Towards a Learning Optimizer for Shared Clouds
Summary: CARDLEARNER learns cardinalities from past cloud runs, using subgraph templates for accurate estimates. Explores join variations to curb bias, uses many small models, and feeds predictions back to future runs, achieving 5x error reduction and 2-3x speedups. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chenggang Wu (University of California Berkeley)
- 2. Alekh Jindal (Microsoft)
- 3. Saeed Amizadeh (Microsoft)
- 4. Hiren Patel (Microsoft)
- 5. Wangchao Le (Microsoft)
- 6. Shi Qiao (Microsoft)
- 7. Sriram Rao (Meta)
BibTeX Citation
@article{wu_vldb19,
title = {{Towards a Learning Optimizer for Shared Clouds}},
author = {Wu, Chenggang and Jindal, Alekh and Amizadeh, Saeed and Patel, Hiren and Le, Wangchao and Qiao, Shi and Rao, Sriram},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {3},
pages = {210--222},
doi = {10.14778/3291264.3291267},
url = {https://doi.org/10.14778/3291264.3291267},
year = {2019}
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