Review on Fragmentation in Distributed Database Environment

Abstract

In Traditional environments, there are many advantages of distributed data warehouses. Distributed processing is the efficient way to increase efficiency of data. But the efficiency of query processing is a critical issue in data warehousing system, as decision support applications require minimum response times to answer complex, ad-hoc queries having aggregations, multi-ways joins overvast repositories of data. To achieve this, the fragmentation of data warehouse is the best to reduce the query execution time. The execution time reduces when queries runs over smaller datasets. The system performance is increased by allowing data to be spread across datamarts. So, it is very important to manage an appropriate methodology for data fragmentation and fragment allocation. Here focus is on the distributed data warehouses, which combines the known predicate construction techniques with a clustering method to fragment data warehouse relations by using the data mining-based horizontal fragmentation methodology for a relational DDW environment. DW decentralization gives the better performance; in the fragments are allocated to the corresponding site according to their frequency.