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The joined table retains each row—even if no other matching row exists. Outer joins subdivide further into left outer joins, right outer joins, and full outer joins, depending on which table's rows are retained: left, right, or both (in this case left and right refer to the two sides of the JOIN keyword).
The outer join ( ) or full outer join in effect combines the results of the left and right outer joins. The full outer join is written as R S where R and S are relations. [f] The result of the full outer join is the set of all combinations of tuples in R and S that are equal on their common attribute names, in addition to tuples in S that have ...
The following example EXCEPT query returns all rows from the Orders table where Quantity is between 1 and 49, and those with a Quantity between 76 and 100. Worded another way; the query returns all rows where the Quantity is between 1 and 100, apart from rows where the quantity is between 50 and 75.
SQL outer joins, including left outer joins, right outer joins, and full outer joins, automatically produce Nulls as placeholders for missing values in related tables. For left outer joins, for instance, Nulls are produced in place of rows missing from the table appearing on the right-hand side of the LEFT OUTER JOIN operator. The following ...
The sort-merge join (also known as merge join) is a join algorithm and is used in the implementation of a relational database management system. The basic problem of a join algorithm is to find, for each distinct value of the join attribute, the set of tuples in each relation which display that value. The key idea of the sort-merge algorithm is ...
While joins and other table operations provide computationally superior (i.e. faster) alternatives in many cases (all depending on implementation), the use of subqueries introduces a hierarchy in execution that can be useful or necessary. In the following example, the aggregation function AVG receives as input the result of a subquery:
For example, one variant of the block nested loop join reads an entire page of tuples into memory and loads them into a hash table. It then scans S {\displaystyle S} , and probes the hash table to find S {\displaystyle S} tuples that match any of the tuples in the current page of R {\displaystyle R} .
Join and meet are dual to one another with respect to order inversion. A partially ordered set in which all pairs have a join is a join-semilattice. Dually, a partially ordered set in which all pairs have a meet is a meet-semilattice. A partially ordered set that is both a join-semilattice and a meet-semilattice is a lattice.