Subgraph search over massive disk resident graphs

Authors:
Peng Peng;Lei Zou;Lei Chen;Xuemin Lin;Dongyan Zhao
Affiliations:
Peking University, China;Peking University, China;Hong Kong of Science and Technology, Hong Kong, China;University of New South Wales, Australia;Peking University, China and Key Laboratory of Computational Linguistics, Ministry of Education, China
Venue:
SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
Year:
2011

Citing 17
Cited 1

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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.