Paper Info
Title
Performance Implications of SSDs in Virtualized Hadoop Clusters
Abstract
BigData manipulates a massive volume of data for which the traditional techniques are not effective. Apache Hadoop is currently a most popular software framework supporting BigData analysis. As the scale of Hadoop cluster grows larger, building Hadoop clusters in virtualized environment draws a great attention. However, the performance optimization of Hadoop cluster in virtualized environment is difficult because of the virtualization overhead. In this paper the performance implications of SSDs in virtualized Hadoop clusters is identified and the overhead of virtualization is shown to be minimized with SSDs. The study presented in this paper reveals that the main virtualization overhead is I/O bottleneck due to fragmented and randomized I/O workload aggravated by virtualization. However, SSDs are more tolerable to the workload than HDDs. As a result, the virtualization overhead with SSDs is much less than with HDDs. Also, in the case of SSDs, the virtualized Hadoop cluster sustains good performance regardless of the number of VMs.
Year
DOI
Venue
2014
10.1109/BigData.Congress.2014.90
BigData Congress
Keywords
Field
DocType
bigdata,public domain software,solid-state drives,hadoop, virtualization, ssd, bigdata, cloud computing,virtualization,performance implications,ssd,big data,software framework,bigdata analysis,storage management,data analysis,virtualization overhead,software performance evaluation,input-output programs,i-o workload,hadoop,virtualisation,i-o bottleneck,virtualized apache hadoop clusters,cloud computing
Virtualization,Bottleneck,Cluster (physics),Workload,Computer science,Big data,Operating system,Software framework,Cloud computing
Conference
ISSN
ISBN
Citations 
2379-7703
978-1-4799-5056-0
1
PageRank 
References 
Authors
0.36
6
4
Name
Order
Citations
PageRank
Sungyong Ahn131.40
Sangkyu Park210.36
Jae-Ki Hong391.53
Wooseok Chang471.85