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An inner join (or join) requires each row in the two joined tables to have matching column values, and is a commonly used join operation in applications but should not be assumed to be the best choice in all situations. Inner join creates a new result table by combining column values of two tables (A and B) based upon the join-predicate.
A right join is employed over the Target (the INTO table) and the Source (the USING table / view / sub-query)--where Target is the left table and Source is the right one. The four possible combinations yield these rules:
The derived table functionality allows the user to reference the subquery as a table. The derived table is sometimes referred to as an inline view or a subselect. In the following example, the SQL statement involves a join from the initial "Book" table to the derived table "sales".
In a SQL database query, a correlated subquery (also known as a synchronized subquery) is a subquery (a query nested inside another query) that uses values from the outer query. This can have major impact on performance because the correlated subquery might get recomputed every time for each row of the outer query is processed.
Derived table functionality allows the user to reference the subquery as a table. The derived table also is referred to as an inline view or a select in from list. In the following example, the SQL statement involves a join from the initial Books table to the derived table "Sales".
In section Inner join, the statement, "The following example is equivalent to the previous one, but this time using implicit join notation:" is false because the two example queries are not equivalent and do not produce the same result. In order to make the two queries equivalent, the second query should read:
The join operation defined for relational databases is often referred to as a natural join (⋈). In this type of join, two relations are connected by their common attributes. MySQL's approximation of a natural join is the Inner join operator. In SQL, an INNER JOIN prevents a cartesian product from occurring when there are two tables in a query.
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.