Star Join Query Performance Under Space Limited Environment Using Transaction Sensitive Sliding Window Model
The data warehouse is an integrated collection of various data sources. It uses indexing technique to reduce the cost of processing complex queries in data warehouse. Therefore, the automatic index selection plays vital role in database field. The classical data mining techniques are used to find choice of configuration indexes. However, storage limitation is obstacle for processing of Star Join Queries. So, there is need for developing an approach that process Star Join Queries under storage limitation environment. Maximal Frequent pattern mining technique is applied to transaction sensitive sliding window. This paper describes an approach for Star Join Query Performance under Storage Limited Environment Using Sliding Window Model. The results obtained shows that the approach generates configuration indexes to enhance the performance using space limited environment.
Keywords- Online Analytical Processing (OLAP), Join Index, Maximal Frequent Pattern, Sliding Window