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Query optimization is a feature of many relational database management systems and other databases such as NoSQL and graph databases.The query optimizer attempts to determine the most efficient way to execute a given query by considering the possible query plans.
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]
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.
RBO is slowly being deprecated. For CBO to be used, all the tables referenced by the query must be analyzed. To analyze a table, a DBA can launch code from the DBMS_STATS package. Other tools for query optimization include: SQL Trace [1] Oracle Trace and TKPROF [2] Microsoft SMS (SQL) Execution Plan [3] Tableau Performance Recording (all DB) [4
Database tuning describes a group of activities used to optimize and homogenize the performance of a database. It usually overlaps with query tuning, but refers to design of the database files, selection of the database management system (DBMS) application, and configuration of the database's environment ( operating system , CPU , etc.).
Given two queries and and a database schema, the query containment problem is the problem of deciding whether for all possible database instances over the input database schema, () (). The main application of query containment is in query optimization: Deciding whether two queries are equivalent is possible by simply checking mutual containment.
She played a fundamental role in the development of System R, a pioneering relational database implementation, and wrote the canonical paper on relational query optimization. [2] She is a pioneer in relational database management and inventor of the technique of cost-based query optimization.
A query failing to be sargable is known as a non-sargable query and typically has a negative effect on query time, so one of the steps in query optimization is to convert them to be sargable. The effect is similar to searching for a specific term in a book that has no index, beginning at page one each time, instead of jumping to a list of ...