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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:
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:
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]
An SQL select statement and its result. In computing, a database is an organized collection of data or a type of data store based on the use of a database management system (DBMS), the software that interacts with end users, applications, and the database itself to capture and analyze the data.
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:
There is also an IGNORE clause for the INSERT statement, [7] which tells the server to ignore "duplicate key" errors and go on (existing rows will not be inserted or updated, but all new rows will be inserted). SQLite's INSERT OR REPLACE INTO works similarly. It also supports REPLACE INTO as an alias for compatibility with MySQL. [8]
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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.