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Lukasz Ziarek 2015-06-20 22:41:23 -04:00
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sections/1-introduction.tex
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@ -25,3 +25,6 @@ workloads.
% workloads based on query complexity, and database activity in Section~\ref{sec:queryc} and Section~\ref{sec:dba} respectively. Based on this
% detailed analysis and a review of related work, we sketch the requirements for a TPC-MOBILE benchmark in Section~\ref{sec:pocketdata}. We wrap up with conclusions in Section~\ref{sec:conc}.
%% LocalWords: smartphone Android Android's SQLite io smartphones
%% LocalWords: testbed PhoneLab TPC

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sections/2-overview.tex
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@ -8,3 +8,5 @@ Optimization targets also differ substantially. Latency is a primary concern, b
Finally, unlike typical server-class benchmark workloads where throughput is a key factor, embedded databases have fixed, ``small data"~\cite{Dit2015CIDR} workloads and need to share computing resources fairly with other processes on the same device. This means that in stark contrast to server-class workloads, the database is idle more frequently. Periods of low-utilization are opportunities for background optimization, but must be managed against the needs of other applications running on the device, as well as the device's limited power budget. We use the term ``pocket data" to refer to data management settings that exhibit such characteristics.
Pocket data workloads represent a growing, and extremely important class of database consumers. Unfortunately, research and development on embedded databases (\textit{e.g.},~\cite{jeong2013iostack,kang2013xftl}) is presently obligated to rely on micro-benchmarks or anecdotal observations about the needs and requirements of embedded database engines. In this paper, we lay out the characteristics of a one month trace of SQLite operations performed on eleven Android smartphones participating in the PhoneLab experimental platform~\cite{phonelab}. We believe that a new TPC-MOBILE benchmark that captures these characteristics can provide a principled, standardized way to evaluate advances in mobile database technology, which will in turn, help to drive the development of such advances.
%% LocalWords: OLTP OLAP SQLite ms Android smartphones PhoneLab TPC