aFlux: Graphical flow-based data analytics | Zendy

Tanmaya Mahapatra | Zendy; Christian Prehofer | Zendy

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aFlux: Graphical flow-based data analytics

Author(s) -

Tanmaya Mahapatra,

Christian Prehofer

Publication year - 2019

Publication title -

software impacts

Language(s) - English

Resource type - Journals

ISSN - 2665-9638

DOI - 10.1016/j.simpa.2019.100007

Subject(s) - computer science , big data , spark (programming language) , abstraction , analytics , programming language , programming paradigm , data flow diagram , code (set theory) , data analysis , data science , software engineering , database , data mining , philosophy , set (abstract data type) , epistemology

aFlux is a graphical flow-based programming tool designed to support the modelling of data analytics applications. It supports high-level programming of Big Data applications with early-stage flow validation and automatic code generation for frameworks like Spark, Flink, Pig and Hive. The graphical programming concepts used in aFlux constitute the first approach towards supporting high-level Big Data application development by making it independent of the target Big Data frameworks. This programming at a higher level of abstraction helps to lower the complexity and its ensued learning curve involved in the development of Big Data applications.

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