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Ultrawrap: SPARQL Execution on Relational Data
| Citations: | 19 - 5 self |
BibTeX
@MISC{Sequeda_ultrawrap:sparql,
author = {Juan F. Sequeda and Daniel P. Miranker},
title = {Ultrawrap: SPARQL Execution on Relational Data},
year = {}
}
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Abstract
Abstract: The Semantic Web’s promise to achieve web-wide data integration requires the inclusion of legacy relational data as RDF, which, in turn, requires the execution of SPARQL queries on the legacy relational database. In this paper we explore a hypothesis: existing commercial relational databases already subsume the algorithms and optimizations needed to support effective SPARQL execution on existing relationally stored data. The experiment, embodied in a system called Ultrawrap, comprises encoding a logical representation of the database as a graph using SQL views and a simple syntactic translation of SPARQL queries to SQL queries on those views. Thus, in the course executing a SPARQL query, the SQL optimizer both instantiates a mapping of relational data to RDF and optimizes its execution. Other approaches typically implement aspects of query optimization and execution outside the SQL environment. Ultrawrap is evaluated using two benchmarks across the three major relational database management systems. We identify two important optimizations: detection of unsatisfiable conditions and self-join elimination, such that, when applied, SPARQL queries execute at nearly the same speed as semantically equivalent native SQL queries, providing strong evidence of the validity of the hypothesis. 1.
Keyphrases
relational data sparql execution sparql query commercial relational database major relational database management system unsatisfiable condition semantic web strong evidence web-wide data integration query optimization legacy relational data equivalent native sql query sql view sql query sql environment important optimization self-join elimination implement aspect effective sparql execution simple syntactic translation legacy relational database logical representation
