Subgraph search over massive disk resident graphs

Peng Peng, Lei Zou*, Lei Chen, Xuemin Lin, Dongyan Zhao

*Corresponding author for this work

Research output: Chapter in Book/Conference Proceeding/ReportConference Paper published in a bookpeer-review

Abstract

Due to the wide applications, subgraph queries have attracted lots of attentions in database community. In this paper, we focus on subgraph queries over a large graph G. Different from existing feature-based approaches, we propose a bitmap structure based on edges to index the graph. At run time, we decompose Q into a set of adjacent edge pairs (AEP). We develop edge join (EJ) algorithms to address AEP subqueries. The bitmap index can reduce both I/O and CPU cost. More importantly, the bitmap index has the linear space complexity instead of the exponential complexity in feature-based approaches, which confirms its good scalability. Extensive experiments show that our method outperforms existing ones in both online and offline performances significantly.

Original languageEnglish
Title of host publicationScientific and Statistical Database Management - 23rd International Conference, SSDBM 2011, Proceedings
Pages312-321
Number of pages10
DOIs
Publication statusPublished - 2011
Event23rd International Conference on Scientific and Statistical Database Management, SSDBM 2011 - Portland, OR, United States
Duration: 20 Jul 201122 Jul 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6809 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on Scientific and Statistical Database Management, SSDBM 2011
Country/TerritoryUnited States
CityPortland, OR
Period20/07/1122/07/11

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