Abstract
Scalability in multi-dimensional systems is addressed for analysis in Scientific and statistical databases (SSDB) and On-Line Analytical Processing (OLAP) applications. The Parallel and Scalable Infrastructure for Multidimensional Online analytical processing (PARSIMONY) system is described. Sparsity of data sets is handled by using chunks to store data as a sparse set using a Bit encoded sparse structure. Performance results for high dimensional data sets on a distributed memory parallel machine (IBM SP-2) show good speedup and scalability.
| Original language | English (US) |
|---|---|
| Pages | 102-111 |
| Number of pages | 10 |
| State | Published - Jan 1 1999 |
| Event | Proceedings of the 1999 11th International Conference on Scientific and Statistical Database Management (SSDBM'99) - Cleveland, OH, USA Duration: Jul 28 1999 → Jul 30 1999 |
Other
| Other | Proceedings of the 1999 11th International Conference on Scientific and Statistical Database Management (SSDBM'99) |
|---|---|
| City | Cleveland, OH, USA |
| Period | 7/28/99 → 7/30/99 |
ASJC Scopus subject areas
- Software
- Applied Mathematics
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Cite this
Goil, S., & Choudhary, A. N. (1999). Infrastructure for scalable parallel multidimensional analysis. 102-111. Paper presented at Proceedings of the 1999 11th International Conference on Scientific and Statistical Database Management (SSDBM'99), Cleveland, OH, USA, .