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Incorporating Super-Operators in Big-Data Query Optimizers

Summary: Fuses shuffle-inducing Join, UnionAll, Spool, and GroupBy subqueries into parametric streaming super-operators, targeting dominant big-data costs. Abstract operator trees and matching avoid rule explosion; SCOPE reduces resource cost 1.7× and latency 1.5× without slower optimization. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
12418
Venue
VLDB
Year
2020
Pagerank
5.9470844e-05
Overall Rank
6,194 | 57.51%
DOI
10.14778/3368289.3368299

Incoming Non-self Citations Over Time

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BibTeX Citation

@article{leeka_vldb20,
        title = {{Incorporating Super-Operators in Big-Data Query Optimizers}},
        author = {Leeka, Jyoti and Rajan, Kaushik},
        journal = {PVLDB},
        series = {{VLDB} '20},
        volume = {13},
        number = {3},
        pages = {348--360},
        doi = {10.14778/3368289.3368299},
        url = {https://doi.org/10.14778/3368289.3368299},
        year = {2020}
}

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