SkinnerDB

Author:

Trummer Immanuel1,Wang Junxiong1,Maram Deepak1,Moseley Samuel1,Jo Saehan1,Antonakakis Joseph1

Affiliation:

1. Cornell University, Ithaca, NY, USA

Publisher

ACM

Reference48 articles.

1. A. Aboulnaga P. Haas M. Kandil S. Lightstone G. Lohman V. Markl I. Popivanov and V. Raman. 2004. Automated statistics collection in DB2 UDB. In PVLDB. 1169--1180. A. Aboulnaga P. Haas M. Kandil S. Lightstone G. Lohman V. Markl I. Popivanov and V. Raman. 2004. Automated statistics collection in DB2 UDB. In PVLDB. 1169--1180.

2. Mert Akdere and Ugur Cetintemel. 2011. Learning-based query performance modeling and predection. In ICDE. 390--401. ftp://ftp.cs.brown.edu/pub/techreports/11/cs11-01.pdf 10.1109/ICDE.2012.64 Mert Akdere and Ugur Cetintemel. 2011. Learning-based query performance modeling and predection. In ICDE. 390--401. ftp://ftp.cs.brown.edu/pub/techreports/11/cs11-01.pdf 10.1109/ICDE.2012.64

3. Khaled H Alyoubi Sven Helmer and Peter T Wood. 2015. Ordering selection operators under partial ignorance.. In CIKM . 1521--1530. arxiv: 1507.08257 Khaled H Alyoubi Sven Helmer and Peter T Wood. 2015. Ordering selection operators under partial ignorance.. In CIKM . 1521--1530. arxiv: 1507.08257

4. Ron Avnur and Jm Hellerstein. 2000. Eddies: continuously adaptive query processing . In SIGMOD. 261--272. 10.1145/335191.335420 Ron Avnur and Jm Hellerstein. 2000. Eddies: continuously adaptive query processing . In SIGMOD. 261--272. 10.1145/335191.335420

5. Brian Babcock and S Chaudhuri. 2005. Towards a robust query optimizer: a principled and practical approach. In SIGMOD . 119--130. http://dl.acm.org/citation.cfm?id=1066172 10.1145/1066157.1066172 Brian Babcock and S Chaudhuri. 2005. Towards a robust query optimizer: a principled and practical approach. In SIGMOD . 119--130. http://dl.acm.org/citation.cfm?id=1066172 10.1145/1066157.1066172

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1. DB-BERT: making database tuning tools “read” the manual;The VLDB Journal;2023-12-27

2. A Learned Query Rewrite System;Proceedings of the VLDB Endowment;2023-08

3. Join Order Selection with Deep Reinforcement Learning: Fundamentals, Techniques, and Challenges;Proceedings of the VLDB Endowment;2023-08

4. ADOPT: Adaptively Optimizing Attribute Orders for Worst-Case Optimal Join Algorithms via Reinforcement Learning;Proceedings of the VLDB Endowment;2023-07

5. Exploiting Access Pattern Characteristics for Join Reordering;Proceedings of the 19th International Workshop on Data Management on New Hardware;2023-06-18

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