Abstract
Abstract 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.
Highlights
Data analytics has gained prominence in recent years
The learning curve associated with it is steep, and it requires a considerable amount of expertise to use Big Data analytics
We believe that one promising solution is to enable domain experts, who are not necessarily programmers, to develop the Big Data applications by providing them with domain-specific graphical tools based on the flow-based programming paradigm [5]
Summary
Data analytics has gained prominence in recent years. developing Big Data applications is not a trivial task. We believe that one promising solution is to enable domain experts, who are not necessarily programmers, to develop the Big Data applications by providing them with domain-specific graphical tools based on the flow-based programming paradigm [5] This conceptual approach for high-level Big Data programming involves the following (see Fig. 1 for illustration of these ideas): 1. Conceptual approach aFlux implements the modular composable components selected from Big Data frameworks like Pig, Hive, Spark and Flink as actors and enables high-level Big Data programming with flow validation and automatic code generation. Installation aFlux uses Maven [17] for project management and can be installed from the Git [18] repository (codemetadata table lists all requisite information) It can be compiled on any operating system including Windows, macOS and Linux if Java 8 development environment is present. The web application can be accessed from any standard web browser including Safari, Firefox, Opera and Google Chrome
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