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Join indices

In new application areas of relational database systems, such as artificial intelligence, the join operator is used more extensively than in conventional applications. In this paper, we propose a simple data structure, called a join index, for improving the performance of joins in the context of complex queries. For most of the joins, updates to join indices incur very little overhead. Some properties of a join index are (i) its efficient use of memory and adaptiveness to parallel execution, (ii) its compatibility with other operations (including select and union), (iii) its support for abstract data type join predicates, (iv) its support for multirelation clustering, and (v) its use in representing directed graphs and in evaluating recursive queries. Finally, the analysis of the join algorithm using join indices shows its excellent performance.

Association for Computing Machinery (ACM)

Patrick Valduriez

ACM Transactions on Database Systems

2002

Title: Join indices

Description:

In new application areas of relational database systems, such as artificial intelligence, the join operator is used more extensively than in conventional applications.

In this paper, we propose a simple data structure, called a join index, for improving the performance of joins in the context of complex queries.

For most of the joins, updates to join indices incur very little overhead.

Some properties of a join index are (i) its efficient use of memory and adaptiveness to parallel execution, (ii) its compatibility with other operations (including select and union), (iii) its support for abstract data type join predicates, (iv) its support for multirelation clustering, and (v) its use in representing directed graphs and in evaluating recursive queries.

Finally, the analysis of the join algorithm using join indices shows its excellent performance.

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