Abstract

Global query management provides the ability to combine data from different local databases in a single retrieval operation. The necessity for global query management arises in an open, heterogeneous multidatabase system, since autonomy and heterogeneity of component databases have given rise to a number of new major issues regarding the global query optimization strategy and context mediation including data conversion and query translation. For instance, some local DBMSs never support semijoin operator which has been proposed in order that data transmission between sites could be reduced. In this regard, the global query optimization strategies developed for homogeneous distributed database systems make extensive use of semijoins which are not attractive in the multidatabase context since this may increase the local processing time. Moreover, these do not consider the cost incurred as a result of data conversion and query translation. Our basic principle to get a high performance is that we decompose a global query to the finest level of subqueries in order to explore all possible execution plans. This reduces the overall processing cost in an heterogeneous distributed database system because subqueries that are sent to the local databases have to be converted. The lesser number of subqueries implies less conversion cost.

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