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Maintenance of top-k materialized views

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Abstract

In this paper we present results on the problem of maintaining materialized top-k views and provide results in two directions. The first problem we tackle concerns the maintenance of top-k views in the presence of high deletion rates. We provide a principled method that complements the inefficiency of the state of the art independently of the statistical properties of the data and the characteristics of the update streams. The second problem we have been concerned with has to do with the efficient maintenance of multiple top-k views in the presence of updates to their base relation. To this end, we provide theoretical guarantees for the nucleation (practically, inclusion) of a view with respect to another view and the reflection of this property to the management of updates. We also provide algorithmic results towards the maintenance of a large number of views, via their appropriate structuring in hierarchies of views.

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References

  1. Baikousi, E., Vassiliadis, P.: Tuning the top-k view update process. In: 3rd Multidisciplinary Workshop on Advances in Preference Handling (M-Pref 2007), held in conjunction with VLDB 2007, Vienna, Austria, 23 September 2007

  2. Das, G., Gunopulos, D., Koudas, N., Tsirogiannis, D.: Answering top-k queries using views. In: Proc. of the 32nd VLDB Conference, pp. 451–462, Seoul, Korea, 2006

  3. DeGroot, M.H., Schervish, M.J.: Probability and Statistics. Addison-Wesley, Reading (2002)

    Google Scholar 

  4. Fagin, R.: Combining fuzzy information from multiple systems. In: Proc. of the 15th ACM Symposium on Principles of Database Systems, pp. 216–226, Montreal, Canada, 1996

  5. Fagin, R.: Fuzzy queries in multimedia database systems. In: Proc. of the 17th ACM Symposium on Principles of Database Systems, pp. 1–10, Seattle, USA, 1998

  6. Fagin, R., Lotem, A., Naor, M.: Optimal aggregation algorithms for middleware. J. Comput. Syst. Sci. 66(4), 614–656 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  7. Graefe, G.: Dynamic query evalutation plans: Some course corrections. Bull. Tech. Comm. Data Eng. 23(2), 3–6 (2000)

    Google Scholar 

  8. Güntzer, U., Balke, W.-T., Kießling, W.: Optimizing multi-feature queries for image databases. In: Proc. of the 26th VLDB Conference, pp. 419–428, Cairo, Egypt, 2000

  9. Hristidis, V., Papakonstantinou, Y.: Algorithms and applications for answering ranked queries using ranked views. VLDB J. 13(1), 49–70 (2004)

    Article  Google Scholar 

  10. Hristidis, V., Koudas, N., Papakonstantinou, Y.: PREFER a system for the efficient execution of multi-parametric ranked queries. In: Proc. of the ACM Special Interest Group on Management of Data Conference (SIGMOD), pp. 259–270, Santa Barbara, USA, 2001

  11. Kossmann, D.: The state of the art in distributed query processing. ACM Comput. Surv. 32(4), 422–469 (2000)

    Article  Google Scholar 

  12. Marian, A., Bruno, N., Gravano, L.: Evaluating top-k queries over web-accessible databases. ACM Trans. Database Syst. (TODS) 29(2), 319–362 (2004)

    Article  Google Scholar 

  13. Mouratidis, K., Bakiras, S., Papadias, D.: Continuous monitoring of top-k queries over sliding windows. In: Proc. of the ACM Special Interest Group on Management of Data Conference (SIGMOD), pp. 635–646, Chicago, Illinois, USA, 2006

  14. Nepal, S., Ramakrishna, M.V.: Query processing issues in image (multimedia) databases. In: Proc. of the 15th International Conference on Data Engineering (ICDE), pp. 22–29, Sydney, Australia, 1999

  15. Papadias, D., Tao, Y., Fu, G., Seeger, B.: Progressive skyline computation in database systems. ACM Trans. Database Syst. (TODS) 30(1), 41–82 (2005)

    Article  Google Scholar 

  16. Schlossnagle, T.: Dissecting today’s Internet traffic spikes. Posted on 15 January 2009 at http://omniti.com/seeds/dissecting-todays-internet-traffic-spikes

  17. Trivedi, K.S.: Probability and Statistics with Reliability, Queuing and Computer Science Applications. Wiley, New York (2002)

    Google Scholar 

  18. Vlachou, A., Doulkeridis, C., Norvag, K., Vazirgiannis, M.: On efficient top-k query processing in highly distributed environments. In: Proc. of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2008, Vancouver, BC, Canada, June 2008

  19. Yi, K., Yu, H., Yang, J., Xia, G., Chen, Y.: Efficient maintenance of materialized top-k views. In: Proceedings of the 19th International Conference on Data Engineering (ICDE), pp. 189–200, Bangalore, India, 2003

  20. Zhao, K., Tao, Y., Zhou, S.: Efficient top-k processing in large-scaled distributed environments. Data Knowl. Eng. 63, 315–335 (2007)

    Article  Google Scholar 

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Correspondence to Eftychia Baikousi.

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Communicated by Ihab F. Ilyas.

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Baikousi, E., Vassiliadis, P. Maintenance of top-k materialized views. Distrib Parallel Databases 27, 95–137 (2010). https://doi.org/10.1007/s10619-009-7057-4

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