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A Distributed SPARQL Query Processing Scheme Considering Data Locality and Query Execution Path
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데이터 지역성 및 질의 수행 경로를 고려한 분산 SPARQL 질의 처리 기법

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Type
Academic journal
Author
Byounghoon Kim (충북대학교) Daeyun Kim (충북대학교) Geonsik Ko (충북대학교) Yeonwoo Noh (충북대학교) Jongtae Lim (충북대학교) kyoungsoo Bok (충북대학교) Byoungyup Lee (배재대학교) Jaesoo Yoo (충북대학교)
Journal
Korean Institute of Information Scientists and Engineers KIISE Transactions on Computing Practices Vol.23 No.5 KCI Accredited Journals
Published
2017.5
Pages
275 - 283 (9page)

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A Distributed SPARQL Query Processing Scheme Considering Data Locality and Query Execution Path
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Abstract· Keywords

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A large amount of RDF data has been generated along with the increase of semantic web services. Various distributed storage and query processing schemes have been studied to efficiently use the massive amounts of RDF data. In this paper, we propose a distributed SPARQL query processing scheme that considers the data locality and query execution path of large RDF data. The proposed scheme considers the data locality and query execution path in order to reduce join and communication costs. In a distributed environment, when processing a SPARQL query, it is divided into several sub-queries according to the conditions of the WHERE clause by considering the data locality. The proposed scheme reduces data communication costs by grouping and processing the sub-queries through the index based on associated nodes. In addition, in order to reduce unnecessary joins and latency when processing the query, it creates an efficient query execution path considering data parsing cost, the amount of each node"s data communication, and latency. It is shown through various performance evaluations that the proposed scheme outperforms the existing scheme.
#RDF #SPARQL #질의 처리 #조인 비용 #RDF #SPARQL #query processing #join cost

Contents

요약
Abstract
1. 서론
2. 관련 연구
3. 제안하는 질의 처리 기법
4. 성능평가
5. 결론
References

References (9)

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Ontology, [Online]. Available: https://www.w3.org/standards/semanticweb/ontology SPARQL, [Online]. Available: https://www.w3.org/TR/rdf-sparql-query/, 2008. B. Quilitz and U. Leser, Querying Distributed RDF Data Source with SPARQL, Proc. of European Semantic Web Conference, pp. 524-538, 2008. RDF, [Online]. Available: https://www.w3.org/TR/rdf11-new/, 2014. K. Zeng, J. Yang, H. Wang, B. Shao, and Z. Wang, A distributed graph engine for web scale RDF data, Proc. of the VLDB Endowment, Vol. 6, No. 4, pp. 265-276, 2013.

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