Volume & Issue no: Volume 6, Issue 5, September - October 2017
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Title: |
Improving the Performance of Resource Allocation in
Multitenancy MapReduce Using YARN |
Author Name: |
Sunanda CP, Santhosh Kumar B |
Abstract: |
Abstract
Multitenancy MapReduce has earned the importance in the
massive bigdata technology. In a multitenant MapReduce
environment, multiple tenants with different demands can share
a variety of Hadoop computing resources (e.g., network,
processor, memory, storage and data) within a single Hadoop
system, while each tenant remains logically isolated. This useful
MapReduce Multitenancy concept offers highly efficient, and
cost-effective systems without wasting Hadoop computing
resources to enterprises requiring similar environments for data
processing and management. In this paper, we are proposing
an improved resource allocation approach supporting
multitenancy features for Apache Hadoop, a large scale
distributed system commonly used for processing big data using
YARN. We initially implement the Hadoop framework focusing
on “yet another resource negotiator (YARN)”, which is mainly
used for managing Hadoop resources, map reduce application
runtime, and Hadoop user access controls in the latest version
of Hadoop. We then identify the problems of YARN for
supporting multitenancy and then derive the solution
framework to solve these problems. Based on these
requirements, we design the details of multitenant Hadoop. We
also present the industrial multitenant Hadoop implementation
that results to validate the bigdata access control and to
evaluate the performance enhancement of multitenant Hadoop.
The proposed multitenant Hadoop framework work is optimized
for geographically distributed data centers considering the
locations of data and users.
Keywords: Access control, big data, cloud, Hadoop,
multitenancy, resource management, yet another resource
negotiator (YARN), geographically distributed data centers. |
Cite this article: |
Sunanda CP, Santhosh Kumar B , "
Improving the Performance of Resource Allocation in
Multitenancy MapReduce Using YARN" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) ,
Volume 6, Issue 5, September - October 2017 , pp.
009-017 , ISSN 2278-6856.
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