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Optimizing I/O for Big Array Analytics

Summary: Introduces a declarative framework for big array analytics via nested-loop tasks, exposing shared I/O opportunities. An optimizer finds execution plans that exploit cross-step I/O sharing, yielding notable data-movement savings. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10706
Venue
VLDB
Year
2012
Pagerank
6.8783832e-05
Overall Rank
4,137 | 71.62%
DOI
10.14778/2824032.2824057

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{zhang_vldb12,
        title = {{Optimizing I/O for Big Array Analytics}},
        author = {Zhang, Yi and Yang, Jun},
        journal = {PVLDB},
        series = {{VLDB} '12},
        volume = {8},
        number = {12},
        pages = {1666--1677},
        doi = {10.14778/2824032.2824057},
        url = {https://doi.org/10.14778/2824032.2824057},
        year = {2012}
}

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