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Multi-query optimization for subgraph isomorphism search

Published: 01 November 2016 Publication History

Abstract

Existing work on subgraph isomorphism search mainly focuses on a-query-at-a-time approaches: optimizing and answering each query separately. When multiple queries arrive at the same time, sequential processing is not always the most efficient. In this paper, we study multi-query optimization for subgraph isomorphism search. We first propose a novel method for efficiently detecting useful common sub-graphs and a data structure to organize them. Then we propose a heuristic algorithm based on the data structure to compute a query execution order so that cached intermediate results can be effectively utilized. To balance memory usage and the time for cached results retrieval, we present a novel structure for caching the intermediate results. We provide strategies to revise existing single-query subgraph isomorphism algorithms to seamlessly utilize the cached results, which leads to significant performance improvement. Extensive experiments verified the effectiveness of our solution.

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  1. Multi-query optimization for subgraph isomorphism search

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    Published In

    cover image Proceedings of the VLDB Endowment
    Proceedings of the VLDB Endowment  Volume 10, Issue 3
    November 2016
    216 pages
    ISSN:2150-8097
    Issue’s Table of Contents

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    VLDB Endowment

    Publication History

    Published: 01 November 2016
    Published in PVLDB Volume 10, Issue 3

    Author Tags

    1. multi-query optimization
    2. subgraph isomorphism

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