TY - GEN
T1 - On Multiple Semantics for Declarative Database Repairs
AU - Gilad, Amir
AU - Deutch, Daniel
AU - Roy, Sudeepa
N1 - Publisher Copyright:
© 2020 Association for Computing Machinery.
PY - 2020/6/14
Y1 - 2020/6/14
N2 - We study the problem of database repairs through a rule-based framework that we refer to as Delta Rules. Delta rules are highly expressive and allow specifying complex, cross-relations repair logic associated with Denial Constraints, Causal Rules, and allowing to capture Database Triggers of interest. We show that there are no one-size-fits-all semantics for repairs in this inclusive setting, and we consequently introduce multiple alternative semantics, presenting the case for using each of them. We then study the relationships between the semantics in terms of their output and the complexity of computation. Our results formally establish the tradeoff between the permissiveness of the semantics and its computational complexity. We demonstrate the usefulness of the framework in capturing multiple data repair scenarios for an academic search database and the TPC-H databases, showing how using different semantics affects the repair in terms of size and runtime, and examining the relationships between the repairs. We also compare our approach with SQL triggers and a state-of-the-art data repair system.
AB - We study the problem of database repairs through a rule-based framework that we refer to as Delta Rules. Delta rules are highly expressive and allow specifying complex, cross-relations repair logic associated with Denial Constraints, Causal Rules, and allowing to capture Database Triggers of interest. We show that there are no one-size-fits-all semantics for repairs in this inclusive setting, and we consequently introduce multiple alternative semantics, presenting the case for using each of them. We then study the relationships between the semantics in terms of their output and the complexity of computation. Our results formally establish the tradeoff between the permissiveness of the semantics and its computational complexity. We demonstrate the usefulness of the framework in capturing multiple data repair scenarios for an academic search database and the TPC-H databases, showing how using different semantics affects the repair in terms of size and runtime, and examining the relationships between the repairs. We also compare our approach with SQL triggers and a state-of-the-art data repair system.
KW - database constraints
KW - provenance
KW - repairs
KW - triggers
UR - http://www.scopus.com/inward/record.url?scp=85086280002&partnerID=8YFLogxK
U2 - 10.1145/3318464.3389721
DO - 10.1145/3318464.3389721
M3 - Conference contribution
AN - SCOPUS:85086280002
T3 - Proceedings of the ACM SIGMOD International Conference on Management of Data
SP - 817
EP - 831
BT - SIGMOD 2020 - Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data
PB - Association for Computing Machinery
T2 - 2020 ACM SIGMOD International Conference on Management of Data, SIGMOD 2020
Y2 - 14 June 2020 through 19 June 2020
ER -