Materialized view evolution support in data warehouse environment

As a sufficiently abstract level, the data in the data warehouse can be seen as a set of materialized views, where the base data resides at the information sources. These materialized views are designed based on the users' requirements (e.g., frequently asked queries). However, a data warehouse is a dynamic environment, i.e., when user query requirement changes, the existing materialized views should evolve to meet the new requirement. These changes will demand schema changes at the warehouse and should be handled with as little disruption or modification to other components of the warehousing system as possible. We propose a framework to determine if the existing materialized views will be affected by the requirement changes, and how they are affected. Algorithms are proposed to deal with the situation when a new query is added in. The aim of the algorithms is to efficiently get the new materialized views by analysing the relationships among queries using MVPP, a specification for a query processing plan.