Skip to main content
SpringerLink
Log in
SpringerLink
Log in

OntoDS: An Ontology-Aware Distributed Storage Scheme for RDF Graphs

  • Conference paper
  • First Online:
Web Information Systems Engineering – WISE 2019 (WISE 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11881))

Included in the following conference series:

Abstract

With the development of the Semantic Web, the amount of RDF data has been increasing rapidly. It is no longer feasible to store entire data sets on a single machine, and still be able to access the data at reasonable performance. Consequently, the requirement for clustered RDF database systems is becoming more and more important. At the same time, the native storage scheme of RDF data is less mature in many aspects compared with relational storage scheme. SQL-on-Hadoop is a distributed relational database engine for big data with many factors, which uses Hadoop to improve the fault tolerance of the system and is fully transactional. However, currently, there is no SQL-on-Hadoop relational database that realizes a subsystem for RDF data storage. In this paper, we propose an Ontology-aware Distributed Storege scheme for RDF, called OntoDS, which modifies the relational RDF data storage scheme DB2RDF to build a novel scheme for RDF data and optimizes the partitioning of RDF graphs by distributing RDF triples based on ontologies to meet the need for RDF graph data storage and query load. The experimental results on the benchmark datasets show that our distributed RDF storage scheme is about 1–1.5 times faster than the state-of-the-art native storage schemes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. W3C: RDF 1.1 concepts and abstract syntax (2014)

    Google Scholar 

  2. Lehmann, J., et al.: DBpedia-a large-scale, multilingual knowledge base extracted from Wikipedia. Semant. Web 6(2), 167–195 (2015)

    Article  Google Scholar 

  3. Wang, X., Zou, L., Wang, C., Peng, P., Feng, Z.: Research on knowledge graph data management: a survey. Ruan Jian Xue Bao/J. Softw. 30(7), 2139–2174 (2019). (in Chinese). http://www.jos.org.cn/1000-9825/5841.htm

    MATH  Google Scholar 

  4. Abadi, D.J., Marcus, A., Madden, S.R., Hollenbach, K.: SW-Store: a vertically partitioned DBMS for Semantic Web data management. VLDB J. 18(2), 385–406 (2009)

    Article  Google Scholar 

  5. Bornea, M.A., et al.: Building an efficient RDF store over a relational database. In: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data, pp. 121–132. ACM (2013)

    Google Scholar 

  6. Sun, W., Fokoue, A., Srinivas, K., Kementsietsidis, A., Hu, G., Xie, G.: SQLgraph: an efficient relational-based property graph store. In: Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, pp. 1887–1901. ACM (2015)

    Google Scholar 

  7. Floratou, A., Minhas, U.F., Özcan, F.: SQL-on-Hadoop: full circle back to shared-nothing database architectures. Proc. VLDB Endowment 7(12), 1295–1306 (2014)

    Article  Google Scholar 

  8. Krishnamoorthy, M.S.: A note on some simplified NP-complete graph problems. ACM Sigact News 9(3), 24–24 (1977)

    Article  MATH  Google Scholar 

  9. Welsh powell algorithm. https://iq.opengenus.org/welsh-powell-algorithm/

  10. Guo, Y., Pan, Z., Heflin, J.: LUBM: a benchmark for owl knowledge base systems. Web Semant. Sci. Serv. Agents World Wide Web 3(2–3), 158–182 (2005)

    Article  Google Scholar 

  11. Chang, L., et al.: HAWQ: a massively parallel processing SQL engine in hadoop. In: Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data, pp. 1223–1234. ACM (2014)

    Google Scholar 

  12. Peng, P., Zou, L., Chen, L., Zhao, D.: Adaptive distributed RDF graph fragmentation and allocation based on query workload. IEEE Trans. Knowl. Data Eng. 31(4), 670–685 (2018)

    Article  Google Scholar 

  13. Papailiou, N., Tsoumakos, D., Konstantinou, I., Karras, P., Koziris, N.: H 2 RDF+: an efficient data management system for big RDF graphs. In: Proceedings of the 2014 ACM SIGMOD International Conference on Management of data, pp. 909–912. ACM (2014)

    Google Scholar 

  14. Schätzle, A., Przyjaciel-Zablocki, M., Neu, A., Lausen, G.: Sempala: interactive SPARQL query processing on hadoop. In: Mika, P., et al. (eds.) ISWC 2014. LNCS, vol. 8796, pp. 164–179. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11964-9_11

    Chapter  Google Scholar 

  15. He, L., et al.: Stylus: a strongly-typed store for serving massive RDF data. Proc. VLDB Endowment 11(2), 203–216 (2017)

    Article  Google Scholar 

Download references

Acknowledgments

This work is supported by the National Natural Science Foundation of China (61572353, 61402323) and the Natural Science Foundation of Tianjin (17JCYBJC15400).

Author information

Authors and Affiliations

  1. College of Intelligence and Computing, Tianjin University, Tianjin, China

    Baozhu Liu, Xin Wang & Yajun Yang

  2. Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, China

    Xin Wang & Yajun Yang

  3. School of Information, Renmin University of China, Beijing, China

    Yunpeng Chai

Authors
  1. Baozhu Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yajun Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yunpeng Chai
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xin Wang .

Editor information

Editors and Affiliations

  1. University of Hong Kong, Hong Kong SAR, China

    Reynold Cheng

  2. University of Ioannina, Ioannina, Greece

    Nikos Mamoulis

  3. University of California, Los Angeles, CA, USA

    Yizhou Sun

  4. Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR, China

    Xin Huang

A Appendix

A Appendix

1.1 A.1 Queries for DB2RDF

figure e

1.2 A.2 Queries for OntoDS

figure f

1.3 A.3 Queries for gStoreD

figure g

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Liu, B., Wang, X., Yang, Y., Chai, Y. (2019). OntoDS: An Ontology-Aware Distributed Storage Scheme for RDF Graphs. In: Cheng, R., Mamoulis, N., Sun, Y., Huang, X. (eds) Web Information Systems Engineering – WISE 2019. WISE 2020. Lecture Notes in Computer Science(), vol 11881. Springer, Cham. https://doi.org/10.1007/978-3-030-34223-4_41

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-34223-4_41

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34222-7

  • Online ISBN: 978-3-030-34223-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation