GHive: A Demonstration of GPU-Accelerated Query Processing in Apache Hive
Summary: GHive enables GPU-accelerated OLAP in Apache Hive by orchestrating CPU-GPU execution for Hive operators. Compared with CPU-only Hive, it delivers measurable speedups, with intuitive visualizations and per-operator profiling to pinpoint GPU benefits. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Haotian Liu (Southern University of Science and Technology)
- 2. Bo Tang (Southern University of Science and Technology)
- 3. Jiashu Zhang (Southern University of Science and Technology)
- 4. Yangshen Deng (Southern University of Science and Technology)
- 5. Xinying Zheng (Southern University of Science and Technology)
- 6. Qiaomu Shen (Southern University of Science and Technology)
- 7. Xiao Yan (Southern University of Science and Technology)
- 8. Dan Zeng (Southern University of Science and Technology)
- 9. Zunyao Mao (Southern University of Science and Technology)
- 10. Chaozu Zhang (Southern University of Science and Technology)
- 11. Zhengxin You (Southern University of Science and Technology)
- 12. Zhihao Wang (Southern University of Science and Technology)
- 13. Runzhe Jiang (Southern University of Science and Technology)
- 14. Fang Wang (Hong Kong Polytechnic University)
- 15. Man Lung Yiu (Hong Kong Polytechnic University)
- 16. Huan Li (Aalborg University)
- 17. Mingji Han (University of Massachusetts Amherst)
- 18. Qian Li (Huawei; Southern University of Science and Technology)
- 19. Zhenghai Luo (Huawei)
BibTeX Citation
@inproceedings{liu_sigmod22,
title = {{GHive: A Demonstration of GPU-Accelerated Query Processing in Apache Hive}},
author = {Liu, Haotian and Tang, Bo and Zhang, Jiashu and Deng, Yangshen and Zheng, Xinying and Shen, Qiaomu and Yan, Xiao and Zeng, Dan and Mao, Zunyao and Zhang, Chaozu and You, Zhengxin and Wang, Zhihao and Jiang, Runzhe and Wang, Fang and Yiu, Man Lung and Li, Huan and Han, Mingji and Li, Qian and Luo, Zhenghai},
series = {{SIGMOD} '22},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3514221.3520166},
url = {https://dl.acm.org/doi/10.1145/3514221.3520166},
year = {2022}
}
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,511 | DPDPU: Data Processing with DPUs | 2025 | CIDR | 5.25736e-05 |
| 11,231 | Accelerating Merkle Patricia Trie with GPU | 2024 | VLDB | 5.093636e-05 |
| 11,485 | DHive: Query Execution Performance Analysis via Dataflow in Apache Hive | 2023 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 32 | Hive - A Warehousing Solution Over a Map-Reduce Framework | 2009 | VLDB | 0.00050111008 |
| 2,706 | Major Technical Advancements in Apache Hive | 2014 | SIGMOD | 8.2287564e-05 |
| 3,555 | Apache Hive: From MapReduce to Enterprise-grade Big Data Warehousing | 2019 | SIGMOD | 7.3115321e-05 |
| 3,791 | Hardware-conscious Query Processing in GPU-accelerated Analytical Engines | 2019 | CIDR | 7.1235328e-05 |
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