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MauveDB: supporting model-based user views in database systems (2006)
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| Venue: | In SIGMOD |
| Citations: | 107 - 7 self |
BibTeX
@INPROCEEDINGS{Deshpande06mauvedb:supporting,
author = {Amol Deshpande},
title = {MauveDB: supporting model-based user views in database systems},
booktitle = {In SIGMOD},
year = {2006},
pages = {73--84}
}
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Abstract
Real-world data — especially when generated by distributed measurement infrastructures such as sensor networks — tends to be incomplete, imprecise, and erroneous, making it impossible to present it to users or feed it directly into applications. The traditional approach to dealing with this problem is to first process the data using statistical or probabilistic models that can provide more robust interpretations of the data. Current database systems, however, do not provide adequate support for applying models to such data, especially when those models need to be frequently updated as new data arrives in the system. Hence, most scientists and engineers who depend on models for managing their data do not use database systems for archival or querying at all; at best, databases serve as a persistent raw data store. In this paper we define a new abstraction called modelbased views and present the architecture of MauveDB, the system we are building to support such views. Just as traditional database views provide logical data independence, model-based views provide independence from the details of the underlying data generating mechanism and hide the irregularities of the data by using models to present a consistent view to the users. MauveDB supports a declarative language for defining model-based views, allows declarative querying over such views using SQL, and supports several different materialization strategies and techniques to efficiently maintain them in the face of frequent updates. We have implemented a prototype system that currently supports views based on regression and interpolation, using the Apache Derby open source DBMS, and we present results that show the utility and performance benefits that can be obtained by supporting several different types of modelbased views in a database system. 1.
Keyphrases
database system model-based user view model-based view modelbased view declarative language consistent view real-world data sensor network performance benefit persistent raw data store several different materialization strategy frequent update logical data independence traditional database view current database system adequate support new abstraction first process prototype system distributed measurement infrastructure robust interpretation several different type present result new data arrives probabilistic model apache derby open source dbms traditional approach
