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Enabling Fine-Grained HTTP Caching of SPARQL Query Results

  • Gregory Todd Williams
  • Jesse Weaver
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7031)

Abstract

As SPARQL endpoints are increasingly used to serve linked data, their ability to scale becomes crucial. Although much work has been done to improve query evaluation, little has been done to take advantage of caching. Effective solutions for caching query results can improve scalability by reducing latency, network IO, and CPU overhead. We show that simple augmentation of the database indexes found in common SPARQL implementations can directly lead to effective caching at the HTTP protocol level. Using tests from the Berlin SPARQL benchmark, we evaluate the potential of such caching to improve overall efficiency of SPARQL query evaluation.

Keywords

Search Tree Query Result Access Pattern Graph Pattern SPARQL Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Gregory Todd Williams
    • 1
  • Jesse Weaver
    • 1
  1. 1.Tetherless World ConstellationRensselaer Polytechnic InstituteTroyUSA

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