Name
Abstract | ||
|---|---|---|
What-if analysis is an important type of DSS analysis processing procedure. It analyzes hypothetical scenarios based on historical data. The data cube view must be updated when the what-if condition is changed. Since source data must be kept in order to compute the new aggregate value when new tuples are inserted or deleted, in what-if analysis, incrementally computing a data cube for holistic aggregation functions is a difficult problem. In this paper, we adopt delta cube strategy and work area technique to incrementally compute data cube for MEDIAN function. The size of work area has important influence on the efficiency of the incremental computing. This paper optimizes the size of work area based on the number and the cardinality of dimension attributes of the cuboid. Performance study shows that our algorithms are effective over large databases. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-00672-2_23 | APWeb/WAIM |
Keywords | Field | DocType |
dss analysis processing procedure,work area,important influence,historical data,what-if analysis,median cubes,source data,delta cube strategy,data cube view,work area technique,incremental computation,data cube,cube | Source data,Tuple,Computer science,Algorithm,Cardinality,Theoretical computer science,Cuboid,Klee–Minty cube,Data cube,Computation,Cube | Conference |
Volume | ISSN | Citations |
5446 | 0302-9743 | 1 |
PageRank | References | Authors |
0.40 | 15 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yanqin Xiao | 1 | 4 | 1.51 |
| Yansong Zhang | 2 | 26 | 9.75 |
| Shan Wang | 3 | 594 | 71.65 |
| Hong Chen | 4 | 99 | 23.20 |