Advertisement

Materialized View Selection Using Simulated Annealing

  • T. V. Vijay Kumar
  • Santosh Kumar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7678)

Abstract

A data warehouse is designed for the purpose of answering decision making queries. These queries are usually long and exploratory in nature and have high response time, when processed against a continuously expanding data warehouse leading to delay in decision making. One way to reduce this response time is by using materialized views, which store pre-computed summarized information for answering decision queries. All views cannot be materialized due to their exponential space overhead. Further, selecting optimal subset of views is an NP-Complete problem. Alternatively, several view selection algorithms exist in literature, out of which most are empirical or based on heuristics like greedy, evolutionary etc. It has been observed that most of these view selection approaches find it infeasible to select good quality views for materialization for higher dimensional data sets. In this paper, a randomized view selection algorithm based on simulated annealing, for selecting Top-K views from amongst all possible sets of views in a multidimensional lattice, is presented. It is shown that the simulated annealing based view selection algorithm, in comparison to the better known greedy view selection algorithm, is able to select better quality views for higher dimensional data sets.

Keywords

Data Warehouse Materialized Views View Selection Randomized Algorithm Simulated Annealing 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Agrawal, S., Chaudhari, S., Narasayya, V.: Automated Selection of Materialized Views and Indexes in SQL databases. In: 26th International Conference on Very Large Data Bases (VLDB 2000), Cairo, Egypt, pp. 495–505 (2000)Google Scholar
  2. 2.
    Aouiche, K., Jouve, P.-E., Darmont, J.: Clustering-Based Materialized View Selection in Data Warehouses. In: Manolopoulos, Y., Pokorný, J., Sellis, T.K. (eds.) ADBIS 2006. LNCS, vol. 4152, pp. 81–95. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  3. 3.
    Aouiche, K., Darmont, J.: Data mining-based materialized view and index selection in data warehouse. Journal of Intelligent Information Systems, 65–93 (2009)Google Scholar
  4. 4.
    Baralis, E., Paraboschi, S., Teniente, E.: Materialized View Selection in a Multidimansional Database. In: 23rd International Conference on Very Large Data Bases (VLDB 1997), Athens, Greece, pp. 156–165 (1997)Google Scholar
  5. 5.
    Chaudhuri, S., Shim, K.: Including Groupby in Query Optimization. In: Proceedings of the International Conference on Very Large Database Systems (1994)Google Scholar
  6. 6.
    Chirkova, R., Halevy, A.Y., Suciu, D.: A Formal Perspective on the View Selection Problem. In: Proceedings of VLDB, pp. 59–68 (2001)Google Scholar
  7. 7.
    Galindo-Legaria, C., Pellenkoft, A., Kersten, M.: Fast, Randomized Join-Order Selection - Why Use Transformations? In: Proc: VLDB (1994)Google Scholar
  8. 8.
    Golfarelli, M., Rizzi, S.: View Materialization for Nested GPSJ Queries. In: Proceedings of the International Workshop on Design and Management of Data Warehouses (DMDW 2000), Stockholm, Sweden (2000)Google Scholar
  9. 9.
    Gupta, H., Mumick, I.S.: Selection of Views to Materialize in a Data warehouse. IEEE Transactions on Knowledge & Data Engineering 17(1), 24–43 (2005)CrossRefGoogle Scholar
  10. 10.
    Gupta, A., Harinarayan, V., Quass, D.: Generalized Projections: A Powerful Approach to Aggregation. In: Proceedings of the International Conference of Very Large Database Systems (1995)Google Scholar
  11. 11.
    Gupta, H., Harinarayan, V., Rajaraman, V., Ullman, J.: Index Selection for OLAP. In: Proceedings of the 13th International Conference on Data Engineering, ICDE 1997, Birmingham, UK (1997)Google Scholar
  12. 12.
    Haider, M., Vijay Kumar, T.V.: Materialised Views Selection using Size and Query Frequency. International Journal of Value Chain Management (IJVCM) 5(2), 95–105 (2011)CrossRefGoogle Scholar
  13. 13.
    Harinarayan, V., Rajaraman, A., Ullman, J.D.: Implementing Data Cubes Efficiently. In: ACM SIGMOD, Montreal, Canada, pp. 205–216 (1996)Google Scholar
  14. 14.
    Horng, J.T., Chang, Y.J., Liu, B.J., Kao, C.Y.: Materialized View Selection Using Genetic Algorithms in a Data warehouse System. In: Proceedings of the 1999 Congress on Evolutionary Computation, Washington D.C., USA, vol. 3 (1999)Google Scholar
  15. 15.
    Inmon, W.H.: Building the Data Warehouse, 3rd edn. Wiley Dreamtech India Pvt. Ltd. (2003)Google Scholar
  16. 16.
    Ioannidis, Y.E., Kang, Y.C.: Randomized Algorithms for Optimizing Large Join Queries. In: Proceedings of the 1990 ACM SIGMOD International Conference on Management of Data, ACM SIGMOD Record, vol. 19(2), pp. 312–321 (1990)Google Scholar
  17. 17.
    Kalnis, P., Mamoulis, N., Papadias, D.: View Selection Using Randomized Search. Data and Knowledge Engineering 42(1) (2002)Google Scholar
  18. 18.
    Kirkpatrick, S., Gelat, C., Vecchi, M.: Optimization by Simulated Annealing. Science 220, 671–680 (1983)MathSciNetzbMATHCrossRefGoogle Scholar
  19. 19.
    Lawrence, M.: Multiobjective Genetic Algorithms for Materialized View Selection in OLAP Data Warehouses. In: GECCO 2006, Seattle Washington, USA, July 8-12 (2006)Google Scholar
  20. 20.
    Lee, M., Hammer, J.: Speeding Up Materialized View Selection in Data Warehouses Using a Randomized Algorithm. Int. J. Cooperative Inf. Syst. 10(3), 327–353 (2001)CrossRefGoogle Scholar
  21. 21.
    Lehner, W., Ruf, T., Teschke, M.: Improving Query Response Time in Scientific Databases Using Data Aggregation. In: Proceedings of 7th International Conference and Workshop on Database and Expert Systems Applications, DEXA 1996, Zurich (1996)Google Scholar
  22. 22.
    Lin, Z., Yang, D., Song, G., Wang, T.: User-oriented Materialized View Selection. In: The 7th IEEE International Conference on Computer and Information Technology (2007)Google Scholar
  23. 23.
    Luo, G.: Partial Materialized Views. In: International Conference on Data Engineering (ICDE 2007), Istanbul, Turkey (April 2007)Google Scholar
  24. 24.
    Mohania, M., Samtani, S., Roddick, J., Kambayashi, Y.: Advances and Research Directions in Data Warehousing Technology. Australian Journal of Information Systems (1998)Google Scholar
  25. 25.
    Nahar, S., Sahni, S., Shragowitz, E.: Simulated Annealing and Combinatorial Optimization. In: Proceedings of the 23rd Design Automation Conference, pp. 293–299 (1986)Google Scholar
  26. 26.
    Roussopoulos, N.: Materialized Views and Data Warehouse. In: 4th Workshop KRDB 1997, Athens, Greece (August 1997)Google Scholar
  27. 27.
    Shah, B., Ramachandran, K., Raghavan, V.: A Hybrid Approach for Data Warehouse View Selection. International Journal of Data Warehousing and Mining 2(2), 1–37 (2006)zbMATHCrossRefGoogle Scholar
  28. 28.
    Swami, A., Gupta, A.: Optimization of Large Join Queries. In: Proc. ACM SIGMOD (1988)Google Scholar
  29. 29.
    Teschke, M., Ulbrich, A.: Using Materialized Views to Speed Up Data Warehousing. Technical Report, IMMD 6, Universität Erlangen-Nürnberg (1997)Google Scholar
  30. 30.
    Theodoratos, D., Sellis, T.: Data Warehouse Configuration. In: Proceeding of VLDB, Athens, Greece, pp. 126–135 (1997)Google Scholar
  31. 31.
    Valluri, S., Vadapalli, S., Karlapalem, K.: View Relevance Driven Materrialized View Selection in Data Warehousing Environment. Australian Computer Science Communications 24(2), 187–196 (2002)Google Scholar
  32. 32.
    Vijay Kumar, T.V., Ghoshal, A.: A Reduced Lattice Greedy Algorithm for Selecting Materialized Views. In: Prasad, S.K., Routray, S., Khurana, R., Sahni, S. (eds.) ICISTM 2009. CCIS, vol. 31, pp. 6–18. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  33. 33.
    Vijay Kumar, T.V., Haider, M., Kumar, S.: Proposing Candidate Views for Materialization. In: Prasad, S.K., Vin, H.M., Sahni, S., Jaiswal, M.P., Thipakorn, B. (eds.) ICISTM 2010. CCIS, vol. 54, pp. 89–98. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  34. 34.
    Vijay Kumar, T.V., Haider, M.: A Query Answering Greedy Algorithm for Selecting Materialized Views. In: Pan, J.-S., Chen, S.-M., Nguyen, N.T. (eds.) ICCCI 2010, Part II. LNCS (LNAI), vol. 6422, pp. 153–162. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  35. 35.
    Vijay Kumar, T.V., Goel, A., Jain, N.: Mining Information for Constructing Materialised Views. International Journal of Information and Communication Technology 2(4), 386–405 (2010)CrossRefGoogle Scholar
  36. 36.
    Vijay Kumar, T.V., Haider, M.: Greedy Views Selection Using Size and Query Frequency. In: Unnikrishnan, S., Surve, S., Bhoir, D. (eds.) ICAC3 2011. CCIS, vol. 125, pp. 11–17. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  37. 37.
    Vijay Kumar, T.V., Haider, M., Kumar, S.: A View Recommendation Greedy Algorithm for Materialized Views Selection. In: Dua, S., Sahni, S., Goyal, D.P. (eds.) ICISTM 2011. CCIS, vol. 141, pp. 61–70. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  38. 38.
    Vijay Kumar, T.V., Haider, M.: Selection of Views for Materialization Using Size and Query Frequency. In: Das, V.V., Thomas, G., Lumban Gaol, F. (eds.) AIM 2011. CCIS, vol. 147, pp. 150–155. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  39. 39.
    Vijay Kumar, T.V., Haider, M.: Materialized Views Selection for Answering Queries. In: Kannan, R., Andres, F. (eds.) ICDEM 2010. LNCS, vol. 6411, pp. 44–51. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  40. 40.
    Vijay Kumar, T.V., Kumar, S.: Materialized View Selection Using Genetic Algorithm. In: Parashar, M., Kaushik, D., Rana, O.F., Samtaney, R., Yang, Y., Zomaya, A. (eds.) IC3 2012. CCIS, vol. 306, pp. 225–237. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  41. 41.
    Vijay Kumar, T.V., Devi, K.: Materialized View Construction in Data Warehouse for Decision Making. International Journal of Business Information Systems (IJBIS) 11(4), 379–396 (2012)CrossRefGoogle Scholar
  42. 42.
    Widom, J.: Research Problems in Data Warehousing. In: 4th International Conference on Information and Knowledge Management, Baltimore, Maryland, pp. 25–30 (1995)Google Scholar
  43. 43.
    Yang, J., Karlapalem, K., Li, Q.: Algorithms for Materialized View Design in Data Warehousing Environment. The Very Large databases (VLDB) Journal, 136–145 (1997)Google Scholar
  44. 44.
    Yousri, N.A.R., Ahmed, K.M., El-Makky, N.M.: Algorithms for Selecting Materialized Views in a Data Warehouse. In: The Proceedings of the ACS/IEEE 2005 International Conference on Computer Systems and Applications, AICCSA 2005, pp. 27–21. IEEE Computer Society (2005)Google Scholar
  45. 45.
    Zhang, C., Yao, X., Yang, J.: Evolving Materialized Views in a Data Warehouse. In: IEEE CEC, pp. 823–829 (1999)Google Scholar
  46. 46.
    Zhang, C., Yao, X., Yang, J.: An Evolutionary Approach to Materialized Views Selection in a Data Warehouse Environment. IEEE Transactions on Systems, Man and Cybernatics, 282–294 (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • T. V. Vijay Kumar
    • 1
  • Santosh Kumar
    • 1
  1. 1.School of Computer and Systems SciencesJawaharlal Nehru UniversityNew DelhiIndia

Personalised recommendations