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RP-DBSCAN: A Superfast Parallel DBSCAN Algorithm Based on Random Partitioning

Summary: RP-DBSCAN uses pseudo random, cell-based partitioning to balance load in parallel DBSCAN on skewed data. Compact two-level cell dictionary enables local clustering with light cross-partition merge on Spark, yielding up to 180x speedup. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5595
Venue
SIGMOD
Year
2018
Pagerank
7.6144184e-05
Overall Rank
3,234 | 77.82%
DOI
10.1145/3183713.3196887

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{song_sigmod18,
        title = {{RP-DBSCAN: A Superfast Parallel DBSCAN Algorithm Based on Random Partitioning}},
        author = {Song, Hwanjun and Lee, Jae-Gil},
        series = {{SIGMOD} '18},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3183713.3196887},
        url = {https://dl.acm.org/doi/10.1145/3183713.3196887},
        year = {2018}
}

Incoming Citations (Sorted by Pagerank)

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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
291 OPTICS: Ordering Points To Identify the Clustering Structure 1999 SIGMOD 0.00022264197
962 DBSCAN Revisited: Mis-Claim, Un-Fixability, and Approximation 2015 SIGMOD 0.00012936472
2,556 NG-DBSCAN: Scalable Density-Based Clustering for Arbitrary Data 2017 VLDB 8.4162172e-05
3,020 Dynamic Density Based Clustering 2017 SIGMOD 7.8445412e-05
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