Performance Tuning of Queries in Distributed System using Secure Materialized View Approach

Data warehouse is technique to collect and process data from heterogenous, distributed repository in distinct manner so that knowledge can extract from it's this information are stored in autonomous system there must be some defined way to access it. To access this information we must consider the time and space complexity as data warehouse include historical data that means data from decades so there must be some efficient way to access it. To enhance query performance different approaches are there like hybrid integration system is one of the alternative where most frequent used data are stored in intermediate table i.e. the space from where distributed system can access data commonly, query optimized techniques, implementation of appropriate data type, minimal time query complexity which indirectly effect to accelerate performance of query. We are focused on materialized view that is the provision where you can store the most recent data which extracted for commonly used query in avg transaction into a specialized space or we say MV table so that later on when query fire it will map with table query and resultant data will be extracted. Ultimately we are trying to reduce access time of query. As rather than going to base table every time it will search in MV table and return to user it reduce the access time of complex operation like merge, join and aggregation.