NDLI: Nonuniform Compression in Databases with Haar Wavelet

Content Provider	IEEE Xplore Digital Library
Author	Chen, S. Nucci, A.
Copyright Year	2007
Description	Author affiliation: Dept. of Comput. Sci., Rutgers Univ., NJ (Chen, S.)
Abstract	Data synopsis is a lossy compressed representation of data stored into databases that helps the query optimizer to speed up the query process, e.g. time to retrieve the data from the database. An efficient data synopsis must provide accurate information about the distribution of data to the query optimizer at any point in time. Due to the fact that some data will be queried more often than others, a good data synopsis should consider the use of nonuniform accuracy, e.g. provide better approximation of data that are queried the most. Although, the generation of data synopsis is a critical step to achieve a good approximation of the initial data representation, data synopsis must be updated over time when dealing with time varying data. In this paper, we introduce new Haar wavelet synopses for nonuniform accuracy and time-varying data that can be generated in linear time and space, and updated in sublinear time. The efficiency of our new data synopses is validated against other linear methods by using both synthetic and real data sets
Starting Page	223
Ending Page	232
File Size	322358
Page Count	10
File Format	PDF
ISBN	0769527914
ISSN	10680314
DOI	10.1109/DCC.2007.59
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-03-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Approximation algorithms Cost function Query processing Information retrieval Data structures Distributed databases Database systems Computer science Data compression Approximation error
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications

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