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Set Similarity Joins on MapReduce: An Experimental Survey

Summary: An experimental survey uniformly compares ten MapReduce set-similarity join algorithms across twelve diverse datasets. All fail to scale under some conditions; analytic and empirical results expose sensitivity to long/frequent sets and low thresholds, motivating new designs. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11793
Venue
VLDB
Year
2018
Pagerank
6.7984322e-05
Overall Rank
4,260 | 70.78%
DOI
10.14778/3231751.3231760

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Authors

BibTeX Citation

@article{fier_vldb18,
        title = {{Set Similarity Joins on MapReduce: An Experimental Survey}},
        author = {Fier, Fabian and Augsten, Nikolaus and Bouros, Panagiotis and Leser, Ulf and Freytag, Johann-Christoph},
        journal = {PVLDB},
        series = {{VLDB} '18},
        volume = {11},
        number = {10},
        pages = {1110--1122},
        doi = {10.14778/3231751.3231760},
        url = {https://doi.org/10.14778/3231751.3231760},
        year = {2018}
}

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