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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.
A subquery can use values from the outer query, in which case it is known as a correlated subquery. Since 1999 the SQL standard allows WITH clauses, i.e. named subqueries often called common table expressions (named and designed after the IBM DB2 version 2 implementation; Oracle calls these subquery factoring).
A derived table is the use of referencing an SQL subquery in a FROM clause. Essentially, the derived table is a subquery that can be selected from or joined to. The derived table functionality allows the user to reference the subquery as a table. The derived table is sometimes referred to as an inline view or a subselect.
Unlike Oracle's earlier connect-by clause, recursive CTEs were designed with fixpoint semantics from the beginning. [1] Recursive CTEs from the standard were relatively close to the existing implementation in IBM DB2 version 2. [1]
A right join is employed over the Target (the INTO table) and the Source (the USING table / view / sub-query)--where Target is the left table and Source is the right one. The four possible combinations yield these rules:
Set operations in SQL is a type of operations which allow the results of multiple queries to be combined into a single result set. [ 1 ] Set operators in SQL include UNION , INTERSECT , and EXCEPT , which mathematically correspond to the concepts of union , intersection and set difference .
Read-only views do not support such operations because the DBMS cannot map the changes to the underlying base tables. A view update is done by key preservation. Some systems support the definition of INSTEAD OF triggers on views. This technique allows the definition of other logic for execution in place of an insert, update, or delete operation ...
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]