NDLI: Parallel Aggregation Queries over Star Schema: A Hierarchical Encoding Scheme and Efficient Percentile Computing as a Case

Content Provider	IEEE Xplore Digital Library
Author	Xiongpai Qin Huiju Wang Xiaoyong Du Shan Wang
Copyright Year	2011
Abstract	Big data analysis is a main challenge we meet recently. Cloud computing is attracting more and more big data analysis applications, due to its well scalability and fault-tolerance. Some aggregation functions, like SUM, can be computed in parallel, because they satisfy distributive law of addition. Unfortunately, some of statistical functions are not naturally parallelizable. That means they do not satisfy distributive law of addition. In this paper, we focus on percentile computing problem. We proposed an iterative-style prediction-based parallel algorithm in a distributed system. Prediction is done through a sampling technique. Experiment results verify the efficiency of our algorithm.
Starting Page	329
Ending Page	334
File Size	408630
Page Count	6
File Format	PDF
ISBN	9781457703911
DOI	10.1109/ISPA.2011.34
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-26
Publisher Place	Korea (South)
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Histograms Percentile Query processing Prediction algorithms Encoding Iterative Indexes Hierarchical Encoding Convergence
Content Type	Text
Resource Type	Article

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Parallel Aggregation Queries over Star Schema: A Hierarchical Encoding Scheme and Efficient Percentile Computing as a Case