A Demonstration of ST-Hadoop: A MapReduce Framework for Big Spatio-temporal Data
Summary: ST-Hadoop is the first open-source MapReduce framework with native spatio-temporal support, indexing ST data in HDFS to yield orders-of-magnitude speedups over Hadoop and SpatialHadoop for large queries. Demonstrated on a 24-node cluster with ~1B Twitter and NYC Taxi records. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Louai Alarabi (University of Minnesota)
- 2. Mohamed F. Mokbel (University of Minnesota)
BibTeX Citation
@article{alarabi_vldb17,
title = {{A Demonstration of ST-Hadoop: A MapReduce Framework for Big Spatio-temporal Data}},
author = {Alarabi, Louai and Mokbel, Mohamed F.},
journal = {PVLDB},
series = {{VLDB} '17},
volume = {10},
number = {12},
pages = {1961--1964},
doi = {10.14778/3137765.3137819},
url = {https://doi.org/10.14778/3137765.3137819},
year = {2017}
}Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,155 | VRE: A Versatile, Robust, and Economical Trajectory Data System | 2022 | VLDB | 5.6869288e-05 |
| 10,990 | Polaris: An Interactive and Scalable Data Infrastructure for Polar Science | 2025 | VLDB | 5.093636e-05 |
| 11,392 | ST4ML: Machine Learning Oriented Spatio-Temporal Data Processing at Scale | 2023 | SIGMOD | 5.093636e-05 |
| 11,801 | IMO: A Toolbox for Simulating and Querying “Infected” Moving Objects | 2020 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|
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