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Eigen+: Memory Over-Subscription for Alibaba Cloud Databases
Summary: Eigen+ reframes memory over-subscription as Pareto-driven classification to isolate high-risk instances, not forecast aggregate usage. It profiles and schedules these instances to guide bin-packing under SLOs, achieving 36% better memory allocation with no OOM.
(summarized by gpt-5-nano on Feb 09 2026)
Paper ID
h80cf33c89031f4c8
Venue
SIGMOD
Year
2025
Pagerank
5.0745433e-05
Overall Rank
10,126 | 31.95%
DOI
10.1145/3722212.3724435
Incoming Non-self Citations Over Time
BibTeX Citation
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@inproceedings{li_sigmod25,
title = {{Eigen+: Memory Over-Subscription for Alibaba Cloud Databases}},
author = {Li, Ji You and Zhang, Jiachi and Liu, Yuhang and Zhou, Wenchao and Zhou, Xin and Zhou, Fangyuan and Li, Feifei},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3722212.3724435},
url = {https://dl.acm.org/doi/10.1145/3722212.3724435},
year = {2025}
}
Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 cited papers.
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Moneyball: Proactive Auto-Scaling in Microsoft Azure SQL Database Serverless
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9.213369e-05
2,230
Fuxi: a Fault-Tolerant Resource Management and Job Scheduling System at Internet Scale
2014
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iBTune: Individualized Buffer Tuning for Large-scale Cloud Databases
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2024
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4,668
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11,505
Flux: Decoupled Auto-Scaling for Heterogeneous Query Workload in Alibaba AnalyticDB
2024
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