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Type of publication:Article
Entered by:
TitleStatistical Structures for Internet-Scale Data Management
Bibtex cite IDRACTI-RU1-2009-88
Journal Statistical Structures for Internet-Scale Data Management
Year published 2009
Keywords Distributed information systems,Data management over peer-to-peer data networks,Distributed data synopses
Efficient query processing in traditional database management systems relies on statistics on base data. For centralized systems, there is a rich body of research results on such statistics, from simple aggregates to more elaborate synopses such as sketches and histograms. For Internet-scale distributed systems, on the other hand, statisticsmanagement still poses major challenges. With the work in this paper we aim to endow peer-to-peer data management over structured overlays with the power associated with such statistical information, with emphasis on meeting the scalability challenge. To this end, we first contribute efficient, accurate, and decentralized algorithms that can compute key aggregates such as Count, CountDistinct, Sum, and Average. We show how to construct several types of histograms, such as simple Equi-Width, Average Shifted Equi-Width, and Equi-Depth histograms. We present a full-fledged open-source implementation of these tools for distributed statistical synopses, and report on a comprehensive experimental performance evaluation, evaluating our contributions in terms of efficiency, accuracy, and scalability.
Ntarmos, Nikos
Triantafillou, Peter
Weikum, Gerhard
fulltext.pdf (main file)
Publication ID755