Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce
Summary: Hadoop-GIS brings scalable spatial warehousing to MapReduce/Hive via spatial partitioning and implicit parallel query execution. Global partition indexes, on-demand local indexes, RESQUE, and boundary-object handling deliver SDBMS-comparable or superior performance for compute-intensive queries. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ablimit Aji (Emory University)
- 2. Fusheng Wang (Emory University)
- 3. Hoang Vo (Emory University)
- 4. Rubao Lee (Ohio State University)
- 5. Qiaoling Liu (Emory University)
- 6. Xiaodong Zhang (Ohio State University)
- 7. Joel Saltz (Emory University)
BibTeX Citation
@article{aji_vldb13,
title = {{Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce}},
author = {Aji, Ablimit and Wang, Fusheng and Vo, Hoang and Lee, Rubao and Liu, Qiaoling and Zhang, Xiaodong and Saltz, Joel},
journal = {PVLDB},
series = {{VLDB} '13},
volume = {6},
number = {11},
pages = {1009--1020},
doi = {10.14778/2536222.2536227},
url = {https://doi.org/10.14778/2536222.2536227},
year = {2013}
}
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