A stream processing abstraction framework

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...

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Published in:Frontiers in Big Data
Main Authors: Ilaria Bartolini, Marco Patella
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-10-01
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fdata.2023.1227156/full
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author Ilaria Bartolini
Marco Patella
author_facet Ilaria Bartolini
Marco Patella
author_sort Ilaria Bartolini
collection DOAJ
container_title Frontiers in Big Data
description 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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spelling doaj-art-e528b9d9cb9547dcbe43ddb3b1ea1dd42025-08-19T21:41:32ZengFrontiers Media S.A.Frontiers in Big Data2624-909X2023-10-01610.3389/fdata.2023.12271561227156A stream processing abstraction frameworkIlaria BartoliniMarco PatellaReal-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.https://www.frontiersin.org/articles/10.3389/fdata.2023.1227156/fullstream processingreal-time analysisBig Datamultimedia data streamssoftware framework
spellingShingle Ilaria Bartolini
Marco Patella
A stream processing abstraction framework
stream processing
real-time analysis
Big Data
multimedia data streams
software framework
title A stream processing abstraction framework
title_full A stream processing abstraction framework
title_fullStr A stream processing abstraction framework
title_full_unstemmed A stream processing abstraction framework
title_short A stream processing abstraction framework
title_sort stream processing abstraction framework
topic stream processing
real-time analysis
Big Data
multimedia data streams
software framework
url https://www.frontiersin.org/articles/10.3389/fdata.2023.1227156/full
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