COST BASED GRAPHICAL VERTICAL FRAGMENTATION IN RELATIONAL DATABASED

Abstract

In a distributed database environment, query processing heavily depends upon locality of the requested data at the query site. When relations are vertically fragmented, data locality can be improved significantly since the fragments can be replicated flexibly without replication incurring overwhelming update cost. Vertical partitioning clusters attributes of a relation to generate fragments suitable for subsequent allocation over a distributed platform. Partitioning is also important for centralized and web databases because data items that are mostly accessed together should reside in the same fragment. The target is to minimize the execution time of user applications. In this thesis we use graphical and heuristic approach for vertical fragmentation scheme for the DDBMS to allocate the fragments generated by the graphical approach. In our proposal where allocation is handled along with Fragmentation, Fragmentation will be done by using graphical approach and then using the cost model of heuristic approach, these fragments will be allocated. Input consists of a set of relations, together with information about the important transactions on the proposed database. It is not necessary to collect information about 100% of transactions. According to 80-20 rule [2], 20% of heavily used transactions account for the 80% of database activity. Hence we provide information about 20% of heavily used transaction.