by Yannis Theodoridis, Timos Sellis
ftp://ftp.dbnet.ece.ntua.gr/pub/papers/reports/1995/tr9503.ps.Z
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Abstract:
In this paper we report on our research in the field of multi-dimensional data structures and specifically on the development of powerful analytical models that predict the performance of a data structure. We present a model that estimates the performance of R-trees (and variants based on the original method) when a window query needs to be answered. The proposed formula that estimates the number of disk accesses is a function of data properties only, namely, the amount of data and their density in the work space. Selectivity of a query is also estimated by transforming the analytical formula. Our experimental results show that the proposed analytical model is very accurate, the relative error being usually below 5%, for various distributions and sizes of input datasets.
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