Skip to main content
SpringerLink
Log in

Distributed Query Evaluation over Large RDF Graphs

  • Conference paper
  • First Online:
Web and Big Data (APWeb-WAIM 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11809))

  • 641 Accesses

Abstract

RDF is increasingly being used to encode data for the semantic web and data exchange. There have been a large number of studies that address RDF data management over different distributed platforms. In this paper we provide an overview of these studies. This paper divide the studies of existing distributed RDF systems into two categories: partitioning-based approaches and cloud-based approaches. We also introduce a partition-tolerant distributed RDF system, gStore\(^D\).

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Abdelaziz, I., Harbi, R., Khayyat, Z., Kalnis, P.: A survey and experimental comparison of distributed SPARQL engines for very large RDF data. PVLDB 10(13), 2049–2060 (2017)

    Google Scholar 

  2. Google: Freebase data dumps (2017)

    Google Scholar 

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

    Google Scholar 

  4. Huang, J., Abadi, D.J., Ren, K.: Scalable SPARQL querying of large RDF graphs. PVLDB 4(11), 1123–1134 (2011)

    Google Scholar 

  5. Kaoudi, Z., Manolescu, I.: RDF in the clouds: a survey. VLDB J. 24(1), 67–91 (2015)

    Article  Google Scholar 

  6. Karypis, G., Kumar, V.: Multilevel graph partitioning schemes. In: ICPP, pp. 113–122 (1995)

    Google Scholar 

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

    Google Scholar 

  8. Madkour, A., Aly, A.M., Aref, W.G.: WORQ: workload-driven RDF query processing. In: Vrandečić, D., et al. (eds.) ISWC 2018. LNCS, vol. 11136, pp. 583–599. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00671-6_34

    Chapter  Google Scholar 

  9. Mahdisoltani, F., Biega, J., Suchanek, F.M.: YAGO3: a knowledge base from multilingual Wikipedias (2015)

    Google Scholar 

  10. Peng, P., Zou, L., Chen, L., Zhao, D.: Query workload-based RDF graph fragmentation and allocation. In: EDBT, pp. 377–388 (2016)

    Google Scholar 

  11. 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 (2019)

    Article  Google Scholar 

  12. Peng, P., Zou, L., Guan, R.: Accelerating partial evaluation in distributed SPARQL query evaluation. In: ICDE, pp. 112–123 (2019)

    Google Scholar 

  13. Peng, P., Zou, L., Özsu, M.T., Chen, L., Zhao, D.: Processing SPARQL queries over distributed RDF graphs. VLDB J. 25(2), 243–268 (2016)

    Article  Google Scholar 

  14. Schätzle, A., Przyjaciel-Zablocki, M., Skilevic, S., Lausen, G.: S2RDF: RDF querying with SPARQL on spark. PVLDB 9(10), 804–815 (2016)

    Google Scholar 

  15. Shao, B., Wang, H., Li, Y.: Trinity: a distributed graph engine on a memory cloud. In: SIGMOD, pp. 505–516 (2013)

    Google Scholar 

  16. Wu, B., Zhou, Y., Yuan, P., Liu, L., Jin, H.: Scalable SPARQL querying using path partitioning. In: ICDE, pp. 795–806 (2015)

    Google Scholar 

  17. Wylot, M., Mauroux, P.: DiploCloud: efficient and scalable management of RDF data in the cloud. TKDE, PP(99) (2015)

    Google Scholar 

Download references

Acknowledgment

This work was supported by NSFC under grant 61702171, Hunan Provincial Natural Science Foundation of China under grant 2018JJ3065, and the Fundamental Research Funds for the Central Universities.

Author information

Authors and Affiliations

  1. Hunan University, Changsha, China

    Peng Peng

Authors
  1. Peng Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Peng Peng .

Editor information

Editors and Affiliations

  1. University of Electronic Science and Technology of China, Chengdu, China

    Jingkuan Song

  2. Massey University, Auckland, New Zealand

    Xiaofeng Zhu

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

Peng, P. (2019). Distributed Query Evaluation over Large RDF Graphs. In: Song, J., Zhu, X. (eds) Web and Big Data. APWeb-WAIM 2019. Lecture Notes in Computer Science(), vol 11809. Springer, Cham. https://doi.org/10.1007/978-3-030-33982-1_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-33982-1_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33981-4

  • Online ISBN: 978-3-030-33982-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation