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Speculative Distributed CSV Data Parsing for Big Data Analytics

Summary: Speculative distributed CSV parsing aligns field/record boundaries across chunks without context to enable parallel parsing. Robust syntax-error detection; Spark tests on 11k real-world datasets show substantial performance gains over prior parsers. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hc10508c09ebc7f00
Venue
SIGMOD
Year
2019
Pagerank
8.0761736e-05
Overall Rank
2,735 | 81.62%
DOI
10.1145/3299869.3319898

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{ge_sigmod19,
        title = {{Speculative Distributed CSV Data Parsing for Big Data Analytics}},
        author = {Ge, Chang and Li, Yinan and Eilebrecht, Eric and Chandramouli, Badrish and Kossmann, Donald},
        series = {{SIGMOD} '19},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3299869.3319898},
        url = {https://dl.acm.org/doi/10.1145/3299869.3319898},
        year = {2019}
}

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