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semQA: SPARQL with Idempotent Disjunction.

E Patrick Shironoshita1, Yves R Jean-Mary, Ray M Bradley

  • 1INFOTECH Soft, Inc., 9200 S. Dadeland Blvd., Suite 620, Miami, FL 33156. E-mail: patrick@infotechsoft.com , reggie@infotechsoft.com , rbradley@infotechsoft.com.

IEEE Transactions on Knowledge and Data Engineering
|November 17, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces semQA, an extension to SPARQL query language, replacing Union with an idempotent Or operator. This enables better query optimization and distributed processing for RDF data.

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Area of Science:

  • Computer Science
  • Database Systems
  • Semantic Web Technologies

Background:

  • The SPARQL LeftJoin operator's non-distributivity over Union hinders algebraic manipulation of graph patterns.
  • This limitation restricts query plan generation for distributed processing and optimization.

Purpose of the Study:

  • Introduce semQA, an algebraic extension for SPARQL, to address the non-distributivity issue.
  • Enable enhanced algebraic manipulation and query optimization for RDF data.

Main Methods:

  • Replaced the standard Union operator with an idempotent disjunction operator (Or) in SPARQL graph patterns.
  • Developed an algorithm to derive original query solution sets from transformed queries using Or.
  • Analyzed the combined complexity of SPARQL, proving it NP-complete and not generally fixed-parameter tractable.

Main Results:

  • semQA facilitates query transformation through a set of equivalences, enabling distinct query forms.
  • The proposed algorithm successfully derives solution sets from queries employing the Or operator.
  • SPARQL's combined complexity is NP-complete, and it's not fixed-parameter tractable in general cases.

Conclusions:

  • semQA overcomes the limitations of SPARQL's LeftJoin operator, improving algebraic manipulation.
  • The semQA methodology offers significant processing cost reductions compared to the standard SPARQL evaluation.
  • The complexity analysis provides crucial insights into the computational challenges of SPARQL query processing.