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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.
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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Total Score: 109
Country: India
Subject: Uncategorized
Authors: Dr. B.Thirumala Rao,N.V.Sridevi,V.Krishna Reddy,L.S.S.Reddy (PhD/Dr. count: 1)
View Count (all-time): 118
Total Views (Real + Logic): 21217
Total Downloads (simulated): 11007
Publish Date: 1970 01, Thu
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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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