On Multi-Column Foreign Key Discovery

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 appro...

• Type: Journal
• Year: 2010
• Where: PVLDB
• Authors: Meihui Zhang, Marios Hadjieleftheriou, Beng Chin Ooi, Cecilia M. Procopiuc, Divesh Srivastava
• Keywords: Foreign Keys, Multi-column Foreign Keys, PVLDB 2010, Single-column Foreign Keys