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Efficient Query Re-optimization with Judicious Subquery Selections

Summary: QuerySplit re-optimization generates subqueries from the logical plan, not the global plan. A cost function favors small, low-damage subqueries to delay large joins; in PostgreSQL, it yields 35% faster JOB vs baselines, within 4% of optimal. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hb060cf953cc6907d
Venue
SIGMOD
Year
2023
Pagerank
5.3852872e-05
Overall Rank
8,164 | 45.12%
DOI
10.1145/3589330

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{zhao_sigmod23,
        title = {{Efficient Query Re-optimization with Judicious Subquery Selections}},
        author = {Zhao, Junyi and Zhang, Huanchen and Gao, Yihan},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3589330},
        url = {https://dl.acm.org/doi/10.1145/3589330},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 9 of 9 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 29 of 29 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 0.00061066921
53 Eddies: Continuously Adaptive Query Processing 2000 SIGMOD 0.00040860054
85 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035864347
91 On the Propagation of Errors in the Size of Join Results 1991 SIGMOD 0.0003475226
98 LEO - DB2's LEarning Optimizer 2001 VLDB 0.00034106982
145 Neo: A Learned Query Optimizer 2019 VLDB 0.0002908188
149 Efficient Mid-Query Re-Optimization of Sub-Optimal Query Execution Plans 1998 SIGMOD 0.00028981723
272 An Overview of Query Optimization in Relational Systems 1998 PODS 0.00022509573
318 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021167555
406 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019045544
461 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.00017829982
481 Robust Query Processing through Progressive Optimization 2004 SIGMOD 0.00017603972
512 NeuroCard: One Cardinality Estimator for All Tables 2021 VLDB 0.00017050173
688 Cardinality Estimation Done Right: Index-Based Join Sampling 2017 CIDR 0.00014753664
1,060 Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions 2011 VLDB 0.00012224575
1,064 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012202282
1,156 QuickSel: Quick Selectivity Learning with Mixture Models 2020 SIGMOD 0.00011777105
1,257 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00011310561
1,465 Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities 2019 SIGMOD 0.00010576304
1,508 Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation 2015 SIGMOD 0.00010440205
1,515 DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems 2021 VLDB 0.00010417728
1,580 Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries 2020 SIGMOD 0.00010180835
2,522 Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation 2022 VLDB 8.3477168e-05
3,210 Efficiently Approximating Selectivity Functions using Low Overhead Regression Models 2020 VLDB 7.5363533e-05
3,271 Estimating Cardinalities with Deep Sketches 2019 SIGMOD 7.4744941e-05
3,982 Simplicity Done Right for Join Ordering 2021 CIDR 6.8750228e-05
4,045 Adaptive Query Processing in the Looking Glass 2005 CIDR 6.8328968e-05
6,113 Robustness Metrics for Relational Query Execution Plans 2018 VLDB 5.8823242e-05
7,597 On the Calculation of Optimality Ranges for Relational Query Execution Plans 2018 SIGMOD 5.4872821e-05
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