Abstract
Histograms are a lossy compression technique widely applied in various application contexts, like query optimization, statistical and temporal databases, OLAP applications, and so on. This paper presents a new histogram based on a hierarchical decomposition of the original data distribution kept in a complete binary tree. This tree, thus containing a set of pre-computed hierarchical queries, is encoded in a compressed form using bit saving in representing integer numbers. The approach, extending a recently proposed technique based on the application of such a decomposition to the buckets of a pre-existing histogram, is shown by several experiments to improve the accuracy of the state-of-the-art histograms.
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Buccafurri, F., Furfaro, F., Lax, G., Saccá, D.: Binary-tree histograms with tree indices. In: Hameurlain, A., Cicchetti, R., Traunmüller, R. (eds.) DEXA 2002. LNCS, vol. 2453, p. 861. Springer, Heidelberg (2002)
Buccafurri, F., Pontieri, L., Rosaci, D., Saccà, D.: Improving Range Query Estimation on Histograms. In: ICDE 2002, San Jose (CA), USA (2002)
Buccafurri, F., Rosaci, D., Saccá, D.: Compressed datacubes for fast OLAP applications. In: Mohania, M., Tjoa, A.M. (eds.) DaWaK 1999. LNCS, vol. 1676, pp. 65–77. Springer, Heidelberg (1999)
Koudas, N., Muthukrishnan, S., Srivastava, D.: Optimal Histograms for Hierarchical Range Queries. In: Proc. of Symposium on Principles of Database Systems - PODS, Dallas, Texas, pp. 196–204 (2000)
Malvestuto, F.: A Universal-Scheme Approach to Statistical Databases Containing Homogeneous Summary Tables. ACM TODS 18(4), 678–708 (1993)
Matias, Y., Vitter, J.S., Wang, M.: Wavelet-based histograms for selectivity estimation. In: Proceedings of the 1998 ACM SIGMOD Conference on Management of Data, Seattle, Washington (June 1998)
Natsev, A., Rastogi, R., Shim, K.: WALRUS: A Similarity Retrieval Algorithm for Image Databases. In: Proceedings of the 1999 ACM SIGMOD Conference on Management of Data (1999)
Poosala, V.: Histogram-based Estimation Techniques in Database Systems. PhD dissertation, University of Wisconsin-Madison (1997)
Poosala, V., Ioannidis, Y.E., Haas, P.J., Shekita, E.J.: Improved histograms for selectivity estimation of range predicates. In: Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data, pp. 294–305 (1996)
Poosala, V., Ganti, V., Ioannidis, Y.E.: Approximate Query Answering using Histograms. IEEE Data Engineering Bulletin 22 (March 1999)
Selinger, P.G., Astrahan, M.M., Chamberlin, D.D., Lorie, R.A., Price, T.T.: Access path selection in a relational database management system. In: Proc. of ACM SIGMOD Internatinal Conference, pp. 23–24 (1979)
Sitzmann, I., Stuckey, P.J.: Improving Temporal Joins Using Histograms. In: Proc. of the Int. Conference, Database and Expert Systems Applications – DEXA (2000)
Stollnitz, E.J., Derose, T.D., Salesin, D.H.: Wavelets for Computer Graphics. Morgan Kauffmann, San Francisco (1996)
Vitter, J.S., Wang, M., Iyer, B.: Data Cube Approximation and Histograms via Wavelet. In: Proceedings of the 1998 CIKM International Conference on Information and Knowledge Management, Washington (1998)
Vitter, J.S., Wang, M.: Approximate Computation of Multidimansional Aggregates of Sparse Data using Wavelets. In: Proceedings of the 1999 ACM SIGMOD International Conference on Management of Data (1999)
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Buccafurri, F., Lax, G. (2003). Pre-computing Approximate Hierarchical Range Queries in a Tree-Like Histogram. In: Kambayashi, Y., Mohania, M., Wöß, W. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2003. Lecture Notes in Computer Science, vol 2737. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45228-7_35
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DOI: https://doi.org/10.1007/978-3-540-45228-7_35
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