Robust Query Driven Cardinality Estimation under Changing Workloads

Summary: Apply random masking of table/column features and introduce join-bitmaps (consistent sampling via sideways information passing) so query-driven cardinality models rely on robust DBMS statistics and tolerate unseen tables/columns and data drift. Yields strong generalization (JOBLight→JOB), up to 2× runtime improvement versus PostgreSQL, robustness to data updates, and no regressions under drift. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 13014
Venue: VLDB
Year: 2023
Pagerank: 6.2037371e-05
Overall Rank: 4,417 | 69.28%
DOI: 10.14778/3583140.3583164

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 34 of 34 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
4,593	Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift	2023	SIGMOD	6.0606891e-05
5,401	ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads	2024	VLDB	5.5285035e-05
5,832	Stage: Query Execution Time Prediction in Amazon Redshift	2024	SIGMOD	5.3111109e-05
6,383	Sample-Efficient Cardinality Estimation Using Geometric Deep Learning	2024	VLDB	5.0884322e-05
6,750	Breaking It Down: An In-depth Study of Index Advisors	2024	VLDB	4.9392771e-05
6,898	Disclosure-Compliant Query Answering	2024	SIGMOD	4.8925595e-05
7,336	Refactoring Index Tuning Process with Benefit Estimation	2024	VLDB	4.7599411e-05
7,467	Yannakakis+: Practical Acyclic Query Evaluation with Theoretical Guarantees	2025	SIGMOD	4.7218691e-05
7,828	Modeling Shifting Workloads for Learned Database Systems	2024	SIGMOD	4.6407986e-05
7,990	Blueprinting the Cloud: Unifying and Automatically Optimizing Cloud Data Infrastructures with BRAD	2024	VLDB	4.6117441e-05
8,020	The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions	2024	VLDB	4.6040862e-05
8,834	ByteCard: Enhancing ByteDance’s Data Warehouse with Learned Cardinality Estimation	2024	SIGMOD	4.4394021e-05
8,896	SQL-Factory: A Multi-Agent Framework for High-Quality and Large-Scale SQL Generation	2026	VLDB	4.427232e-05
9,345	LIMAO: A Framework for Lifelong Modular Learned Query Optimization	2025	VLDB	4.3536343e-05
9,352	Db2une: Tuning Under Pressure via Deep Learning	2024	VLDB	4.3522361e-05
9,485	Spatial Query Optimization With Learning	2024	VLDB	4.3341665e-05
9,587	Low Rank Learning for Offline Query Optimization	2025	SIGMOD	4.3215645e-05
9,728	SPACE: Cardinality Estimation for Path Queries Using Cardinality-Aware Sequence-based Learning	2025	SIGMOD	4.2942813e-05
9,812	A Practical Theory of Generalization in Selectivity Learning	2025	VLDB	4.2783272e-05
9,825	Athena: An Effective Learning-based Framework for Query Optimizer Performance Improvement	2025	SIGMOD	4.2751057e-05
9,845	Path-centric Cardinality Estimation for Subgraph Matching	2025	VLDB	4.2721228e-05
9,878	PRICE: A Pretrained Model for Cross-Database Cardinality Estimation	2025	VLDB	4.2656547e-05
9,917	Check Out the Big Brain on BRAD: Simplifying Cloud Data Processing with Learned Automated Data Meshes	2023	VLDB	4.2561557e-05
9,960	An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL	2025	SIGMOD	4.2294678e-05
10,049	Approximate Query Processing under Updates	2026	SIGMOD	4.1945683e-05
10,129	WoW: A Window-to-Window Incremental Index for Range-Filtering Approximate Nearest Neighbor Search	2026	SIGMOD	4.1945683e-05
10,217	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	4.1945683e-05
10,219	Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking	2026	SIGMOD	4.1945683e-05
10,288	TATA: An Efficient Framework for Task Transfer in Query Plan Representation	2026	VLDB	4.1945683e-05
10,619	Data-Agnostic Cardinality Learning from Imperfect Workloads	2025	VLDB	4.1945683e-05
10,630	Conformal Prediction for Verifiable Learned Query Optimization	2025	VLDB	4.1945683e-05
10,726	Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries	2025	VLDB	4.1945683e-05
10,859	Graph Transformers for Query Plan Representation: Potentials and Challenges	2025	VLDB	4.1945683e-05
10,868	LEAP: A Low-cost Spark SQL Query Optimizer using Pairwise Comparison	2025	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 30 of 30 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
71	How Good Are Query Optimizers, Really?	2016	VLDB	0.00059038975
182	LEO - DB2's LEarning Optimizer	2001	VLDB	0.00036962631
333	Neo: A Learned Query Optimizer	2019	VLDB	0.00027206884
372	Selectivity Estimation using Probabilistic Models	2001	SIGMOD	0.00025354779
429	The Aqua Approximate Query Answering System	1999	SIGMOD	0.00023476494
608	DeepDB: Learn from Data, not from Queries!	2020	VLDB	0.00019235898
629	Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors	2009	VLDB	0.00018942366
640	Bao: Making Learned Query Optimization Practical	2021	SIGMOD	0.00018759152
758	Deep Unsupervised Cardinality Estimation	2020	VLDB	0.0001706608
910	NeuroCard: One Cardinality Estimator for All Tables	2021	VLDB	0.00015423056
1,254	Selectivity Estimation for Range Predicates using Lightweight Models	2019	VLDB	0.00013027411
1,547	Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions	2011	VLDB	0.00011442359
1,638	Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation	2022	VLDB	0.00011049779
1,703	Are We Ready For Learned Cardinality Estimation?	2021	VLDB	0.00010836769
1,737	QuickSel: Quick Selectivity Learning with Mixture Models	2020	SIGMOD	0.00010720294
2,142	Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities	2019	SIGMOD	9.4507296e-05
2,364	Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries	2020	SIGMOD	8.9554751e-05
2,762	FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation	2021	VLDB	8.1585394e-05
2,783	Flow-Loss: Learning Cardinality Estimates That Matter	2021	VLDB	8.1293383e-05
2,841	Selectivity Estimation in Extensible Databases - A Neural Network Approach	1998	VLDB	8.0287389e-05
3,266	Learned Cardinality Estimation: An In-depth Study	2022	SIGMOD	7.3074684e-05
3,499	Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation	2021	VLDB	7.0376445e-05
3,725	Estimating Cardinalities with Deep Sketches	2019	SIGMOD	6.8170734e-05
3,924	A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation	2021	SIGMOD	6.6271553e-05
3,954	Efficiently Approximating Selectivity Functions using Low Overhead Regression Models	2020	VLDB	6.5926838e-05
3,990	FactorJoin: A New Cardinality Estimation Framework for Join Queries	2023	SIGMOD	6.5581983e-05
4,359	Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning	2021	VLDB	6.2569955e-05
4,523	Simplicity Done Right for Join Ordering	2021	CIDR	6.1135504e-05
5,258	One Model to Rule them All: Towards Zero-Shot Learning for Databases	2022	CIDR	5.5998705e-05
5,645	Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts	2022	SIGMOD	5.3923454e-05

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