Incremental Query Optimizer Statistics in Amazon Redshift
Summary: Amazon Redshift introduces sketch-based incremental optimizer statistics, updating only modified data rather than rescanning petabyte-scale tables. Production deployment cuts weekly statistics-collection compute by 40% while preserving or improving plan and ML-prediction accuracy. (summarized by gpt-5.6-luna on Aug 28 2026)
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Authors
- 1. Pascal Pfeil (Amazon)
- 2. Zhe Heng Eng (Amazon)
- 3. Magnus Müller (Amazon)
- 4. George Erickson (Amazon)
- 5. Roger Kim (Amazon)
- 6. Mohammed Al-Kateb (Amazon)
- 7. Majid Saeedan (Amazon)
- 8. Dominik Horn (Amazon)
- 9. Orestis Polychroniou (Amazon)
- 10. Mengchu Cai (Amazon)
- 11. Tim Kraska (Massachusetts Institute of Technology)
BibTeX Citation
@article{pfeil_vldb26,
title = {{Incremental Query Optimizer Statistics in Amazon Redshift}},
author = {Pfeil, Pascal and Eng, Zhe Heng and Müller, Magnus and Erickson, George and Kim, Roger and Al-Kateb, Mohammed and Saeedan, Majid and Horn, Dominik and Polychroniou, Orestis and Cai, Mengchu and Kraska, Tim},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {12},
pages = {3941--3954},
doi = {10.14778/3827998.3828007},
url = {https://doi.org/10.14778/3827998.3828007},
year = {2026}
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