Have Your Cake and Eat it, Too: Data Provenance for Turing-Complete SQL Queries

Tobias Müller

Proceedings of the VLDB 2016 PhD Workshop, New Delhi, India, September 2016.


We report on our work about the computation of data provenance for feature-rich SQL. Among further constructs, our prototype supports correlated subqueries, aggregations, recursive queries and window functions. Our analysis approach completely sidesteps relational algebra and instead requires a translation of the input query into an imperative-style program. Provided that the target language is Turing-complete, any SQL query can be covered. We employ a new variant of program analysis which consists of a dynamic and a static part. This two-step approach enables us to dodge limitations that a Turing-complete computation model entails for program analyses otherwise. The derived data provenance directly reflects the data provenance of the original SQL query.