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Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation

Summary: Learning-based Progressive Cardinality Estimation (LPCE) combines a light LPCE-I with a refinement LPCE-R to accelerate end-to-end query execution. Runtime re-optimization uses actual operator cardinalities to refine plans, integrated into PostgreSQL and beating state-of-the-art estimators on end-to-end time. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6532
Venue
SIGMOD
Year
2023
Pagerank
4.7926382e-05
Overall Rank
7,220 | 49.83%
DOI
10.1145/3588708

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Incoming Citations (Sorted by Pagerank)

Showing 11 of 11 citing papers.

Rank Citing Paper Year Venue Pagerank
8,003 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 4.6049527e-05
8,706 nsDB: Architecting the Next Generation Database by Integrating Neural and Symbolic Systems 2024 VLDB 4.4587004e-05
8,896 SQL-Factory: A Multi-Agent Framework for High-Quality and Large-Scale SQL Generation 2026 VLDB 4.4229886e-05
9,811 A Practical Theory of Generalization in Selectivity Learning 2025 VLDB 4.2742278e-05
9,824 Athena: An Effective Learning-based Framework for Query Optimizer Performance Improvement 2025 SIGMOD 4.2710095e-05
9,959 An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL 2025 SIGMOD 4.2254157e-05
10,014 BEE: Towards Redundancy Reduction via Block-Separator Decomposition for Subgraph Matching 2026 SIGMOD 4.1905499e-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 4.1905499e-05
10,577 QOVIS: Understanding and Diagnosing Query Optimizer via a Visualization-assisted Approach 2025 VLDB 4.1905499e-05
10,872 LEAP: A Low-cost Spark SQL Query Optimizer using Pairwise Comparison 2025 VLDB 4.1905499e-05
10,876 LASER: Buffer-Aware Learned Query Scheduling in Master-Standby Databases 2025 VLDB 4.1905499e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 32 of 32 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 0.00059446482
116 Eddies: Continuously Adaptive Query Processing 2000 SIGMOD 0.00046191288
181 LEO - DB2's LEarning Optimizer 2001 VLDB 0.00036970794
203 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00034868567
221 Efficient Mid-Query Re-Optimization of Sub-Optimal Query Execution Plans 1998 SIGMOD 0.00033182072
329 Neo: A Learned Query Optimizer 2019 VLDB 0.00027301488
527 Self-tuning Histograms: Building Histograms Without Looking at Data 1999 SIGMOD 0.00020862475
606 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00019251186
634 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00018844568
650 Robust Query Processing through Progressive Optimization 2004 SIGMOD 0.0001865144
752 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00017138049
804 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.0001643674
838 Independence is Good: Dependency-Based Histogram Synopses for High-Dimensional Data 2001 SIGMOD 0.00016024923
905 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00015423174
1,104 Cardinality Estimation Done Right: Index-Based Join Sampling 2017 CIDR 0.0001398479
1,239 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00013091459
1,638 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00011050093
1,699 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00010848882
1,756 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00010659753
2,090 Balsa: Learning a Query Optimizer Without Expert Demonstrations 2022 SIGMOD 9.5668285e-05
2,222 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2019 SIGMOD 9.2598438e-05
2,364 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD 8.955077e-05
2,632 Plan Bouquets: Query Processing without Selectivity Estimation 2014 SIGMOD 8.4153283e-05
2,769 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 8.1512848e-05
2,781 Flow-Loss: Learning Cardinality Estimates That Matter 2021 VLDB 8.1282042e-05
3,455 Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation 2022 VLDB 7.0760196e-05
3,492 Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation 2021 VLDB 7.0435484e-05
3,924 A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation 2021 SIGMOD 6.6227223e-05
3,955 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 6.5895015e-05
4,543 FACE: A Normalizing Flow based Cardinality Estimator 2022 VLDB 6.0953507e-05
6,879 ROX: Run-time Optimization of XQueries 2009 SIGMOD 4.8934866e-05
7,611 Learning to be a Statistician: Learned Estimator for Number of Distinct Values 2022 VLDB 4.6920008e-05
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