Left Bit Right: For SPARQL Join Queries with OPTIONAL Patterns (Left-outer-joins)
Medha Atre

TL;DR
This paper introduces Left Bit Right (LBR), a novel optimization technique for SPARQL OPTIONAL pattern queries that significantly improves query processing speed by using graph-based representations and advanced pruning strategies.
Contribution
LBR is the first method to optimize well-designed nested BGP and OPTIONAL queries using supernode graphs and combined optimization strategies, outperforming existing RDF stores.
Findings
LBR processes complex queries up to 11 times faster than Virtuoso and MonetDB.
LBR performs on par with state-of-the-art systems for highly selective queries.
Evaluation on billion-triple RDF graphs demonstrates scalability and efficiency.
Abstract
SPARQL basic graph pattern (BGP) (a.k.a. SQL inner-join) query optimization is a well researched area. However, optimization of OPTIONAL pattern queries (a.k.a. SQL left-outer-joins) poses additional challenges, due to the restrictions on the \textit{reordering} of left-outer-joins. The occurrence of such queries tends to be as high as 50% of the total queries (e.g., DBPedia query logs). In this paper, we present \textit{Left Bit Right} (LBR), a technique for \textit{well-designed} nested BGP and OPTIONAL pattern queries. Through LBR, we propose a novel method to represent such queries using a graph of \textit{supernodes}, which is used to aggressively prune the RDF triples, with the help of compressed indexes. We also propose novel optimization strategies -- first of a kind, to the best of our knowledge -- that combine together the characteristics of \textit{acyclicity} of queries,…
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Taxonomy
TopicsSemantic Web and Ontologies · Advanced Database Systems and Queries · Data Management and Algorithms
