A stream processing abstraction framework

被引:0
|
作者
Bartolini, Ilaria [1 ]
Patella, Marco [1 ]
机构
[1] Univ Bologna, Dept Comp Sci & Engn DISI, Alma Mater Studiorum, Bologna, Italy
来源
FRONTIERS IN BIG DATA | 2023年 / 6卷
关键词
stream processing; real-time analysis; Big Data; multimedia data streams; software framework;
D O I
10.3389/fdata.2023.1227156
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:15
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