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Characterization of Randomized External Source Output Map Reduce Expressions
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 123 - Number 14 |
| Year of Publication: 2015 |
| Authors: Ravi (Ravinder) Prakash G., Kiran M. |
10.5120/ijca2015905403
|
Ravi (Ravinder) Prakash G., Kiran M. . Characterization of Randomized External Source Output Map Reduce Expressions. International Journal of Computer Applications. 123, 14 ( August 2015), 9-16. DOI=10.5120/ijca2015905403
Abstract
An intention of MapReduce Sets for External Source Output expressions analysis has to suggest criteria how External Source Output expressions in External Source Output data can be defined in a meaningful way and how they should be compared. Similitude based MapReduce Sets for External Source Output Expression Analysis and MapReduce Sets for Assignment is expected to adhere to fundamental principles of the scientific External Source Output process that are expressiveness of External Source Output models and reproducibility of their External Source Output inference. External Source Output expressions are assumed to be elements of a External Source Output expression space or Conjecture class and External Source Output data provide “information” which of these External Source Output expressions should be used to interpret the External Source Output data. An inference External Source Output algorithm constructs the mapping between External Source Output data and External Source Output expressions, in particular by a External Source Output cost minimization process. Fluctuations in the External Source Output data often limit the External Source Output precision, which we can achieve to uniquely identify a single External Source Output expression as interpretation of the External Source Output data. We advocate an information theoretic perspective on External Source Output expression analysis to resolve this dilemma where the tradeoff between External Source Output informativeness of statistical inference External Source Output and their External Source Output stability is mirrored in the information-theoretic External Source Output optimum of high External Source Output information rate and zero communication expression error. The inference External Source Output algorithm is considered as an outlier object External Source Output path, which naturally limits the resolution of the External Source Output expression space given the uncertainty of the External Source Output 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.
- 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.
- 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.
- 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.
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