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AdaptDB: Adaptive Partitioning for Distributed Joins

Summary: AdaptDB adaptively refines distributed table partitioning as workloads evolve. Its hyper-join matches overlapping storage blocks to avoid broad shuffles, while smooth repartitioning reduces overlap incrementally, yielding 2–3× faster TPC-H and real-world queries. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11742
Venue
VLDB
Year
2017
Pagerank
6.692321e-05
Overall Rank
4,456 | 69.43%
DOI
10.14778/3055540.3055549

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{lu_vldb17,
        title = {{AdaptDB: Adaptive Partitioning for Distributed Joins}},
        author = {Lu, Yi and Shanbhag, Anil and Jindal, Alekh and Madden, Samuel},
        journal = {PVLDB},
        series = {{VLDB} '17},
        volume = {10},
        number = {5},
        pages = {589--600},
        doi = {10.14778/3055540.3055549},
        url = {https://doi.org/10.14778/3055540.3055549},
        year = {2017}
}

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