Extending the CMHD Compact Data Structure to Compute Aggregations over Data Warehouses

Abstract

Compact data structures are data structures that allow compacting data without losing the ability of querying them in their compact form. We present algorithms to extend the functionality of the compact data structure CMHD (Compact representation of Multidimensional data on Hierarchical Domains), which allows the computation of aggregate queries with SUM function on multidimensional matrices. We implement the rest of aggregate functions, i.e., functions MIN , MAX , COUNT and AVG . We use the CMHD over Data Warehouses (DWs), that are collection of data organized to support the decision-making process. The improvement of efficiency of query processing in DWs is a very important issue. Therefore, various efforts have been made in that direction, such as materialization of views, use of indexes, among others. We show through experimentation over DWs with synthetic data, that by using a compact representation of DWs, we can achieve better performance in processing aggregate queries.