TY  - JOUR
A1  - Jiang, Lan
A1  - Naumann, Felix
T1  - Holistic primary key and foreign key detection
T2  - Journal of intelligent information systems : JIIS
N2  - Primary keys (PKs) and foreign keys (FKs) are important elements of relational schemata in various applications, such as query optimization and data integration. However, in many cases, these constraints are unknown or not documented. Detecting them manually is time-consuming and even infeasible in large-scale datasets. We study the problem of discovering primary keys and foreign keys automatically and propose an algorithm to detect both, namely Holistic Primary Key and Foreign Key Detection (HoPF). PKs and FKs are subsets of the sets of unique column combinations (UCCs) and inclusion dependencies (INDs), respectively, for which efficient discovery algorithms are known. Using score functions, our approach is able to effectively extract the true PKs and FKs from the vast sets of valid UCCs and INDs. Several pruning rules are employed to speed up the procedure. We evaluate precision and recall on three benchmarks and two real-world datasets. The results show that our method is able to retrieve on average 88% of all primary keys, and 91% of all foreign keys. We compare the performance of HoPF with two baseline approaches that both assume the existence of primary keys.
KW  - Data profiling application
KW  - Primary key
KW  - Foreign key
KW  - Database
KW  - management
Y1  - 2019
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/57216
SN  - 0925-9902
SN  - 1573-7675
VL  - 54
IS  - 3
SP  - 439
EP  - 461
PB  - Springer
CY  - Dordrecht
ER  -