ADERIS: An Adaptive Query Processor for Joining Federated SPARQL Endpoints

  • Steven Lynden
  • Isao Kojima
  • Akiyoshi Matono
  • Yusuke Tanimura
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7045)


Integrating distributed RDF data is facilitated by Linked Data and shared ontologies, however joins over distributed SPARQL services can be costly, time consuming operations. This paper describes the design and implementation of ADERIS, a query processing system for efficiently joining data from multiple distributed SPARQL endpoints. ADERIS decomposes federated SPARQL queries into multiple source queries and integrates the results utilising two techniques: adaptive join reordering, for which a cost model is defined, and the optimisation of subsequent queries to data sources to retrieve further data. The benefit of the approach in terms of minimising response time is illustrated by sample queries containing common SPARQL join patterns.


Query Processing Query Execution SPARQL Query Query Plan Triple Pattern 
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

  • Steven Lynden
    • 1
  • Isao Kojima
    • 1
  • Akiyoshi Matono
    • 1
  • Yusuke Tanimura
    • 1
  1. 1.Information Technology Research InstituteNational Institute of Advanced Industrial Science and Technology (AIST)TsukubaJapan

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