Paper Info
Title
An online approximate aggregation query processing method based on Hadoop
Abstract
This paper proposed a Hadoop-based iterative sampling approximate aggregation query processing method. According to the user desire precision and the first sample data, we could compute the sample size to meet the user desired precision. In order to avoid the effects of data bias, this paper proposed a “layered sampling” method to ensure that the approximate aggregation result is statistically meaningful.
Year
DOI
Venue
2016
10.1109/CSCWD.2016.7565974
2016 IEEE 20th International Conference on Computer Supported Cooperative Work in Design (CSCWD)
Keywords
Field
DocType
Online Aggregation,Iteration,Sampling,Query Processing,Hadoop
Query optimization,Data mining,Algorithm design,Computer science,Iterative method,Theoretical computer science,Sampling (statistics),Online aggregation,Distributed database,Cluster analysis,Sample size determination
Conference
ISBN
Citations 
PageRank 
978-1-5090-1916-8
2
0.37
References 
Authors
6
5
Name
Order
Citations
PageRank
Zhiqiang Zhang116223.92
Jianghua Hu220.71
Xiaoqin Xie31810.36
Haiwei Pan45221.31
Xiaoning Feng5194.78