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Reseach Article

Can one find External Source Input Expressions for which there exist Map Reduce Configurations?

by Ravi (Ravinder) Prakash G, Kiran M. and
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 128 - Number 12
Year of Publication: 2015
Authors: Ravi (Ravinder) Prakash G, Kiran M. and
10.5120/ijca2015906680

Ravi (Ravinder) Prakash G, Kiran M. and . Can one find External Source Input Expressions for which there exist Map Reduce Configurations?. International Journal of Computer Applications. 128, 12 ( October 2015), 14-21. DOI=10.5120/ijca2015906680

@article{ 10.5120/ijca2015906680,
author = { Ravi (Ravinder) Prakash G, Kiran M. and },
title = { Can one find External Source Input Expressions for which there exist Map Reduce Configurations? },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 128 },
number = { 12 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 14-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume128/number12/22924-2015906680/ },
doi = { 10.5120/ijca2015906680 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:21:25.770644+05:30
%A Ravi (Ravinder) Prakash G
%A Kiran M. and
%T Can one find External Source Input Expressions for which there exist Map Reduce Configurations?
%J International Journal of Computer Applications
%@ 0975-8887
%V 128
%N 12
%P 14-21
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

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

References
  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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
  9. 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.
  10. 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
  11. 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.
  12. 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.
  13. 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.
  14. Ravi (Ravinder) Prakash G and Kiran M., On Job Chaining MapReduce Meta Expressions of Mapping and Reducing Entropy Densities. International Journal of Computer Applications 113(15): 20-27, March 2015.
  15. Ravi (Ravinder) Prakash G, Kiran M. "On Chain Folding Problems of Chain Mapper and Chain Reducer Meta Expressions". International Journal of Computer Applications 116(16): 35-42, April 2015.
  16. Ravi (Ravinder) Prakash G and Kiran M."On Job Merging MapReduce Meta Expressions for Multiple Decomposition Mapping and Reducing". International Journal of Computer Applications 118 (13):14-21, May 2015.
  17. Ravi (Ravinder) Prakash G. and Kiran M." Characterization of Randomized External Source Output Map Reduce Expressions". International Journal of Computer Applications 123(14):9-16, August 2015.
  18. Ravi (Ravinder) Prakash G. and Kiran M., Does there Exist Pruning Decomposition for MapReduce Expressions Arrangements?. International Journal of Computer Applications 125(12): 41-48, September 2015.
Index Terms

Computer Science
Information Sciences

Keywords

MapReduce External Source Input expressions kernel function.