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The X-flex cross-platform scheduler: who's the fairest of them all?

Published: 08 December 2014 Publication History

Abstract

We introduce the X-Flex cross-platform scheduler. X-Flex is intended as an alternative to the Dominant Resource Fairness (DRF) scheduler currently employed by both YARN and Mesos. There are multiple design differences between X-Flex and DRF. For one thing, DRF is based on an instantaneous notion of fairness, while X-Flex monitors instantaneous fairness in order to take a long-term view. The definition of instantaneous fairness itself is different among the two schedulers. Furthermore, the packing of containers into processing nodes in DRF is done online, while in X-Flex it is performed offline in order to improve packing quality. Finally, DRF is essentially an extension to multiple dimensions of the Fair MapReduce scheduler. As such it makes scheduling decisions at a very low level. X-Flex, on the other hand, takes the perspective that some frameworks have sufficient structure to make higher level scheduling decisions. So X-Flex allows this, and also gives platforms a great deal of autonomy over the degree of sharing they will permit with other platforms. We describe the technical details of X-Flex and provide experiments to show its excellent performance.

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Cited By

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  • (2019)Jargon of Hadoop MapReduce scheduling techniques: a scientific categorizationThe Knowledge Engineering Review10.1017/S026988891800037134Online publication date: 15-Mar-2019
  • (2015)Algorithms for scheduling deadline-sensitive malleable tasks2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)10.1109/ALLERTON.2015.7447050(530-537)Online publication date: Sep-2015

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cover image ACM Other conferences
Industry papers: Proceedings of the Middleware Industry Track
December 2014
37 pages
ISBN:9781450332194
DOI:10.1145/2676727
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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Association for Computing Machinery

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Publication History

Published: 08 December 2014

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Author Tags

  1. DRF
  2. YARN
  3. cross-platform scheduling

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Middleware '14

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Overall Acceptance Rate 5 of 23 submissions, 22%

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Cited By

View all
  • (2019)Jargon of Hadoop MapReduce scheduling techniques: a scientific categorizationThe Knowledge Engineering Review10.1017/S026988891800037134Online publication date: 15-Mar-2019
  • (2015)Algorithms for scheduling deadline-sensitive malleable tasks2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton)10.1109/ALLERTON.2015.7447050(530-537)Online publication date: Sep-2015

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