Multi-query optimization for subgraph isomorphism search

Xuguang Ren, Junhu Wang
<span title="2016-11-01">2016</span> <i title="VLDB Endowment"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/p6rqwwpkkjbcldejepcehaalby" style="color: black;">Proceedings of the VLDB Endowment</a> </i> &nbsp;
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 subgraphs and a data structure to organize them. Then we propose a heuristic algorithm based on the
more &raquo; ... ta 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. Keywords Multi-query optimization, subgraph isomorphism
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14778/3021924.3021929">doi:10.14778/3021924.3021929</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bfdwuspxy5dfhajrgki5hzev3e">fatcat:bfdwuspxy5dfhajrgki5hzev3e</a> </span>
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