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Materialized View Selection Considering the Diversity of Semantic Web Databases

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Advances in Databases and Information Systems (ADBIS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8716))

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Abstract

With the extensive use of ontologies in various domains, Semantic Web Databases (\(\mathcal{SWDB}s\)) have appeared in the database landscape. Materialized views are one of the most popular optimization structures in advanced databases. Queries represent the most important input of the problem of selecting materialized views. In the context of \(\mathcal{SWDB}\), queries are expressed using the SPARQL language. A SPARQL query consists of a set of triple patterns executed on a set of triples representing the logical level of the \(\mathcal{SWDB}\). But a \(\mathcal{SWDB}\) may have several deployments according to the used storage layout (vertical, horizontal, binary). As a consequence the process of selecting materialized views has to consider this diversity. In this paper, we first present the difficulty of the process of materializing views in the context of \(\mathcal{SWDB}\) considering the diversity of storage layouts. Secondly, we define two approaches to select materialized views. The first approach hides the implementation aspects and views are selected at the ontological level using a rule-based approach. In the second approach, views are selected at the logical level and the view selection is guided by a cost model which considers the diverse storage layouts that can be used. Finally, intensive experiments are conducted by the means of the Lehigh University Benchmark and we empirically compare our finding with state-of-the-art algorithms.

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References

  1. Gupta, H.: Selection and maintenance of views in a data warehouse. PhD thesis (1999)

    Google Scholar 

  2. Morzy, T., Wojciechowski, M., Zakrzewicz, M.: Materialized data mining views. In: Zighed, D.A., Komorowski, J., Żytkow, J.M. (eds.) PKDD 2000. LNCS (LNAI), vol. 1910, pp. 65–74. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  3. Arion, A., Benzaken, V., Manolescu, I., Papakonstantinou, Y.: Structured materialized views for xml queries. In: VLDB, pp. 87–98 (2007)

    Google Scholar 

  4. Adali, S., Candan, K.S., Papakonstantinou, Y., Subrahmanian, V.S.: Query caching and optimization in distributed mediator systems. ACM SIGMOD, 137–148 (1996)

    Google Scholar 

  5. Upadhyaya, P., Balazinska, M., Suciu, D.: How to price shared optimizations in the cloud. VLDB 5(6), 562–573 (2012)

    Google Scholar 

  6. Mami, I., Bellahsene, Z.: A survey of view selection methods. SIGMOD Record 41(1), 20–29 (2012)

    Article  Google Scholar 

  7. Dhote, C., Ali, M.: Materialized view selection in data warehousing: A survey. Journal of Applied Sciences 9(1), 401–414 (2009)

    Article  Google Scholar 

  8. Mbaiossoum, B., Bellatreche, L., Jean, S.: Towards performance evaluation of semantic databases management systems. In: Gottlob, G., Grasso, G., Olteanu, D., Schallhart, C. (eds.) BNCOD 2013. LNCS, vol. 7968, pp. 107–120. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  9. Bechhofer, S., van Harmelen, F., Hendler, J., Horrocks, I., McGuinness, D., Patel-Schneider, P., Stein, L.: Owl web ontology language reference. W3C (2004), http://www.w3.org/TR/owl-ref/

  10. Brickley, D., Guha, R.: Rdf vocabulary description language 1.0: Rdf schema. W3C (2002), http://www.w3.org/TR/rdf-schema/

  11. Pierra, G.: Context representation in domain ontologies and its use for semantic integration of data. Journal of Data Semantics (JoDS) 10, 174–211 (2008)

    Google Scholar 

  12. Goasdoué, F., Karanasos, K., Leblay, J., Manolescu, I.: View selection in semantic web databases. VLDB 5(2), 97–108 (2011)

    Google Scholar 

  13. Castillo, R., Leser, U.: Selecting materialized views for RDF data. In: Daniel, F., Facca, F.M. (eds.) ICWE 2010. LNCS, vol. 6385, pp. 126–137. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  14. Dritsou, V., Constantopoulos, P., Deligiannakis, A., Kotidis, Y.: Optimizing query shortcuts in RDF databases. In: Antoniou, G., Grobelnik, M., Simperl, E., Parsia, B., Plexousakis, D., De Leenheer, P., Pan, J. (eds.) ESWC 2011, Part II. LNCS, vol. 6644, pp. 77–92. Springer, Heidelberg (2011)

    Google Scholar 

  15. Yang, J., Karlapalem, K., Li, Q.: Algorithms for materialized view design in data warehousing environment. In: VLDB, pp. 136–145 (1997)

    Google Scholar 

  16. Arias, M., Fernández, J.D., Martínez-Prieto, M.A., de la Fuente, P.: An empirical study of real-world sparql queries. CoRR abs/1103.5043 (2011)

    Google Scholar 

  17. Frasincar, F., Houben, G.J., Vdovjak, R., Barna, P.: Ral: An algebra for querying RDF. World Wide Web 7(1), 83–109 (2004)

    Article  Google Scholar 

  18. Cyganiak, R.: A relational algebra for SPARQL. Technical report, Digital Media Systems Laboratory, HP Laboratories Bristol (2005)

    Google Scholar 

  19. Garcia-Molina, H., Ullman, J.D., Widom, J.: Database Systems: The Complete Book, 2nd edn. Prentice Hall Press, Upper Saddle River (2008)

    Google Scholar 

  20. Stocker, M., Seaborne, A., Bernstein, A., Kiefer, C., Reynolds, D.: Sparql basic graph pattern optimization using selectivity estimation. In: WWW, pp. 595–604 (2008)

    Google Scholar 

  21. Kaoudi, Z., Kyzirakos, K., Koubarakis, M.: SPARQL query optimization on top of DHTs. In: Patel-Schneider, P.F., Pan, Y., Hitzler, P., Mika, P., Zhang, L., Pan, J.Z., Horrocks, I., Glimm, B. (eds.) ISWC 2010, Part I. LNCS, vol. 6496, pp. 418–435. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  22. Hylock, R., Currim, F.: A maintenance centric approach to the view selection problem. Information Systems 38(7), 971–987 (2013)

    Article  Google Scholar 

  23. Troiano, L., Pasquale, D.D.: A java library for genetic algorithms addressing memory and time issues. In: NaBIC, pp. 642–647 (2009)

    Google Scholar 

  24. Guo, Y., Pan, Z., Heflin, J.: Lubm: A benchmark for owl knowledge base systems. Web Semantics: Science, Services and Agents on the World Wide Web 3(2-3) (2011)

    Google Scholar 

  25. Theodoratos, D., Sellis, T.: Designing data warehouses (1999)

    Google Scholar 

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Mbaiossoum, B., Bellatreche, L., Jean, S. (2014). Materialized View Selection Considering the Diversity of Semantic Web Databases. In: Manolopoulos, Y., Trajcevski, G., Kon-Popovska, M. (eds) Advances in Databases and Information Systems. ADBIS 2014. Lecture Notes in Computer Science, vol 8716. Springer, Cham. https://doi.org/10.1007/978-3-319-10933-6_13

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  • DOI: https://doi.org/10.1007/978-3-319-10933-6_13

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10932-9

  • Online ISBN: 978-3-319-10933-6

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