Optimization Technique for Multi-Join Operation in Active Data Warehouse

In current scenario of fast changing data content in most dynamic heterogeneous application, data format transformation and data updates needs to be handled in traditional data ware housing. Many researches have been made under active data warehousing which keep the latest updates of more dynamic large multi-format data warehouses. Previous work presented a mesh join operation algorithm a frequently encountered operation which join a fast stream of source updates with a disk-based relation under the constraint of limited memory. The access cost of two join inputs is done by relying on fast sequential scans of disk-based relation and shared I/O cost of accessing disk-based relation across multiple tuples of source stream updates. Since the source streams receives. It develop a systematic cost enabled tuning of MESHJOIN for maximizing throughput under a specific memory budget, or minimizing memory consumption for a specific throughput. Since source streams have more number of relations in different directions, the previous work does not support multi-way joins To overcome the issues obtained from the previous work, here we are going to present a new technique optimization scheme for multiple relations of joins being generated by streams from different direction in active data warehousing retrieval of data based on multiple queries. Here, multiple on-line aggregations play a major role in the efficient and more precise user query data extraction. It evolves an optimizationtechnique to have a more cohesive multi-relation joins of the stream tuples. Experimental simulations are carried out to evaluate the performance of proposed optimization technique with both synthetic and real data sets in terms of Execution time, and operational overhead being used to get optimal threshold for multi-relational joinsgeneration.