Space Efficiency in Synopsis Construction Algorithms

Histograms and Wavelet synopses have been found to be useful in query optimization, approximate query answering and mining. Over the last few years several good synopsis algorithms have been proposed. These have mostly focused on the running time of the synopsis constructions, optimum or approximate, vis-a-vis their quality. However the space complexity of synopsis construction algorithms has not been investigated as thoroughly. Many of the optimum synopsis construction algorithms (as well as few of the approximate ones) are expensive in space. In this paper, we propose a general technique that reduces space complexity. We show that the notion of “working space” proposed in these contexts is redundant. We believe that our algorithm also generalizes to a broader range of dynamic programs beyond synopsis construction. Our modifications can be easily adapted to existing algorithms. We demonstrate the performance benefits through experiments on real-life and synthetic data.