Skip to content
Home

Database Learning

Database-learning methods that improve estimation and reduce computation using workload history.

How can databases reuse workload history to improve future decisions?

Database-learning methods that improve estimation and reduce computation using workload history.

Methods and questions

  • workload feedback
  • learned selectivity estimation
  • probabilistic guarantees

Projects

Publications

QuickSel: Quick Selectivity Learning with Mixture Models

Yongjoo Park, Shucheng Zhong, Barzan Mozafari

SIGMOD 2020 · ACM SIGMOD International Conference on Management of Data

Paper ↗Technical Report ↗Project ↗
Cite
@inproceedings{ea3d8506-1f2f-40ea-8bcb-6a74f72e12f0,
  title = {QuickSel: Quick Selectivity Learning with Mixture Models},
  author = {Yongjoo Park and Shucheng Zhong and Barzan Mozafari},
  booktitle = {ACM SIGMOD International Conference on Management of Data},
  year = {2020},
  doi = {10.1145/3318464.3389727}
}
Paper ↗Technical Report ↗Project ↗
Cite
@inproceedings{50db23fc-a5a3-4d7f-ac07-2a696129c92f,
  title = {BlinkML: Efficient Maximum Likelihood Estimation with Probabilistic Guarantees},
  author = {Yongjoo Park and Jingyi Qing and Xiaoyang Shen and Barzan Mozafari},
  booktitle = {ACM SIGMOD International Conference on Management of Data},
  year = {2019},
  doi = {10.1145/3299869.3300077}
}
Paper ↗Project ↗
Cite
@inproceedings{3cebf7e2-930f-4c8a-aa17-75a4c32cb001,
  title = {Database Learning: Toward a Database that Becomes Smarter Every Time},
  author = {Yongjoo Park and Ahmad Shahab Tajik and Michael J. Cafarella and Barzan Mozafari},
  booktitle = {ACM SIGMOD International Conference on Management of Data},
  year = {2017},
  doi = {10.1145/3035918.3064013}
}