Dynamic reduction of query result sets for interactive visualizaton
Name
Stonebraker_Dynamic reduction.pdf
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1.65 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Battle, Leilani
Stonebraker, Michael
Chang, Remco
Date Issued
October 2013
Journal
2013 IEEE International Conference on Big Data
Citation
Battle, Leilani, Michael Stonebraker, and Remco Chang. “Dynamic Reduction of Query Result Sets for Interactive Visualizaton.” 2013 IEEE International Conference on Big Data (October 6-9, 2013) Silicon Valley, CA. IEEE. p.1-8.
Version
Original manuscript
Abstract
Modern database management systems (DBMS) have been designed to efficiently store, manage and perform computations on massive amounts of data. In contrast, many existing visualization systems do not scale seamlessly from small data sets to enormous ones. We have designed a three-tiered visualization system called ScalaR to deal with this issue. ScalaR dynamically performs resolution reduction when the expected result of a DBMS query is too large to be effectively rendered on existing screen real estate. Instead of running the original query, ScalaR inserts aggregation, sampling or filtering operations to reduce the size of the result. This paper presents the design and implementation of ScalaR, and shows results for an example application, displaying satellite imagery data stored in SciDB as the back-end DBMS.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/BigData.2013.6691708
