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Evaluating Regular Path Queries on Compressed Adjacency Matrices

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String Processing and Information Retrieval (SPIRE 2023)

Abstract

Regular Path Queries (RPQs), which are essentially regular expressions to be matched against the labels of paths in labeled graphs, are at the core of graph database query languages like SPARQL. A way to solve RPQs is to translate them into a sequence of operations on the adjacency matrices of each label. We design and implement a Boolean algebra on sparse matrix representations and, as an application, use them to handle RPQs. Our baseline representation uses the same space as the previously most compact index for RPQs and excels in handling the hardest types of queries. Our more succinct structure, based on \(k^2\)-trees, is 4 times smaller and still solves complex RPQs in reasonable time.

Supported by ANID - Millennium Science Initiative Program – Code ICN17_002, and Fondecyt Grant 1-230755, Fondecyt Grant 1221926; CITIC is funded by Xunta de Galicia and CIGUS; GAIN/Xunta de Galicia Grant ED431C 2021/53 (GRC); Xunta de Galicia/FEDER-UE Grant IN852D 2021/3; MCIN/AEI and NextGenerationEU/PRTR Grants [PID2020-114635RB-I00, TED2021-129245B-C21].

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Notes

  1. 1.

    If v is not a power of 2 we round it up to the next power, leaving the extended cells empty. This imposes almost no extra overhead on the \(k^2\)-tree representation.

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Correspondence to Adrián Gómez-Brandón .

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Arroyuelo, D., Gómez-Brandón, A., Navarro, G. (2023). Evaluating Regular Path Queries on Compressed Adjacency Matrices. In: Nardini, F.M., Pisanti, N., Venturini, R. (eds) String Processing and Information Retrieval. SPIRE 2023. Lecture Notes in Computer Science, vol 14240. Springer, Cham. https://doi.org/10.1007/978-3-031-43980-3_4

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  • DOI: https://doi.org/10.1007/978-3-031-43980-3_4

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