Range aggregate queries find frequent application in data ana- lytics. In many use cases, approximate results are preferred over accurate results if they can be computed rapidly and satisfy ap- proximation guarantees. Inspired by a recent indexing approach, we provide means of representing a discrete point dataset by continuous functions that can then serve as compact index struc- tures. More specifically, we develop a polynomial-based indexing approach, called PolyFit, for processing approximate range ag- gregate queries. PolyFit is capable of supporting multiple types of range aggregate queries, including COUNT, SUM, MIN and MAX aggregates, with guaranteed absolute and relative error bounds. Experimental results show that PolyFit is faster and more accurate and compact than existing learned index structures.
|Title of host publication
|Advances in Database Technology - EDBT 2021 - 24th International Conference on Extending Database Technology, Proceedings
|Yannis Velegrakis, Demetris Zeinalipour, Panos K. Chrysanthis, Francesco Guerra
|Place of Publication
|Number of pages
|Published - 23 Mar 2021
|Proceedings of the International Conference on Extending Database Technology