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Grosbeak: A Data Warehouse Supporting Resource-Aware Incremental Computing

Summary: Grosbeak is a resource-aware data warehouse for recurring analytic jobs that uses incremental, small batches as data arrive. It schedules these batches on idle capacity to smooth resource skew and improve utilization, demonstrated on real pipelines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5943
Venue
SIGMOD
Year
2020
Pagerank
5.2570781e-05
Overall Rank
9,514 | 34.73%
DOI
10.1145/3318464.3384708

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{wang_sigmod20,
        title = {{Grosbeak: A Data Warehouse Supporting Resource-Aware Incremental Computing}},
        author = {Wang, Zuozhi and Zeng, Kai and Huang, Botong and Chen, Wei and Cui, Xiaozong and Wang, Bo and Liu, Ji and Fan, Liya and Qu, Dachuan and Hou, Zhenyu and Guan, Tao and Li, Chen and Zhou, Jingren},
        series = {{SIGMOD} '20},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3318464.3384708},
        url = {https://dl.acm.org/doi/10.1145/3318464.3384708},
        year = {2020}
}

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
438 DBToaster: Higher-order Delta Processing for Dynamic, Frequently Fresh Views 2012 VLDB 0.00018471721
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