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2018 | OriginalPaper | Chapter

An Empirical Evaluation of RDF Graph Partitioning Techniques

Authors : Adnan Akhter, Axel-Cyrille Ngomo Ngonga, Muhammad Saleem

Published in: Knowledge Engineering and Knowledge Management

Publisher: Springer International Publishing

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Abstract

With the significant growth of RDF data sources in both numbers and volume comes the need to improve the scalability of RDF storage and querying solutions. Current implementations employ various RDF graph partitioning techniques. However, choosing the most suitable partitioning for a given RDF graph and application is not a trivial task. To the best of our knowledge, no detailed empirical evaluation exists to evaluate the performance of these techniques. In this work, we present an empirical evaluation of RDF graph partitioning techniques applied to real-world RDF data sets and benchmark queries. We evaluate the selected RDF graph partitioning techniques in terms of their partitioning time, partitioning imbalance (in sizes), and query run time performances achieved, based on real-world data sets and queries selected using the FEASIBLE benchmark generation framework.

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next chapter Fuzzy Semantic Labeling of Semi-structured Numerical Datasets

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UniProt: http://www.uniprot.org/statistics/.

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Please see T-Test tab of the excel sheet goo.gl/fxa4cJ.

Acosta, M., Vidal, M.-E., Lampo, T., Castillo, J., Ruckhaus, E.: ANAPSID: an adaptive query processing engine for SPARQL endpoints. In: Aroyo, L., et al. (eds.) ISWC 2011. LNCS, vol. 7031, pp. 18–34. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-25073-6_2CrossRef

Buluç, A., Meyerhenke, H., Safro, I., Sanders, P., Schulz, C.: Recent advances in graph partitioning. In: Kliemann, L., Sanders, P. (eds.) Algorithm Engineering. LNCS, vol. 9220, pp. 117–158. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-49487-6_4CrossRef

Charalambidis, A., et al.: SemaGrow: optimizing federated SPARQL queries. In: SEMANTICS (2015)

Erling, O., Mikhailov, I.: Towards web scale RDF. In: Proceedings of SSWS (2008)

Janke, D., et al.: Impact analysis of data placement strategies on query efforts in distributed RDF stores. JWS (2018)

Galárraga, L., et al.: Partout: a distributed engine for efficient RDF processing. In: WWW (2014)

Görlitz, O., Staab, S.: SPLENDID: SPARQL endpoint federation exploiting void descriptions. In: COLD (2011)

Gurajada, S., et al.: Triad: a distributed shared-nothing RDF engine based on asynchronous message passing. In: SIGMOD (2014)

Hammoud, M., et al.: DREAM: distributed RDF engine with adaptive query planner and minimal communication. In: VLDB (2015)

10.

Harris, S., et al.: 4store: the design and implementation of a clustered RDF store. In: SSWS (2009)

11.

Harth, A., Umbrich, J., Hogan, A., Decker, S.: YARS2: a federated repository for querying graph structured data from the web. In: Aberer, K., et al. (eds.) The Semantic Web. ISWC 2007, ASWC 2007. Lecture Notes in Computer Science, vol. 4825, pp. 211–224. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-76298-0_16CrossRef

12.

Herodotou, H., et al.: Query optimization techniques for partitioned tables. In: SIGMOD (2011)

13.

Huang, J., et al.: Scalable SPARQL querying of large RDF graphs. In: VLDB (2011)

14.

Janke, D., et al.: Koral: a glass box profiling system for individual components of distributed RDF stores. In: BLINK-ISWC (2017)

15.

Karypis, G., et al.: A fast and high quality multilevel scheme for partitioning irregular graphs. SIAM JSC 20, 359–392 (1998)MathSciNetMATH

16.

Khandelwal, A., et al.: ZipG: a memory-efficient graph store for interactive queries. In: ACM ICMD (2017)

17.

Neumann, T., et al.: The RDF-3X engine for scalable management of RDF data. In: VLDB (2010)

18.

Owens, A., et al.: Clustered TDB: a clustered triple store for Jena (2008)

19.

Saleem, M., Mehmood, Q., Ngonga Ngomo, A.C.: FEASIBLE: a feature-based SPARQL benchmark generation framework. In: Arenas, M., et al. (eds.) The Semantic Web - ISWC 2015. ISWC 2015. Lecture Notes in Computer Science, vol. 9366, pp. 52–69. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-25007-6_4CrossRef

20.

Saleem, M., et al.: A fine-grained evaluation of SPARQL endpoint federation systems. SWJ (2016)

21.

Schätzle, A., Przyjaciel-Zablocki, M., Neu, A., Lausen, G.: Sempala: interactive SPARQL query processing on Hadoop. In: Mika, P., et al. (eds.) The Semantic Web - ISWC 2014. ISWC 2014. Lecture Notes in Computer Science, vol. 8796, pp. 164–179. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11964-9_11

22.

Schätzle, A., et al.: S2RDF: RDF querying with SPARQL on spark. In: VLDB (2016)

23.

Schwarte, A., Haase, P., Hose, K., Schenkel, R., Schmidt, M.: FedX: optimization techniques for federated query processing on linked data. In: Aroyo, L., et al. (eds.) The Semantic Web - ISWC 2011. ISWC 2011. Lecture Notes in Computer Science, vol. 7031, pp. 601–616. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-25073-6_38CrossRef

24.

Tomaszuk, D., Skonieczny, Ł., Wood, D.: RDF graph partitions: a brief survey. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds.) BDAS 2015. CCIS, vol. 521, pp. 256–264. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-18422-7_23CrossRef

25.

Wang, X., et al.: LHD: optimising linked data query processing using parallelisation. In: LDOW (2013)

26.

Yan, Y., et al.: Efficient indices using graph partitioning in RDF triple stores. In: ICDE (2009)

27.

Zeng, K., et al.: A distributed graph engine for web scale RDF data. In: Proceedings of the VLDB Endowment (2013)CrossRef

Title: An Empirical Evaluation of RDF Graph Partitioning Techniques
Authors: Adnan Akhter
Axel-Cyrille Ngomo Ngonga
Muhammad Saleem
Publisher: Springer International Publishing
Book: Knowledge Engineering and Knowledge Management
Print ISBN: 978-3-030-03666-9

Electronic ISBN: 978-3-030-03667-6

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-030-03667-6_1

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