MOOLAP: Towards multi-objective OLAP

Shyam Antony, Ping Wu, Divyakant Agrawal, Amr El Abbadi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)


Aggregation is among the core functionalities of OLAP systems. Frequently, such queries are issued in decision support systems to identify interesting groups of data. When more than one aggregation function is involved and the notion of interest is not clearly defined, skyline queries provide a robust mechanism to capture the potentially interesting points where (i) users do not need to specify a ranking function and (ii) the result is independent of the dimension scales. To provide better exploration functionalities in OLAP systems, we propose to use skyline queries over aggregated data to identify the most interesting groups. Since aggregation functions have to be ad-hoc to cover a wide variety of user interests, the skyline over the aggregates has to be computed on the fly. Hence any algorithm to compute such a skyline must be fast and be able to progressively produce the result set with potential skyline groups being produced as early as possible. We explore a family of algorithms which try to consume only as many data records as are necessary to compute the skyline and design an optimal algorithm. We further refine the algorithm by taking into account systems issues such as disk behavior which are often ignored but have strong impact on real system performance. Experimental results validate the performance and progressive benefits of our algorithm.

Original languageEnglish
Title of host publicationProceedings of the 2008 IEEE 24th International Conference on Data Engineering, ICDE'08
Number of pages3
Publication statusPublished - 1 Oct 2008
Event2008 IEEE 24th International Conference on Data Engineering, ICDE'08 - Cancun, Mexico
Duration: 7 Apr 200812 Apr 2008

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627


Other2008 IEEE 24th International Conference on Data Engineering, ICDE'08


ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems

Cite this

Antony, S., Wu, P., Agrawal, D., & El Abbadi, A. (2008). MOOLAP: Towards multi-objective OLAP. In Proceedings of the 2008 IEEE 24th International Conference on Data Engineering, ICDE'08 (pp. 1394-1396). [4497567] (Proceedings - International Conference on Data Engineering).