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Selectivity Estimation over Multiple Data Streams using Micro-clustering

Sudhanshu Gupta, Deepak Garg

Selectivity estimation is an important task for query optimization. We propose a technique to perform range query estimation over multiple data streams using micro-clustering. The technique maintains cluster statistics in terms of micro-clusters and cosine series for all streams. These microclusters maintain data distribution information about the stream values using cosine coefficients. These cosine coefficients are used for estimating range queries. The estimation can be done over a range of data values spread over a number of streams.