Dynamic Job Ordering and Slot Configurations for MapReduce Workloads

Dynamic Job Ordering and Slot Configurations for MapReduce Workloads

MapReduce is a popular parallel computing paradigm for large-scale data processing in clusters and data centers. A MapReduce workload generally contains a set of jobs, each of which consists of multiple map tasks followed by multiple reduce tasks. Due to 1) that map tasks can only run in map slots a...

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Bibliographic Details
Main Authors: Tang, Shanjiang, Lee, Bu-Sung, He, Bingsheng
Other Authors: School of Computer Engineering
Format: Article
Language:English
Published: 2016
Subjects:
flow-shops
scheduling algorithm
job ordering
MapReduce
Hadoop
Online Access:https://hdl.handle.net/10356/80385
http://hdl.handle.net/10220/40666
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Institution: Nanyang Technological University
Language: English

Internet

https://hdl.handle.net/10356/80385
http://hdl.handle.net/10220/40666

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