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Cluster Computing

, Volume 22, Supplement 1, pp 2471–2484 | Cite as

An iterative sampling method for online aggregation

  • Zhiqiang ZhangEmail author
  • Jianghua Hu
  • Xiaoqin Xie
  • Haiwei Pan
  • Xiaoning Feng
Article
  • 308 Downloads

Abstract

Online aggregation (OLA) makes it possible to save cost by taking acceptable approximate early answers. Compared to the precise results, computing the approximate ones are more cost effective, especially for large-scale datasets. The user can terminate the processing at any time, when he/she is satisfied with the quality of the result. And the performance of OLA relies on the sampling approach and estimation model. But in large scale distributed computing environment, how to realize OLA more efficiently is a challenging problem. In this paper, we consider the problem of providing OLA in the distributed computing environment and propose a Hadoop-based iterative sampling method for online aggregation. The desired precision of the user can be met by two iteration samplings. To avoid the effects of data bias, we propose a “layered sampling” method to ensure that the approximate aggregation result is statistically meaningful. The experimental results showed the “layered sampling” method considers not only the time efficiency, but also the usage of computing and storage resources of Hadoop.

Keywords

Online aggregation Iteration Sampling Query processing Hadoop 

Notes

Acknowledgements

This work is supported by the National Natural Science Foundation of China (No. 61672181, 61202090, 61272184), Natural Science Foundation of Heilongjiang Province (No. LC2017029, F2016005), the Science and Technology Innovation Talents Special Fund of Harbin (Nos. 2016RAXXJ 036, 2015RQQXJ067), the opening found of Key Laboratory of Machine Perception (Ministry of Education), Peking University (K-2016-02).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.School of InformationZhejiang University of Finance & EconomicsHangzhouChina
  2. 2.College of Computer Science and TechnologyHarbin Engineering UniversityHarbinChina

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