Matthew Michael Denny and Michael Franklin

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2006-28

March 21, 2006

Many analysis applications require the ability to repeatedly execute sophisticated modeling functions, which can each take minutes or even hours to produce a single answer. Because of this expense, such applications have largely been unable to directly use such models in queries, with either on-demand or continuous query processing technology. Query processors are hindered in their ability to optimize expenseive modeling functions due to the ``black box'' nature of exisiting user-defined function (UDF) interfaces. In this paper, we address the problem of querying over sophisticated models with the development of VAOs (Variable-Accuracy Operators). VAOs use a new function interface that exposes the trade-off between compute time and accuracy that exists in many modeling functions. Using this interface, VAOs adaptively run each function call in a query only to an accuracy needed to answer the query, thus eliminating unneeded work. In this paper, we present the design of VAOs for a set of common query operations. We show the effectiveness of VAOs using a prototype implementation running financial queries over real bond market data.

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BibTeX citation:

@techreport{Denny:EECS-2006-28,
    Author= {Denny, Matthew Michael and Franklin, Michael},
    Title= {Adaptive Execution of Variable-Accuracy Functions},
    Year= {2006},
    Month= {Mar},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2006/EECS-2006-28.html},
    Number= {UCB/EECS-2006-28},
    Abstract= {Many analysis applications require the ability to repeatedly execute sophisticated modeling functions, which can each take minutes or even hours to produce a single answer.  Because of this expense, such applications have largely been unable to directly use such models in queries, with either on-demand or continuous query processing technology.  Query processors are hindered in their ability to optimize expenseive modeling functions due to the ``black box'' nature of exisiting user-defined function (UDF) interfaces. In this paper, we address the problem of querying over sophisticated models with the development of VAOs (Variable-Accuracy Operators).  VAOs use a new function interface that exposes the trade-off between compute time and accuracy that exists in many modeling functions.  Using this interface, VAOs adaptively run each function call in a query only to an accuracy needed to answer the query, thus eliminating unneeded work.  In this paper, we present the design of VAOs for a set of common query operations.  We show the effectiveness of VAOs using a prototype implementation running financial queries over real bond market data.},
}

EndNote citation:

%0 Report
%A Denny, Matthew Michael 
%A Franklin, Michael 
%T Adaptive Execution of Variable-Accuracy Functions
%I EECS Department, University of California, Berkeley
%D 2006
%8 March 21
%@ UCB/EECS-2006-28
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2006/EECS-2006-28.html
%F Denny:EECS-2006-28