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A query optimizer will not always choose the most efficient query plan for a given query. In some databases the query plan can be reviewed, problems found, and then the query optimizer gives hints on how to improve it. In other databases, alternatives to express the same query (other queries that return the same results) can be tried. Some ...
The query optimizer attempts to determine the most efficient way to execute a given query by considering the possible query plans. [1] Generally, the query optimizer cannot be accessed directly by users: once queries are submitted to the database server, and parsed by the parser, they are then passed to the query optimizer where optimization ...
In various SQL implementations, a hint is an addition to the SQL standard that instructs the database engine on how to execute the query. For example, a hint may tell the engine to use or not to use an index (even if the query optimizer would decide otherwise).
Query optimization consists in determining from a query the most efficient manner (or manners) to execute it. Query optimization can be formalized as translating a relational calculus expression delivering an answer A into efficient relational algebraic expressions delivering the same answer A.
Query Optimization This paper is an introduction into the use of the relational algebra in optimizing queries, and includes numerous citations for more in-depth study. Relational Algebra System for Oracle and Microsoft SQL Server; Pireal – An experimental educational tool for working with Relational Algebra
If there are relational data streams and the logical query plan is based on relational operators from the Relational algebra, a query optimizer can use the algebraic equivalences to optimize the plan. These may be, for example, to push selection operators down to the sources, because they are not so computationally intensive like join operators.
This pre-established query command is kept in the data dictionary. Unlike ordinary base tables in a relational database , a view does not form part of the physical schema : as a result set, it is a virtual table [ 1 ] computed or collated dynamically from data in the database when access to that view is requested.
Query rewriting is a typically automatic transformation that takes a set of database tables, views, and/or queries, usually indices, often gathered data and query statistics, and other metadata, and yields a set of different queries, which produce the same results but execute with better performance (for example, faster, or with lower memory use). [1]