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Application- or user-specific database objects in relational databases are usually created with data definition language (DDL) commands, which in SQL for example can be CREATE, ALTER and DROP. [4] [5] Rows or tuples from the database can represent objects in the sense of object-oriented programming, but are not considered database objects. [6]
Had the engine loaded the rows using a table scan, it would then have to perform the additional work of sorting the returned rows. In some extreme cases - e.g. the statistics maintained by the database engine indicate that the table contains a very small number of rows - the optimizer may still decide to use a table scan for this type of query:
In computing, a materialized view is a database object that contains the results of a query.For example, it may be a local copy of data located remotely, or may be a subset of the rows and/or columns of a table or join result, or may be a summary using an aggregate function.
Title Authors ----- ----- SQL Examples and Guide 4 The Joy of SQL 1 An Introduction to SQL 2 Pitfalls of SQL 1 Under the precondition that isbn is the only common column name of the two tables and that a column named title only exists in the Book table, one could re-write the query above in the following form:
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.
Title Authors ----- ----- SQL Examples and Guide 4 The Joy of SQL 1 An Introduction to SQL 2 Pitfalls of SQL 1 Under the precondition that isbn is the only common column name of the two tables and that a column named title only exists in the Book table, one could re-write the query above in the following form:
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.
A database table can be thought of as consisting of rows and columns. [1] Each row in a table represents a set of related data, and every row in the table has the same structure. For example, in a table that represents companies, each row might represent a single company. Columns might represent things like company name, address, etc.