Audrey Cheng
EECS Department
University of California, Berkeley
Technical Report No. UCB/EECS-2022-270
December 16, 2022
http://www2.eecs.berkeley.edu/Pubs/TechRpts/2022/EECS-2022-270.pdf
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.
Advisor: Ion Stoica and Natacha Crooks
BibTeX citation:
@mastersthesis{Cheng:EECS-2022-270, Author = {Cheng, Audrey}, Title = {Take Out the TraChe: Maximizing (Tra)nsactional Ca(che) Hit Rate}, School = {EECS Department, University of California, Berkeley}, Year = {2022}, Month = {Dec}, URL = {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2022/EECS-2022-270.html}, Number = {UCB/EECS-2022-270}, Abstract = {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.} }
EndNote citation:
%0 Thesis %A Cheng, Audrey %T Take Out the TraChe: Maximizing (Tra)nsactional Ca(che) Hit Rate %I EECS Department, University of California, Berkeley %D 2022 %8 December 16 %@ UCB/EECS-2022-270 %U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2022/EECS-2022-270.html %F Cheng:EECS-2022-270