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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]
UPDATE table_name SET column_name = value [, column_name = value ... ] [ WHERE condition ] For the UPDATE to be successful, the user must have data manipulation privileges ( UPDATE privilege) on the table or column and the updated value must not conflict with all the applicable constraints (such as primary keys , unique indexes, CHECK ...
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:
The query evaluation, and thus query containment, is LOGCFL-complete and thus in polynomial time. [9] Acyclicity of conjunctive queries is a structural property of queries that is defined with respect to the query's hypergraph : [ 6 ] a conjunctive query is acyclic if and only if it has hypertree-width 1.
Additionally there is a single-row version, UPDATE OR INSERT INTO tablename (columns) VALUES (values) [MATCHING (columns)], but the latter does not give you the option to take different actions on insert versus update (e.g. setting a new sequence value only for new rows, not for existing ones.)
The consequence of this is that a different query plan is compiled and stored for each different length. In general, the maximum number of "duplicate" plans is the product of the lengths of the variable length columns as specified in the database. For this reason, it is important to use the standard Add method for variable length columns: command.
In SQL, the data manipulation language comprises the SQL-data change statements, [3] which modify stored data but not the schema or database objects. Manipulation of persistent database objects, e.g., tables or stored procedures, via the SQL schema statements, [3] rather than the data stored within them, is considered to be part of a separate data definition language (DDL).
The MultiDimensional eXpressions (MDX) language provides a specialized syntax for querying and manipulating the multidimensional data stored in OLAP cubes. [1] While it is possible to translate some of these into traditional SQL, it would frequently require the synthesis of clumsy SQL expressions even for very simple MDX expressions.