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Robust Performance in Database Query Processing (Dagstuhl Seminar 17222)
Authors and all authors of the abstracts in this report
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Dagstuhl Reports, Volume 7, Issue 5
Volume: Dagstuhl Reports, Volume 7
Journal: Dagstuhl Reports (DagRep) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2017-12-21
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Renata Borovica-Gajic, Goetz Graefe, and Allison Lee. Robust Performance in Database Query Processing (Dagstuhl Seminar 17222). In Dagstuhl Reports, Volume 7, Issue 5, pp. 169-180, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)
https://doi.org/10.4230/DagRep.7.5.169
https://doi.org/10.4230/DagRep.7.5.169
Abstract
The Dagstuhl Seminar 17222 on "Robust performance in database query processing", held from 28/May until 02/June 2017, brought together researchers from academia and industry to discuss aspects of robustness in database management systems that have not been addressed by the previous instances of the seminar. This article summarizes the main discussion topics, and presents the summary of the outputs of four work groups that discussed: i) updates and database utilities, ii) parallelism, partitioning and skew, iii) dynamic join sequences, and iv) machine learning techniques used to explain unexpected performance observations.
Keywords
- Robust Query Performance
- Database Management Systems
- Adaptive Query Processing
- Query Optimization
- Query Execution
- Updates
- Parallelism
- Data Skew
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