Subscribe

Issue No.03 - March (2012 vol.24)

pp: 492-505

Eric Lo , Hong Kong Polytechnic University, Hong Kong

Man Lung Yiu , Hong Kong Polytechnic University, Hong Kong

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2010.253

ABSTRACT

Data cube is a key element in supporting fast OLAP. Traditionally, an aggregate function is used to compute the values in data cubes. In this paper, we extend the notion of data cubes with a new perspective. Instead of using an aggregate function, we propose to 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: 1) the skyline operation is computational intensive, 2) the skyline operation is holistic, and 3) a group-by skyline cube contains both grouping and skyline dimensions, rendering it infeasible to precompute all cuboids in advance. This paper gives details on how to store, materialize, and query such cubes.

INDEX TERMS

Query processing; data warehouse and repository.

CITATION

Eric Lo, Man Lung Yiu, "Measuring the Sky: On Computing Data Cubes via Skylining the Measures",

*IEEE Transactions on Knowledge & Data Engineering*, vol.24, no. 3, pp. 492-505, March 2012, doi:10.1109/TKDE.2010.253REFERENCES