skip to main content
10.1145/2463664.2465216acmconferencesArticle/Chapter ViewAbstractPublication PagesmodConference Proceedingsconference-collections
research-article

Querying graph databases

Published:22 June 2013Publication History

ABSTRACT

Graph databases have gained renewed interest in the last years, due to its applications in areas such as the Semantic Web and Social Networks Analysis. We study the problem of querying graph databases, and, in particular, the expressiveness and complexity of evaluation for several general-purpose query languages, such as the regular path queries and its extensions with conjunctions and inverses. We distinguish between two semantics for these languages. The first one, based on simple paths, easily leads to intractability, while the second one, based on arbitrary paths, allows tractable evaluation for an expressive family of languages.

We also study two recent extensions of these languages that have been motivated by modern applications of graph databases. The first one allows to treat paths as first-class citizens, while the second one permits to express queries that combine the topology of the graph with its underlying data.

References

  1. . Abiteboul, P. Buneman, D. Suciu. Data on the Web: From Relations to Semistructured Data and XML. Morgan Kauffman, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. . Abiteboul, R. Hull, V. Vianu. Foundations ofdatabases. Addison-Wesley, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. . Abiteboul, D. Quass, J. McHugh, J. Widom,J. L. Wiener. The Lorel query language for semistructureddata. Int. J. on Digital Libraries 1(1), pages 68--88, 1997.Google ScholarGoogle ScholarCross RefCross Ref
  4. S. Abiteboul, V. Vianu. Regular path queries with constraints. JCSS 58(3), pages 428--452, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. R. Angles, C. Gutiérrez. Survey of graph database models. ACM Comput. Surv. 40(1), 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. . Alon, R. Yuster, U. Zwick. Finding and counting given length cycles (Extended abstract). In ESA 1994, pages 354--364. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. M. K. Anand, S. Bowers, B. Ludäscher. Techniques for efficiently querying scientific workflow provenancegraphs. In EDBT 2010, pages 287--298. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. K. Anyanwu, A. P. Sheth. ρ-queries: enabling querying for semantic associations on the semantic web. In WWW 2003, pages 690--699. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. K. Anyanwu, A. Maduko, A. P. Sheth. SPARQ2L: towards support for subgraph extraction queries in RDF databases. In WWW 2007, pages 797--806. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. M. Arenas, J. Pérez. Querying semantic web data with SPARQL. In PODS2011, pages 305--316. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. M. Arenas, S. Conca, J. Pérez. Counting beyond a Yottabyte, or how SPARQL 1.1 property paths will prevent adoption of the standard. In WWW 2012, pages 629--638. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. . Barceló, D. Figueira, L. Libkin. Graph-logics withrational relations and the generalized intersection problem. In LICS 2012, pages 115--124. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. . Barceló, L. Libkin, A. W. Lin, P. T. Wood. Expressive languages for path queries over graph-structured Data. TODS 37(4), 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. . Barceló, L. Libkin, J. Reutter. Querying graphpatterns. In PODS 2011, pages 199--210. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. . Barceló, L. Libkin, J. Reutter. Parameterizedregular expressions and their languages. TCS 474, pages 21--45,2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. . Barceló, L. Libkin, M. Romero. Efficientapproximations of conjunctive queries. In PODS, pages 249--260,2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. . Barceló, J. Reutter, J. Pérez. Relativeexpressiveness of nested regular expressions. In AMW 2012, pages 180--195.Google ScholarGoogle Scholar
  18. . Barceló, M. Romero, M. Y. Vardi. Semantic acyclicity on graph databases. In PODS 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. C.L. Barrett, R. Jacob, M.V. Marathe. Formal-language-constrained pathproblems. SIAM J. on Comp., 30(3), pages 809--837, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. J.M. Berstel. Transductions and Context-Free Languages. B. G. Teubner, 1979.Google ScholarGoogle ScholarCross RefCross Ref
  21. A. Blumensath, E. Grädel. Automatic structures. In LICS 2000,pages 51--62. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. . Bojanczyk, A. Muscholl, Th. Schwentick, L. Segoufin. Two-variable logic on data trees and XML reasoning. JACM 56(3), 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. . Bojanczyk. Automata for data words and data trees. In RTA, 2010.Google ScholarGoogle Scholar
  24. P. Buneman. Semistructured data. In PODS 1997, pages 117--121. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. . Buneman, W. Fan, S. Weinstein. Path constraints insemistructured databases. JCSS 61(2), pages 146--193, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. P. Buneman, M. F. Fernandez, D. Suciu. UnQL: A query language andalgebra for semistructured data based on structural recursion. VLDB J. 9(1), pages 76--110, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. . Calvanese, G. de Giacomo, M. Lenzerini, M. Y. Vardi. Containment of conjunctive regular path queries with inverse. In KR 2000, pages 176--185.Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. . Calvanese, G. de Giacomo, M. Lenzerini, M. Y. Vardi. Rewriting of regular expressions and regular path queries. J. Comput. Syst. Sci. (JCSS), 64(3), pages 443--465, 2002. JCSS, 64(3), pages 443--465, 2002.Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. . Calvanese, G. de Giacomo, M. Lenzerini,M. Y. Vardi. View-based query containment. In PODS 2003, pages 56--67. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. D. Calvanese, G. de Giacomo, M. Lenzerini, M. Y. Vardi. Reasoning on regular path queries. SIGMOD Record 32(4), pages 83--92, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. . Chambart, Ph. Schnoebelen. Post embedding problem isnot primitive recursive, with applications to channel systems. In FSTTCS2007, pages 265--276. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. A. Chandra and P. Merlin. Optimal implementation of conjunctive queries in relationaldata bases. In STOC 1977, pages77--90. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. M. P. Consens, A. O. Mendelzon. Expressing structural hypertext queries in GraphLog. In Hypertext 1989, pages 269--292. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. . P. Consens, A. O. Mendelzon. GraphLog: a visual formalismfor real life recursion. In PODS 1990, pages 404--416. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. . P. Consens, A. O. Mendelzon. Low complexityaggregation in graphLog and datalog. TCS 116 (1 & 2), pages 95--116, 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. I. Cruz, A. Mendelzon, P. Wood. A graphical query language supporting recursion. In SIGMOD 1987, pages 323--330. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. L3S dblp bibliography DB: http://dblp.l3s.de/d2r/Google ScholarGoogle Scholar
  38. S. DeRose. J. Clark. Xml path language (xpath). W3CRecommendation, November 1999, http://www.w3.org/TR/xpath.Google ScholarGoogle Scholar
  39. A. Deutsch, V. Tannen. Optimization properties forclasses of conjunctive regular path queries. In DBPL 2001, pages21--39. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. A. Dries, S. Nijssen, L. De Raedt. A query language for analyzing networks. In CIKM 2009, pages 485--494. Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. C. Elgot, J. Mezei. On relations defined by generalizedfinite automata. IBM Journal of Research and Development, 9(1),pages 47--68, 1965. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. W. Fan. Graph pattern matching revised for social networkanalysis. In ICDT 2012, pages 8--21. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. M. F. Fernández, D. Florescu, A. Y. Levy, D. Suciu. Declarativespecification of web sites with Strudel. VLDB J. 9(1), pages38--55, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. M. F. Fernandez, D. Suciu. Optimizing regular path expressions usinggraph schemas. In ICDE 1998, pages 14--23. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. G. H. L. Fletcher, M. Gyssens, D. Leinders, J. Van den Bussche, D. Van Gucht, S. Vansummeren, Y. Wu. Relative expressive power of navigational querying on graphs. In ICDT 2011, pages 197--207. Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. D. Florescu, A. Y. Levy, D. Suciu. Query containment for conjunctivequeries with regular expressions. In PODS 1998, pages 139--148. Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. D. D. Freydenberger, D. Reidenbach. Bad news on decision problems forpatterns. Inf. Comput. 208(1), pages 83--96, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. D. D. Freydenberger, N. Schweikardt. Expressiveness and staticanalysis of extended conjunctive regular path queries. In AMW 2011.Google ScholarGoogle Scholar
  49. Ch. Frougny, J. Sakarovitch. Rational relations with bounded delay. In STACS 1991, pages 50--63. Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. G. Grahne, A. Thomo. Query containment and rewriting using views for regular path queriesunder constraints. In PODS 2003, pages 111--122. Google ScholarGoogle ScholarDigital LibraryDigital Library
  51. . Greenlaw, J. Hoover, W. Ruzzo. Limits to parallel computation: P-completeness theory. OxfordUniversity Press, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  52. D. Gusfield. Algorithms on strings, trees and sequences: Computerscience and computational biology. Cambridge University Press, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  53. R. H. Güting. GraphDB: Modeling and querying graphs in databases. In VLDB 1994, pages 297--308. Google ScholarGoogle ScholarDigital LibraryDigital Library
  54. M. Gyssens, J. Paredaens, J. Van den Bussche, D. Van Gucht. A graph-oriented object databasemodel. IEEE Trans. Knowl. Data Eng. 6(4), pages 572--586, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  55. . Harel, D. Kozen, J. Tiuryn. Dynamic Logic. MIT Press, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. S. Harris, A. Seaborne. SPARQL 1.1 query language. W3Cworking draft. http://www.w3.org/TR/sparql11-query/, July 2012.Google ScholarGoogle Scholar
  57. J. Hellings, B. Kuijpers, J. Van den Bussche, X. Zhang. Walk logic as a framework for path query languages on graphdatabases. In ICDT 2013, pages 117--128. Google ScholarGoogle ScholarDigital LibraryDigital Library
  58. D.A. Holland, U. Braun, D. Maclean, K.K. Muniswamy-Reddy, M.I. Seltzer. Choosing a data model and query language for provenance. In IPAW 2008, pages 98--115.Google ScholarGoogle Scholar
  59. nfinite graph. http://objectivity.comGoogle ScholarGoogle Scholar
  60. T. Jiang, A. Salomaa, K. Salomaa, S. Yu. Decision problems for patterns. JCSS 50(1), pages 53--63, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  61. M. Kaminski, N. Francez. Finite memory automata. TCS, 134(2), pages 329--363, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  62. K. Kochut, M. Janik. SPARQLeR: Extended Sparql for semantic association discovery. In ESWC 2007, pages 145--159. Google ScholarGoogle ScholarDigital LibraryDigital Library
  63. Z. Lacroix, H. Murthy, F. Naumann, L. Raschid. Links andpaths through life sciences data Sources. In DILS 2004, pages203--211.Google ScholarGoogle ScholarCross RefCross Ref
  64. A. LaPaugh, Ch. Papadimitriou. The even path problem for graphs and digraphs. Networks 14(4),pages 507--513, 1984.Google ScholarGoogle Scholar
  65. . Libkin, D. Vrgoć. Regular path queries on graphswith data. In ICDT 2012, pages 74--85. Google ScholarGoogle ScholarDigital LibraryDigital Library
  66. L. Libkin, W. Martens, D. Vrgo\vc. Querying graph databases with XPath. In ICDT 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  67. K. Losemann, W. Martens. The complexity of evaluating path expressions in SPARQL. In PODS2012, pages 101--112. Google ScholarGoogle ScholarDigital LibraryDigital Library
  68. N. Martínez-Bazan, V. Muntés-Mulero, S. Gomez-Villamor, J. Nin, M. Sánchez-Martínez, J. L. Larriba-Pey. Dex: high-performance exploration on large graphsfor information retrieval. In CIKM 2007, pages 573--582. Google ScholarGoogle ScholarDigital LibraryDigital Library
  69. A. Mendelzon, P. Wood. Finding regular simple paths in graph databases. SIAM J. Comput. 24(6), pages 1235--1258, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  70. neo4j. http://www.neo4j.org/Google ScholarGoogle Scholar
  71. F. Neven, Th. Schwentick, V. Vianu. Finite state machinesfor strings over infinite alphabets. ACM TOCL 5(3), pages 403--435, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  72. Ch. Papadimitriou, M. Yannakakis.On the complexity of database queries. In PODS 1997, pages12--19. Google ScholarGoogle ScholarDigital LibraryDigital Library
  73. J. Paredaens, P. Peelman, L. Tanca. G-Log: A graph-based query language. IEEE Trans. Knowl. Data Eng. 7(3), pages 436--453, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  74. J. Pérez, M. Arenas, C. Gutierrez. nSPARQL: A navigational language for RDF. Journal of Web Semantics 8(4), pages 255--270, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  75. J. Reutter. Containment of nested regular expressions. http://arxiv.org/abs/1304.2637Google ScholarGoogle Scholar
  76. R. Ronen, O. Shmueli. SoQL: A language for querying andcreating data in social networks. In ICDE 2009, pages 1595--1602. Google ScholarGoogle ScholarDigital LibraryDigital Library
  77. A. Salomaa. Patterns. Bulletin of the EATCS 54, pages 194--206,1994.Google ScholarGoogle Scholar
  78. M. San Martín, C. Gutierrez, P. T. Wood. SNQL: A social networks query and transformation language. In AMW 2011.Google ScholarGoogle Scholar
  79. L. J. Stockmeyer, A. R. Meyer. Word problems requiring exponential time: Preliminary report. In STOC 1973, pages 1--9. Google ScholarGoogle ScholarDigital LibraryDigital Library
  80. M. Y. Vardi. The complexity of relational querylanguages. In STOC 1982, pages 137--146. Google ScholarGoogle ScholarDigital LibraryDigital Library
  81. .Y. Vardi. On the complexity of bounded variablequeries. In PODS 1995, pages 266--276. Google ScholarGoogle ScholarDigital LibraryDigital Library
  82. G. Weikum, G. Kasneci, M. Ramanath, F. M. Suchanek. Database and information-retrieval methods for knowledgediscovery. CACM 52(4), pages 56--64, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  83. M. Yannakakis. Algorithms for acyclic database schemes. In VLDB 1981, pages 82--94. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Querying graph databases

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      PODS '13: Proceedings of the 32nd ACM SIGMOD-SIGACT-SIGAI symposium on Principles of database systems
      June 2013
      334 pages
      ISBN:9781450320665
      DOI:10.1145/2463664
      • General Chair:
      • Richard Hull,
      • Program Chair:
      • Wenfei Fan

      Copyright © 2013 ACM

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 22 June 2013

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article

      Acceptance Rates

      PODS '13 Paper Acceptance Rate24of97submissions,25%Overall Acceptance Rate476of1,835submissions,26%

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader
    About Cookies On This Site

    We use cookies to ensure that we give you the best experience on our website.

    Learn more

    Got it!