An incremental approach for real-time Big Data visual analytics

被引：3
|
作者：
Garcia, Ignacio [1 ]
Casado, Ruben [1 ]
Bouchachia, Abdelhamid [2 ]
机构：
[1] Treelogic, Dept Res & Innovat, Asturias, Spain
[2] Bournemouth Univ, Dept Comp, Machine Intelligence Grp, Poole BH12 5BB, Dorset, England
来源：
2016 IEEE 4TH INTERNATIONAL CONFERENCE ON FUTURE INTERNET OF THINGS AND CLOUD WORKSHOPS (FICLOUDW) | 2016年
关键词：
big data; streaming processing; visualization; incremental computation;
D O I：
10.1109/W-FiCloud.2016.46
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In the age of Big Data, the real-time interactive visualization is a challenge due to latency of executing calculation over terabytes (even, petabytes) datasets. The execution of an operation has to finish before its outcome is displayed, which would be an issue in those scenarios where low-latency responses are required. To address such a requirement, this paper introduces a new approach for real-time visualization of extremely large data-at-rest as well as data-in-motion by showing intermediate results as soon as they become available. This should allow the data analyst to take decisions in real-time.
引用
收藏
页码：177 / 182
页数：6
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