A Study on Using Uncertain Time Series Matching Algorithms in Map-Reduce Applications

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Babaii Rizvandi, Nikzad; Taheri, Javid; Zomaya, Albert; Moraveji, Reza


2012-10-07


Journal Article


Concurrency and Computation: Practice and Experience


In this paper, we study CPU utilization time patterns of several Map-Reduce applications. After extracting running patterns of several applications, the patterns with their statistical information are saved in a reference database to be later used to tweak system parameters to efficiently execute unknown applications in future. To achieve this goal, CPU utilization patterns of new applications along with its statistical information are compared with the already known ones in the reference database to find/predict their most probable execution patterns. Because of different patterns lengths, the Dynamic Time Warping (DTW) is utilized for such comparison; a statistical analysis is then applied to DTWs’ outcomes to select the most suitable candidates. Moreover, under a hypothesis, another algorithm is proposed to classify applications under similar CPU utilization patterns. Three widely used text processing applications (WordCount, Distributed Grep, and Terasort) and another application (Exim Mainlog parsing) are used to evaluate our hypothesis in tweaking system parameters in executing similar applications. Results were very promising and showed effectiveness of our approach on 5-node Map-Reduce platform


Map-Reduce, Pattern Matching, Configuration parameters, statistical analysis


nicta:5504


Babaii Rizvandi, Nikzad; Taheri, Javid; Zomaya, Albert; Moraveji, Reza. A Study on Using Uncertain Time Series Matching Algorithms in Map-Reduce Applications. Concurrency and Computation: Practice and Experience. 2012-10-07. <a href="http://hdl.handle.net/102.100.100/99249?index=1" target="_blank">http://hdl.handle.net/102.100.100/99249?index=1</a>



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