Novel Algorithms for Materialized View Selection and Preservation in Data Warehousing Environment
Gaurav P. Ambatkar, Pratyoosh Rai, Tripti Arjariya · 2014
Data warehousing and online analytical processing represents some of the most up-to-date trends in computing environments to large scale processing and analysis of data. The theory attempted to address the range of problems associated with this flow, mainly the high costs associated with it. In the absence of a data warehousing architecture, an enormous amount of redundancy was required to maintain multiple decision support environments. In larger corporations it was typical for several decision support environments to control independently. Though each environment served different users, they often essential much of the same stored data. The process of gathering, cleaning and integrate data from various source, generally from long-term accessible operational systems. Data warehousing technology is becoming necessary for the efficient business policy formulation and execution. For the success of any data warehouse accurate and timely consolidate information along with immediate and efficient query response times is the basic fundamental constraint.The materialization of all views is nearly impossible because of the materialized view storage space and maintenance cost restriction thus proper materialized views selection is one of the intelligent decision in designing a data warehouse to get best possible efficiency. In this paper, we represent a structure for selecting best materialized view so as to achieve the effective combination of good response time, low processing cost and low maintenance cost in a particular storage space restriction. The framework implementation parameters include frequency cost, storage cost and processing cost. The structure select the best cost successful