Approaches for Query Optimization using Materialized Views in Dynamic Distributed Environment: A Review

摘要

Data warehouse in present scenario contains data from multiple heterogeneous data source. Data sources are dynamic in nature as information schema are continuously evolving and changing. In loosely coupled environment data sources are independent hence updates from various data sources are synchronous. Frequency of addition, deletion and updation operations on based relation have increased because of dynamic nature of data source. Analyzing query response time in distributed heterogeneous environment consists of communication part to establish a connection with heterogeneous data source and data transmission part to transfer data across distributed sites. Selection and maintenance of views is vital task in order to provide maximum efficiency by cutting down query processing and maintenance cost. Integrating data from distributed dynamic environment is big challenge. Querying data from heterogeneous sources is an important research issues in distributed environment. Materialized Views can be used to precompute and store results in data warehouse. Data warehouses, decision support applications and mobile computing environment widely use materialized views for reducing query response time. In distributed environment materialized views are replicated at multiple sites and concurrent updated are performed at multiple sites whenever underlying base relations are modified. Various conflict resolution methods are employed while replicating views at distributed sites. View maintenance cost is enlarged if all the views are materialized in distributed environment at multiple sites but it gives best performance for user queries. Using materializing views in data warehouse includes challenge of identification of which views to materialize, performance consideration, view adaption, view maintenance. We present various approaches for query optimization on materialized views in distributed dynamic environment proposed by researchers. In this paper comparative studies on research work of various authors have been surveyed based on important query optimization parameters.