Emergent models, frameworks, and hardware technologies for Big data analytics

被引：5
|
作者：
Groppe, Sven [1 ]
机构：
[1] Univ Lubeck, Inst Informat Syst, Ratzeburger Allee 160, D-23562 Lubeck, Germany
来源：
JOURNAL OF SUPERCOMPUTING | 2020年 / 76卷 / 03期
关键词：
Big data; Computer architectures; FPGA; GPU; Cloud Computing; Fog Computing; Dew Computing; Semantic Web; RDF; INTERNET;
D O I：
10.1007/s11227-018-2277-x
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Today's state-of-the-art Big data analytics engines handle masses of data, but will reach to their limits, as the future Big data flood is predicted to still grow with an increasing speed. Hence we need to think about the next development phase and future features of Big data analytics engines. In this paper, we discuss possible future enhancements in the area of Big data analytics with focus on emergent models, frameworks, and hardware technologies. We point out a selection of new challenges and open research questions.
引用
收藏
页码：1800 / 1827
页数：28
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