Summary: TeShu: a unified, extensible shuffle service that represents optimization choices as parameterized shuffle templates capturing application, workload, and data‑center variability. Templates are instantiated via efficient sampling to quickly find near‑optimal shuffles.
(summarized by gpt-5-mini on Feb 09 2026)
Paper ID
499
Venue
CIDR
Year
2023
Pagerank
5.093636e-05
Overall Rank
11,360 | 22.07%
DOI
-
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Authors
1.
Qizhen Zhang
(Microsoft; University of Pennsylvania; University of Toronto)
@inproceedings{zhang_cidr23,
address = {Amsterdam, Netherlands},
series = {{CIDR} '23},
title = {{Templating Shuffles}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Zhang, Qizhen and Wu, Jiacheng and Chen, Ang and Liu, Vincent and Loo, Boon Thau},
year = {2023}
}
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