A stream processing abstraction framework.

Front Big Data

Department of Computer Science and Engineering (DISI), Alma Mater Studiorum, University of Bologna, Bologna, Italy.

Published: October 2023

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10634501PMC
http://dx.doi.org/10.3389/fdata.2023.1227156DOI Listing

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