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Performance evaluation of cloud service with hadoop for twitter data

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<p>In the era of rapid growth of cloud computing, performance calculation of cloud service is an essential criterion to assure quality of service. Nevertheless, it is a perplexing task to effectively analyze the performance of cloud service due to the complexity of cloud resources and the diversity of Big Data applications. Hence, we propose to examine the performance of Big Data applications with Hadoop and thus to figure out the performance in cloud cluster. Hadoop is built based on MapReduce, one of the widely used programming models in Big Data. In this paper, the performance analysis of Hadoop MapReduce WordCount application for Twitter data is presented. A 4-node in-house Hadoop cluster was setup and experiment was carried out for analyzing the performance. Through this work, it was concluded that Hadoop is efficient for BigData applications with 3 or more nodes with replication factor 3. Also, it was observed that system time was relatively more compared to user time for BigData applications beyond 80GB. This experiment had also thrown certain pattern on actual data blocks used to process the WordCount application. </p>
Title: Performance evaluation of cloud service with hadoop for twitter data
Description:
<p>In the era of rapid growth of cloud computing, performance calculation of cloud service is an essential criterion to assure quality of service.
Nevertheless, it is a perplexing task to effectively analyze the performance of cloud service due to the complexity of cloud resources and the diversity of Big Data applications.
Hence, we propose to examine the performance of Big Data applications with Hadoop and thus to figure out the performance in cloud cluster.
Hadoop is built based on MapReduce, one of the widely used programming models in Big Data.
In this paper, the performance analysis of Hadoop MapReduce WordCount application for Twitter data is presented.
A 4-node in-house Hadoop cluster was setup and experiment was carried out for analyzing the performance.
Through this work, it was concluded that Hadoop is efficient for BigData applications with 3 or more nodes with replication factor 3.
Also, it was observed that system time was relatively more compared to user time for BigData applications beyond 80GB.
This experiment had also thrown certain pattern on actual data blocks used to process the WordCount application.
 </p>.

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