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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