Affiliation:
1. School of Information Engineering, Liaodong University, Dandong 118003, China
2. Department of Information Engineering, Liaoning Mechatronics College, Dandong 118009, China
Abstract
With a rapid growth in the available resource description framework (RDF) data from disparate domains, the SPARQL query processing with graph structures has become increasingly important. In this pursuit, we designed a two-phase SPARQL query optimization method to process the SPARQL query. The structural characteristics of RDF data graphs, predicate path sequence indices (PPS-indices), were used to efficiently prune the search space, which captured the inherent features of the RDF data graphs, while the database is updated. Our storage model was based on a relational database. Compared to a baseline solution, the proposed method effectively reduced the cardinalities of the intermediate results during the query processing, and at least an order of magnitude improvement is achieved in filtering performance, thereby improving the efficiency of the query execution.
Funder
Department of Education of Liaoning Province
Subject
Electrical and Electronic Engineering,Instrumentation,Control and Systems Engineering
Cited by
2 articles.
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1. Retracted: A Two-Phase Method for Optimization of the SPARQL Query;Journal of Sensors;2024-01-31
2. Datenformate;Computational Methods für die Sozial- und Geisteswissenschaften;2023