Description

Data cube is a key element in supporting fast OLAP. Traditionally, an aggregate function is used to compute the values in data cubes. The notion of data cubes with a new perspective. Instead of using an aggregate function and build data cubes using the skyline operation as the “aggregate function”. Data cubes built in this way are called “group-by skyline cubes” and can support a variety of analytical tasks. Nevertheless, there are several challenges in implementing group-by skyline cubes in data warehouses: The skyline operation is computational intensive. The skyline operation is holistic. A group-by skyline cube contains both grouping and skyline dimensions, rendering it infeasible to pre-compute all cuboids in advance. This paper gives details on how to store, materialize, and query such cubes. Skyline operation as an “aggregate function” in data cubes and the notion of group-by skyline cubes is a completely new model.