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On Job Chaining MapReduce Meta Expressions of Mapping and Reducing Entropy Densities

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International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 113 - Number 15
Year of Publication: 2015
Authors:
Ravi (ravinder) Prakash G
Kiran M
10.5120/19902-2008

Ravi (ravinder) Prakash G and Kiran M. Article: On Job Chaining MapReduce Meta Expressions of Mapping and Reducing Entropy Densities. International Journal of Computer Applications 113(15):20-27, March 2015. Full text available. BibTeX

@article{key:article,
	author = {Ravi (ravinder) Prakash G and Kiran M},
	title = {Article: On Job Chaining MapReduce Meta Expressions of Mapping and Reducing Entropy Densities},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {113},
	number = {15},
	pages = {20-27},
	month = {March},
	note = {Full text available}
}

Abstract

An intention of MapReduce Sets for Job chaining expressions analysis has to suggest criteria how Job chaining expressions in Job chaining data can be defined in a meaningful way and how they should be compared. Similitude based MapReduce Sets for Job chaining Expression Analysis and MapReduce Sets for Assignment is expected to adhere to fundamental principles of the scientific Job chaining process that are expressiveness of Job chaining models and reproducibility of their Job chaining inference. Job chaining expressions are assumed to be elements of a Job chaining expression space or Conjecture class and Job chaining data provide "information" which of these Job chaining expressions should be used to interpret the Job chaining data. An inference Job chaining algorithm constructs the mapping between Job chaining data and Job chaining expressions, in particular by a Job chaining cost minimization process. Fluctuations in the Job chaining data often limit the Job chaining precision, which we can achieve to uniquely identify a single Job chaining expression as interpretation of the Job chaining data. We advocate an information theoretic perspective on Job chaining expression analysis to resolve this dilemma where the tradeoff between Job chaining informativeness of statistical inference Job chaining and their Job chaining stability is mirrored in the information-theoretic Job chaining optimum of high Job chaining information rate and zero communication expression error. The inference Job chaining algorithm is considered as an outlier object Job chaining path, which naturally limits the resolution of the Job chaining expression space given the uncertainty of the Job chaining data.

References

  • Ravi Prakash G, Kiran M, and Saikat Mukherjee, Asymmetric Key-Value Split Pattern Assumption over MapReduce Behavioral Model, International Journal of Computer Applications, Volume 86 – No 10, Page 30-34, January 2014.
  • Kiran M. , Saikat Mukherjee and Ravi Prakash G. , Characterization of Randomized Shuffle and Sort Quantifiability in MapReduce Model, International Journal of Computer Applications, 51-58, Volume 79, No. 5, October 2013.
  • Amresh Kumar, Kiran M. , Saikat Mukherjee and Ravi Prakash G. , Verification and Validation of MapReduce Program model for Parallel K-Means algorithm on Hadoop Cluster, International Journal of Computer Applications, 48-55, Volume 72, No. 8, June 2013.
  • Kiran M. , Amresh Kumar, Saikat Mukherjee and Ravi Prakash G. , Verification and Validation of MapReduce Program Model for Parallel Support Vector Machine Algorithm on Hadoop Cluster, International Journal of Computer Science Issues, 317-325, Vol. 10, Issue 3, No. 1, May 2013.
  • Ravi Prakash G, Kiran M and Saikat Mukherjee, On Randomized Preference Limitation Protocol for Quantifiable Shuffle and Sort Behavioral Implications in MapReduce Programming Model, Parallel & Cloud Computing, Vol. 3, Issue 1, 1-14, January 2014.
  • Ravi Prakash G, and Kiran M, On The Least Economical MapReduce Sets for Summarization Expressions, International Journal of Computer Applications, 13-20, Volume 94, No. 7, May 2014.
  • Ravi (Ravinder) Prakash G, Kiran M. , On Randomized Minimal MapReduce Sets for Filtering Expressions, International Journal of Computer Applications, Volume 98, No. 3, Pages 1-8, July 2014.
  • Ravi (Ravinder) Prakash G and Kiran M. , How Minimal are MapReduce Arrangements for Binning Expressions. International Journal of Computer Applications Volume 99 (11): 7-14, August 2014
  • Ravi (Ravinder) Prakash G and Kiran M. , Shuffling Expressions with MapReduce Arrangements and the Role of Binary Path Symmetry. International Journal of Computer Applications 102 (16): 19-24, September 2014.
  • Ravi (Ravinder) Prakash G and Kiran M; How Reduce Side Join Part File Expressions Equal MapReduce Structure into Task Consequences, Performance? International Journal of Computer Applications, Volume 105(2):8-15, November 2014
  • Ravi (Ravinder) Prakash G and Kiran M; How Replicated Join Expressions Equal Map Phase or Reduce Phase in a MapReduce Structure? International Journal of Computer Applications, Volume 107 (12): 43-50, No 12, December 2014.
  • Ravi (Ravinder) Prakash G and Kiran M. , On Composite Join Expressions of Map-side with many Reduce Phase. International Journal of Computer Applications Volume 110(9): 37-44, January 2015.
  • Ravi (Ravinder) Prakash G and Kiran M. "On the MapReduce Arrangements of Cartesian product Specific Expressions". International Journal of Computer Applications 112(9):34-41, February 2015.