An Efficient I-MINE Algorithm for Materialized Views in a Data Warehouse Environment

The ability to afford decision makers with both accurate and timely consolidated information as well as rapid query response times is the fundamental requirement for the success of a Data Warehouse. Selecting views to materialize for the purpose of supporting the decision making efficiently is one of the most significant decisions in designing Data Warehouse. Selecting a set of derived views to materialize which minimizes the sum of total query response time & maintenance of the selected views is defined as view selection problem. Therefore, to select an appropriate set of a view is the major target that diminishes the entire query response time and also maintains the selected views. Selecting a suitable set of views that minimizes the total cost associated with the materialized views is the key objective of data warehousing. However, these views have maintenance cost, so materialization of all views is not possible. In this paper we are taking into consideration of query frequency, query processing cost and space requirement. In order to find the frequent queries, we make use of I-mine mining techniques from which the frequently user accessible queries will be generated. Then, an appropriate set of views can be selected to materialize by minimizing the total query response time and/or the storage space along with maximizing the query frequency. These can be utilized by the users to obtain the quicker results once a set of views is materialized for the data warehouse.

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