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SELECT is the most common operation in SQL, called "the query". SELECT retrieves data from one or more tables, or expressions. Standard SELECT statements have no persistent effects on the database. Some non-standard implementations of SELECT can have persistent effects, such as the SELECT INTO syntax provided in some databases. [4]
A query includes a list of columns to include in the final result, normally immediately following the SELECT keyword. An asterisk ("*") can be used to specify that the query should return all columns of the queried tables. SELECT is the most complex statement in SQL, with optional keywords and clauses that include:
A hierarchical query is a type of SQL query that handles hierarchical model data. They are special cases of more general recursive fixpoint queries, which compute transitive closures. In standard SQL:1999 hierarchical queries are implemented by way of recursive common table expressions (CTEs).
The input and output domains may be the same, such as for SUM, or may be different, such as for COUNT. Aggregate functions occur commonly in numerous programming languages, in spreadsheets, and in relational algebra. The listagg function, as defined in the SQL:2016 standard [2] aggregates data from multiple rows into a single concatenated string.
SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd [12] in the early 1970s. [13] This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San ...
In a SQL database query, a correlated subquery (also known as a synchronized subquery) is a subquery (a query nested inside another query) that uses values from the outer query. This can have major impact on performance because the correlated subquery might get recomputed every time for each row of the outer query is processed.
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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]