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Scalable Continuous Query Processing by Tracking Hotspots

Summary: Scalable framework groups continuous queries by overlapping predicates and maintains a dynamic hotspot-based partition with near-log amortized updates. Hotspot-focused processing of heavy select-join and band-join workloads yields orders-of-magnitude throughput gains and enables linear-time interval histograms. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9638
Venue
VLDB
Year
2006
Pagerank
5.093636e-05
Overall Rank
12,712 | 12.79%
DOI
10.14778/1164135.1164139

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Authors

BibTeX Citation

@article{agarwal_vldb06,
        title = {{Scalable Continuous Query Processing by Tracking Hotspots}},
        author = {Agarwal, Pankaj K. and Xie, Junyi and Yang, Jun and Yu, Hai},
        journal = {PVLDB},
        series = {{VLDB} '06},
        pages = {31--42},
        doi = {10.14778/1164135.1164139},
        url = {https://doi.org/10.14778/1164135.1164139},
        year = {2006}
}

Incoming Citations (Sorted by Pagerank)

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Rank Citing Paper Year Venue Pagerank
6,006 End-to-End Support for Joins in Large-Scale Publish/Subscribe Systems 2008 VLDB 6.0119118e-05
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