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Continuous Analytics Over Discontinuous Streams

Summary: Order-independent continuous analytics over discontinuous streams: parallelize over independent sub-streams with arbitrary time ranges and defer consolidation to on-demand use. Truviso realizes this, enabling late data, parallelism, recovery, and transactional consistency. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4385
Venue
SIGMOD
Year
2010
Pagerank
9.4348569e-05
Overall Rank
1,945 | 86.66%
DOI
10.1145/1807167.1807290

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{krishnamurthy_sigmod10,
        title = {{Continuous Analytics Over Discontinuous Streams}},
        author = {Krishnamurthy, Sailesh and Franklin, Michael J. and Davis, Jeffrey and Farina, Daniel and Golovko, Pasha and Li, Alan and Thombre, Neil},
        series = {{SIGMOD} '10},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1807167.1807290},
        url = {https://dl.acm.org/doi/10.1145/1807167.1807290},
        year = {2010}
}

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