Range Sum Queries in Dynamic OLAP Data Cubes

The data cube is frequently adopted to implement On-Line Analytical Processing (OLAP) and provides aggregate information to support the analysis of contents of databases and data warehouses. Range-sum queries require accessing large data cubes and adding the contents of massive cells immediately. Techniques have thus been proposed to accelerate range-sum queries by applying pre-aggregated specified cells of data cubes. However, this faster response leads to higher update cost and possible need for extra memory space overhead to store these pre-aggregated values. To offer the best trade-off choice, this study presents a novel approach that considers both query cost and update cost to construct data cubes. In addition, we shall also construct a space-optimal high-dimensional data cube and propose a flexible and optimal framework, called the Flexible Data Cube (FDC) approach. The FDC method can support a model to select or integrate these pre-aggregation techniques for each dimension.