DocumentCode :
3019998
Title :
Automatic relationship discovery in self-managing database systems
Author :
Ilyas, Ihab ; Markl, Volker ; Haas, Peter J. ; Brown, Paul G. ; Aboulnaga, Ashraf
Author_Institution :
Purdue Univ., West Lafayette, IN, USA
fYear :
2004
fDate :
17-18 May 2004
Firstpage :
340
Lastpage :
341
Abstract :
In this paper, we describe CORDS, an algorithm that automatically discovers correlations and soft functional dependencies (FDs) between pairs of columns and, based on these relationships, determines a set of statistics to maintain. This data-driven technology is an essential complement to query-driven approaches such as LEO, helping to ensure acceptable performance during slow learning periods. CORDS focuses on column pairs because this greatly simplifies the algorithms, and experiments have shown that the marginal benefit of capturing n-way dependencies for n > 2 is relatively small.
Keywords :
data mining; database management systems; fault tolerant computing; query processing; self-adjusting systems; statistical analysis; CORDS; LEO; automatic relationship discovery; data-driven technology; n-way dependencies; query-driven approaches; self-managing database systems; soft functional dependencies; Character generation; Cost function; Database systems; Error analysis; Feedback; Linear approximation; Low earth orbit satellites; Relational databases; Statistical analysis; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Autonomic Computing, 2004. Proceedings. International Conference on
Print_ISBN :
0-7695-2114-2
Type :
conf
DOI :
10.1109/ICAC.2004.1301405
Filename :
1301405
Link To Document :
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