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VisTrees: fast indexes for interactive data exploration

Muhammad El-Hindi; Zheguang Zhao; Carsten Binnig; Tim Kraska
In: Carsten Binnig; Alan D. Fekete; Arnab Nandi (Hrsg.). Proceedings of the Workshop on Human-In-the-Loop Data Analytics, HILDA@SIGMOD. Workshop on Human-In-the-Loop Data Analytics (HILDA-2016), located at SIGMOD/PODS'16, June 28, San Francisco, CA, USA, ACM, 2016.


Visualizations are arguably the most important tool to explore, understand and convey facts about data. As part of interactive data exploration, visualizations might be used to quickly skim through the data and look for patterns. Unfortunately, database systems are not designed to efficiently support these workloads. As a result, visualizations often take very long to produce, creating a significant barrier to interactive data analysis. In this paper, we focus on the interactive computation of histograms for data exploration. To address this issue, we present a novel multi-dimensional index structure called . As a key contribution, this paper presents several techniques to better align the design of multi-dimensional indexes with the needs of visualization tools for data exploration. Our experiments show that the achieves a speed increase of up to three orders of magnitude compared to traditional multi-dimensional indexes and enables an interactive speed of below 500ms even on large data sets.

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