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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
h65a232b036d1f7de
Venue
SIGMOD
Year
2024
Pagerank
5.6513231e-05
Overall Rank
6,840 | 54.16%
DOI
10.1145/3639300

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{kim_sigmod24,
        title = {{ASM: Harmonizing Autoregressive Model, Sampling, and Multi-dimensional Statistics Merging for Cardinality Estimation}},
        author = {Kim, Kyoungmin and Lee, Sangoh and Kim, Injung and Han, Wook-Shin},
        series = {{SIGMOD} '24},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3639300},
        url = {https://dl.acm.org/doi/10.1145/3639300},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 8 of 8 citing papers.

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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
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061463175
84 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035920657
142 Neo: A Learned Query Optimizer 2019 VLDB 0.00029114937
320 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021128745
355 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00020146245
405 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019020138
453 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.0001801482
508 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017108973
594 Wander Join: Online Aggregation via Random Walks 2016 SIGMOD 0.00015814493
646 Exploiting Statistics on Query Expressions for Optimization 2002 SIGMOD 0.00015166402
689 Cardinality Estimation Done Right: Index-Based Join Sampling 2017 CIDR 0.00014725904
690 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014703258
706 Optimizing Subgraph Queries by Combining Binary and Worst-Case Optimal Joins 2019 VLDB 0.00014622696
752 Join Size Estimation Subject to Filter Conditions 2015 VLDB 0.00014234789
983 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00012677179
1,064 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012181459
1,156 QuickSel: Quick Selectivity Learning with Mixture Models 2020 SIGMOD 0.00011759683
1,281 Orca: A Modular Query Optimizer Architecture for Big Data 2014 SIGMOD 0.00011198917
1,444 Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities 2019 SIGMOD 0.00010616242
1,740 Flow-Loss: Learning Cardinality Estimates That Matter 2021 VLDB 9.7289523e-05
2,009 FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation 2021 VLDB 9.1813272e-05
2,348 Learned Cardinality Estimation: An In-depth Study 2022 SIGMOD 8.5910072e-05
2,584 Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation 2021 VLDB 8.2435322e-05
2,829 G-CARE: A Framework for Performance Benchmarking of Cardinality Estimation Techniques for Subgraph Matching 2020 SIGMOD 7.9469964e-05
2,852 FactorJoin: A New Cardinality Estimation Framework for Join Queries 2023 SIGMOD 7.9201312e-05
3,060 A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation 2021 SIGMOD 7.6828463e-05
3,740 FACE: A Normalizing Flow based Cardinality Estimator 2022 VLDB 7.0398782e-05
3,995 Simplicity Done Right for Join Ordering 2021 CIDR 6.8530469e-05
4,202 Kepler: Robust Learning for Faster Parametric Query Optimization 2023 SIGMOD 6.7258607e-05
4,459 Warper: Efficiently Adapting Learned Cardinality Estimators to Data and Workload Drifts 2022 SIGMOD 6.5757572e-05
5,075 SafeBound: A Practical System for Generating Cardinality Bounds 2023 SIGMOD 6.2721634e-05
5,837 Pre-training Summarization Models of Structured Datasets for Cardinality Estimation 2022 VLDB 5.9600736e-05
8,188 Efficient Query Re-optimization with Judicious Subquery Selections 2023 SIGMOD 5.3649397e-05
9,240 NeuroSketch: Fast and Approximate Evaluation of Range Aggregate Queries with Neural Networks 2023 SIGMOD 5.1867235e-05
10,249 Turbo-Charging SPJ Query Plans with Learned Physical Join Operator Selections 2022 VLDB 5.0412674e-05
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