Are We Ready For Learned Cardinality Estimation?

Summary: Assess readiness of learned cardinality estimators for production; static workloads yield gains, but training/inference costs are high. Dynamic updates hurt accuracy; sensitivity to correlation, skew, and domain shifts; emphasizes cost control and trustworthiness. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 12352
Venue: VLDB
Year: 2021
Pagerank: 0.00012504851
Overall Rank: 1,053 | 92.69%
DOI: 10.14778/3461535.3461552

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 10 of 60 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,197	Qualitative Join Discovery in Data Lakes using Examples	2026	SIGMOD	5.1725247e-05
10,219	Practical Parameterized Query Optimization via Efficient Plan Reuse and List-wise Ranking	2026	SIGMOD	5.1725247e-05
10,227	Sample-based Distinct Cardinality Estimation for Multiple Attributes in Multi-Dataset Queries	2026	VLDB	5.1725247e-05
10,241	Robust Predicate Transfer with Dynamic Execution	2026	VLDB	5.1725247e-05
10,491	FAAQP: Fast and Accurate Approximate Query Processing based on Bitmap-augmented Sum-Product Network	2025	SIGMOD	5.1725247e-05
10,707	The Accuracy of Cardinality Estimators: Unraveling the Evaluation Result Conundrum	2025	VLDB	5.1725247e-05
10,945	Sub-optimal Join Order Identification with L1-error	2024	SIGMOD	5.1725247e-05
11,087	Presto’s History-based Query Optimizer	2024	VLDB	5.1725247e-05
11,192	Efficient and Effective Cardinality Estimation for Skyline Family	2023	SIGMOD	5.1725247e-05
11,196	A Step Toward Deep Online Aggregation	2023	SIGMOD	5.1725247e-05

Outgoing Citations (Sorted by Pagerank)

Showing 2 of 52 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
4,218	Adaptive Statistics in Oracle 12c	2017	VLDB	6.8883873e-05
5,161	Learned Approximate Query Processing: Make it Light, Accurate and Fast	2021	CIDR	6.4045304e-05

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