Abstract

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.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.