TQEx: Tensor-based Query Engine Enhanced by Bridging the Gap
Summary: Analyzes the gap between irregular SQL and uniform tensor runtimes; derives guidelines (var-length storage, tensorized joins/aggregates, multi-XPU mapping) to bridge it. Implements TQEx—tensor-based engine with tailored storage/operators—up to 41.9× vs TQP and ~12–28× vs DuckDB/HeavyDB on TPC-H. (summarized by gpt-5-mini on Feb 11 2026)
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Authors
- 1. Haitao Zhang (Wuhan University)
- 2. Ran Pang (Wuhan University)
- 3. Yuanyuan Zhu (Wuhan University)
- 4. Hao Zhang (Huawei)
- 5. Congli Gao (Huawei)
- 6. Ming Zhong (Wuhan University)
- 7. Jiawei Jiang (Wuhan University)
- 8. Tieyun Qian (Wuhan University)
- 9. Jeffrey Xu Yu (Hong Kong University of Science and Technology)
BibTeX Citation
@inproceedings{zhang_sigmod26,
title = {{TQEx: Tensor-based Query Engine Enhanced by Bridging the Gap}},
author = {Zhang, Haitao and Pang, Ran and Zhu, Yuanyuan and Zhang, Hao and Gao, Congli and Zhong, Ming and Jiang, Jiawei and Qian, Tieyun and Yu, Jeffrey Xu},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3769835},
url = {https://dl.acm.org/doi/10.1145/3769835},
year = {2026}
}
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