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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
ha87c839d10690cae
Venue
SIGMOD
Year
2020
Pagerank
5.3511996e-05
Overall Rank
8,345 | 43.90%
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
1,786 Procedural Extensions of SQL: Understanding their usage in the wild 2021 VLDB 9.6326265e-05
11,177 Approximating Opaque Top-k Queries 2025 SIGMOD 4.9793485e-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 0.0023947656
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061066921
53 Eddies: Continuously Adaptive Query Processing 2000 SIGMOD 0.00040860054
91 On the Propagation of Errors in the Size of Join Results 1991 SIGMOD 0.0003475226
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
295 Towards Estimation Error Guarantees for Distinct Values 2000 PODS 0.00021914399
481 Robust Query Processing through Progressive Optimization 2004 SIGMOD 0.00017603972
569 Towards a Robust Query Optimizer: A Principled and Practical Approach 2005 SIGMOD 0.00016245271
836 Proactive Re-Optimization 2005 SIGMOD 0.00013557047
896 Froid: Optimization of Imperative Programs in a Relational Database 2018 VLDB 0.00013209291
1,122 Least Expected Cost Query Optimization: An Exercise in Utility 1999 PODS 0.0001193884
1,257 Sampling-Based Query Re-Optimization 2016 SIGMOD 0.00011310561
1,603 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2019 SIGMOD 0.00010097649
1,800 SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning 2018 VLDB 9.6093317e-05
1,821 Least Expected Cost Query Optimization: What Can We Expect? 2002 PODS 9.5687882e-05
1,987 Plan Bouquets: Query Processing without Selectivity Estimation 2014 SIGMOD 9.250242e-05
2,735 Speculative Distributed CSV Data Parsing for Big Data Analytics 2019 SIGMOD 8.0761736e-05
2,993 Extracting Equivalent SQL from Imperative Code in Database Applications 2016 SIGMOD 7.7721951e-05
4,069 Dynamically Optimizing Queries over Large Scale Data Platforms 2014 SIGMOD 6.821366e-05
4,256 BlackMagic: Automatic Inlining of Scalar UDFs into SQL Queries with Froid 2019 VLDB 6.7007882e-05
4,818 Continuous Cloud-Scale Query Optimization and Processing 2013 VLDB 6.3964573e-05
7,438 DBridge: Translating Imperative Code to SQL 2017 SIGMOD 5.5272264e-05
9,748 PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development 2018 SIGMOD 5.1349531e-05
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