Permanent URL to this publication: http://dx.doi.org/10.5167/uzh-24448
Data provenance is essential in applications such as scientific computing, curated databases, and data warehouses. Several systems have been developed that provide provenance functionality for the relational data model. These systems support only a subset of SQL, a severe limitation in practice since most of the application domains that benefit from provenance information use complex queries. Such queries typically involve nested subqueries, aggregation and/or user defined functions. Without support for these constructs, a provenance management system is of limited use.
In this paper we address this limitation by exploring the problem of provenance derivation when complex queries are involved. More precisely, we demonstrate that the widely used definition of Why-provenance fails in the presence of nested subqueries, and show how the definition can be modified to produce meaningful results for nested subqueries. We further present query rewrite rules to transform an SQL query into a query propagating provenance. The solution introduced in this paper allows us to track provenance information for a far wider subset of SQL than any of the existing approaches. We have incorporated these ideas into the Perm provenance management system engine and used it to evaluate the feasibility and performance of our approach.
|Item Type:||Conference or Workshop Item (Paper), refereed, original work|
|Communities & Collections:||03 Faculty of Economics > Department of Informatics|
|DDC:||000 Computer science, knowledge & systems|
|Uncontrolled Keywords:||provenance, query rewrite, nested subqueries|
|Event End Date:||26 March 2009|
|Deposited On:||16 Dec 2009 08:14|
|Last Modified:||09 Jul 2012 04:01|
|Series Name:||ACM International Conference Proceeding Series (AICPS)|
Scopus®. Citation Count: 5
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