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MONSOON: Multi-Step Optimization and Execution of Queries with Partially Obscured Predicates

Summary: Monsoon optimizes queries in the presence of UDFs that partially obscure predicates by interleaving statistics collection with execution. It can collect stats on UDFs or on partial-plan results, then re-optimize, with a principled interleaving strategy formalized as a Markov decision process. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6005
Venue
SIGMOD
Year
2020
Pagerank
5.4658735e-05
Overall Rank
8,211 | 43.67%
DOI
10.1145/3318464.3389728

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{sikdar_sigmod20,
        title = {{MONSOON: Multi-Step Optimization and Execution of Queries with Partially Obscured Predicates}},
        author = {Sikdar, Sourav and Jermaine, Chris},
        series = {{SIGMOD} '20},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3318464.3389728},
        url = {https://dl.acm.org/doi/10.1145/3318464.3389728},
        year = {2020}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
1,892 Procedural Extensions of SQL: Understanding their usage in the wild 2021 VLDB 9.5277793e-05
10,751 Approximating Opaque Top-k Queries 2025 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 25 of 25 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
1 Access Path Selection in a Relational Database Management System 1979 SIGMOD 0.0024089429
18 How Good Are Query Optimizers, Really? 2016 VLDB 0.00059284255
53 Eddies: Continuously Adaptive Query Processing 2000 SIGMOD 0.00041071971
89 On the Propagation of Errors in the Size of Join Results 1991 SIGMOD 0.00035031529
151 Efficient Mid-Query Re-Optimization of Sub-Optimal Query Execution Plans 1998 SIGMOD 0.00029161879
154 Neo: A Learned Query Optimizer 2019 VLDB 0.00028726181
288 Towards Estimation Error Guarantees for Distinct Values 2000 PODS 0.00022296371
290 An Overview of Query Optimization in Relational Systems 1998 PODS 0.0002227038
492 Robust Query Processing through Progressive Optimization 2004 SIGMOD 0.0001756877
566 Towards a Robust Query Optimizer: A Principled and Practical Approach 2005 SIGMOD 0.00016436005
829 Proactive Re-Optimization 2005 SIGMOD 0.00013769838
894 Froid: Optimization of Imperative Programs in a Relational Database 2018 VLDB 0.00013367658
1,104 Least Expected Cost Query Optimization: An Exercise in Utility 1999 PODS 0.00012157634
1,256 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00011457194
1,712 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2019 SIGMOD 9.9492299e-05
1,795 Least Expected Cost Query Optimization: What Can We Expect? 2002 PODS 9.738718e-05
1,815 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2018 VLDB 9.6894541e-05
1,987 Plan Bouquets: Query Processing without Selectivity Estimation 2014 SIGMOD 9.3517129e-05
2,939 Extracting Equivalent SQL from Imperative Code in Database Applications 2016 SIGMOD 7.9395908e-05
3,074 Speculative Distributed CSV Data Parsing for Big Data Analytics 2019 SIGMOD 7.7844208e-05
4,180 BlackMagic: Automatic Inlining of Scalar UDFs into SQL Queries with Froid 2019 VLDB 6.8487143e-05
4,481 Dynamically Optimizing Queries over Large Scale Data Platforms 2014 SIGMOD 6.6754521e-05
4,742 Continuous Cloud-Scale Query Optimization and Processing 2013 VLDB 6.5269203e-05
7,297 DBridge: Translating Imperative Code to SQL 2017 SIGMOD 5.6525237e-05
9,572 PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development 2018 SIGMOD 5.2528121e-05
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