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An SQL UPDATE statement changes the data of one or more records in a table. Either all the rows can be updated, or a subset may be chosen using a condition. The UPDATE statement has the following form: [1] UPDATE table_name SET column_name = value [, column_name = value ...] [WHERE condition]
A simple example would be a database having tables sales2005 and sales2006 that have identical structures but are separated because of performance considerations. A UNION query could combine results from both tables. Note that UNION ALL does not guarantee the order of rows. Rows from the second operand may appear before, after, or mixed with ...
In a relational database, a candidate key uniquely identifies each row of data values in a database table. A candidate key comprises a single column or a set of columns in a single database table. No two distinct rows or data records in a database table can have the same data value (or combination of data values) in those candidate key columns ...
The WHERE clause eliminates all rows from the result set where the comparison predicate does not evaluate to True. The GROUP BY clause projects rows having common values into a smaller set of rows. [clarification needed] GROUP BY is often used in conjunction with SQL aggregation functions or to eliminate duplicate rows from a result set.
In SQL, a window function or analytic function [1] is a function which uses values from one or multiple rows to return a value for each row. (This contrasts with an aggregate function, which returns a single value for multiple rows.) Window functions have an OVER clause; any function without an OVER clause is not a window function, but rather ...
In SQL procedures, a cursor makes it possible to define a result set (a set of data rows) and perform complex logic on a row by row basis. By using the same mechanics, a SQL procedure can also define a result set and return it directly to the caller of the SQL procedure or to a client application.
In situations where the number of unique values of a column is far less than the number of rows in the table, column-oriented storage allow significant savings in space through data compression. Columnar storage also allows fast execution of range queries (e.g., show all records where a particular column is between X and Y, or less than X.)
For optimistic locking each row has an independent version number, typically a sequential counter. This allows a process to atomically update a row and increment its counter only if another process has not incremented the counter. But CDC cannot use row-level versions to find all changes unless it knows the original "starting" version of every row.