Efficient And Exact Computation Of Inclusion Dependencies For Data Integration

Efficient and Exact Computation of Inclusion Dependencies for Data Integration

Data obtained from foreign data sources often come with only superficial structural information, such as relation names and attribute names. Other types of metadata that are important for effective integration and meaningful querying of such data sets are missing. In particular, relationships among attributes, such as foreign keys, are crucial metadata for understanding the structure of an unknown database. The discovery of such relationships is difficult, because in principle for each pair of attributes in the database each pair of data values must be compared. A precondition for a foreign key is an inclusion dependency (IND) between the key and the foreign key attributes. We present with Spider an algorithm that efficiently finds all INDs in a given relational database. It leverages the sorting facilities of DBMS but performs the actual comparisons outside of the database to save computation. Spider analyzes very large databases up to an order of magnitude faster than previous approaches. We also evaluate in detail the effectiveness of several heuristics to reduce the number of necessary comparisons. Furthermore, we generalize Spider to find composite INDs covering multiple attributes, and partial INDs, which are true INDs for all but a certain number of values. This last type is particularly relevant when integrating dirty data as is often the case in the life sciences domain - our driving motivation.

Proceedings of the ... Ph. D. Retreat of the HPI Research School on Service-Oriented Systems Engineering

Selected Papers of the International Workshop on Smalltalk Technologies

The goal of the IWST workshop series is to create and foster a forum around advancements of or experience in Smalltalk. The workshop welcomes contributions to all aspects, theoretical as well as practical, of Smalltalk-related topics.