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A SELECT statement retrieves zero or more rows from one or more database tables or database views. In most applications, SELECT is the most commonly used data manipulation language (DML) command. As SQL is a declarative programming language, SELECT queries specify a result set, but do not specify how to calculate it.
The SQL From clause is the source of a rowset to be operated upon in a Data Manipulation Language (DML) statement. From clauses are very common, and will provide the rowset to be exposed through a Select statement, the source of values in an Update statement, and the target rows to be deleted in a Delete statement.
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 FROM clause, which indicates the table(s) to retrieve data from.
SQL statements are used to perform tasks such as insert data to a database, delete or update data in a database, or retrieve data from a database. Though database systems use SQL, they also have their own additional proprietary extensions that are usually only used on their system.
DQL statements are used for performing queries on the data within schema objects. The purpose of DQL commands is to get the schema relation based on the query passed to it. Although often considered part of DML, the SQL SELECT statement is strictly speaking an example of DQL. When adding FROM or WHERE data manipulators to the SELECT statement ...
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).
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If a query contains GROUP BY, rows from the tables are grouped and aggregated. After the aggregating operation, HAVING is applied, filtering out the rows that don't match the specified conditions. Therefore, WHERE applies to data read from tables, and HAVING should only apply to aggregated data, which isn't known in the initial stage of a query.