NDLI: Optimal Resource Provisioning Approach based on Cost Modeling for Spark Applications in Public Clouds

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Optimal Resource Provisioning Approach based on Cost Modeling for Spark Applications in Public Clouds

Content Provider	ACM Digital Library
Author	Ruan, Jianfei Dong, Bo Zheng, Qinghua
Abstract	Efficient resource provisioning is required when running Spark applications in public clouds. However, how to optimize resource provisioning to minimize the time and/or monetary cost for a specific application remains an intractable problem since resource provisioning may differ from application to application and even be affected by the amount of input data. Existing resource settings heavily rely on random selection or previous deployer experience, frequently leading to low-quality resource provisioning. Therefore, there is an urgent need to propose an approach towards optimal resource provisioning for Spark applications in public clouds. This is a PhD proposal, where an approach based on time and monetary cost modeling is presented for cloud resource provisioning optimization under two typical constrained scenarios. The approach systematically drives resource provisioning for a specific Spark application, which may save a significant amount of time and money, compared to randomly selected settings.
Starting Page	1
Ending Page	4
Page Count	4
File Format	PDF
ISBN	9781450337281
DOI	10.1145/2843966.2843972
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-12-07
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Resource provisioning Public cloud Cost model Spark Optimization
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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