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Dynamic Speculative Optimizations for SQL Compilation in Apache Spark

Summary: Dynamic speculative optimizations for Spark SQL compilation via runtime profiling and adaptive codegen to reduce data access and deserialization overhead on textual formats. Achieves up to 4.4x speedups on TPC-H with CSV/JSON, illustrating a unique runtime-driven codegen approach for Spark. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12460
Venue
VLDB
Year
2020
Pagerank
5.3099969e-05
Overall Rank
9,167 | 37.11%
DOI
10.14778/3377369.3377382

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{schiavio_vldb20,
        title = {{Dynamic Speculative Optimizations for SQL Compilation in Apache Spark}},
        author = {Schiavio, Filippo and Bonetta, Daniele and Binder, Walter},
        journal = {PVLDB},
        series = {{VLDB} '20},
        volume = {13},
        number = {5},
        pages = {754--767},
        doi = {10.14778/3377369.3377382},
        url = {https://doi.org/10.14778/3377369.3377382},
        year = {2020}
}

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