Efficiently Detecting Inclusion Dependencies

Data sources for data integration often come with spurious schema definitions such as undefined foreign key constraints. Such metadata are important for querying the database and for database integration. We present our algorithm SPIDER (single pass inclusion dependency recognition) for detecting inclusion dependencies, as these are the automatically testable part of a foreign key constraint. For IND detection all pairs of attributes must be tested. SPIDER solves this task very efficiently by testing all attribute pairs in parallel. It analyzes a 2 GB database in ~ 20 min and a 21 GB database in ~ 4 h.