ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation

Summary: ASM harmonizes autoregressive per-table statistics, sampling for join merging, and multidimensional statistics merging to estimate many queries without join-key independence. This yields better plans with similar or lower overhead and wider query coverage than CE. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6854
Venue: SIGMOD
Year: 2024
Pagerank: 4.8251036e-05
Overall Rank: 7,123 | 50.45%
DOI: 10.1145/3639300

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 8 of 8 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
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
9,812	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
10,197	Qualitative Join Discovery in Data Lakes using Examples	2026	SIGMOD	4.1945683e-05
10,293	Vodka: Rethink Benchmarking Philosophy in HTAP Systems	2026	VLDB	4.1945683e-05
10,619	Data-Agnostic Cardinality Learning from Imperfect Workloads	2025	VLDB	4.1945683e-05
10,699	The Accuracy of Cardinality Estimators: Unraveling the Evaluation Result Conundrum	2025	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 35 of 35 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
204	Learned Cardinalities: Estimating Correlated Joins with Deep Learning	2019	CIDR	0.00034784455
333	Neo: A Learned Query Optimizer	2019	VLDB	0.00027206884
608	DeepDB: Learn from Data, not from Queries!	2020	VLDB	0.00019235898
640	Bao: Making Learned Query Optimization Practical	2021	SIGMOD	0.00018759152
758	Deep Unsupervised Cardinality Estimation	2020	VLDB	0.0001706608
790	Exploiting Statistics on Query Expressions for Optimization	2002	SIGMOD	0.0001663283
806	An End-to-End Learning-based Cost Estimator	2020	VLDB	0.00016434274
910	NeuroCard: One Cardinality Estimator for All Tables	2021	VLDB	0.00015423056
943	Wander Join: Online Aggregation via Random Walks	2016	SIGMOD	0.00015145883
1,105	Cardinality Estimation Done Right: Index-Based Join Sampling	2017	CIDR	0.00013990395
1,193	Join Size Estimation Subject to Filter Conditions	2015	VLDB	0.00013414989
1,254	Selectivity Estimation for Range Predicates using Lightweight Models	2019	VLDB	0.00013027411
1,333	Optimizing Subgraph Queries by Combining Binary and Worst-Case Optimal Joins	2019	VLDB	0.00012523806
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
2,249	Orca: A Modular Query Optimizer Architecture for Big Data	2014	SIGMOD	9.2034693e-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
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
3,646	G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching	2020	SIGMOD	6.8853079e-05
3,924	A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation	2021	SIGMOD	6.6271553e-05
3,990	FactorJoin: A New Cardinality Estimation Framework for Join Queries	2023	SIGMOD	6.5581983e-05
4,523	Simplicity Done Right for Join Ordering	2021	CIDR	6.1135504e-05
4,543	FACE: A Normalizing Flow based Cardinality Estimator	2022	VLDB	6.1011198e-05
5,423	Kepler: Robust Learning for Faster Parametric Query Optimization	2023	SIGMOD	5.5130233e-05
5,645	Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts	2022	SIGMOD	5.3923454e-05
5,972	SafeBound: A Practical System for Generating Cardinality Bounds	2023	SIGMOD	5.2474768e-05
6,368	Pre-training Summarization Models of Structured Datasets for Cardinality Estimation	2022	VLDB	5.0937722e-05
9,107	NeuroSketch: Fast and Approximate Evaluation of Range Aggregate Queries with Neural Networks	2023	SIGMOD	4.3950706e-05
9,662	Efficient Query Re-optimization with Judicious Subquery Selections	2023	SIGMOD	4.3097631e-05
9,869	Turbo-Charging SPJ Query Plans with Learned Physical Join Operator Selections	2022	VLDB	4.2675361e-05

Semantically Similar Papers

Overall Rank	Paper	Year	Venue	Pagerank
7,221	Speeding Up End-to-end Query Execution via Learning-based Progressive Cardinality Estimation	2023	SIGMOD	4.797194e-05
684	Towards a Robust Query Optimizer: A Principled and Practical Approach	2005	SIGMOD	0.00018179769
7,358	Weighted Distinct Sampling: Cardinality Estimation for SPJ Queries	2021	SIGMOD	4.7529363e-05
204	Learned Cardinalities: Estimating Correlated Joins with Deep Learning	2019	CIDR	0.00034784455
8,697	Convolution and Cross-Correlation of Count Sketches Enables Fast Cardinality Estimation of Multi-Join Queries	2024	SIGMOD	4.4657888e-05
3,990	FactorJoin: A New Cardinality Estimation Framework for Join Queries	2023	SIGMOD	6.5581983e-05
3,013	Cardinality Estimation Using Sample Views with Quality Assurance	2007	SIGMOD	7.7137441e-05
1,703	Are We Ready For Learned Cardinality Estimation?	2021	VLDB	0.00010836769
3,449	Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation	2022	VLDB	7.0824319e-05
1,105	Cardinality Estimation Done Right: Index-Based Join Sampling	2017	CIDR	0.00013990395