Abstract
In this paper, we present an approach to enhancing the performance of the rule-based OWL reasoning on Spark based on a locally optimal executable strategy. Firstly, we divide all rules (27 in total) into four main classes, namely, SPO rules (5 rules), type rules (7 rules), sameAs rules (7 rules), and schema rules (8 rules) since, as we investigated, those triples corresponding to the first three classes of rules are overwhelming (e.g., over 99 % in the LUBM dataset) in our practical world. Secondly, based on the interdependence among those entailment rules in each class, we pick out an optimal rule executable order of each class and then combine them into a new rule execution order of all rules. Finally, we implement the new rule execution order on Spark in a prototype called RORS. The experimental results show that the running time of RORS is improved by about 30 % as compared to Kim & Park’s algorithm (2015) using the LUBM200 (27.6 million triples).
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References
Liu, C., Qi, G., Wang, H., Yu, Y.: Large scale fuzzy pD\(^\text{* }\) reasoning using mapreduce. In: Aroyo, L., Welty, C., Alani, H., Taylor, J., Bernstein, A., Kagal, L., Noy, N., Blomqvist, E. (eds.) ISWC 2011, Part I. LNCS, vol. 7031, pp. 405–420. Springer, Heidelberg (2011)
Gu, R., Wang, S., Wang, F., Yuan, C., Huang, Y.: Efficient large scale RDFS/OWL reasoning with Spark. In: Proceedings of IPDPS 2015, pp. 700–709. IEEE (2015)
Guo, Y., Pan, Z., Heflin, J.: LUBM: a benchmark for OWL knowledge base systems. J. Web Seman. 3(2–3), 158–182 (2005)
Kim, J., Park, Y.: Scalable OWL-horst ontology reasoning using Spark. In: Proceedings of BigComp 2015, pp. 79–86 (2015)
Urbani, J., Kotoulas, S., Maassen, J., Van Harmelen, F., Bal, H.: OWL reasoning with WebPIE: calculating the closure of 100 billion triples. In: Aroyo, L., Antoniou, G., Hyvönen, E., ten Teije, A., Stuckenschmidt, H., Cabral, L., Tudorache, T. (eds.) The Semantic Web: Research and Applications. LNCS, vol. 6088, pp. 213–227. Springer, Heidelberg (2010)
Acknowledgments
This work is supported by the program of the National Key Research and Development Program of China (2016YFB1000603) and the National Natural Science Foundation of China (NSFC) (61502336, 61373035, 61572353). Xiaowang Zhang is supported by Tianjin Thousand Young Talents Program.
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Liu, Z., Feng, Z., Zhang, X., Wang, X., Rao, G. (2016). RORS: Enhanced Rule-Based OWL Reasoning on Spark. In: Li, F., Shim, K., Zheng, K., Liu, G. (eds) Web Technologies and Applications. APWeb 2016. Lecture Notes in Computer Science(), vol 9932. Springer, Cham. https://doi.org/10.1007/978-3-319-45817-5_43
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DOI: https://doi.org/10.1007/978-3-319-45817-5_43
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