Data Warehouse Query Processing and Optimization Architecture

Data warehouse query processing must satisfy different requirements such as: simple/complex front-end ad hoc query, query used in the applications including data mining applications, query used to obtain information from metadata containing structured, unstructured and semi-structured data such as XML (eXtended Markup Language) documents. In this paper, we will explain several robust algorithms based on heuristic rules and methods to satisfy major changing requirements of data warehouse text-based query processing and optimization. These algorithms can be used in both distributed and centralized systems. Making query processing more robust and flexible will increase its complexity. We will demonstrate how to increase flexibility while minimizing complexity. 1.0 Introduction and Statement of

[1]  Ali Bahrami,et al.  Object Oriented Systems Development , 1998 .

[2]  Harris M. Burte,et al.  Unified life cycle engineering , 1987 .

[3]  Ophir Frieder,et al.  IIT Intranet Mediator: bringing data together on a corporate intranet , 2002 .

[4]  J. Ostling,et al.  Steps to successful data warehousing for Telehealth/Telemedicine , 2001, Proceedings 2001 Symposium on Applications and the Internet Workshops (Cat. No.01PR0945).

[5]  Alin Deutsch,et al.  XML-QL: A Query Language for XML , 1998 .

[6]  Jian Yang,et al.  Tackling the challenges of materialized view design in data warehousing environment , 1997, Proceedings Seventh International Workshop on Research Issues in Data Engineering. High Performance Database Management for Large-Scale Applications.

[7]  Hassan Pournaghshband,et al.  A Practical Approach to the Evaluation and Selection of CASE Tools , 2003, Software Engineering Research and Practice.