Stavros Maroulis, Nikos Bikakis, George Papastefanatos, Panos Vassiliadis, Yannis Vassiliou
In-situ processing has received a great deal of attention in recent years. In in-situ scenarios, big raw data files which do not fit in main memory, must be efficiently handled on-the-fly using commodity hardware, without the overhead of a preprocessing phase or the loading of data into a database system. This paper presents RawVis, an open source data visualization system for in-situ visual exploration and analytics over big raw data. RawVis implements novel indexing schemes and adaptive processing techniques allowing users to perform efficient visual and analytics operations directly over the data files. RawVis provides real-time interaction, reporting low response time, over large data files, using commodity hardware.
Stavros Maroulis, Nikos Bikakis, George Papastefanatos, Panos Vassiliadis, Yannis Vassiliou. RawVis: A System for Efficient In-situ Visual Analytics. Demo paper at ACM SIGMOD 2021, originally planed for Xi'an, Shaanxi, China, on June 20 - June 25, 2021.
Local copy of the paper (PDF)
The paper is part of a larger effort on interactive data exploration -- see the VisualFacts project
Online demonstration for RawVis here and here.
A 5' video presentation is available as a youtube video.
A 15' video presentation is available as a youtube video.