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Influence of YARN Schedulers on Power Consumption and Processing Time for Various Big Data Benchmarks
Abstract
Climate change caused by human activities can influence the lives of everybody onthe planet. The environmental concerns must be taken into consideration by all fields of studyincludingICT. Green Computing aims to reduce negative effects of IT on the environment while,at the same time, maintaining all of the possible benefits it provides. Several Big Data platformslike Apache Spark orYARNhave become widely used in analytics and High-PerformanceComputing systems due to the reliability and usability of Map Reduce implementations. Theauthors research the power consumption and energy efficiency of HadoopYARNschedulers usingApache Spark under three different workloads. The test cases include: sorting large binary files,counting unique words in large text files and processing satellite imagery from the Sentinel-2mission. The presented results show small (2%–11%) but distinct differences in the powerconsumption ofFIFOandFAIRschedulers
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- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.17466/tq2018/22.4/c
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Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
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TASK Quarterly
no. 22,
pages 303 - 312,
ISSN: 1428-6394 - Language:
- English
- Publication year:
- 2019
- Bibliographic description:
- Drypczewski K., Proficz J., Stepnowski A.: Influence of YARN Schedulers on Power Consumption and Processing Time for Various Big Data Benchmarks// TASK Quarterly -Vol. 22,iss. 4 (2019), s.303-312
- DOI:
- Digital Object Identifier (open in new tab) 10.17466/tq2018/22.4/c
- Sources of funding:
-
- Free publication
- Verified by:
- Gdańsk University of Technology
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