DocumentCode :
3422810
Title :
Enhancement of Hadoop Clusters with Virtualization Using the Capacity Scheduler
Author :
Raj, Ashish ; Kaur, Kanwalpreet ; Dutta, U. ; Sandeep, V.V. ; Rao, Smitha
fYear :
2012
fDate :
12-15 Dec. 2012
Firstpage :
50
Lastpage :
57
Abstract :
We present a virtualized setup of a Hadoop cluster that provides greater computing capacity with lesser resources, since a virtualized cluster requires fewer physical machines. The master node of the cluster is set up on a physical machine, and slave nodes are set up on virtual machines (VMs) that may be on a common physical machine. Hadoop configured VM images are created by cloning of VMs, which facilitates fast addition and deletion of nodes in the cluster without much overhead. Also, we have configured the Hadoop virtualized cluster to use capacity scheduler instead of the default FIFO scheduler. The capacity scheduler schedules tasks based on the availability of RAM and virtual memory (VMEM) in slave nodes before allocating any job. So instead of queuing up the jobs, they are efficiently allocated on the VMs based on the memory available. Various configuration parameters of Hadoop are analyzed and the virtualized cluster is fine-tuned to ensure best performance and maximum scalability.
Keywords :
pattern clustering; random-access storage; scheduling; virtual machines; virtualisation; Hadoop cluster enhancement; RAM; VM images; VMEM; capacity scheduler; computing capacity; default FIFO scheduler; physical machines; slave nodes; virtual machines; virtual memory; virtualization; virtualized cluster; Cloning; Hardware; Memory management; Random access memory; Resource management; Virtualization; Hadoop; MapReduce; VM cloning; capacity scheduler; virtualization; virtualized cluster;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Services in Emerging Markets (ICSEM), 2012 Third International Conference on
Conference_Location :
Mysore
Print_ISBN :
978-1-4673-5729-6
Type :
conf
DOI :
10.1109/ICSEM.2012.15
Filename :
6468179
Link To Document :
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