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The purpose of query optimization, which is an automated process, is to find the way to process a given query in minimum time. The large possible variance in time justifies performing query optimization, though finding the exact optimal query plan, among all possibilities, is typically very complex, time-consuming by itself, may be too costly ...
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]
Some query tools can generate embedded hints in the query, for use by the optimizer. Some databases - like Oracle - provide a plan table for query tuning. This plan table will return the cost and time for executing a query. Oracle offers two optimization approaches: CBO or Cost Based Optimization; RBO or Rule Based Optimization
The main application of query containment is in query optimization: Deciding whether two queries are equivalent is possible by simply checking mutual containment. The query containment problem is undecidable for relational algebra and SQL but is decidable and NP-complete for conjunctive queries.
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.).
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.
The skyline operator is the subject of an optimization problem and computes the Pareto optimum on tuples with multiple dimensions.. This operator is an extension to SQL proposed by Börzsönyi et al. [1] to filter results from a database to keep only those objects that are not worse in multiple dimensions than any other.
Identifying whether a query is monotonic can be crucial for query optimization, especially in view maintenance and data stream management. Since the answer set for a monotonic query can only grow as more tuples are added to the database, query processing may be optimized by executing only the new portions of the database and adding the new ...