Analysis and improvement of map-reduce data distribution in read mapping applications
Espinosa, Antonio (Universitat Autònoma de Barcelona. Departament d'Arquitectura de Computadors i Sistemes Operatius)
Hernández Budé, Porfidio (Universitat Autònoma de Barcelona. Departament d'Arquitectura de Computadors i Sistemes Operatius)
Moure, Juan C. (Universitat Autònoma de Barcelona. Departament d'Arquitectura de Computadors i Sistemes Operatius)
Protasio Ramirez, Joan (Universitat Autònoma de Barcelona. Departament d'Arquitectura de Computadors i Sistemes Operatius)
Ripoll Aracil, Ana (Ana) (Universitat Autònoma de Barcelona. Departament d'Arquitectura de Computadors i Sistemes Operatius)

Additional title:	Analysis and optimization of map reduce data distribution in read mapping applications
Date:	2012
Abstract:	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. Algorithms designed for the paradigm must implement regular data distribution patterns so that appropriate use of resources is ensured. Good scalability and performance on Map-Reduce applications greatly depend on the design of regular intermediate data generation-consumption patterns at the map and reduce phases. We describe the data distribution patterns found in current Map-Reduce read mapping bioinformatics applications and show some data decomposition principles to greatly improve their scalability and performance.
Grants:	Ministerio de Ciencia y Tecnología CSD2007-00050
Rights:	Tots els drets reservats.
Language:	Anglès
Document:	Article ; recerca ; Versió acceptada per publicar
Subject:	Bioinformatics ; Read mapping ; Map reduce ; Scalability
Published in:	The journal of supercomputing, Vol. 62 (2012) , p. 1305-1317, ISSN 1573-0484

DOI: 10.1007/s11227-012-0792-8

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