University of Illinois Urbana-Champaign

Mélange: Multi-tenant scheduling with adaptive eviction for graph processing clusters

Mehar, Jayasi

Content Files
MEHAR-THESIS-2018.pdf

Permalink

https://hdl.handle.net/2142/101212

Description

Title
Mélange: Multi-tenant scheduling with adaptive eviction for graph processing clusters
Author(s)
Mehar, Jayasi
Issue Date
2018-04-24
Director of Research (if dissertation) or Advisor (if thesis)
Gupta, Indranil
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2018-09-04T20:36:52Z
Keyword(s)
  • graph processing
  • multi-tenancy
  • eviction
  • scheduling
Abstract
Multi-tenancy is an important approach to resource consolidation in cluster management. In this thesis we design and evaluate Mélange, an efficient multi-tenant scheduler targeted towards graph processing jobs. Mélange supports job priorities and eviction, while attempting to avoid starvation. We propose novel ways of exploiting domain-specific knowledge to achieve better scheduling decisions for graph processing jobs. We evaluate static eviction policies and design Mélange to adapt to the cluster and job state at run time to reduce overhead costs during eviction. We have developed Mélange as a cross-layer scheduler built over Apache Giraph and YARN, and show experimental results with synthetic as well as production workloads.
Graduation Semester
2018-05
Type of Resource
text
Permalink
http://hdl.handle.net/2142/101212
Copyright and License Information
Copyright 2018 Jayasi Mehar

Owning Collections

Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at Illinois
Dissertations and Theses - Computer Science
Dissertations and Theses from the Siebel School of Computer Science