The BigDawg monitoring framework
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
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| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2016
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| Online Access: | http://hdl.handle.net/1721.1/105942 |
| _version_ | 1826192284135194624 |
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| author | Chen, Peinan |
| author2 | Michael R. Stonebraker. |
| author_facet | Michael R. Stonebraker. Chen, Peinan |
| author_sort | Chen, Peinan |
| collection | MIT |
| description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016. |
| first_indexed | 2024-09-23T09:09:08Z |
| format | Thesis |
| id | mit-1721.1/105942 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T09:09:08Z |
| publishDate | 2016 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1059422019-04-10T21:03:11Z The BigDawg monitoring framework Chen, Peinan Michael R. Stonebraker. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. 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. 2016-12-22T15:15:47Z 2016-12-22T15:15:47Z 2016 2016 Thesis http://hdl.handle.net/1721.1/105942 965198906 eng 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 44 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Chen, Peinan The BigDawg monitoring framework |
| title | The BigDawg monitoring framework |
| title_full | The BigDawg monitoring framework |
| title_fullStr | The BigDawg monitoring framework |
| title_full_unstemmed | The BigDawg monitoring framework |
| title_short | The BigDawg monitoring framework |
| title_sort | bigdawg monitoring framework |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/105942 |
| work_keys_str_mv | AT chenpeinan thebigdawgmonitoringframework AT chenpeinan bigdawgmonitoringframework |