An Optimizing Query Processor with an Efficient Caching Mechanism for Distributed Databases

This paper provides an efficient way of querying among many distributed and heterogeneous data sources. We describe a database optimization framework that supports data and computation reuse, query scheduling and caching mechanism to speed up the evaluation of multiquery workload. The Caching query result is stored as an eXtensible Markup Language (XML) document. An XML oriented common data model and an XML Parser (XP) accept the SQL statement, which consists of selection constructs to impose constraints, project construct and also to update the database distributed. It also maintains the historical database to store the historical data. Using this optimized query processor and XML cache could simply fasten the query processing. The experimental results show that execution time is optimized and query cost is reduced