Efficient and Scalable Functional Dependency Discovery on Distributed Data-Parallel Platforms

Functional dependencies (FDs) play a very important role in many data management tasks such as schema normalization, data cleaning, and query optimization. Meanwhile, there are ever-increasing application demands for efficient FD discovery on large-scale datasets. Unfortunately, due to huge runtime...

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Vydané v:	IEEE transactions on parallel and distributed systems Ročník 30; číslo 12; s. 2663 - 2676
Hlavní autori:	Zhu, Guanghui, Wang, Qian, Tang, Qiwei, Gu, Rong, Yuan, Chunfeng, Huang, Yihua
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.12.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Adaptive sampling Algorithms Classification Data management Data processing data-parallel algorithms Datasets Dependence Distributed algorithms distributed computing Distributed databases Functional dependency discovery Optimization Query processing Remuneration Scalability Sorting algorithms Switches Switching
ISSN:	1045-9219, 1558-2183
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