Extendible arrays for statistical databases and OLAP applications
Doron Rotem, Jianmin Zhao · 2002
Online analytical processing (OLAP) is becoming increasingly important as today's organizations frequently make business decisions based on statistical analysis of their enterprise data. This data is multidimensional and is derived from transactional data using various levels of aggregation. As the business model changes frequently, the multidimensional arrays must be extended in terms of the value ranges of each dimension and even new dimensions. We propose new methods to deal with disk resident extendible arrays. A new index data structure for keeping track of the extensions is introduced, and a performance analysis is conducted for array extension and retrievals.