Implementation of Word Count- Hadoop Framework with Map Reduce Algorithm

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2017 by IJCTT Journal
Volume-49 Number-3
Year of Publication : 2017
Authors : Keerthi.Bangari, Sujitha.Meduri, Ch.CY.Rao
  10.14445/22312803/IJCTT-V49P128

MLA

Keerthi.Bangari, Sujitha.Meduri, Ch.CY.Rao "Implementation of Word Count- Hadoop Framework with Map Reduce Algorithm". International Journal of Computer Trends and Technology (IJCTT) V49(3):179-182, July 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
In the technological world there are number of technologies which are generating a large amount of data day by day that leads to formation of a technology called Big Data. Big Data deals with the large and unstructured data that can be computationally analysed to reveal the trends and patterns of a data. In this paper the basic program called Word Count Map Reduce program executed in apache hadoop with a single node setup. Altering in input files and reducing the number of tasks that makes the changes in execution of a program. The aim of this paper is running the Word Count program with different parameters.

References
[1] http://hadoop.apache.org/ ,Apache Hadoop
[2] Maurya, M., & Mahajan, S. (2012, October). Performance analysis of MapReduce programs on Hadoop cluster. In Information and Communication Technologies (WICT), 2012 World Congress On (pp. 505-510). IEEE.
[3] Yang, X. and Sun, J., 2011, September. An analytical performance model of mapreduce. In Cloud Computing and Intelligence Systems (CCIS), 2011 IEEE International Conference on (pp. 306-310). IEEE.M. Wegmuller, J. P. von der Weid, P. Oberson, and N. Gisin, “High resolution fiber distributed measurements with coherent OFDR,” in Proc. ECOC’00, 2000, paper 11.3.4, p. 109.
[4] Zaharia, Matei, et al. "Improving MapReduce performance in heterogeneous environments." Osdi. Vol. 8. No. 4. 2008. (2002) The IEEE website. [Online]. Available: http://www.ieee.org/
[5] https://www.tutorialspoint.com/hadoop/ ,Map Reduce tutorial
[6] Chavan, Vibhavari, and Rajesh N. Phursule. "Survey paper on big data." Int. J. Comput. Sci. Inf. Technol 5, no. 6 (2014): 7932-7939.
[7] Blazhievsky, S., 2013. Introduction to Hadoop, MapReduce and HDFS for Big Data Applications. SNIA Education.
[8] Arora, Suman, and Dr Madhu Goel. "Survey paper on Scheduling in Hadoop." International Journal of Advanced Research in Computer Science and Software Engineering 4.5 (2014).
[9] Tan, Jian, Xiaoqiao Meng, and Li Zhang. "Performance analysis of coupling scheduler for mapreduce/hadoop." INFOCOM, 2012 Proceedings IEEE. IEEE, 2012.

Keywords
Word Count Program, Apache Hadoop, Map Reduce, Big Data, Parameters.