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DOI

Graphs are a natural fit for modeling concepts used in solving diverse problems in science, commerce, engineering, and governance. Responding to the variety of graph data and algorithms, many parallel and distributed graph processing systems exist. However, until now these platforms use a static model of deployment: they only run on a pre-defined set of machines. This raises many conceptual and pragmatic issues, including misfit with the highly dynamic nature of graph processing, and could lead to resource waste and high operational costs. In contrast, in this work we explore a dynamic model of deployment. We first characterize workload dynamicity, beyond mere active-vertex variability. Then, to conduct an in-depth elasticity study of distributed graph processing, we build a prototype, JoyGraph, which is the first such system that implements complex, policy-based, and fine-grained elasticity. Using the state-of-the-art LDBC Graphalytics benchmark and the SPEC Cloud Group's elasticity metrics, we show the benefits of elasticity in graph processing: (i) improved resource utilization, (ii) reduced operational costs, and (iii) aligned operation-workload dynamicity. Furthermore, we explore the cost of elasticity in graph processing. We identify a key drawback: although elasticity does not degrade application throughput, graph-processing workloads are sensitive to data movement while leasing or releasing resources.
Original languageEnglish
Title of host publication2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)
EditorsL. O'Conner
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages382-383
Number of pages2
ISBN (Electronic)978-1-5386-5815-4
ISBN (Print)978-1-5386-5816-1
DOIs
Publication statusPublished - 2018
EventCCGRID 2018: 18th IEEE/ACM International Sympocium on Cluster, Cloud and Grid Computing - Washington, DC, United States
Duration: 1 May 20184 May 2018
Conference number: 18

Conference

ConferenceCCGRID 2018
CountryUnited States
CityWashington, DC
Period1/05/184/05/18

ID: 46652034