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Comparing MapReduce and pipeline implementations for counting triangles

Autor
Edelmira Pasarella; Vidal, M.; Zoltan, A.
Tipus d'activitat
Article en revista
Revista
Electronic proceedings in theoretical computer science
Data de publicació
2017-01-11
Volum
237
Pàgina inicial
20
Pàgina final
33
DOI
https://doi.org/10.4204/EPTCS.237.2 Obrir en finestra nova
Projecte finançador
Modelos y métodos computacionales para datos masivos estructurados
Repositori
http://dx.doi.org/10.4204/EPTCS.237.2 Obrir en finestra nova
http://hdl.handle.net/2117/100102 Obrir en finestra nova
URL
http://eptcs.web.cse.unsw.edu.au/content.cgi?PROLE2016 Obrir en finestra nova
Resum
A common method to define a parallel solution for a computational problem consists in finding a way to use the Divide and Conquer paradigm in order to have processors acting on its own data and scheduled in a parallel fashion. MapReduce is a programming model that follows this paradigm, and allows for the definition of efficient solutions by both decomposing a problem into steps on subsets of the input data and combining the results of each step to produce final results. Albeit used for the impl...
Citació
Pasarella, E., Vidal, M., Zoltan, A. Comparing MapReduce and pipeline implementations for counting triangles. "Electronic proceedings in theoretical computer science", 11 Gener 2017, vol. 237, p. 20-33.
Paraules clau
Mapreduce, Dynamic Pipeline, Counting Triangles, Parallelism
Grup de recerca
ALBCOM - Algorismia, Bioinformàtica, Complexitat i Mètodes Formals

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