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dc.contributor.advisorStonebraker, Michael
dc.contributor.authorWoicik, Matthew
dc.date.accessioned2022-01-14T14:49:43Z
dc.date.available2022-01-14T14:49:43Z
dc.date.issued2021-06
dc.date.submitted2021-06-17T20:14:48.202Z
dc.identifier.urihttps://hdl.handle.net/1721.1/139097
dc.description.abstractMany cloud databases separate their compute from their storage resources. This design introduces a network bottleneck during query execution that can be mitigated through caching and computation pushdown. Depending on the environmental settings and the specific query, the amount of computation pushdown needed to achieve the optimal runtime may vary. This work presents a runtime prediction model that determines the amount of computation pushdown that results in the fastest runtime and analyzes a real-world implementation of this model on the FlexPushdownDB system running in AWS.
dc.publisherMassachusetts Institute of Technology
dc.rightsIn Copyright - Educational Use Permitted
dc.rightsCopyright MIT
dc.rights.urihttp://rightsstatements.org/page/InC-EDU/1.0/
dc.titleDetermining the Optimal Amount of Computation Pushdown to Minimize Runtime for a Cloud Database
dc.typeThesis
dc.description.degreeM.Eng.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
mit.thesis.degreeMaster
thesis.degree.nameMaster of Engineering in Electrical Engineering and Computer Science


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