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SplitDF: Splitting Dataframes for Memory-Efficient Data Analysis

Summary: Introduce “splitting”: lossless join decomposition adding join keys to reduce dataframe redundancy while preserving a unified tabular view, no FD discovery required. SplitDF (Ibis/DuckDB) with automated SplitGen (Velox) achieves 19–61% memory savings with minimal API change. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13637
Venue
VLDB
Year
2024
Pagerank
5.093636e-05
Overall Rank
11,235 | 22.92%
DOI
10.14778/3665844.3665849

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Authors

BibTeX Citation

@article{kakaraparthy_vldb24,
        title = {{SplitDF: Splitting Dataframes for Memory-Efficient Data Analysis}},
        author = {Kakaraparthy, Aarati and Patel, Jignesh M.},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {9},
        pages = {2175--2184},
        doi = {10.14778/3665844.3665849},
        url = {https://doi.org/10.14778/3665844.3665849},
        year = {2024}
}

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