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Clonos: Consistent Causal Recovery for Highly-Available Streaming Dataflows
Summary: Clonos enables instant local recovery for streaming dataflows with exactly-once guarantees by switching to passive standby operators. Causal logging tracks nondeterminism to enforce causally consistent recovery with output deduplication; evaluated on Nexmark vs Flink with negligible overhead and no determinism assumptions.
(summarized by gpt-5-nano on Feb 09 2026)
Paper ID
h1d6ed55c6752fc58
Venue
SIGMOD
Year
2021
Pagerank
6.3513193e-05
Overall Rank
4,889 | 67.23%
DOI
10.1145/3448016.3457320
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(CC BY 4.0)
Incoming Non-self Citations Over Time
BibTeX Citation
@inproceedings{silvestre_sigmod21,
title = {{Clonos: Consistent Causal Recovery for Highly-Available Streaming Dataflows}},
author = {Silvestre, Pedro F. and Fragkoulis, Marios and Spinellis, Diomidis and Katsifodimos, Asterios},
series = {{SIGMOD} '21},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3448016.3457320},
url = {https://dl.acm.org/doi/10.1145/3448016.3457320},
year = {2021}
}
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