Efficient Execution of SPARQL Queries with OPTIONAL and UNION Expressions

TL;DR

This paper introduces a novel BGP-based evaluation framework for efficiently executing SPARQL queries with UNION and OPTIONAL operators, significantly improving performance over existing methods.

Contribution

It presents a new BE-tree representation and cost-driven transformations for optimizing complex SPARQL-UO query execution.

Findings

Outperforms state-of-the-art methods by orders of magnitude

Reduces intermediate result sizes and search space

Enhances query execution efficiency

Abstract

The proliferation of RDF datasets has resulted in studies focusing on optimizing SPARQL query processing. Most existing work focuses on basic graph patterns (BGPs) and ignores other vital operators in SPARQL, such as UNION and OPTIONAL. SPARQL queries with these operators, which we abbreviate as SPARQL-UO, pose serious query plan generation challenges. In this paper, we propose techniques for executing SPARQL-UO queries using BGP execution as a building block, based on a novel BGP-based Evaluation (BE)-Tree representation of query plans. On top of this, we propose a series of cost-driven BE-tree transformations to generate more efficient plans by reducing the search space and intermediate result sizes, and a candidate pruning technique that further enhances efficiency at query time. Experiments confirm that our method outperforms the state-of-the-art by orders of magnitude.