DBScholar

Back to papers

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
12857
Venue
VLDB
Year
2022
Pagerank
8.7022189e-05
Overall Rank
2,355 | 83.85%
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 39 of 39 citing papers.

Rank Citing Paper Year Venue Pagerank
2,553 LLM-R^2: A Large Language Model Enhanced Rule-based Rewrite System for Boosting Query Efficiency 2025 VLDB 8.4283807e-05
5,701 Lemo: A Cache-Enhanced Learned Optimizer for Concurrent Queries 2023 SIGMOD 6.1167049e-05
5,712 Sample-Efficient Cardinality Estimation Using Geometric Deep Learning 2024 VLDB 6.1123894e-05
5,767 A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies 2024 VLDB 6.0945741e-05
6,088 How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks 2025 SIGMOD 5.9813965e-05
6,259 R-Bot: An LLM-based Query Rewrite System 2025 VLDB 5.93967e-05
6,327 Breaking It Down: An In-depth Study of Index Advisors 2024 VLDB 5.9124005e-05
6,921 Rethinking Learned Cost Models: Why Start from Scratch? 2023 SIGMOD 5.7388557e-05
6,997 E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model 2025 VLDB 5.7300324e-05
7,076 Refactoring Index Tuning Process with Benefit Estimation 2024 VLDB 5.7098893e-05
7,825 RCRank: Multimodal Ranking of Root Causes of Slow Queries in Cloud Database Systems 2025 VLDB 5.5367884e-05
7,846 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.5331459e-05
8,163 Learned Offline Query Planning via Bayesian Optimization 2025 SIGMOD 5.4751517e-05
8,572 T3: Accurate and Fast Performance Prediction for Relational Database Systems With Compiled Decision Trees 2025 SIGMOD 5.4102362e-05
9,520 Experimental Analysis of Large-scale Learnable Vector Storage Compression 2024 VLDB 5.2561283e-05
9,556 CAFE: Towards Compact, Adaptive, and Fast Embedding for Large-scale Recommendation Models 2024 SIGMOD 5.2528121e-05
9,615 Wii: Dynamic Budget Reallocation In Index Tuning 2024 SIGMOD 5.2436464e-05
9,626 Spatial Query Optimization With Learning 2024 VLDB 5.2434488e-05
10,130 Does A Fish Need a Bicycle? The Case for On-Chip NPUs in DBMS 2026 CIDR 5.093636e-05
10,196 Are Learned DBMS Components Robust to Workload Drift?: [Experiments & Analysis] 2026 SIGMOD 5.093636e-05
10,316 GenJoin: Conditional Generative Plan-to-Plan Query Optimizer that Learns from Subplan Hints 2026 SIGMOD 5.093636e-05
10,327 Rainbow: Risk-aware Index Benefit Estimation Facing Out Of Distribution Workloads 2026 SIGMOD 5.093636e-05
10,340 AgentTune: An Agent-Based Large Language Model Framework for Database Knob Tuning 2026 SIGMOD 5.093636e-05
10,343 APQO: An Adaptive Framework for Parametric Query Optimization 2026 SIGMOD 5.093636e-05
10,413 Understanding and Detecting Query Performance Regression in Practical Index Tuning: [Experiments & Analysis] 2026 SIGMOD 5.093636e-05
10,445 Divo: Learning a Stable and Effective Query Optimizer with a Diverse Workload 2026 SIGMOD 5.093636e-05
10,492 Reqo: A Comprehensive Learning-Based Cost Model for Robust and Explainable Query Optimization 2026 SIGMOD 5.093636e-05
10,506 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 5.093636e-05
10,513 LIO: A lightweight and interpretable query optimizer based on an evolutionary forest 2026 VLDB 5.093636e-05
10,559 OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning 2026 VLDB 5.093636e-05
10,586 TATA: An Efficient Framework for Task Transfer in Query Plan Representation 2026 VLDB 5.093636e-05
10,626 Libra: One-Shot Parameter Sensitivity Estimation for Transfer Learning in Database Performance Prediction 2026 VLDB 5.093636e-05
10,815 Esc: An Early-Stopping Checker for Budget-aware Index Tuning 2025 VLDB 5.093636e-05
10,886 AQETuner: Reliable Query-level Configuration Tuning for Analytical Query Engines 2025 VLDB 5.093636e-05
10,969 Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries 2025 VLDB 5.093636e-05
11,065 Learned Cost Models for Query Optimization: From Batch to Streaming Systems 2025 VLDB 5.093636e-05
11,083 Graph Transformers for Query Plan Representation: Potentials and Challenges 2025 VLDB 5.093636e-05
11,091 LEAP: A Low-cost Spark SQL Query Optimizer using Pairwise Comparison 2025 VLDB 5.093636e-05
11,103 RankPQO: Learning-to-Rank for Parametric Query Optimization 2025 VLDB 5.093636e-05
Previous Page 1 / 1 Next

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
18 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059284255
84 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035838391
154 Neo: A Learned Query Optimizer 2019 VLDB 0.00028726181
184 DB2 Design Advisor: Integrated Automatic Physical Database Design 2004 VLDB 0.00026256101
378 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00019638121
388 Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors 2009 VLDB 0.00019410042
465 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.0001803934
476 The Making of TPC-DS 2006 VLDB 0.00017860667
524 Automatic SQL Tuning in Oracle 10g 2004 VLDB 0.00017120666
563 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.0001650812
692 Independence is Good: Dependency-Based Histogram Synopses for High-Dimensional Data 2001 SIGMOD 0.00014919816
1,170 QuickSel: Quick Selectivity Learning with Mixture Models 2020 SIGMOD 0.00011827259
1,279 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011361878
1,481 Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms 2020 VLDB 0.00010644613
1,536 Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses 2018 VLDB 0.00010460864
1,668 Global Optimization of Histograms 2001 SIGMOD 0.00010057026
2,822 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 8.0898536e-05
3,545 Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning 2021 VLDB 7.3249967e-05
3,953 Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload 2021 SIGMOD 6.996368e-05
Previous Page 1 / 1 Next

Semantically Similar Papers