Indexing Query Graphs to Speed Up Graph Query Processing

Wang, J., Ntarmos, N. and Triantafillou, P. (2016) Indexing Query Graphs to Speed Up Graph Query Processing. In: EDBT: 19th International Conference on Extending Database Technology, Bordeaux, France, 15-18 March 2016, ISBN 9783893180707 (doi: 10.5441/002/edbt.2016.07)

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Subgraph/supergraph queries although central to graph an- alytics, are costly as they entail the NP-Complete problem of subgraph isomorphism. We present a fresh solution, the novel principle of which is to acquire and utilize knowledge from the results of previously executed queries. Our ap- proach, iGQ, encompasses two component subindexes to identify if a new query is a subgraph/supergraph of pre- viously executed queries and stores related key informa- tion. iGQ comes with novel query processing and index space management algorithms, including graph replacement policies. The end result is a system that leads to signifi- cant reduction in the number of required subgraph isomor- phism tests and speedups in query processing time. iGQ can be incorporated into any sub/supergraph query processing method and help improve performance. In fact, it is the only contribution that can speedup significantly both subgraph and supergraph query processing. We establish the princi- ples of iGQ and formally prove its correctness. We have im- plemented iGQ and have incorporated it within three popu- lar recent state of the art index-based graph query process- ing solutions. We evaluated its performance using real-world and synthetic graph datasets with different characteristics, and a number of query workloads, showcasing its benefits.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Triantafillou, Professor Peter and Ntarmos, Dr Nikos and Wang, Jing
Authors: Wang, J., Ntarmos, N., and Triantafillou, P.
College/School:College of Science and Engineering > School of Computing Science
Copyright Holders:Copyright © 2016 The Authors
Publisher Policy:Reproduced under a Creative Commons License

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