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On Job Merging MapReduce Meta Expressions for Multiple Decomposition Mapping and Reducing
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 118 - Number 13 |
| Year of Publication: 2015 |
| Authors: Ravi (ravinder) Prakash G, Kiran M |
10.5120/20804-3501
|
Ravi (ravinder) Prakash G, Kiran M . On Job Merging MapReduce Meta Expressions for Multiple Decomposition Mapping and Reducing. International Journal of Computer Applications. 118, 13 ( May 2015), 14-21. DOI=10.5120/20804-3501
Abstract
An intention of MapReduce Sets for Job Merging expressions analysis has to suggest criteria how Job Merging expressions in Job Merging data can be defined in a meaningful way and how they should be compared. Similitude based MapReduce Sets for Job Merging Expression Analysis and MapReduce Sets for Assignment is expected to adhere to fundamental principles of the scientific Job Merging process that are expressiveness of Job Merging models and reproducibility of their Job Merging inference. Job Merging expressions are assumed to be elements of a Job Merging expression space or Conjecture class and Job Merging data provide "information" which of these Job Merging expressions should be used to interpret the Job Merging data. An inference Job Merging algorithm constructs the mapping between Job Merging data and Job Merging expressions, in particular by a Job Merging cost minimization process. Fluctuations in the Job Merging data often limit the Job Merging precision, which we can achieve to uniquely identify a single Job Merging expression as interpretation of the Job Merging data. We advocate an information theoretic perspective on Job Merging expression analysis to resolve this dilemma where the tradeoff between Job Merging informativeness of statistical inference Job Merging and their Job Merging stability is mirrored in the information-theoretic Job Merging optimum of high Job Merging information rate and zero communication expression error. The inference Job Merging algorithm is considered as an outlier object Job Merging path, which naturally limits the resolution of the Job Merging expression space given the uncertainty of the Job Merging 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.
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