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.

Advisors: Ion Stoica and Natacha Crooks

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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