DOI

With the widespread adoption of Linked Data, the efficient processing of SPARQL queries gains importance. A crucial category of queries that is prone to optimization is "top-k" queries, i.e. queries returning the top k results ordered by a specified ranking function. Top-k queries can be expressed in SPARQL by appending to a SELECT query the ORDER BY and LIMIT clauses, which impose a sorting order on the result set, and limit the number of results. However, the ORDER BY and LIMIT clauses in SPARQL algebra are result modifiers, i.e. their evaluation is performed only after the evaluation of the other query clauses. The evaluation of ORDER BY and LIMIT clauses in SPARQL engines typically requires the process of all the matching solutions (possibly thousands), followed by a monolithically computation of the ranking function for each solution, even if only a limited number (e.g. K = 10) of them were requested, thus leading to poor performance. In this paper, we present SPARQL-RANK, an extension of the SPARQL algebra and execution model that supports ranking as a firstclass SPAR-QL construct. The new algebra and execution model allow for splitting the ranking function and interleaving it with other operations. We also provide a prototypal open source implementation of SPARQL-RANK based on ARQ, and we carry out a series of preliminary experiments.

Original languageEnglish
Title of host publicationSearch Computing: Broadening Web Search
Pages143-156
Number of pages14
Volume7538
DOIs
StatePublished - 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7538
ISSN (Print)03029743
ISSN (Electronic)16113349

ID: 36754716