Title :
Formalizing MapReduce with CSP
Author :
Yang, Fan ; Su, Wen ; Zhu, Huibiao ; Li, Qin
Author_Institution :
Shanghai Key Lab. of Trustworthy Comput., East China Normal Univ., Shanghai, China
Abstract :
As a programming model, MapReduce is popularly and widely used in processing and generating large cluster of data sets distributed on large amount of machines. With its widespread use, its validity and other major properties need to be analyzed in a formal framework. In this paper, a formal model is presented using CSP method. We focus on the dominant parts of MapReduce and formalize them in detail. Through this formal model, the processing and function of each component can be clearly reflected. Moreover, we illustrate this formal model by an example computation. The result reflects the validity of MapReduce in some appropriate applications.
Keywords :
Internet; learning (artificial intelligence); pattern clustering; CSP; example computation; formal framework; formalizing MapReduce; programming model; Cloud computing; Concurrent computing; Conferences; Data engineering; Distributed computing; Erbium; File systems; Laboratories; Software engineering; Systems engineering and theory; CSP; Cloud Computing; MapReduce;
Conference_Titel :
Engineering of Computer Based Systems (ECBS), 2010 17th IEEE International Conference and Workshops on
Conference_Location :
Oxford
Print_ISBN :
978-1-4244-6537-8
Electronic_ISBN :
978-1-4244-6538-5
DOI :
10.1109/ECBS.2010.50
