Dynamic Prefetching of Data Tiles for Interactive Visualization
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MIT-CSAIL-TR-2015-031.pdf
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Author(s)
Battle, Leilani
Chang, Remco
Stonebraker, Michael
Advisor(s)
Michael Stonebraker
Date Issued
October 19, 2015
Series/Report no.
MIT-CSAIL-TR-2015-031
Abstract
In this paper, we present ForeCache, a general-purpose tool for exploratory browsing of large datasets. ForeCache utilizes a client-server architecture, where the user interacts with a lightweight client-side interface to browse datasets, and the data to be browsed is retrieved from a DBMS running on a back-end server. We assume a detail-on-demand browsing paradigm, and optimize the back-end support for this paradigm by inserting a separate middleware layer in front of the DBMS. To improve response times, the middleware layer fetches data ahead of the user as she explores a dataset. We consider two different mechanisms for prefetching: (a) learning what to fetch from the user's recent movements, and (b) using data characteristics (e.g., histograms) to find data similar to what the user has viewed in the past. We incorporate these mechanisms into a single prediction engine that adjusts its prediction strategies over time, based on changes in the user's behavior. We evaluated our prediction engine with a user study, and found that our dynamic prefetching strategy provides: (1) significant improvements in overall latency when compared with non-prefetching systems (430% improvement); and (2) substantial improvements in both prediction accuracy (25% improvement) and latency (88% improvement) relative to existing prefetching techniques.
Subjects
visualization
interactive exploration
databases
Terms of Use
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
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