Approximate query processing based on wavelet transform

Approximate query processing has emerged as a cost-effective approach for dealing with the large database system. Recent work has demonstrated the effectiveness of the wavelet transform in reducing large amounts of data to compact set of wavelet coefficients. In this paper, we extend related works about approximate query processing using wavelet. Two algorithms about how to do union and difference operations directly in wavelet domain are presented. Also we propose an algorithm on the direct update of wavelet coefficients when the original database is changed. The experimental results have shown that the accuracy of using wavelet is better than that of random sampling to do union and difference operations. And when the update amount of data is not too much, the direct update of wavelet is almost as good as the optimal selected wavelet synopses.