Join processing in relational databases
Author(s) -
Priti Mishra,
Margaret H. Eich
Publication year - 1992
Publication title -
acm computing surveys
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.079
H-Index - 163
eISSN - 1557-7341
pISSN - 0360-0300
DOI - 10.1145/128762.128764
Subject(s) - tuple , computer science , joins , relational algebra , join (topology) , sort merge join , relational database , cartesian product , partition (number theory) , conjunctive query , relational database management system , database , relation (database) , theoretical computer science , relational model , query optimization , hash join , data mining , programming language , mathematics , discrete mathematics , combinatorics
The join operation is one of the fundamental relational database query operations. It facilitates the retrieval of information from two different relations based on a Cartesian product of the two relations. The join is one of the most diffidult operations to implement efficiently, as no predefined links between relations are required to exist (as they are with network and hierarchical systems). The join is the only relational algebra operation that allows the combining of related tuples from relations on different attribute schemes. Since it is executed frequently and is expensive, much research effort has been applied to the optimization of join processing. In this paper, the different kinds of joins and the various implementation techniques are surveyed. These different methods are classified based on how they partition tuples from different relations. Some require that all tuples from one be compared to all tuples from another; other algorithms only compare some tuples from each. In addition, some techniques perform an explicit partitioning, whereas others are implicit.
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