An Offline Optimal SPARQL Query Planning Approach to Evaluate Online Heuristic Planners

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8786)


In graph databases, a given graph query can be executed in a large variety of semantically equivalent ways. Each such execution plan produces the same results, but at different computation costs. The query planning problem consists of finding, for a given query, an execution plan with the minimum cost. The traditional greedy or heuristic cost-based approaches addressing the query planning problem do not guarantee by design the optimality of the chosen execution plan. In this paper, we present a principled framework to solve the query planning problem by casting it into an Integer Linear Programming problem, and discuss its applications to testing and improving heuristic-based query planners.


RDF SPARQL Query Optimization Query Planning ILP 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.IBM T.J. Watson ResearchYorktown HeightsUSA

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