Optimisation Techniques for Flexible SPARQL Queries

التفاصيل البيبلوغرافية
العنوان: Optimisation Techniques for Flexible SPARQL Queries
المؤلفون: Riccardo Frosini, Alexandra Poulovassilis, Peter T. Wood, Andrea Calí
المصدر: ACM Transactions on the Web. 16:1-44
بيانات النشر: Association for Computing Machinery (ACM), 2022.
سنة النشر: 2022
مصطلحات موضوعية: csis, Computer Networks and Communications
الوصف: Resource Description Framework datasets can be queried using the SPARQL language but are often irregularly structured and incomplete, which may make precise query formulation hard for users. The SPARQLARlanguage extends SPARQL 1.1 with two operators—APPROX and RELAX—to allow flexible querying over property paths. These operators encapsulate different dimensions of query flexibility, namely, approximation and generalisation, and they allow users to query complex, heterogeneous knowledge graphs without needing to know precisely how the data is structured. Earlier work has described the syntax, semantics, and complexity of SPARQLAR, has demonstrated its practical feasibility, but has also highlighted the need for improving the speed of query evaluation. In the present article, we focus on the design of two optimisation techniques targeted at speeding up the execution of SPARQLARqueries and on their empirical evaluation on three knowledge graphs: LUBM, DBpedia, and YAGO. We show that applying these optimisations can result in substantial improvements in the execution times of longer-running queries (sometimes by one or more orders of magnitude) without incurring significant performance penalties for fast queries.
وصف الملف: application/pdf
تدمد: 1559-114X
1559-1131
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f1d5420dda5f0b7a376fc5f77d06fcad
https://doi.org/10.1145/3532855
حقوق: OPEN
رقم الأكسشن: edsair.doi.dedup.....f1d5420dda5f0b7a376fc5f77d06fcad
قاعدة البيانات: OpenAIRE