A Resource-Aware Deep Cost Model for Big Data Query Processing-Reference-Cited by-同舟云学术

A Resource-Aware Deep Cost Model for Big Data Query Processing

Published:2022-05 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 38th International Conference on Data Engineering (ICDE)
language:
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Author:

Li Yan¹,Wang Liwei¹,Wang Sheng¹,Sun Yuan²,Peng Zhiyong¹

Affiliation:

1. School of Computer Science, Wuhan University

2. School of Computing and Information Systems, The University of Melbourne

Funder

National Key Research and Development Project of China

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9835153/9835154/09835426.pdf?arnumber=9835426

Reference44 articles.

1. Long Short-Term Memory

2. Distributed representations of words and phrases and their compositionality;mikolov;NIPS,2013

3. Don't cry over spilled records: Memory elasticity of data-parallel applications and its application to cluster scheduling;iorgulescu;USENIX-ATC 2017,2017

4. PerfOrator

5. Cherrypick: Adaptively unearthing the best cloud configurations for big data analytics;alipourfard;NSDI,2017

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