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Graph queries through Datalog optimizations

  • Stony Brook University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

This paper describes the use of a powerful graph query language for querying programs, and a novel combination of transformations for generating efficient implementations of the queries. The language supports graph path expressions that allow convenient use of both vertices and edges of arbitrary kinds as well as additional global and local parameters in graph paths. Our implementation method combines transformation to Datalog, recursion conversion, demand transformation, and specialization, and finally generates efficient analysis programs with precise complexity guarantees. This combination improves an O(V E) time complexity factor using previous methods to O(E), where V and E are the numbers of graph vertices and edges, respectively. We also describe implementations and experiments that confirm the analyzed complexities.

Original languageEnglish
Title of host publicationPPDP'10 - Proceedings of the 2010 Symposium on Principles and Practice of Declarative Programming
Pages25-34
Number of pages10
DOIs
StatePublished - 2010
Event12th International ACM SIGPLAN Symposium on Principles and Practice of Declarative Programming, PPDP 2010 - Hagenberg, Austria
Duration: Jul 26 2010Jul 28 2010

Publication series

NamePPDP'10 - Proceedings of the 2010 Symposium on Principles and Practice of Declarative Programming

Conference

Conference12th International ACM SIGPLAN Symposium on Principles and Practice of Declarative Programming, PPDP 2010
Country/TerritoryAustria
CityHagenberg
Period07/26/1007/28/10

Keywords

  • Complexity analysis
  • Datalog
  • Demand-driven evaluation
  • Graph query languages
  • Optimization
  • Program analysis
  • Program transformation

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