This is the open codebase for the project: Learned BMTree
PostgreSQL: https://www.postgresql.org/download/
Python Environment:
conda env create -f environment.ymlTraining with the uniform dataset and skew query workload:
# Training
nohup python exp_opt_fast.py --data uniform_1000000 --query skew_1000_dim2 &Testing BMTree under PostgreSQL:
# PostgreSQL Test
python pg_test.py --pg_test_method bmtree --data uniform_1000000 --query skew_2000_dim2 --bmtree mcts_bmtree_uni_skew_1000 --db_password ''Kindly cite our paper if you find it helpful:
@inproceedings{bmtree2023,
title={Towards Designing and Learning Piecewise Space-Filling Curves},
author={Li, Jiangneng and Wang, Zheng and Cong, Gao and Long, Cheng and Kiah, Han Mao and Cui, Bin},
journal={Proceedings of the VLDB Endowment},
volume={16},
number={9},
year={2023},
publisher={VLDB Endowment}
}
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