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Analyzing the Impact of Cardinality Estimation on Execution Plans in Microsoft SQL Server

Summary: Empirical study of cardinality-estimation effects on plan quality in Microsoft SQL Server using complex real-world queries (aggregates, outer joins, subqueries) and both row- and column-oriented layouts. Introduces a sensitivity analysis that selectively supplies accurate subexpression cardinalities while injecting graded errors, and evaluates runtime mitigations (bitmap filtering, adaptive joins). (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
h50ec9f42e8ce6c2c
Venue
VLDB
Year
2023
Pagerank
6.2888728e-05
Overall Rank
5,044 | 66.20%
DOI
10.14778/3611479.3611494
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{lee_vldb23,
        title = {{Analyzing the Impact of Cardinality Estimation on Execution Plans in Microsoft SQL Server}},
        author = {Lee, Kukjin and Dutt, Anshuman and Narasayya, Vivek and Chaudhuri, Surajit},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {11},
        pages = {2871--2883},
        doi = {10.14778/3611479.3611494},
        url = {https://doi.org/10.14778/3611479.3611494},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 13 of 13 citing papers.

Rank Citing Paper Year Venue Pagerank
3,909 SQLStorm: Taking Database Benchmarking into the LLM Era 2025 VLDB 6.9127576e-05
4,882 LpBound: Pessimistic Cardinality Estimation using ℓp-Norms of Degree Sequences 2025 SIGMOD 6.3565046e-05
6,590 Towards Query Optimizer as a Service (QOaaS) in a Unified LakeHouse Ecosystem: Can One QO Rule Them All? 2025 CIDR 5.7233093e-05
7,432 POLAR: Adaptive and Non-invasive Join Order Selection via Plans of Least Resistance 2024 VLDB 5.5133928e-05
7,997 The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions 2024 VLDB 5.3938336e-05
8,412 PARQO: Penalty-Aware Robust Plan Selection in Query Optimization 2024 VLDB 5.3211467e-05
9,031 ByteCard: Enhancing ByteDance’s Data Warehouse with Learned Cardinality Estimation 2024 SIGMOD 5.219814e-05
9,518 LpBound in Action: Cardinality Estimation with One-Sided Guarantees 2025 SIGMOD 5.151324e-05
10,143 Still Asking: How Good Are Query Optimizers, Really? 2025 VLDB 5.0597449e-05
10,323 This is Going to Sound Crazy, But What If We Used Large Language Models to Boost Automatic Database Tuning Algorithms By Leveraging Prior History? We Will Find Better Configurations More Quickly Than Retraining From Scratch! 2026 SIGMOD 5.0241309e-05
10,370 An Elephant Under The Microscope: Analyzing The Interaction Of Optimizer Components In PostgreSQL 2025 SIGMOD 5.0010514e-05
10,676 Understanding and Detecting Query Performance Regression in Practical Index Tuning: [Experiments & Analysis] 2026 SIGMOD 4.9605343e-05
11,394 The Accuracy of Cardinality Estimators: Unraveling the Evaluation Result Conundrum 2025 VLDB 4.9605343e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 17 of 17 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
91 On the Propagation of Errors in the Size of Join Results 1991 SIGMOD 0.00034691614
259 An Overview of Query Optimization in Relational Systems 1998 PODS 0.00022881075
381 Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors 2009 VLDB 0.00019497061
471 Robust Query Processing through Progressive Optimization 2004 SIGMOD 0.00017691682
690 Selectivity Estimation for Range Predicates using Lightweight Models 2019 VLDB 0.00014703258
946 Enhancements to SQL Server Column Stores 2013 SIGMOD 0.00012911968
983 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00012677179
1,513 DSB: A Decision Support Benchmark for Workload-Driven and Traditional Database Systems 2021 VLDB 0.00010394557
1,541 Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses 2018 VLDB 0.00010288394
1,740 Flow-Loss: Learning Cardinality Estimates That Matter 2021 VLDB 9.7289523e-05
2,888 Query Optimizers: Time to Rethink the Contract? 2009 SIGMOD 7.8895201e-05
3,361 Exact Cardinality Query Optimization for Optimizer Testing 2009 VLDB 7.3621595e-05
4,274 Query Optimization in Oracle 12c Database In-Memory 2015 VLDB 6.6754819e-05
4,415 Bitvector-aware Query Optimization for Decision Support Queries 2020 SIGMOD 6.5965677e-05
5,223 Exact Cardinality Query Optimization with Bounded Execution Cost 2019 SIGMOD 6.210331e-05
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