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Scarlett: coping with skewed content popularity in mapreduce clusters

Published: 10 April 2011 Publication History

Abstract

To improve data availability and resilience MapReduce frameworks use file systems that replicate data uniformly. However, analysis of job logs from a large production cluster shows wide disparity in data popularity. Machines and racks storing popular content become bottlenecks; thereby increasing the completion times of jobs accessing this data even when there are machines with spare cycles in the cluster. To address this problem, we present Scarlett, a system that replicates blocks based on their popularity. By accurately predicting file popularity and working within hard bounds on additional storage, Scarlett causes minimal interference to running jobs. Trace driven simulations and experiments in two popular MapReduce frameworks (Hadoop, Dryad) show that Scarlett effectively alleviates hotspots and can speed up jobs by 20.2%.

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cover image ACM Conferences
EuroSys '11: Proceedings of the sixth conference on Computer systems
April 2011
370 pages
ISBN:9781450306348
DOI:10.1145/1966445
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 10 April 2011

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Author Tags

  1. data locality
  2. datacenter storage
  3. fairness
  4. replication

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EuroSys '11
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EuroSys '11: Sixth EuroSys Conference 2011
April 10 - 13, 2011
Salzburg, Austria

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EuroSys '11 Paper Acceptance Rate 24 of 161 submissions, 15%;
Overall Acceptance Rate 241 of 1,308 submissions, 18%

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  • (2024)dLoRAProceedings of the 18th USENIX Conference on Operating Systems Design and Implementation10.5555/3691938.3691987(911-927)Online publication date: 10-Jul-2024
  • (2024)An Access-Oriented Placement Strategy with Online Erasure Coding in Memory StoresProceedings of the 2024 9th International Conference on Intelligent Information Processing10.1145/3696952.3696974(154-161)Online publication date: 21-Nov-2024
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