Abstract
A MapReduce system gradually becomes an essential technology to achieve the large scale computing on cloud computing. A MapReduce system currently is designed to distribute tasks over nodes in a cloud according to manual configurations of slot numbers in nodes. However, a MapReduce system may have the performance degradation due to the inappropriate configuration of the slot number, because the slot number can not exactly reflect the performance of the node. A MapReduce system can utilize the Automatic Self-Suspended Task (ASST) proposed in this paper to alleviate the performance degradation due to the inappropriate configuration of the slot number in a node on cloud computing. In experiments of this paper, a MapReduce system is proved to have a better performance with the help of ASST for various applications on cloud computing.
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References
Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. Commun. ACM 51(1), 107–113 (2008)
Pallis, G.: Cloud computing: the new frontier of internet computing. IEEE Internet Comput. 14(5), 70–73 (2010)
Murugesan, S.: Cloud computing: the new normal? Computer 46(1), 77–79 (2013)
Brown, R.A.: Hadoop at home: large-scale computing at a small college. ACM SIGCSE Bull. 41(1), 106–110 (2009)
Condie, T., Conway, N., Alvaro, P., Hellerstein, J.M., Elmeleegy, K., Sears, R.: MapReduce online. In: Proceedings of the 7th USENIX Conference on Networked Systems Design and Implementation, pp. 21–21 (2010)
Shvachko, K., Kuang, H., Radia, S., Chansler, R.: The Hadoop distributed file system. In: Proceedings of IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST), pp. 1–10 (2010)
Silberschatz, A., Galvin, P.B., Gagne, G.: Operating System Concepts. Wiley, New York (2008). ISBN 978-0-470-12872-5
Everette, S., Gardner, J.: Exponential smoothing: the state of the art. J. Forecast. 4(1), 1–28 (1985)
George, L.: HBase the Definitive Guide. O’Reilly Media, Sebastopol (2011). ISBN 978-1449396107
Mahapatra, A.K., Biswas, S.: Inverted indexes: types and techniques. IJCSI Int. J. Comput. Sci. Issues 8(4), 384–392 (2011)
Davis, I.J.: A fast radix sort. Comput. J. 35(6), 636–642 (1992)
Acknowledgement
We thank the National Science Council of Taiwan for their support of this project under grant number NSC 102-2221-E-262-014 and NSC 101-2221-E-006-147-MY3. We thank Lunghwa University of Science and Technology for providing us with devices. We thank our friends in National Cheng Kung University for giving us some technical supports. We further offer our special thanks to the reviewers for their valuable comments and suggestions.
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Huang, TC., Shieh, CK., Huang, SW., Chiu, CM., Liang, TY. (2014). Automatic Self-Suspended Task for a MapReduce System on Cloud Computing. In: Peng, WC., et al. Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2014. Lecture Notes in Computer Science(), vol 8643. Springer, Cham. https://doi.org/10.1007/978-3-319-13186-3_25
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DOI: https://doi.org/10.1007/978-3-319-13186-3_25
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