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Flow-Loss: Learning Cardinality Estimates That Matter

Summary: Flow-Loss trains cardinality estimators against optimizer plan costs via a flow-routing formulation over plan graphs, rather than average Q-Error. On the 16K-query CEB benchmark, it yields better runtimes and markedly stronger generalization to unseen templates despite worse estimation accuracy. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
h0ecc8025d49f0dab
Venue
VLDB
Year
2021
Pagerank
9.7289523e-05
Overall Rank
1,740 | 88.34%
DOI
10.14778/3476249.3476259
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{negi_vldb21,
        title = {{Flow-Loss: Learning Cardinality Estimates That Matter}},
        author = {Negi, Parimarjan and Marcus, Ryan and Kipf, Andreas and Mao, Hongzi and Tatbul, Nesime and Kraska, Tim and Alizadeh, Mohammad},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {11},
        pages = {2019--2032},
        doi = {10.14778/3476249.3476259},
        url = {https://doi.org/10.14778/3476249.3476259},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 10 of 60 citing papers.

Rank Citing Paper Year Venue Pagerank
10,769 LIO: A lightweight and interpretable query optimizer based on an evolutionary forest 2026 VLDB 4.9605343e-05
10,771 Sample-based Distinct Cardinality Estimation for Multiple Attributes in Multi-Dataset Queries 2026 VLDB 4.9605343e-05
10,812 OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning 2026 VLDB 4.9605343e-05
10,873 BaCon: Efficient Batch Processing of Counting Queries 2026 VLDB 4.9605343e-05
10,903 ReSequel: Robust LLM-assisted Query Rewriting and Optimization using Templatization and Sampling 2026 VLDB 4.9605343e-05
10,953 QDBO: A Real-time Quantum-augmented Database System Optimizer 2026 VLDB 4.9605343e-05
10,994 TATA: An Efficient Framework for Task Transfer in Query Plan Representation 2026 VLDB 4.9605343e-05
11,347 Robust Plan Evaluation based on Approximate Probabilistic Machine Learning 2025 VLDB 4.9605343e-05
11,501 LEAP: A Low-cost Spark SQL Query Optimizer using Pairwise Comparison 2025 VLDB 4.9605343e-05
11,564 Sub-optimal Join Order Identification with L1-error 2024 SIGMOD 4.9605343e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 28 of 28 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
103 Selectivity Estimation Without the Attribute Value Independence Assumption 1997 VLDB 0.00033847446
142 Neo: A Learned Query Optimizer 2019 VLDB 0.00029114937
171 Wavelet-Based Histograms for Selectivity Estimation 1998 SIGMOD 0.00027063233
287 Selectivity Estimation using Probabilistic Models 2001 SIGMOD 0.00022060616
320 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021128745
372 STHoles: A Multidimensional Workload-Aware Histogram 2001 SIGMOD 0.00019768921
381 Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors 2009 VLDB 0.00019497061
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
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
793 Random Sampling over Joins Revisited 2018 SIGMOD 0.00013903938
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
1,436 Towards a Learning Optimizer for Shared Clouds 2019 VLDB 0.00010658836
1,444 Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities 2019 SIGMOD 0.00010616242
1,583 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD 0.00010148362
1,609 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2019 SIGMOD 0.0001007196
2,228 Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models 2017 VLDB 8.7912743e-05
2,987 Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs 2022 VLDB 7.767043e-05
3,062 Towards a Hands-Free Query Optimizer through Deep Learning 2019 CIDR 7.6809918e-05
3,212 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 7.5145409e-05
3,282 Estimating Cardinalities with Deep Sketches 2019 SIGMOD 7.4491295e-05
3,995 Simplicity Done Right for Join Ordering 2021 CIDR 6.8530469e-05
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