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
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,127 | Guided automated learning for query workload re-optimization | 2019 | VLDB | 4.8230386e-05 |
Previous
Page 1 / 1
Next
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 |
|---|---|---|---|---|
| 1,016 | Memory-Efficient Hash Joins | 2015 | VLDB | 0.00014638492 |
| 7,127 | Guided automated learning for query workload re-optimization | 2019 | VLDB | 4.8230386e-05 |
Previous
Page 1 / 1
Next