Take Out the TraChe: Maximizing (Tra)nsactional Ca(che) Hit Rate


Audrey Cheng, David Chu, Terrance Li, Jason Chan, Natacha Crooks, Joseph M. Hellerstein, and Ion Stoica, UC Berkeley; Xiangyao Yu, University of Wisconsin—Madison


Most caching policies focus on increasing object hit rate to improve overall system performance. However, these algorithms are insufficient for transactions. In this work, we define a new metric, transactional hit rate, to capture when caching reduces latency for transactions. We present DeToX, a caching system that leverages transactional dependencies to make eviction and prefetching decisions. DeToX is able to significantly outperform single-object alternatives on real-world workloads and popular OLTP benchmarks, providing up to a 130% increase in transaction hit rate and 3.4x improvement in cache efficiency.

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King Abdullah University of Science and Technology (KAUST)

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@inproceedings {288548,
author = {Audrey Cheng and David Chu and Terrance Li and Jason Chan and Natacha Crooks and Joseph M. Hellerstein and Ion Stoica and Xiangyao Yu},
title = {Take Out the {TraChe}: Maximizing (Tra)nsactional Ca(che) Hit Rate},
booktitle = {17th USENIX Symposium on Operating Systems Design and Implementation (OSDI 23)},
year = {2023},
isbn = {978-1-939133-34-2},
address = {Boston, MA},
pages = {419--439},
url = {https://www.usenix.org/conference/osdi23/presentation/cheng},
publisher = {USENIX Association},
month = jul

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