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Formal derivation of distributed MapReduce

Pereverzeva, Inna, Butler, Michael, Salehi Fathabadi, Asieh, Laibinis, Linas and Troubitsyna, Elena (2014) Formal derivation of distributed MapReduce At 4th International ABZ 2014 Conference, France. 02 - 06 Jun 2014. 17 pp.

Record type: Conference or Workshop Item (Paper)


MapReduce is a powerful distributed data processing model that is currently adopted in a wide range of domains to efficiently handle large volumes of data, i.e., cope with the big data surge. In this paper, we propose an approach to formal derivation of the MapReduce framework. Our approach relies on stepwise refinement in Event-B and, in particu- lar, the event refinement structure approach – a diagrammatic notation facilitating formal development. Our approach allows us to derive the system architecture in a systematic and well-structured way. The main principle of MapReduce is to parallelise processing of data by first map- ping them to multiple processing nodes and then merging the results. To facilitate this, we formally define interdependencies between the map and reduce stages of MapReduce. This formalisation allows us to pro- pose an alternative architectural solution that weakens blocking between the stages and, as a result, achieves a higher degree of parallelisation of MapReduce computations.

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Published date: June 2014
Venue - Dates: 4th International ABZ 2014 Conference, France, 2014-06-02 - 2014-06-06
Organisations: Electronic & Software Systems


Local EPrints ID: 363707
PURE UUID: 109b5895-9232-4ba3-8e54-164695884ba7
ORCID for Michael Butler: ORCID iD

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Date deposited: 31 Mar 2014 15:20
Last modified: 18 Jul 2017 02:37

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Author: Inna Pereverzeva
Author: Michael Butler ORCID iD
Author: Asieh Salehi Fathabadi
Author: Linas Laibinis
Author: Elena Troubitsyna

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