Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/39479
Title: On multi-column foreign key discovery
Authors: Zhang, M. 
Hadjieleftheriou, M.
Ooi, B.C. 
Procopiuc, C.M.
Srivastava, D.
Issue Date: 2010
Source: Zhang, M.,Hadjieleftheriou, M.,Ooi, B.C.,Procopiuc, C.M.,Srivastava, D. (2010). On multi-column foreign key discovery. Proceedings of the VLDB Endowment 3 (1) : 805-814. ScholarBank@NUS Repository.
Abstract: A foreign/primary key relationship between relational tables is one of the most important constraints in a database. From a data analysis perspective, discovering foreign keys is a crucial step in understanding and working with the data. Nevertheless, more often than not, foreign key constraints are not specified in the data, for various reasons; e.g., some associations are not known to designers but are inherent in the data, while others become invalid due to data inconsistencies. This work proposes a robust algorithm for discovering single-column and multi-column foreign keys. Previous work concentrated mostly on discovering single-column foreign keys using a variety of rules, like inclusion dependencies, column names, and minimum/maximum values. We first propose a general rule, termed Randomness, that subsumes a variety of other rules. We then develop efficient approximation algorithms for evaluating randomness, using only two passes over the data. Finally, we validate our approach via extensive experiments using real and synthetic datasets. © 2010 VLDB Endowment.
Source Title: Proceedings of the VLDB Endowment
URI: http://scholarbank.nus.edu.sg/handle/10635/39479
ISSN: 21508097
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

55
checked on Dec 8, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.