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QaaD (Query-as-a-Data): Scalable Execution of Massive Number of Small Queries in Spark

Summary: Query-merging via microRDD converts many small Spark queries into a few larger ones; queries embedded as data enable shared inputs. Dynamic partition sizing minimizes runtime overhead, yielding 10.6x-36.6x speedups over Spark for small queries. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6699
Venue
SIGMOD
Year
2023
Pagerank
5.093636e-05
Overall Rank
11,399 | 21.80%
DOI
10.1145/3589279

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Authors

BibTeX Citation

@inproceedings{park_sigmod23,
        title = {{QaaD (Query-as-a-Data): Scalable Execution of Massive Number of Small Queries in Spark}},
        author = {Park, Yeonsu and Tak, Byungchul and Han, Wook-Shin},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3589279},
        url = {https://dl.acm.org/doi/10.1145/3589279},
        year = {2023}
}

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