Data Warehouse Striping: Improved Query Response Time

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 [Bernardino00], 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 scaleup can be obtained. A new technique to process subqueries is also proposed and experimentally evaluated.

[1]  Johann-Christoph Freytag,et al.  AQuES: an agent-based query evaluation system , 1997, Proceedings of CoopIS 97: 2nd IFCIS Conference on Cooperative Information Systems.

[2]  Ramez Elmasri,et al.  Fundamentals of Database Systems , 1989 .

[3]  Jorge Bernardino,et al.  A New Technique to Speedup Queries in Data Warehousing , 2000, ADBIS-DASFAA Symposium.

[4]  Dan Suciu,et al.  Distributed query evaluation on semistructured data , 2002, TODS.

[5]  Hongjun Lu,et al.  Query Processing in Parallel Relational Database Systems , 1994 .

[6]  Jorge Bernardino,et al.  Approximate Query Answering Using Data Warehouse Striping , 2002, Journal of Intelligent Information Systems.

[7]  Jorge Bernardino,et al.  Data warehousing and OLAP: improving query performance using distributed computing , 2000 .

[8]  Jorge Bernardino,et al.  DWS-AQA: a cost effective approach for very large data warehouses , 2002, Proceedings International Database Engineering and Applications Symposium.

[9]  Surajit Chaudhuri,et al.  An overview of data warehousing and OLAP technology , 1997, SGMD.

[10]  Zhengxin Chen.  Computational intelligence for decision support , 1999 .

[11]  Surajit Chaudhuri,et al.  Automated Selection of Materialized Views and Indexes in SQL Databases , 2000, VLDB.

[12]  Jayanta Banerjee,et al.  Oracle8i Index-Organized Table and Its Application to New Domains , 2000, VLDB.

[13]  Alejandro P. Buchmann,et al.  Encoded bitmap indexing for data warehouses , 1998, Proceedings 14th International Conference on Data Engineering.

[14]  David J. DeWitt,et al.  Parallel database systems: the future of high performance database systems , 1992, CACM.

[15]  Jennifer Widom,et al.  A First Course in Database Systems , 1997 .