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dc.contributor.authorBailis, Peter
dc.contributor.authorGan, Edward
dc.contributor.authorMadden, Samuel
dc.contributor.authorNarayanan, Deepak
dc.contributor.authorRong, Kexin
dc.contributor.authorSuri, Sahaana
dc.date.accessioned2021-11-08T20:13:09Z
dc.date.available2021-11-08T20:13:09Z
dc.date.issued2017-05
dc.identifier.urihttps://hdl.handle.net/1721.1/137811
dc.description.abstractAs data volumes continue to rise, manual inspection is becoming increasingly untenable. In response, we present MacroBase, a data analytics engine that prioritizes end-user attention in high-volume fast data streams. MacroBase enables efficient, accurate, and modular analyses that highlight and aggregate important and unusual behavior, acting as a search engine for fast data. MacroBase is able to deliver order-of-magnitude speedups over alternatives by optimizing the combination of explanation and classification tasks and by leveraging a new reservoir sampler and heavy-hitters sketch specialized for fast data streams. As a result, MacroBase delivers accurate results at speeds of up to 2M events per second per query on a single core. The system has delivered meaningful results in production, including at a telematics company monitoring hundreds of thousands of vehicles,en_US
dc.language.isoen
dc.publisherAssociation for Computing Machinery (ACM)en_US
dc.relation.isversionof10.1145/3035918.3035928en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcewebsiteen_US
dc.titleMacroBase: Prioritizing Attention in Fast Dataen_US
dc.typeArticleen_US
dc.identifier.citationBailis, Peter, Gan, Edward, Madden, Samuel, Narayanan, Deepak, Rong, Kexin et al. 2017. "MacroBase: Prioritizing Attention in Fast Data."
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2019-06-18T14:50:28Z
dspace.date.submission2019-06-18T14:50:34Z
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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