Abstract
Traditional database systems assume that clients always consume the results of queries from the beginning. In various new applications especially in WWW, however, clients frequently need a small part of the result from the middle, e.g. retrieving a page in a bulletin board in WWW. To process this partial retrieval, traditional database systems should find all the records and discard unnecessary ones. Although several algorithms for top-k queries have been proposed, there has been no research effort for partial retrieving from the middle of an ordered result. In this paper, we define a mid-(k,n) query, which retrieves n records from the k th record of an ordered result. We also propose an efficient algorithm for mid-(k,n) queries using a slightly modified B + -Tree, named the B + c-Tree. We provide the theoretical analysis and the experimental results that the proposed technique evaluates mid-(k,n) queries efficiently.
This work was supported in part by the Brain Korea 21 Project and in part by the Ministry of Information & Communications, Korea, under the Information Technology Research Center (ITRC) Support Program in 2005.
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References
Comer, D.: Ubiquitous b-tree. ACM Computing Surveys 11, 121–137 (1979)
Carey, M.J., Kossmann, D.: Reducing the braking distance of an sql query engine. In: Proceedings of 24th Int’l. Conf. on Very Large Data Bases, pp. 158–169 (1998)
Donjerkovic, D., Ramakrishnan, R.: Probabilistic optimization of top n queries. In: Proceedings of 25th Int’l. Conf. on Very Large Data Bases, pp. 411–422 (1999)
Chaudhuri, S., Gravano, L.: Evaluating top-k selection queries. In: Proceedings of 25th Int’l. Conf. on Very Large Data Bases, pp. 397–410 (1999)
Chen, C.M., Ling, Y.: A sampling-based estimator for top-k query. In: Proceedings of the 18th Int’l. Conf. on Data Engineering, pp. 617–627 (2002)
Blum, M., Floyd, R.W., Pratt, V.R., Rivest, R.L., Tarjan, R.E.: Time bounds for selection. Journal of Computer and System Sciences 7, 448–461 (1973)
Alsabti, K., Ranka, S., Singh, V.: A one-pass algorithm for accurately estimating quantiles for disk-resident data. In: Proceedings of 23rd Int’l. Conf. on Very Large Data Bases, pp. 346–355 (1997)
Manku, G.S., Rajagopalan, S., Lindsay, B.G.: Approximate medians and other quantiles in one pass and with limited memory. In: Proceedings of the 1998 ACM SIGMOD Int’l. Conf. on Management of Data, pp. 426–435 (1998)
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Kwon, D., Lee, T., Lee, S. (2005). Evaluating Mid-(k, n) Queries Using B + -Tree. In: Andersen, K.V., Debenham, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2005. Lecture Notes in Computer Science, vol 3588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11546924_8
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DOI: https://doi.org/10.1007/11546924_8
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