A METHOD FOR MULTI-DIMENSIONAL HISTOGRAMS USING A MINIMAL SKEW COVER IN A SPACE PARTITIONING TREE AND RECORDING MEDIUM STORING PROGRAM FOR EXECUTING THE SAME

摘要

The present disclosure relates to a multi-dimensional histogram method using a minimal data-skew cover in a space-partitioning tree, which is used to estimate the selectivity of queries, that is, the sizes of query results, and a recording medium storing a program for executing the multi-dimensional histogram method. In the multi-dimensional histogram method, a Database (DB) system receives information required to generate a histogram from an outside of the DB system, and then constructs a space-partitioning tree based on the information required to generate a histogram. The DB system constructs a multi-dimensional histogram based on a minimal data-skew cover in the space-partitioning tree. When the DB system receives a query from the outside, the DB system calculates the estimate of the selectivity for the query by using the multi-dimensional histogram. Further, the present disclosure includes a recording medium storing a program for executing the multi-dimensional histogram method.