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Load Shedding using Window Aggregation Queries on Data Streams
2012
International Journal of Computer Applications
The processes of extracting knowledge structures for continuous, rapid records are known as the Data Stream Mining. The main issue in stream mining is handling streams of elements delivered rapidly which makes it infeasible to store everything in active storage. To overcome this problem of handling voluminous data we exposed a novel load shedding system using window based aggregate function of the data stream in which we accept those tuples in the stream that meet a criterion. Accepted tuples
doi:10.5120/8598-2362
fatcat:ivcneqj7ezbbpkhe6gh7vdhhyi