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Spark SQL: Relational Data Processing in Spark

Summary: Relational processing integrated into Spark via DataFrame API, unifying SQL queries with Spark's functional workflow. Catalyst, a Scala-based extensible optimizer, enables composable rules, code generation, JSON schema inference, and federation to databases. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5084
Venue
SIGMOD
Year
2015
Pagerank
0.00054865648
Overall Rank
24 | 99.84%
DOI
10.1145/2723372.2742797

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{armbrust_sigmod15,
        title = {{Spark SQL: Relational Data Processing in Spark}},
        author = {Armbrust, Michael and Xin, Reynold S. and Lian, Cheng and Huai, Yin and Liu, Davies and Bradley, Joseph K. and Meng, Xiangrui and Kaftan, Tomer and Franklin, Michael J. and Ghodsi, Ali and Zaharia, Matei},
        series = {{SIGMOD} '15},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2723372.2742797},
        url = {https://dl.acm.org/doi/10.1145/2723372.2742797},
        year = {2015}
}

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