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Right and left outer joins are functionally equivalent. Neither provides any functionality that the other does not, so right and left outer joins may replace each other as long as the table order is switched. A Venn diagram representing the full join SQL statement between tables A and B.
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.
In this example, the three lines next to the song entity indicate that an artist can have many songs. The two vertical lines next to the artist entity indicate songs can only have one performer. In the real world, data modeling is critical because as the data grows voluminous, tables linked by keys must be used to speed up programmed retrieval ...
The right outer join ( ) behaves almost identically to the left outer join, but the roles of the tables are switched. The right outer join of relations R and S is written as R S . [ e ] The result of the right 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 ...
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 ...
The recursive join is an operation used in relational databases, also sometimes called a "fixed-point join". It is a compound operation that involves repeating the join operation, typically accumulating more records each time, until a repetition makes no change to the results (as compared to the results of the previous iteration).
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} .
However, in some database systems, it is allowed to use correlated subqueries while joining in the FROM clause, referencing the tables listed before the join using a specified keyword, producing a number of rows in the correlated subquery and joining it to the table on the left. For example, in PostgreSQL, adding the keyword LATERAL before the ...