Jun 8, 2012 · The map-reduce paradigm has shown to be a simple and feasible way of filtering and analyzing large data sets in cloud and cluster systems.
This work describes the use of non-dedicated clusters by a known group of local applications sharing the computational resources with additional ...
We describe the data distribution patterns found in current Map-Reduce read mapping bioinformatics applications and show some data decomposition principles to ...
The map-reduce paradigm has shown to be a simple and feasible way of filtering and analyzing large data sets in cloud and cluster systems.
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Title: Analysis and improvement of map-reduce data distribution in read mapping applications ; Authors: Espinosa Morales, Antonio Miguel;Hernandez Bude, Porfidio ...
High Performance Computing Applications for Science and Engineering. Analysis and improvement of map-reduce data distribution in read mapping applications.
Dive into the research topics of 'Analysis and improvement of map-reduce data distribution in read mapping applications'. Together they form a unique ...
Títol: Analysis and improvement of map-reduce data distribution in read mapping applications ; Autors: Espinosa Morales, Antonio Miguel;Hernandez Bude, Porfidio; ...
This paper suggests the effectively distributing scheme that separates a huge data and operates Map task in the considering the performance of computing node ...
MapReduce is a Java-based, distributed execution framework within the Apache Hadoop Ecosystem. It takes away the complexity of distributed programming.