛ l /) [5] is an open-source relational database management system (RDBMS). [5] [6] Its name is a combination of "My", the name of co-founder Michael Widenius's daughter My, [7] and "SQL", the acronym for Structured Query Language.
Wikipedia preprocessor (wikiprep.pl) is a Perl script that preprocesses raw XML dumps and builds link tables, category hierarchies, collects anchor text for each article etc. Wikipedia SQL dump parser is a .NET library to read MySQL dumps without the need to use MySQL database; WikiDumpParser – a .NET Core library to parse the database dumps.
DBEdit – a free front end for MySQL and other databases; HeidiSQL – a full featured free front end that runs on Windows, and can connect to local or remote MySQL servers to manage databases, tables, column structure, and individual data records. Also supports specialised GUI features for date/time fields and enumerated multiple-value fields [6]
The table below shows the output from a template call (we'll call the template {{Conditional tables/example 1}}) with different values for {{{variable_foo}}}: Template call Result
InnoDB is a storage engine for the database management system MySQL and MariaDB. [1] Since the release of MySQL 5.5.5 in 2010, it replaced MyISAM as MySQL's default table type. [2] [3] It provides the standard ACID-compliant transaction features, along with foreign key support (declarative referential integrity).
If a query contains GROUP BY, rows from the tables are grouped and aggregated. After the aggregating operation, HAVING is applied, filtering out the rows that don't match the specified conditions. Therefore, WHERE applies to data read from tables, and HAVING should only apply to aggregated data, which isn't known in the initial stage of a query.