GALO: Guided Automated Learning for re-Optimization
Summary: GALO automates query performance problem determination via offline learning of common plan patterns, building a knowledge base of plan remedies. RDF/SPARQL-based knowledge base enables online re-optimization of queued queries, delivering gains. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Guilherme Damasio (IBM; Ontario Tech University)
- 2. Spencer Bryson (IBM; Ontario Tech University)
- 3. Vincent Corvinelli (IBM)
- 4. Parke Godfrey (IBM; York University)
- 5. Piotr Mierzejewski (IBM)
- 6. Jaroslaw Szlichta (IBM; Ontario Tech University)
- 7. Calisto Zuzarte (IBM)
BibTeX Citation
@article{damasio_vldb19,
title = {{GALO: Guided Automated Learning for re-Optimization}},
author = {Damasio, Guilherme and Bryson, Spencer and Corvinelli, Vincent and Godfrey, Parke and Mierzejewski, Piotr and Szlichta, Jaroslaw and Zuzarte, Calisto},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {12},
pages = {1778--1781},
doi = {10.14778/3352063.3352064},
url = {https://doi.org/10.14778/3352063.3352064},
year = {2019}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,938 | Guided automated learning for query workload re-optimization | 2019 | VLDB | 5.733869e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 959 | Memory-Efficient Hash Joins | 2015 | VLDB | 0.00012953588 |
| 6,938 | Guided automated learning for query workload re-optimization | 2019 | VLDB | 5.733869e-05 |
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