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Adaptive MapReduce scheduling in shared environments
dc.contributor.author | Polo Bardés, Jordà |
dc.contributor.author | Becerra Fontal, Yolanda |
dc.contributor.author | Carrera Pérez, David |
dc.contributor.author | Torres Viñals, Jordi |
dc.contributor.author | Ayguadé Parra, Eduard |
dc.contributor.author | Steinder, Malgorzata |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors |
dc.contributor.other | Barcelona Supercomputing Center |
dc.date.accessioned | 2015-06-05T08:24:10Z |
dc.date.created | 2014 |
dc.date.issued | 2014 |
dc.identifier.citation | Polo, J. [et al.]. Adaptive MapReduce scheduling in shared environments. A: IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing. "2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2014): Chicago, Illinois: USA, 26-29 May 2014". Chicago, IL: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 61-70. |
dc.identifier.isbn | 978-1-4799-2783-8 |
dc.identifier.uri | http://hdl.handle.net/2117/28187 |
dc.description.abstract | In this paper we present a MapReduce task scheduler for shared environments in which MapReduce is executed along with other resource-consuming workloads, such as transactional applications. All workloads may potentially share the same data store, some of them consuming data for analytics purposes while others acting as data generators. This kind of scenario is becoming increasingly important in data centers where improved resource utilization can be achieved through workload consolidation, and is specially challenging due to the interaction between workloads of different nature that compete for limited resources. The proposed scheduler aims to improve resource utilization across machines while observing completion time goals. Unlike other MapReduce schedulers, our approach also takes into account the resource demands for non-MapReduce workloads, and assumes that the amount of resources made available to the MapReduce applications is variable over time. As shown in our experiments, our proposal improves the management of MapReduce jobs in the presence of variable resource availability, increasing the accuracy of the estimations made by the scheduler, thus improving completion time goals without an impact on the fairness of the scheduler. |
dc.description.sponsorship | This work is partially supported by the Ministry of Science and Technology of Spain and the European Union’s FEDER funds (TIN2012-34557), by the Generalitat de Catalunya (2009-SGR-980) by the BSC-CNS Severo Ochoa program (SEV-2011-00067) and by the by the European Commission's IST activity of the 7th Framework Program under contract number 317862 (COMPOSE) |
dc.format.extent | 10 p. |
dc.language.iso | eng |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors |
dc.subject.lcsh | Data processing service centers |
dc.subject.lcsh | Parallel programming (Computer science) |
dc.subject.other | Adaptive |
dc.subject.other | Analytics |
dc.subject.other | Availability |
dc.subject.other | Distributed |
dc.subject.other | MapReduce |
dc.subject.other | Scheduling |
dc.subject.other | Shared environments |
dc.subject.other | Transactional |
dc.title | Adaptive MapReduce scheduling in shared environments |
dc.type | Conference report |
dc.subject.lemac | Centres informàtics |
dc.subject.lemac | Programació en paral·lel (Informàtica) |
dc.contributor.group | Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions |
dc.identifier.doi | 10.1109/CCGrid.2014.65 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6846441 |
dc.rights.access | Open Access |
local.identifier.drac | 15229973 |
dc.description.version | Postprint (published version) |
dc.relation.projectid | info:eu-repo/grantAgreement/SEV-2011-00067 |
dc.relation.projectid | info:eu-repo/grantAgreement/EC/FP7/317862/EU/Collaborative Open Market to Place Objects at your SErvice/COMPOSE |
dc.date.lift | 10000-01-01 |
local.citation.author | Polo, J.; Becerra, Y.; Carrera, D.; Torres, J.; Ayguade, E.; Steinder, M. |
local.citation.contributor | IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing |
local.citation.pubplace | Chicago, IL |
local.citation.publicationName | 2014 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid 2014): Chicago, Illinois: USA, 26-29 May 2014 |
local.citation.startingPage | 61 |
local.citation.endingPage | 70 |