NDLI: SMapReduce: Optimising Resource Allocation by Managing Working Slots at Runtime

Content Provider	IEEE Xplore Digital Library
Author	Feng Liang Lau, F.C.M.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci., Univ. of Hong Kong, Hong Kong, China (Feng Liang; Lau, F.C.M.)
Abstract	Hadoop version 1 (HadoopV1) and version 2 (YARN) manage the resources in a distributed system in different ways. HadoopV1 executes MapReduce tasks in working slots that are statically configured, YARN uses a set of task containers to encapsulate its memory and CPU resources. However, neither of them considers the runtime performance of the cluster when deciding the proper number of concurrent tasks to run on each node to achieve the optimal throughput. In order to gain higher performance, the users of Hadoop usually need to use their experience to carefully configure the resources of the cluster and the resources needed by their jobs. But as the workload is typically always changing in the cluster, rarely could such a manual configuration lead to optimized performance. In this paper, we study the MapReduce job performance in HadoopV1 and YARN with different resource configurations, and model the cluster throughput in terms of the resource capacity of the cluster. We propose SMapReduce, which can dynamically manage a proper number of concurrent tasks running on each node. SMapReduce can gain the maximum job throughput by considering the thrashing phenomenon and the balancing between map and reduce tasks. Evaluation results show that SMapReduce can yield significant performance speedup comparing to both HadoopV1 and YARN for various MapReduce workloads.
Starting Page	281
Ending Page	290
File Size	450631
Page Count	10
File Format	PDF
ISBN	9781479986491
ISSN	15302075
DOI	10.1109/IPDPS.2015.17
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-25
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Throughput Yarn Heart beat Runtime Containers Resource management Synchronization Performance Modelling Resource Management MapReduce Hadoop
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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SMapReduce: Optimising Resource Allocation by Managing Working Slots at Runtime

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