OpERA: Opportunistic and efficient resource allocation in hadoop YARN by harnessing idle resources

Yi Yao, Han Gao, Jiayin Wang, Ningfang Mi, Bo Sheng

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Efficiently managing resources and improving throughput in a large-scale cluster has become a crucial problem with the explosion of data processing applications in recent years. Hadoop YARN and Mesos, as two universal resource management platforms, have been widely adopted in the commodity cluster for co-deploying multiple data processing frameworks, such as Hadoop MapReduce and Apache Spark. However, in the existing resource management, a certain amount of resources are exclusively allocated to a running task and can only be re-assigned after that task is completed. This exclusive mode unfortunately leads to a potential problem that may underutilize the cluster resources and degrade system performance. To address this issue, we propose a novel opportunistic and efficient resource allocation approach, named OpERA, which breaks the barriers among the encapsulated resource containers by leveraging the knowledge of actual runtime resource utilizations to re-assign opportunistic available resources to the pending tasks. We implement and evaluate OpERA in Hadoop YARN v2.5. Our experimental results show that OpERA significantly reduces the average job execution time and increases the resource (CPU and memory) utilizations.

Original languageEnglish
Title of host publication2016 25th International Conference on Computer Communications and Networks, ICCCN 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509022793
DOIs
Publication statusPublished - 14 Sep 2016
Event25th International Conference on Computer Communications and Networks, ICCCN 2016 - Waikoloa, United States
Duration: 1 Aug 20164 Aug 2016

Publication series

Name2016 25th International Conference on Computer Communications and Networks, ICCCN 2016

Other

Other25th International Conference on Computer Communications and Networks, ICCCN 2016
CountryUnited States
CityWaikoloa
Period1/08/164/08/16

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Keywords

  • Hadoop YARN
  • MapReduce scheduling
  • Resource allocation

Cite this

Yao, Y., Gao, H., Wang, J., Mi, N., & Sheng, B. (2016). OpERA: Opportunistic and efficient resource allocation in hadoop YARN by harnessing idle resources. In 2016 25th International Conference on Computer Communications and Networks, ICCCN 2016 [7568553] (2016 25th International Conference on Computer Communications and Networks, ICCCN 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCCN.2016.7568553