On Analyzing the Errors in a Selectivity Estimation Method Using a Multidimensional File Structure Sang-Wook Kim*, Whan-Kyu Whang*, and Kyu-Young Whang”

In this paper, we discuss the errors in selectivity estimation using the multilevel rid file(MLGF), a multidimensional file structure. We Prst analyze the cause of the estimation errors, and then investigate five factors affecting the accuracy of estimation: (1) the data distrzbution in a region, (2) the number of records stored in the MLGF, (3) the page size, (4) the query region size, and (5) the level of the MLGF directory. Next, we present through extensive experiments the tendency of estimation errors when the value for each factor chany. The results show that the errors decrease when (1) t e dtstrtbukon of records in a rekon becomes closer to ‘the uniform one, (21 the number of reckds in the MLGF increases, (3) the pa e size decreases, (4) the query region size increases, and (5P the level of the MLGF directory containing data distribution information becomes lower.- We dejiny the granule ratio, ‘the core formula renresentinq the basic relationshiv between the estimation ekor and vthe above five factors, ’ and finallu examine the change of estimation errors ’ in relation ‘with ” the change of the granule ratio throu h experiments. 7’he results indicate that with a specific va Hue for the granule ratio, errors tend to be similar regardless of different values for the five factors. 1