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Formal derivation of distributed MapReduce

Formal derivation of distributed MapReduce
Formal derivation of distributed MapReduce
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 particular, 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 mapping 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 propose an alternative architectural solution that weakens blocking between the stages and, as a result, achieves a higher degree of parallelisation of MapReduce computations.
Pereverzeva, Inna
e09a1511-31a5-4635-8630-9e8825c8386c
Butler, Michael
54b9c2c7-2574-438e-9a36-6842a3d53ed0
Salehi Fathabadi, Asieh
b799ee35-4032-4e7c-b4b2-34109af8aa75
Laibinis, Linas
ade0e3db-9dbe-4ee0-9751-99561149e66a
Troubitsyna, Elena
5d1caf79-f1e5-4333-8e3a-f13da8f63c70
Pereverzeva, Inna
e09a1511-31a5-4635-8630-9e8825c8386c
Butler, Michael
54b9c2c7-2574-438e-9a36-6842a3d53ed0
Salehi Fathabadi, Asieh
b799ee35-4032-4e7c-b4b2-34109af8aa75
Laibinis, Linas
ade0e3db-9dbe-4ee0-9751-99561149e66a
Troubitsyna, Elena
5d1caf79-f1e5-4333-8e3a-f13da8f63c70

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

Record type: Conference or Workshop Item (Paper)

Abstract

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 particular, 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 mapping 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 propose 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

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Local EPrints ID: 363707
URI: https://eprints.soton.ac.uk/id/eprint/363707
PURE UUID: 109b5895-9232-4ba3-8e54-164695884ba7
ORCID for Michael Butler: ORCID iD orcid.org/0000-0003-4642-5373

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Date deposited: 31 Mar 2014 15:20
Last modified: 14 Jul 2018 00:36

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