Pre-training Summarization Models of Structured Datasets for Cardinality Estimation
Summary: Pre-trained models convert structured datasets into compact summaries for cardinality estimation, eliminating per-dataset training and speeding up summary construction up to 100x. Uses multiple summaries per dataset and learned summaries for hard columnsets; shows shared frequency and correlation patterns learned from a diverse corpus with incremental updates. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yao Lu (Microsoft)
- 2. Srikanth Kandula (Microsoft)
- 3. Arnd Christian König (Microsoft)
- 4. Surajit Chaudhuri (Microsoft)
BibTeX Citation
@article{lu_vldb22,
title = {{Pre-training Summarization Models of Structured Datasets for Cardinality Estimation}},
author = {Lu, Yao and Kandula, Srikanth and König, Arnd Christian and Chaudhuri, Surajit},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {3},
pages = {414--426},
doi = {10.14778/3494124.3494127},
url = {https://doi.org/10.14778/3494124.3494127},
year = {2022}
}
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