DATA WAREHOUSE STRIPING: IMPROVED QUERY RESPONSE TIME

摘要

The increasing use of decision support systems led to an explosion in the amount of business information that must be managed by the data warehouses. Therefore, data warehouses must have efficient Online Analytical Processing (OLAP) that provides tools to satisfy the information needs of business managers, helping them to make faster and more effective decisions. Improving query response time in such an environment is very difficult and can only be achieved by a combination of different approaches, in particular the use of materialized views, advanced indexes and parallel query processing. However, achieving quick response times with complex OLAP queries is still an open issue. This paper is an extension of our previous work (Bernardino et al. 2000), where we proposed a novel approach to this problem. In this paper, we analyse the scalability performance of data warehouse striping system (DWS) system using different environments. DWS is experimentally evaluated with Oracle 8 as back-end DBMS, for the most typical OLAP operations using different types of queries and it is shown that an optimal speedup and scale-up can be obtained. A new technique to process subqueries is also proposed and experimentally evaluated.