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A stream processing abstraction framework

Authors :
Ilaria Bartolini
Marco Patella
Source :
Frontiers in Big Data, Vol 6 (2023)
Publication Year :
2023
Publisher :
Frontiers Media S.A., 2023.

Abstract

Real-time analysis of large multimedia streams is nowadays made efficient by the existence of several Big Data streaming platforms, like Apache Flink and Samza. However, the use of such platforms is difficult due to the fact that facilities they offer are often too raw to be effectively exploited by analysts. We describe the evolution of RAM3S, a software infrastructure for the integration of Big Data stream processing platforms, to SPAF, an abstraction framework able to provide programmers with a simple but powerful API to ease the development of stream processing applications. By using SPAF, the programmer can easily implement real-time complex analyses of massive streams on top of a distributed computing infrastructure, able to manage the volume and velocity of Big Data streams, thus effectively transforming data into value.

Details

Language :
English
ISSN :
2624909X
Volume :
6
Database :
Directory of Open Access Journals
Journal :
Frontiers in Big Data
Publication Type :
Academic Journal
Accession number :
edsdoj.528b9d9cb9547dcbe43ddb3b1ea1dd4
Document Type :
article
Full Text :
https://doi.org/10.3389/fdata.2023.1227156