2026-09-19T03:03:01Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1060132026-06-06T00:55:13Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Michael Stonebraker.
Gupta, Ankush M
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2016-12-22T15:18:34Z
2016-12-22T15:18:34Z
2016
2016
http://hdl.handle.net/1721.1/106013
965828774
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 (pages 47-48).
Duggan et al.have created a reference implementation of the BigDAWG system: a new architecture for future Big Data applications, guided by the philosophy that "one size does not fit all." Such applications not only call for large-scale analytics, but also for real-time streaming support, smaller analytics at interactive speeds, data visualization, and cross-storage-system queries. The importance and effectiveness of such a system has been demonstrated in a hospital application using data from an intensive care unit (ICU). In this report, we implement and evaluate a concrete version of a cross-system Query Executor and its interface with a cross-system Query Planner. In particular, we focus on cross-engine shuffle joins within the BigDAWG system.
by Ankush M. Gupta.
M.Eng.
48 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.
Cross-engine query execution in federated database systems
Thesis
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<Abstract>Duggan et al.have created a reference implementation of the BigDAWG system: a new architecture for future Big Data applications, guided by the philosophy that "one size does not fit all." Such applications not only call for large-scale analytics, but also for real-time streaming support, smaller analytics at interactive speeds, data visualization, and cross-storage-system queries. The importance and effectiveness of such a system has been demonstrated in a hospital application using data from an intensive care unit (ICU). In this report, we implement and evaluate a concrete version of a cross-system Query Executor and its interface with a cross-system Query Planner. In particular, we focus on cross-engine shuffle joins within the BigDAWG system.</Abstract>
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