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Efficiently querying rdf data in triple stores

Authors:

Li Ma,

Yue PanAuthors Info & Claims

WWW '08: Proceedings of the 17th international conference on World Wide Web

Pages 1053 - 1054

https://doi.org/10.1145/1367497.1367652

Published: 21 April 2008 Publication History

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Abstract

Efficiently querying RDF data is being an important factor in applying Semantic Web technologies to real-world applications. In this context, many efforts have been made to store and query RDF data in relational database using particular schemas. In this paper, we propose a new scheme to store, index, and query RDF data in triple stores. Graph feature of RDF data is taken into considerations which might help reduce the join costs on the vertical database structure. We would partition RDF triples into overlapped groups, store them in a triple table with one more column of group identity, and build up a signature tree to index them. Based on this infrastructure, a complex RDF query is decomposed into multiple pieces of sub-queries which could be easily filtered into some RDF groups using signature tree index, and finally is evaluated with a composed and optimized SQL with specific constraints. We compare the performance of our method with prior art on typical queries over a large scaled LUBM and UOBM benchmark data (more than 10 million triples). For some extreme cases, they can promote 3 to 4 orders of magnitude.

References

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E. Prud'hommeaux and A. Seaborne. SPARQL query language for RDF. W3C candidate recommendation, April 2006.

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Y. Yan, C. Wang, A. Zhou, W. Qian, L. Ma, and Y. Pan. Efficiently querying rdf data in triple stores. Technique report, 2008.

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Bai LZhu L(2023)Pattern Match Query for Spatiotemporal RDF DataUncertain Spatiotemporal Data Management for the Semantic Web10.4018/978-1-6684-9108-9.ch003(63-71)Online publication date: 15-Dec-2023
https://doi.org/10.4018/978-1-6684-9108-9.ch003
Zhou Y(2022)Large-Scale Commodity Knowledge Organization and Intelligent Query OptimizationInternational Journal of Mobile Computing and Multimedia Communications10.4018/IJMCMC.29796513:1(1-25)Online publication date: 22-Apr-2022
https://dl.acm.org/doi/10.4018/IJMCMC.297965
Singh MNerurkar NPandat ABhise M(2022)Hot Data Identification for Dynamic Workload using Parallel setup2022 IEEE Region 10 Symposium (TENSYMP)10.1109/TENSYMP54529.2022.9864336(1-6)Online publication date: 1-Jul-2022
https://doi.org/10.1109/TENSYMP54529.2022.9864336
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Efficiently querying rdf data in triple stores

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Information & Contributors

Information

Published In

WWW '08: Proceedings of the 17th international conference on World Wide Web

April 2008

1326 pages

ISBN:9781605580852

DOI:10.1145/1367497

General Chairs:
Jinpeng Huai
Beihang University, China
,
Robin Chen
AT&T Labs, USA
,
Hsiao-Wuen Hon
Microsoft Research Asia, China
,
Yunhao Liu
HK University of Science and Technology, Hong Kong
,
Program Chairs:
Wei-Ying Ma
Microsoft Research Asia, China
,
Andrew Tomkins
Yahoo! Research, USA
,
Xiaodong Zhang
The Ohio State University, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 April 2008

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WWW '08: The 17th International World Wide Web Conference

April 21 - 25, 2008

Beijing, China

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

View all

Bai LZhu L(2023)Pattern Match Query for Spatiotemporal RDF DataUncertain Spatiotemporal Data Management for the Semantic Web10.4018/978-1-6684-9108-9.ch003(63-71)Online publication date: 15-Dec-2023
https://doi.org/10.4018/978-1-6684-9108-9.ch003
Zhou Y(2022)Large-Scale Commodity Knowledge Organization and Intelligent Query OptimizationInternational Journal of Mobile Computing and Multimedia Communications10.4018/IJMCMC.29796513:1(1-25)Online publication date: 22-Apr-2022
https://dl.acm.org/doi/10.4018/IJMCMC.297965
Singh MNerurkar NPandat ABhise M(2022)Hot Data Identification for Dynamic Workload using Parallel setup2022 IEEE Region 10 Symposium (TENSYMP)10.1109/TENSYMP54529.2022.9864336(1-6)Online publication date: 1-Jul-2022
https://doi.org/10.1109/TENSYMP54529.2022.9864336
Di XWang JCheng SBai L(2019)Pattern Match Query for Spatiotemporal RDF GraphAdvances in Natural Computation, Fuzzy Systems and Knowledge Discovery10.1007/978-3-030-32591-6_57(532-539)Online publication date: 7-Nov-2019
https://doi.org/10.1007/978-3-030-32591-6_57
Song SZhang XGuo B(2019)Large-Scale Semantic Data Management For Urban Computing ApplicationsGreen, Pervasive, and Cloud Computing10.1007/978-3-030-15093-8_8(107-123)Online publication date: 15-Mar-2019
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Zhang WSheng QTaylor KQin Y(2015)Identifying and Caching Hot Triples for Efficient RDF Query ProcessingDatabase Systems for Advanced Applications10.1007/978-3-319-18123-3_16(259-274)Online publication date: 9-Apr-2015
https://doi.org/10.1007/978-3-319-18123-3_16
Fonou-Dombeu JPhiri NHuisman M(2014)Persistent Storage and Query of E-government Ontologies in Relational DatabasesElectronic Government and the Information Systems Perspective10.1007/978-3-319-10178-1_10(118-132)Online publication date: 2014
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Álvarez JLabra JCalmeau RMarín ÁMarín J(2011)Query expansion methods and performance evaluation for reusing linking open data of the European public procurement noticesProceedings of the 14th international conference on Advances in artificial intelligence: spanish association for artificial intelligence10.5555/2075561.2075618(494-503)Online publication date: 7-Nov-2011
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Zhang XChen H(2010)Indexing Ontological Structure Based on Neighbor TreeProceedings of the 2010 International Conference on Technologies and Applications of Artificial Intelligence10.1109/TAAI.2010.51(263-269)Online publication date: 18-Nov-2010
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