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Volume & Issue no: Volume 6, Issue 4, July - August 2017

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Title:
Performance Assessment of Storm and Spark for Twitter Streaming
Author Name:
B. Revathi Reddy, T.Swathi
Abstract:
Abstract Twitter is a rich source of a user’s interests: the public bio, observations, people followed, retweets and favorites. What if we could process all this information in real time to build awesome data analytics that personalize content based on the Twitter profile? Twitter Streaming data processing has been gaining attention due to its application into a wide range of scenarios. To serve the booming demands of streaming data processing, many computation engines have been developed. However, there is still a lack of real-world assessments that would be helpful when choosing the most appropriate platform for serving real-time streaming needs. In order to address this problem, we developed a streaming assessment for two representative computation engines: Storm and Spark Streaming. Instead of testing speed-of-light event processing, Based on our experiments, we provide a performance assessment comparison of the these two data streaming tools in terms of 99th percentile latency and throughput for various configurations. Keywords-Twitter Streaming processing, Assessment, Storm, Spark, Low Latency
Cite this article:
B. Revathi Reddy, T.Swathi , " Performance Assessment of Storm and Spark for Twitter Streaming" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) , Volume 6, Issue 4, July - August 2017 , pp. 218-223 , ISSN 2278-6856.
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International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
ISSN 2278-6856
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