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QueryFormer: A Tree Transformer Model for Query Plan Representation

Summary: QueryFormer, a tree-structured Transformer, encodes query plans, addressing long information paths and parent-child dependencies. It integrates histogram statistics into plan encoding and yields improvements across four ML-based optimization tasks. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h254a7cd04217b059
Venue
VLDB
Year
2022
Pagerank
8.7533306e-05
Overall Rank
2,250 | 84.88%
DOI
10.14778/3529337.3529349

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{zhao_vldb22,
        title = {{QueryFormer: A Tree Transformer Model for Query Plan Representation}},
        author = {Zhao, Yue and Cong, Gao and Shi, Jiachen and Miao, Chunyan},
        journal = {PVLDB},
        series = {{VLDB} '22},
        volume = {15},
        number = {8},
        pages = {1658--1670},
        doi = {10.14778/3529337.3529349},
        url = {https://doi.org/10.14778/3529337.3529349},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 41 of 41 citing papers.

Rank Citing Paper Year Venue Pagerank
2,039 LLM-R^2: A Large Language Model Enhanced Rule-based Rewrite System for Boosting Query Efficiency 2025 VLDB 9.1493268e-05
4,385 R-Bot: An LLM-based Query Rewrite System 2025 VLDB 6.6235293e-05
5,481 A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies 2024 VLDB 6.1125124e-05
5,649 Sample-Efficient Cardinality Estimation Using Geometric Deep Learning 2024 VLDB 6.052326e-05
5,683 How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks 2025 SIGMOD 6.0392183e-05
5,788 Lemo: A Cache-Enhanced Learned Optimizer for Concurrent Queries 2023 SIGMOD 5.9947442e-05
6,105 Breaking It Down: An In-depth Study of Index Advisors 2024 VLDB 5.8860941e-05
7,033 Rethinking Learned Cost Models: Why Start from Scratch? 2023 SIGMOD 5.6168499e-05
7,070 E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model 2025 VLDB 5.6080535e-05
7,217 Refactoring Index Tuning Process with Benefit Estimation 2024 VLDB 5.5834823e-05
7,236 RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems 2025 VLDB 5.5790509e-05
7,460 T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees 2025 SIGMOD 5.5215755e-05
7,977 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.4142519e-05
8,332 Learned Offline Query Planning via Bayesian Optimization 2025 SIGMOD 5.3528188e-05
8,879 Spatial Query Optimization With Learning 2024 VLDB 5.2568354e-05
9,300 GenJoin: Conditional Generative Plan-to-Plan Query Optimizer that Learns from Subplan Hints 2026 SIGMOD 5.1987909e-05
9,700 Experimental Analysis of Large-scale Learnable Vector Storage Compression 2024 VLDB 5.1381949e-05
9,720 APQO: An Adaptive Framework for Parametric Query Optimization 2026 SIGMOD 5.1349531e-05
9,734 CAFE: Towards Compact, Adaptive, and Fast Embedding for Large-scale Recommendation Models 2024 SIGMOD 5.1349531e-05
9,790 Wii: Dynamic Budget Reallocation In Index Tuning 2024 SIGMOD 5.1260323e-05
9,904 AgentTune: An Agent-Based Large Language Model Framework for Database Knob Tuning 2026 SIGMOD 5.1103839e-05
9,956 Graph Transformers for Query Plan Representation: Potentials and Challenges 2025 VLDB 5.1038322e-05
10,143 Does A Fish Need a Bicycle? The Case for On-Chip NPUs in DBMS 2026 CIDR 5.0715586e-05
10,148 Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries 2025 VLDB 5.0715586e-05
10,290 This is Going to Sound Crazy, But What If We Used Large Language Models to Boost Automatic Database Tuning Algorithms By Leveraging Prior History? We Will Find Better Configurations More Quickly Than Retraining From Scratch! 2026 SIGMOD 5.0431863e-05
10,412 Are Learned DBMS Components Robust to Workload Drift?: [Experiments & Analysis] 2026 SIGMOD 4.9793485e-05
10,532 Rainbow: Risk-aware Index Benefit Estimation Facing Out Of Distribution Workloads 2026 SIGMOD 4.9793485e-05
10,604 Understanding and Detecting Query Performance Regression in Practical Index Tuning: [Experiments & Analysis] 2026 SIGMOD 4.9793485e-05
10,633 Divo: Learning a Stable and Effective Query Optimizer with a Diverse Workload 2026 SIGMOD 4.9793485e-05
10,679 Reqo: A Comprehensive Learning-Based Cost Model for Robust and Explainable Query Optimization 2026 SIGMOD 4.9793485e-05
10,698 LIO: A lightweight and interpretable query optimizer based on an evolutionary forest 2026 VLDB 4.9793485e-05
10,741 OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning 2026 VLDB 4.9793485e-05
10,919 ScaleSense: Cost-Intelligent Scaling Framework via Learned Resource Estimation in Alibaba AnalyticDB 2026 VLDB 4.9793485e-05
10,924 TATA: An Efficient Framework for Task Transfer in Query Plan Representation 2026 VLDB 4.9793485e-05
10,941 Ultron: History-Based Query Optimization at Databricks 2026 VLDB 4.9793485e-05
11,072 Libra: One-Shot Parameter Sensitivity Estimation for Transfer Learning in Database Performance Prediction 2026 VLDB 4.9793485e-05
11,224 Esc: An Early-Stopping Checker for Budget-aware Index Tuning 2025 VLDB 4.9793485e-05
11,287 AQETuner: Reliable Query-level Configuration Tuning for Analytical Query Engines 2025 VLDB 4.9793485e-05
11,425 Learned Cost Models for Query Optimization: From Batch to Streaming Systems 2025 VLDB 4.9793485e-05
11,443 LEAP: A Low-cost Spark SQL Query Optimizer using Pairwise Comparison 2025 VLDB 4.9793485e-05
11,453 RankPQO: Learning-to-Rank for Parametric Query Optimization 2025 VLDB 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 19 of 19 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061066921
85 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035864347
145 Neo: A Learned Query Optimizer 2019 VLDB 0.0002908188
187 DB2 Design Advisor: Integrated Automatic Physical Database Design 2004 VLDB 0.0002592488
362 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00019989474
386 Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors 2009 VLDB 0.00019444411
461 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.00017829982
479 The Making of TPC-DS 2006 VLDB 0.00017622471
529 Automatic SQL Tuning in Oracle 10g 2004 VLDB 0.00016866092
560 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.00016403151
701 Independence is Good: Dependency-Based Histogram Synopses for High-Dimensional Data 2001 SIGMOD 0.00014680907
1,156 QuickSel: Quick Selectivity Learning with Mixture Models 2020 SIGMOD 0.00011777105
1,279 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011226878
1,397 Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms 2020 VLDB 0.00010789242
1,542 Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses 2018 VLDB 0.00010308631
1,687 Global Optimization of Histograms 2001 SIGMOD 9.8655879e-05
2,834 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 7.9560627e-05
3,562 Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning 2021 VLDB 7.2046519e-05
3,978 Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload 2021 SIGMOD 6.8807882e-05
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