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Meta-Dataflows: Efficient Exploratory Dataflow Jobs

Summary: Meta-Dataflows (MDFs) model exploratory dataflow workflows with two primitives: explore and choose. Reuse intermediates, prune branches, and align memory planning with future access to accelerate exploratory runs (up to 90%). (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5542
Venue
SIGMOD
Year
2018
Pagerank
5.4601966e-05
Overall Rank
8,237 | 43.49%
DOI
10.1145/3183713.3183760

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{fernandez_sigmod18,
        title = {{Meta-Dataflows: Efficient Exploratory Dataflow Jobs}},
        author = {Fernandez, Raul Castro and Culhane, William and Watcharapichat, Pijika and Weidlich, Matthias and Morales, Victoria Lopez and Pietzuch, Peter},
        series = {{SIGMOD} '18},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3183713.3183760},
        url = {https://dl.acm.org/doi/10.1145/3183713.3183760},
        year = {2018}
}

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