ByteCard: Enhancing ByteDance’s Data Warehouse with Learned Cardinality Estimation
Summary: ByteCard trains and deploys cardinality estimators in ByteHouse, replacing Selinger-style estimates for huge-scale queries. Balancing accuracy and practicality (latency, size, training cost), it yields up to 30% lower 99th percentile latency on real data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yuxing Han (ByteDance)
- 2. Haoyu Wang (ByteDance; East China Normal University)
- 3. Lixiang Chen (ByteDance; East China Normal University)
- 4. Yifeng Dong (ByteDance)
- 5. Xing Chen (ByteDance)
- 6. Benquan Yu (ByteDance)
- 7. Chengcheng Yang (East China Normal University)
- 8. Weining Qian (East China Normal University)
BibTeX Citation
@inproceedings{han_sigmod24,
title = {{ByteCard: Enhancing ByteDance’s Data Warehouse with Learned Cardinality Estimation}},
author = {Han, Yuxing and Wang, Haoyu and Chen, Lixiang and Dong, Yifeng and Chen, Xing and Yu, Benquan and Yang, Chengcheng and Qian, Weining},
series = {{SIGMOD} '24},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3626246.3653376},
url = {https://dl.acm.org/doi/10.1145/3626246.3653376},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,334 | AdaNDV: Adaptive Number of Distinct Value Estimation via Learning to Select and Fuse Estimators | 2025 | VLDB | 5.0225409e-05 |
| 10,812 | OBELISK: Efficient Offline Query Planning with Bayesian Optimization-Informed Language Model Reasoning | 2026 | VLDB | 4.9605343e-05 |
| 11,085 | Vodka: Rethink Benchmarking Philosophy in HTAP Systems | 2026 | VLDB | 4.9605343e-05 |
| 11,260 | PLM4NDV: Minimizing Data Access for Number of Distinct Values Estimation with Pre-trained Language Models | 2025 | SIGMOD | 4.9605343e-05 |
| 11,350 | AQETuner: Reliable Query-level Configuration Tuning for Analytical Query Engines | 2025 | VLDB | 4.9605343e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 38 of 38 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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