Sciweavers

Share
VLDB
1999
ACM

Aggregation Algorithms for Very Large Compressed Data Warehouses

8 years 11 months ago
Aggregation Algorithms for Very Large Compressed Data Warehouses
Many efficient algorithms to compute multidimensional aggregation and Cube for relational OLAP have been developed. However, to our knowledge, there is nothing to date in the literature on aggregation algorithms on compressed data warehouses for multidimensional OLAP. This paper presents a set of aggregation algorithms on very large compressed data warehouses for multidimensional OLAP. These algorithms operate directly on compressed datasets without the need to first decompress them. They are applicable to data warehouses that are compressed using variety of data compression methods. The algorithms have different performance behavior as a function of dataset parameters, sizes of outputs and main memory availability. The analysis and experimental results show that the algorithms have better performance than the traditional aggregation algorithms.
Jianzhong Li, Doron Rotem, Jaideep Srivastava
Added 05 Aug 2010
Updated 05 Aug 2010
Type Conference
Year 1999
Where VLDB
Authors Jianzhong Li, Doron Rotem, Jaideep Srivastava
Comments (0)
books