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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Mahapatra, Tanmaya | - |
dc.date.accessioned | 2024-05-09T03:56:59Z | - |
dc.date.available | 2024-05-09T03:56:59Z | - |
dc.date.issued | 2019-11 | - |
dc.identifier.uri | https://www.sciencedirect.com/science/article/pii/S2665963819300077 | - |
dc.identifier.uri | http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/14782 | - |
dc.description.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. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Flow-Based Programming | en_US |
dc.subject | Graphical Pipelines | en_US |
dc.subject | Mashup tools | en_US |
dc.subject | Graphical Spark Programming | en_US |
dc.subject | Graphical Flink programming | en_US |
dc.title | aFlux: Graphical flow-based data analytics | en_US |
dc.type | Article | en_US |
Appears in Collections: | Department of Computer Science and Information Systems |
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