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Distributed Processing of Networked Data

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Parallel processing



Bulk Synchronous Parallel

MapReduce :

A distributed programming model derived from functional paradigm, dedicated for complex and distributed computations


Social network analysis


The rapid development of the Internet provides many data sets that can be used to extract large and complex social networks. Such structures are characterized by the 3V rule, typical for big data sets: variety, volume, and velocity. These properties require sophisticated environment and specialized methods to be used for processing and analyzing large social networks. The primary purpose of various techniques, measures, and methods commonly called social network analysis (SNA) is to extract useful knowledge from such structures in order to support, e.g., targeted marketing, recommender, and personalized systems, or efficient human collaboration and knowledge exchange.

Due to efficiency reasons, to process large networked data, some complex cluster...

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Distributed Processing of Networked Data, Fig. 1
Distributed Processing of Networked Data, Fig. 2
Distributed Processing of Networked Data, Fig. 3
Distributed Processing of Networked Data, Fig. 4


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This work was partially supported by the National Science Centre, Poland, the decisions no. DEC-2016/21/B/ST6/01463 and DEC-2016/21/D/ST6/02948.

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Correspondence to Przemysław Kazienko .

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Kazienko, P., Indyk, W., Kajdanowicz, T., Bartusiak, R. (2018). Distributed Processing of Networked Data. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY.

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