Interactive visualization of big data leveraging databases for scalable computation
Name
868904018-MIT.pdf
Description
Full printable version
Size
4.72 MB
Format
Adobe PDF
Checksum (MD5)
2df54b6d2ad4d8a0b0b4a4525fc4ec86
Author(s)
Battle, Leilani Marie
Advisor(s)
Michael R. Stonebraker and Samuel R. Madden.
Date Issued
2013
Publisher
Massachusetts Institute of Technology
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 thesis presents the design and implementation of ScalaR, and shows results for two example applications, visualizing earthquake records and satellite imagery data, stored in SciDB as the back-end DBMS.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 55-57).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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