2026-09-18T20:55:22Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1059422026-06-06T00:49:00Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Michael R. Stonebraker.
Chen, Peinan
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2016-12-22T15:15:47Z
2016-12-22T15:15:47Z
2016
2016
http://hdl.handle.net/1721.1/105942
965198906
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (page 44).
In this thesis, I designed and implemented a monitoring framework for the BigDawg federated database system which maintains performance information on benchmark queries. As environmental conditions change, the monitoring framework updates existing performance information to match current conditions. Using this information, the monitoring system can determine the optimal query execution plan for similar incoming queries. A series of test queries were run to assess whether the system correctly determines the optimal plans for such queries.
by Peinan Chen.
M.Eng.
44 pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
The BigDawg monitoring framework
Thesis
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