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MRTree: Functional Testing based on MapReduce´s execution behaviour

Author:
Morán, Jesús; Riva Álvarez, Claudio A. de laUniovi authority; Tuya González, Pablo JavierUniovi authority
Publication date:
2014-08
Editorial:

IEEE

Publisher version:
http://dx.doi.org/10.1109/FiCloud.2014.67
Descripción física:
p. 379-384
Abstract:

MapReduce is a paradigm that allows parallel processing of large amounts of data. MapReduce programs combined with their underlying run-time framework have distinctive features that are prone to include unexpected behaviors not present in other types of programs. This paper describes an approach to functional testing of MapReduce programs based on a hierarchical classification of a number of potential faults that may occur in MapReduce programs over Hadoop. This classification, called MRTree, is then used to derive test cases able to detect the faults represented in MRTree and illustrated with some examples

MapReduce is a paradigm that allows parallel processing of large amounts of data. MapReduce programs combined with their underlying run-time framework have distinctive features that are prone to include unexpected behaviors not present in other types of programs. This paper describes an approach to functional testing of MapReduce programs based on a hierarchical classification of a number of potential faults that may occur in MapReduce programs over Hadoop. This classification, called MRTree, is then used to derive test cases able to detect the faults represented in MRTree and illustrated with some examples

Description:

International Symposium on Big Data Research and Innovation (BigR&I), Barcelona (España)

URI:
http://hdl.handle.net/10651/30820
ISBN:
978-1-4799-4357-9
DOI:
10.1109/FiCloud.2014.67
Patrocinado por:

This work has been performed under the research project TIN2013-46928-C3-1-R, funded by the Spanish Ministry of Economy and Competitiveness and ERDF Funds

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