• myGriffith
    • Staff portal
    • Contact Us⌄
      • Future student enquiries 1800 677 728
      • Current student enquiries 1800 154 055
      • International enquiries +61 7 3735 6425
      • General enquiries 07 3735 7111
      • Online enquiries
      • Staff phonebook
    View Item 
    •   Home
    • Griffith Research Online
    • Conference outputs
    • View Item
    • Home
    • Griffith Research Online
    • Conference outputs
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

  • All of Griffith Research Online
    • Communities & Collections
    • Authors
    • By Issue Date
    • Titles
  • This Collection
    • Authors
    • By Issue Date
    • Titles
  • Statistics

  • Most Popular Items
  • Statistics by Country
  • Most Popular Authors
  • Support

  • Contact us
  • FAQs
  • Admin login

  • Login
  • StarMR: An efficient star-decomposition based query processor for SPARQL basic graph patterns using MapReduce

    Author(s)
    Xu, Qiang
    Wang, Xin
    Li, Jianxin
    Gan, Ying
    Chai, Lele
    Wang, Junhu
    Griffith University Author(s)
    Wang, John
    Year published
    2018
    Metadata
    Show full item record
    Abstract
    With the proliferation of knowledge graphs, large amounts of RDF graphs have been released, which raises the need for addressing the challenge of distributed SPARQL queries. In this paper, we propose an efficient distributed method, called Open image in new window, to answer the SPARQL basic graph pattern (BGP) queries on big RDF graphs using MapReduce. In our method, query graphs are decomposed into a set of stars that utilize the semantic and structural information embedded RDF graphs as heuristics. Two optimization techniques are proposed to further improve the efficiency of our algorithms. One filters out invalid input ...
    View more >
    With the proliferation of knowledge graphs, large amounts of RDF graphs have been released, which raises the need for addressing the challenge of distributed SPARQL queries. In this paper, we propose an efficient distributed method, called Open image in new window, to answer the SPARQL basic graph pattern (BGP) queries on big RDF graphs using MapReduce. In our method, query graphs are decomposed into a set of stars that utilize the semantic and structural information embedded RDF graphs as heuristics. Two optimization techniques are proposed to further improve the efficiency of our algorithms. One filters out invalid input data, the other postpones the Cartesian product operations. The extensive experiments on both synthetic and real-world datasets show that our Open image in new window method outperforms the state-of-the-art method S2X by an order of magnitude.
    View less >
    Conference Title
    Lecture Notes in Computer Science
    Volume
    10987
    DOI
    https://doi.org/10.1007/978-3-319-96890-2_34
    Subject
    Information and computing sciences
    Publication URI
    http://hdl.handle.net/10072/383966
    Collection
    • Conference outputs

    Footer

    Disclaimer

    • Privacy policy
    • Copyright matters
    • CRICOS Provider - 00233E
    • TEQSA: PRV12076

    Tagline

    • Gold Coast
    • Logan
    • Brisbane - Queensland, Australia
    First Peoples of Australia
    • Aboriginal
    • Torres Strait Islander