An Optimal Locality-Aware Task Scheduling Algorithm Based on Bipartite Graph Modelling for Spark Applications

In the distributed computing framework of Spark, cross-node/rack data transfer produced by map tasks and reduce tasks are common problems resulting in performance degradation, such as prolonging of entire execution time and network congestion. To address these problems, this article utilizes the bip...

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Vydané v:	IEEE transactions on parallel and distributed systems Ročník 31; číslo 10; s. 2406 - 2420
Hlavní autori:	Fu, Zhongming, Tang, Zhuo, Yang, Li, Liu, Chubo
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.10.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Benchmarks Communication Communication cost Communications traffic Computer networks data locality Data transfer Data transfer (computers) Distributed processing Graph theory Modelling Optimal scheduling Optimization Performance degradation Performance evaluation Scheduling Scheduling algorithms Spark Sparks Task analysis Task scheduling weighted bipartite graph
ISSN:	1045-9219, 1558-2183
On-line prístup:	Získať plný text
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