| 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 |