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Autotuning PostgreSQL: a blueprint for successful autotuning of real-world applications

Published: 27 May 2018 Publication History

Abstract

Autotuning is a technique for optimizing the performance of sequential and parallel applications. We explore the problem of successfully applying on-line autotuning to real-world applications. We tune PostgreSQL, an open-source database server software, by optimizing tuning parameters that affect table scans. We evaluate the effects on the performance using the TPC-H benchmark and achieve speedups up to 3.9. A video subsuming the process is available at https://dx.doi.org/10.5445/DIVA/2018-192.

References

[1]
Jeff Bilmes, Krste Asanovic, Chee-Whye Chin, and Jim Demmel. 1997. Optimizing Matrix Multiply Using PHiPAC: A Portable, High-Performance, ANSI C Coding Methodology. In Proceedings of the 11th International Conference on Supercomputing (ICS '97). ACM, New York, NY, USA, 340--347.
[2]
B. K. Debnath, D. J. Lilja, and M. F. Mokbel. 2008. SARD: A Statistical Approach for Ranking Database Tuning Parameters. In 2008 IEEE 24th International Conference on Data Engineering Workshop. 11--18.
[3]
Thomas Karcher and Victor Pankratius. 2011. Run-Time Automatic Performance Tuning for Multicore Applications. In Euro-Par 2011 Parallel Processing, Emmanuel Jeannot, Raymond Namyst, and Jean Roman (Eds.). Number 6852 in Lecture Notes in Computer Science. Springer Berlin Heidelberg, 3--14.
[4]
A. Morajko, P. Caymes-Scutari, T. Margalef, and E. Luque. 2007. MATE: Monitoring, Analysis and Tuning Environment for Parallel/Distributed Applications. Concurrency and Computation: Practice and Experience 19, 11 (Aug. 2007), 1517--1531.
[5]
J. A. Neider and R. Mead. 1965. A Simplex Method for Function Minimization. Comput. J. 7, 4 (1965), 308--313.
[6]
Philip Pfaffe, Martin Tillmann, Sigmar Walter, and Walter F. Tichy. 2017. Online-Autotuning in the Presence of Algorithmic Choice. In 2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). 1379--1388.
[7]
Patrick Siarry and Zbigniew Michalewicz. 2008. Advances in Metaheuristics for Hard Optimization. (2008). http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=016716007&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA In: Springer-Online.
[8]
Cristian Ţăpuş, I-Hsin Chung, and Jeffrey K. Hollingsworth. 2002. Active Harmony: Towards Automated Performance Tuning. In Proceedings of the 2002 ACM/IEEE Conference on Supercomputing (SC '02). IEEE Computer Society Press, Los Alamitos, CA, USA, 1--11. http://dl.acm.org/citation.cfm?id=762761.762771
[9]
Transaction Processing Performance Council. 2017. TPC-H. (2017). http://www.tpc.org/tpch/

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Published In

cover image ACM Conferences
ICSE '18: Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings
May 2018
231 pages
ISBN:9781450356633
DOI:10.1145/3183440
  • Conference Chair:
  • Michel Chaudron,
  • General Chair:
  • Ivica Crnkovic,
  • Program Chairs:
  • Marsha Chechik,
  • Mark Harman
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Publication History

Published: 27 May 2018

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Author Tags

  1. PostgreSQL
  2. database
  3. heuristic
  4. on-line autotuning
  5. parameter tuning
  6. run-time optimization
  7. search-based

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Overall Acceptance Rate 276 of 1,856 submissions, 15%

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