Performance Issues of Heterogeneous Hadoop Clusters in Cloud Computing

α
Dr. B.Thirumala Rao
Dr. B.Thirumala Rao
σ
N.V.Sridevi
N.V.Sridevi
ρ
V.Krishna Reddy
V.Krishna Reddy
Ѡ
L.S.S.Reddy
L.S.S.Reddy
α Jawaharlal Nehru Technological University, Kakinada Jawaharlal Nehru Technological University, Kakinada

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Performance Issues of Heterogeneous Hadoop Clusters in Cloud Computing

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Abstract

Nowadays most of the cloud applications process large amount of data to provide the desired results. Data volumes to be processed by cloud applications are growing much faster than computing power. This growth demands new strategies for processing and analyzing information. Dealing with large data volumes requires two things: 1) Inexpensive, reliable storagee 2) New tools for analyzing unstructured and structured data. Hadoop is a powerful open source software platform that addresses both of these problems. The current Hadoop implementation assumes that computing nodes in a cluster are homogeneous in nature. Hadoop lacks performance in heterogeneous clusters where the nodes have different computing capacity. In this paper we address the issues that affect the performance of hadoop in eterogeneous clusters and also provided some guidelines on how to overcome these bottlenecks.

References

7 Cites in Article
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  2. Qi Zhang,Lu Cheng,Raouf Boutaba (2010). Cloud computing: state-of-the-art and research challenges.
  3. S Ghemawat,H Gobioff,S-T Leung (2003). The Google file system.
  4. Jaehwan Lee,Donghun Koo,Kyungmin Park,Jiksoo Kim,Soonwook Hwang (2016). Performance Analysis of Lustre File System using High Performance Storage Devices.
  5. M Zaharia,A Konwinski,A Joseph,Y,I Stoica (2008). Improving mapreduce performance in heterogeneous environments.
  6. Jeffrey Dean,Sanjay Ghemawat (2008). MapReduce.
  7. Haiying Shen,Yingwu Zhu (2009). A proactive lowoverhead file replication scheme for structured p2p content delivery networks.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. B.Thirumala Rao. 1970. \u201cPerformance Issues of Heterogeneous Hadoop Clusters in Cloud Computing\u201d. Unknown Journal GJCST Volume 11 (GJCST Volume 11 Issue 8): .

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May 7, 2011

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Nowadays most of the cloud applications process large amount of data to provide the desired results. Data volumes to be processed by cloud applications are growing much faster than computing power. This growth demands new strategies for processing and analyzing information. Dealing with large data volumes requires two things: 1) Inexpensive, reliable storagee 2) New tools for analyzing unstructured and structured data. Hadoop is a powerful open source software platform that addresses both of these problems. The current Hadoop implementation assumes that computing nodes in a cluster are homogeneous in nature. Hadoop lacks performance in heterogeneous clusters where the nodes have different computing capacity. In this paper we address the issues that affect the performance of hadoop in eterogeneous clusters and also provided some guidelines on how to overcome these bottlenecks.

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Performance Issues of Heterogeneous Hadoop Clusters in Cloud Computing

Dr. B.Thirumala Rao
Dr. B.Thirumala Rao Jawaharlal Nehru Technological University, Kakinada
N.V.Sridevi
N.V.Sridevi
V.Krishna Reddy
V.Krishna Reddy
L.S.S.Reddy
L.S.S.Reddy

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