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The "implicit join notation" simply lists the tables for joining, in the FROM clause of the SELECT statement, using commas to separate them. Thus it specifies a cross join, and the WHERE clause may apply additional filter-predicates (which function comparably to the join-predicates in the explicit notation).
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. The FROM clause can include optional JOIN subclauses to specify the rules for joining tables. The WHERE clause includes a comparison predicate, which restricts the rows returned by ...
A WHERE clause in SQL specifies that a SQL Data Manipulation Language (DML) statement should only affect rows that meet specified criteria. The criteria are expressed in the form of predicates. WHERE clauses are not mandatory clauses of SQL DML statements, but can be used to limit the number of rows affected by a SQL DML statement or returned ...
SELECT is the most complex statement in SQL, with optional keywords and clauses that include: The FROM clause, which indicates the tables to retrieve data from. The FROM clause can include optional JOIN subclauses to specify the rules for joining tables. The WHERE clause includes a comparison predicate, which restricts the rows returned by the ...
A relational database management system uses SQL MERGE (also called upsert) statements to INSERT new records or UPDATE or DELETE existing records depending on whether condition matches. It was officially introduced in the SQL:2003 standard, and expanded [ citation needed ] in the SQL:2008 standard.
PL/SQL refers to a class as an "Abstract Data Type" (ADT) or "User Defined Type" (UDT), and defines it as an Oracle SQL data-type as opposed to a PL/SQL user-defined type, allowing its use in both the Oracle SQL Engine and the Oracle PL/SQL engine. The constructor and methods of an Abstract Data Type are written in PL/SQL.
In SQL the UNION clause combines the results of two SQL queries into a single table of all matching rows.The two queries must result in the same number of columns and compatible data types in order to unite.
The idea was that you could do a JOIN to the DUAL table and create two rows in the result for every one row in your table. Then, by using GROUP BY, the resulting join could be summarized to show the amount of storage for the DATA extent and for the INDEX extent(s). The name, DUAL, seemed apt for the process of creating a pair of rows from just one.