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Bao: Making Learned Query Optimization Practical
Summary: Bao is a bandit-based learned optimizer atop optimizers, offering per-query hints via Thompson sampling and tree-CNNs. Adapts to workload, data, and schema changes, improving end-to-end and tail latency; cloud tests show cost reductions and stronger performance.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 6119
- Venue
- SIGMOD
- Year
- 2021
- Pagerank
- 0.00018844568
- Overall Rank
- 634 | 95.60%
- DOI
-
10.1145/3448016.3452838
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 20 of 120 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 10,282 |
Toward Drift-Aware Database Benchmarking |
2026 |
VLDB |
4.1905499e-05 |
| 10,300 |
TATA: An Efficient Framework for Task Transfer in Query Plan Representation |
2026 |
VLDB |
4.1905499e-05 |
| 10,501 |
Intra-Query Runtime Elasticity for Cloud-Native Data Analysis |
2025 |
SIGMOD |
4.1905499e-05 |
| 10,573 |
PlanRGCN: Predicting SPARQL Query Performance |
2025 |
VLDB |
4.1905499e-05 |
| 10,577 |
QOVIS: Understanding and Diagnosing Query Optimizer via a Visualization-assisted Approach |
2025 |
VLDB |
4.1905499e-05 |
| 10,638 |
Conformal Prediction for Verifiable Learned Query Optimization |
2025 |
VLDB |
4.1905499e-05 |
| 10,641 |
AQETuner: Reliable Query-level Configuration Tuning for Analytical Query Engines |
2025 |
VLDB |
4.1905499e-05 |
| 10,733 |
Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries |
2025 |
VLDB |
4.1905499e-05 |
| 10,757 |
PAR2QO: Parametric Penalty-Aware Robust Query Optimization |
2025 |
VLDB |
4.1905499e-05 |
| 10,778 |
veDB-HTAP: a Highly Integrated, Efficient and Adaptive HTAP System |
2025 |
VLDB |
4.1905499e-05 |
| 10,784 |
GRewriter: Practical Query Rewriting with Automatic Rule Set Expansion in GaussDB |
2025 |
VLDB |
4.1905499e-05 |
| 10,844 |
Learned Cost Models for Query Optimization: From Batch to Streaming Systems |
2025 |
VLDB |
4.1905499e-05 |
| 10,863 |
Graph Transformers for Query Plan Representation: Potentials and Challenges |
2025 |
VLDB |
4.1905499e-05 |
| 10,872 |
LEAP: A Low-cost Spark SQL Query Optimizer using Pairwise Comparison |
2025 |
VLDB |
4.1905499e-05 |
| 10,884 |
RankPQO: Learning-to-Rank for Parametric Query Optimization |
2025 |
VLDB |
4.1905499e-05 |
| 11,002 |
Towards Full Stack Adaptivity in Permissioned Blockchains |
2024 |
VLDB |
4.1905499e-05 |
| 11,087 |
Presto’s History-based Query Optimizer |
2024 |
VLDB |
4.1905499e-05 |
| 11,238 |
AdaChain: A Learned Adaptive Blockchain |
2023 |
VLDB |
4.1905499e-05 |
| 11,320 |
Can Transfer Learning be used to build a Query Optimizer? |
2022 |
CIDR |
4.1905499e-05 |
| 11,352 |
DeepO: A Learned Query Optimizer |
2022 |
SIGMOD |
4.1905499e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 20 of 20 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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