A Performance Analysis of Semantic Caching for Distributed Semi-structured Query Processing

  • Boris Novikov
  • Alice Pigul
  • Anna Yarygina
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6295)

Abstract

Caching is important for any system attempting to achieve high performance. The semantic caching is an approach trying to benefit from certain semantical knowledge of the data to be processed.

The expectation is that semantical information might help to reduce the number of cache misses and in certain cases even avoid queries to the primary data. However, the major obstacle for wide application of semantic caching is the query containment problem which is computationally hard.

In this paper we introduce an approximate conservative algorithm for semantic caching of semistructured queries and analyze its applicability for distributed query processing. Based on this analysis, we outline few scenarios where semantic caching can be benefitial for query processing in a distributed system of heterogeneous semi-structured information resources.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Larson, P.A., Yang, H.Z.: Computing queries from derived relations: Theoretical foundation. Technical report (1987)Google Scholar
  2. 2.
    Ashish, N., Knoblock, C.A., Shahabi, C.: Intelligent caching for information mediators: A kr based approach. In: KRDB, pp. 3.1–3.7 (1998)Google Scholar
  3. 3.
    Bizer, C., Schultz, A.: Benchmarking the performance of storage systems that expose sparql endpoints. In: 4th International Workshop on Scalable Semantic Web Knowledge Base Systems, SSWS 2008 (October 2008)Google Scholar
  4. 4.
    Chidlovskii, B., Borghoff, U.M.: Signature file methods for semantic query caching. In: Nikolaou, C., Stephanidis, C. (eds.) ECDL 1998. LNCS, vol. 1513, pp. 479–498. Springer, Heidelberg (1998)Google Scholar
  5. 5.
    Chidlovskii, B., Borghoff, U.M.: Semantic caching of web queries. The VLDB Journal 9(1), 2–17 (2000)CrossRefGoogle Scholar
  6. 6.
    Chidlovskii, M., Roncancio, C.: Semantic cache mechanism for heterogeneous web querying (1999)Google Scholar
  7. 7.
    Chidlovskiiy, B., Roncancioz, C., Schneidery, M.l.: Optimizing web queries through semantic caching (1999)Google Scholar
  8. 8.
    Chou, H.-T., DeWitt, D.J.: An evaluation of buffer management strategies for relational database systems. In: VLDB, pp. 127–141. Morgan Kaufmann, San Francisco (1985)Google Scholar
  9. 9.
    Chu, W.W., Chen, Q., Hwang, A.: Query answering via cooperative data inference. J. Intell. Inf. Syst. 3(1), 57–87 (1994)CrossRefGoogle Scholar
  10. 10.
    Cluet, S., Kapitskaia, O., Srivastava, D.: Using ldap directory caches. In: PODS, pp. 273–284. ACM Press, New York (1999)Google Scholar
  11. 11.
    Dar, S., Franklin, M., Jonsson, B., Srivastava, D., Tan, M.: Semantic data caching and replacement. In: VLDB 1996: Proceedings of the 22th International Conference on Very Large Data Bases, pp. 330–341. Morgan Kaufmann Publishers Inc., San Francisco (1996)Google Scholar
  12. 12.
    Erling, O., Mikhailov, I.: Rdf support in the virtuoso dbms. In: CSSW, pp. 59–68 (2007)Google Scholar
  13. 13.
    Faroult, S., Robson, P.: (2006)Google Scholar
  14. 14.
    Godfrey, P., Gryz, J.: Answering queries by semantic caches. In: Bench-Capon, T.J.M., Soda, G., Tjoa, A.M. (eds.) DEXA 1999. LNCS, vol. 1677, pp. 485–498. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  15. 15.
    Guo, S., Sun, W., Weiss, M.A.: Solving satisfiability and implication problems in database systems. ACM Trans. Database Syst. 21(2), 270–293 (1996)CrossRefGoogle Scholar
  16. 16.
    Guo, S., Sun, W., Weiss, M.A.: Addendum to “on satisfiability, equivalence, and implication problems involving conjunctive queries in database systems”. IEEE Trans. Knowl. Data Eng. 10(5), 863 (1998)Google Scholar
  17. 17.
    Ishikawa, Y., Kitagawa, H.: A semantic caching method based on linear constraints. In: Proc. of International Symposium on Database Applications in Non-Traditional Environments, DANTE 1999 (1999)Google Scholar
  18. 18.
    Jonsson, B.T., Arinbjarnar, M., Thorsson, B., Franklin, M.J., Srivastava, D.: Performance and overhead of semantic cache management. ACM Trans. Interet Technol. 6(3), 302–331 (2006)CrossRefGoogle Scholar
  19. 19.
    Keller, A.M., Basu, J.: A predicate-based caching scheme for client-server database architectures. The VLDB Journal 5, 35–47 (1996)CrossRefGoogle Scholar
  20. 20.
    Levy, A.Y.: Answering queries using views: A survey. Technical Report, VLDB Journal (2000)Google Scholar
  21. 21.
    Levy, A.Y., Mendelzon, A.O., Sagiv, Y.: Answering queries using views (extended abstract). In: PODS 1995: Proceedings of the Fourteenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, pp. 95–104. ACM, New York (1995)CrossRefGoogle Scholar
  22. 22.
    Melvin, C., Roussopoulos, C.N.: The implementation and performance evaluation of the adms query optimizer: Integrating query result caching and matching (1994)Google Scholar
  23. 23.
    Vaidehi, V., Sumalatha, M.R., Kannan, A.: Xml query processing - semantic cache system (2007)Google Scholar
  24. 24.
    Padmanabhan, V.N., Mogul, J.C.: Using predictive prefetching to improve world wide web latency. Computer Communication Review 26, 22–36 (1996)CrossRefGoogle Scholar
  25. 25.
    Pérez, J., Arenas, M., Gutierrez, C.: Semantics and complexity of sparql. ACM Trans. Database Syst. 34(3), 1–45 (2009)CrossRefGoogle Scholar
  26. 26.
    Qian, X.: Query folding. In: Proceedings of the 12th International Conference on Data Engineering, pp. 48–55. IEEE Computer Society, Los Alamitos (1996)Google Scholar
  27. 27.
    Ren, K.V.Q., Dunham, M.H.: Semantic caching and query processing. IEEE Transactions on Knowledge and Data Engineering 15, 192–210 (2003)CrossRefGoogle Scholar
  28. 28.
    Sacco, G.: Index access with a finite buffer space. In: VLDB14, pp. 301–310 (1988)Google Scholar
  29. 29.
    Shen, H.T., Li, J., Li, M., Ni, J., Wang, W. (eds.): APWeb Workshops 2006. LNCS, vol. 3842. Springer, Heidelberg (2006)Google Scholar
  30. 30.
    Sivasubramanian, S., Pierre, G., van Steen, M., Alonso, G.: GlobeCBC: Content-blind result caching for dynamic web applications. Technical Report IR-CS-022, Vrije Universiteit, Amsterdam, The Netherlands (June 2006)Google Scholar
  31. 31.
    Petropoulos, M., Hristidis, V.: Semantic caching of xml databases (2002)Google Scholar
  32. 32.
    Xu, W.: The framework of an xml semantic caching system. In: WebDB, pp. 127–132 (2005)Google Scholar
  33. 33.
    Xu, W., Ozsoyoglu, Z.M.: Rewriting xpath queries using materialized views. In: VLDB, pp. 121–132 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Boris Novikov
    • 1
  • Alice Pigul
    • 1
  • Anna Yarygina
    • 1
  1. 1.Saint-Petersburg University 

Personalised recommendations