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...
| Published in: | Frontiers in Big Data |
|---|---|
| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-10-01
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| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fdata.2023.1227156/full |
| _version_ | 1852649968172531712 |
|---|---|
| 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. |
| format | Article |
| id | doaj-art-e528b9d9cb9547dcbe43ddb3b1ea1dd4 |
| institution | Directory of Open Access Journals |
| issn | 2624-909X |
| language | English |
| publishDate | 2023-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| 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 |
| work_keys_str_mv | AT ilariabartolini astreamprocessingabstractionframework AT marcopatella astreamprocessingabstractionframework AT ilariabartolini streamprocessingabstractionframework AT marcopatella streamprocessingabstractionframework |
