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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]
The FETCH FIRST clause specifies the number of rows to return. Some SQL databases instead have non-standard alternatives, e.g. LIMIT, TOP or ROWNUM. The clauses of a query have a particular order of execution, [5] which is denoted by the number on the right hand side. It is as follows:
The following is an Oracle syntax example of a row level trigger that is called AFTER an update FOR EACH ROW affected. This trigger is called on an update to a phone book database. When the trigger is called it adds an entry into a separate table named phone_book_audit.
The rows represent instances of that type of entity (such as "Lee" or "chair") and the columns represent values attributed to that instance (such as address or price). For example, each row of a class table corresponds to a class, and a class corresponds to multiple students, so the relationship between the class table and the student table is ...
Application- or user-specific database objects in relational databases are usually created with data definition language (DDL) commands, which in SQL for example can be CREATE, ALTER and DROP. [4] [5] Rows or tuples from the database can represent objects in the sense of object-oriented programming, but are not considered database objects. [6]
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.)
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Select only then {rows} rows with filter: First Page: select only the first {rows} rows, depending on the type of database; Next Page: select only the first {rows} rows, depending on the type of database, where the {unique_key} is greater than {last_val} (the value of the {unique_key} of the last row in the current page)