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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 ...
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.
Machine learning based query term weight and synonym analyzer for query expansion. LucQE - open-source, Java. Provides a framework along with several implementations that allow to perform query expansion with the use of Apache Lucene. Xapian is an open-source search library which includes support for query expansion; ReQue open-source, Python ...
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.
SQLAlchemy offers tools for database schema generation, querying, and object-relational mapping. Key features include: A comprehensive embedded domain-specific language for SQL in Python called "SQLAlchemy Core" that provides means to construct and execute SQL queries. A powerful ORM that allows the mapping of Python classes to database tables.
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.
Presto (including PrestoDB, and PrestoSQL which was re-branded to Trino) is a distributed query engine for big data using the SQL query language. Its architecture allows users to query data sources such as Hadoop, Cassandra, Kafka, AWS S3, Alluxio, MySQL, MongoDB and Teradata, [1] and allows use of multiple data sources within a query.
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.). Database ...