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Generalized Scale Independence Through Incremental Precomputation

Summary: Generalized scale independence via incremental materialized views to keep query latency nearly constant as data grows. Static-analysis guided view selection/maintenance to bound costs; validated on TPC-W, near-constant latency up to hundreds of machines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4802
Venue
SIGMOD
Year
2013
Pagerank
6.8031294e-05
Overall Rank
4,250 | 70.85%
DOI
10.1145/2463676.2465333

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{armbrust_sigmod13,
        title = {{Generalized Scale Independence Through Incremental Precomputation}},
        author = {Armbrust, Michael and Liang, Eric and Kraska, Tim and Fox, Armando and Franklin, Michael J. and Patterson, David A.},
        series = {{SIGMOD} '13},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2463676.2465333},
        url = {https://dl.acm.org/doi/10.1145/2463676.2465333},
        year = {2013}
}

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