Towards a Parallel Approach for Incremental Mining of Functional Dependencies on Multi-core Systems

A general assumption in all existing algorithms for mining functional dependencies is that the database is static. However, real life databases are frequently updated. To the best of our knowledge, the discovery of functional dependencies in dynamic databases has never been studied. A naive solution consists in re-applying one of the existing algorithms to discover functional dependencies holding on the updated database. Nevertheless, in many domains, where response time is crucial, re-executing algorithms from the scratch would be inacceptable. To address this problem, we propose to harness the multi-core systems for an incremental technique for discovering the new set of functional dependencies satisfied by the updated database. Through a detailed experimental study, we show that our parallel algorithm scales very well with the number of cores available.