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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]
There is also an IGNORE clause for the INSERT statement, [7] which tells the server to ignore "duplicate key" errors and go on (existing rows will not be inserted or updated, but all new rows will be inserted). SQLite's INSERT OR REPLACE INTO works similarly. It also supports REPLACE INTO as an alias for compatibility with MySQL. [8]
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.
With the same table, the query SELECT C1 FROM T will result in the elements from the column C1 of all the rows of the table being shown. This is similar to a projection in relational algebra , except that in the general case, the result may contain duplicate rows.
The query retrieves all rows from the Book table in which the price column contains a value greater than 100.00. The result is sorted in ascending order by title. The asterisk (*) in the select list indicates that all columns of the Book table should be included in the result set.
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).
"Nuts, cheap, unrelenting, optimistic, sweet. She’s just crazy, Oh my God. But she writes great songs," the pop legend says about Warren in 'Diane Warren: Relentless'
A right outer join (or right join) closely resembles a left outer join, except with the treatment of the tables reversed. Every row from the "right" table (B) will appear in the joined table at least once. If no matching row from the "left" table (A) exists, NULL will appear in columns from A for those rows that have no match in B.