Big Data technologies are rapidly becoming a key enabler for modern industries. However, the entry costs inherent to "going Big" are considerable, ranging from learning curve, renting/buying infrastructure, etc. A key component of these costs is the time spent on learning about and designing with the many big data frameworks (e.g., Spark, Storm, HadoopMR, etc.) on the market. To reduce said costs while decreasing time-to-market we advocate the usage of Model-Driven Engineering (MDE), i.e., software engineering by means of models and their automated manipulation. This paper outlines a tool architecture to support MDE for big data applications, illustrating with a case-study.

Towards a model-driven design tool for big data architectures

Guerriero, Michele;TAJFAR, SAEED;Tamburri, Damian A.;Di Nitto, Elisabetta
2016-01-01

Abstract

Big Data technologies are rapidly becoming a key enabler for modern industries. However, the entry costs inherent to "going Big" are considerable, ranging from learning curve, renting/buying infrastructure, etc. A key component of these costs is the time spent on learning about and designing with the many big data frameworks (e.g., Spark, Storm, HadoopMR, etc.) on the market. To reduce said costs while decreasing time-to-market we advocate the usage of Model-Driven Engineering (MDE), i.e., software engineering by means of models and their automated manipulation. This paper outlines a tool architecture to support MDE for big data applications, illustrating with a case-study.
2016
2016 IEEE/ACM 2nd International Workshop on Big Data Software Engineering (BIGDSE)
9781450341523
Big Data Applications Design; MDE; meta-models; model transformation; architecture framework; design tool
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1061464
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