Show simple item record

dc.contributor.authorBattle, Leilani
dc.contributor.authorStonebraker, Michael
dc.contributor.authorChang, Remco
dc.date.accessioned2014-10-09T18:58:40Z
dc.date.available2014-10-09T18:58:40Z
dc.date.issued2013-10
dc.identifier.isbn978-1-4799-1293-3
dc.identifier.otherINSPEC Accession Number: 13999124
dc.identifier.urihttp://hdl.handle.net/1721.1/90853
dc.description.abstractModern 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.en_US
dc.language.isoen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/BigData.2013.6691708en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceMIT web domainen_US
dc.titleDynamic reduction of query result sets for interactive visualizatonen_US
dc.typeArticleen_US
dc.identifier.citationBattle, 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.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorBattle, Leilanien_US
dc.contributor.mitauthorStonebraker, Michaelen_US
dc.relation.journal2013 IEEE International Conference on Big Dataen_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsBattle, Leilani; Stonebraker, Michael; Chang, Remcoen_US
dc.identifier.orcidhttps://orcid.org/0000-0001-9184-9058
dc.identifier.orcidhttps://orcid.org/0000-0003-3870-636X
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record