Optimizing join index based join processing: a graph partitioning approach

Sivakumar Ravada, Shashi Shekhar, Chang tien Lu, Sanjay Chawla

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

The cost of join computation, which uses a join-index in a sequential system with limited buffer space, depends primarily on the page access sequence used to fetch the pages of the base relations. In this paper, we introduce a graph-partitioning model that will minimize the length of the page access sequence thus minimizes the redundant I/O, given a fixed buffer. Experiments with Sequoia 2000 data sets show that, the graph-partitioning method outperforms the existing methods based on sorting and online clustering, particularly for a small number of buffers and high join selectivity.

Original languageEnglish
Title of host publicationProceedings of the IEEE Symposium on Reliable Distributed Systems
PublisherIEEE Comp Soc
Pages302-308
Number of pages7
Publication statusPublished - 1998
Externally publishedYes
EventProceedings of the 1998 IEEE 17th Symposium on Reliable Distributed Systems, SRDS - West Lafayette, IN, USA
Duration: 20 Oct 199823 Oct 1998

Other

OtherProceedings of the 1998 IEEE 17th Symposium on Reliable Distributed Systems, SRDS
CityWest Lafayette, IN, USA
Period20/10/9823/10/98

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ASJC Scopus subject areas

  • Hardware and Architecture

Cite this

Ravada, S., Shekhar, S., Lu, C. T., & Chawla, S. (1998). Optimizing join index based join processing: a graph partitioning approach. In Proceedings of the IEEE Symposium on Reliable Distributed Systems (pp. 302-308). IEEE Comp Soc.