Multiple-Objective Compression of Data Cubes in Cooperative OLAP Environments

  • Authors:
  • Alfredo Cuzzocrea

  • Affiliations:
  • ICAR Inst. and DEIS Dept., University of Calabria, Cosenza, Italy I-87036

  • Venue:
  • ADBIS '08 Proceedings of the 12th East European conference on Advances in Databases and Information Systems
  • Year:
  • 2008

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Abstract

Traditional data cube compression techniques do not consider the yet relevant problem of compressing data cubes in the presence of multiple objectives rather than only one (e.g., a given space bound). Starting from next-generation OLAP scenarios where this problem makes sense, such as those drawn by cooperative OLAP environments, in this paper we fulfill this lack via (i) introducing and rigorously formalizing the novel multiple-objective data cube compression paradigm, and (ii) providing an effective solution to this problem by means of a greedy algorithm able to find a sub-optimal solution and, as a consequence, an "intermediate" data cube compressed representation that accommodates a large family of even different OLAP queries, which model the multiple requirements in our proposed framework. Finally, we complete our analytical contribution with a wide experimental analysis on benchmark data cubes.