A Dynamic Warehouse Design Based on Simulated Annealing Algorithm

Abstract

The amount of information available to large-scale enterprises is growing rapidly. New information is being generated continuously by operational systems. Decision support functions in a warehouse such as On-Line Analytical Processing (OLAP), involving hundreds or thousands of complex aggregate queries over large volumes of data. A data warehouse can be seen as a set of materialized views defined over some relations. In this paper, when a query is posed to answer, here will be used the suitable materialized views with tables in order to produce best views and tables which will be used for constructing any new query. In order to achieve and implement the Dynamic Warehouse Design,  creating three complex OLAP queries with join and aggregation operation, creating views and updating them by using windows task scheduler and batch files based on base table updating, creating lattice of views by using multiple view processing plan operation, simulated annealing(SA) algorithm was developed and introduced for query re writing by replacing dynamically suitable views instead of tables and introducing best tables and views that will used by user to construct the suitable query. The main goals of this work are to show the utilization of derived data such as materialized views for run time re optimization of aggregate queries (quick response time), effective, transparency and accuracy are important factors in the success of any data warehouse.