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Perm: Processing provenance and data on the same data model through query rewriting


Glavic, B; Alonso, G (2009). Perm: Processing provenance and data on the same data model through query rewriting. In: 25th International Conference on Data Engineering, Shanghai, 29 March 2009 - 2 April 2009, 174-185.

Abstract

Data provenance is information that describes how a given data item was produced. The provenance includes source and intermediate data as well as the transformations involved in producing the concrete data item. In the context of a relational databases, the source and intermediate data
items are relations, tuples and attribute values. The transformations are SQL queries and/or functions on the relational data items. Existing approaches capture provenance information by extending the underlying data model. This has the intrinsic disadvantage that the provenance must be stored and accessed using a different model than the actual data. In this paper, we present an alternative approach that uses query rewriting to annotate result tuples with provenance information. The rewritten query and its result use the same model and can, thus, be queried, stored and optimized using standard relational database techniques. In the paper we formalize the query rewriting procedures, prove their correctness, and evaluate a first implementation of the ideas using PostgreSQL. As the experiments indicate, our approach efficiently provides provenance information inducing only a small overhead on normal operations.

Abstract

Data provenance is information that describes how a given data item was produced. The provenance includes source and intermediate data as well as the transformations involved in producing the concrete data item. In the context of a relational databases, the source and intermediate data
items are relations, tuples and attribute values. The transformations are SQL queries and/or functions on the relational data items. Existing approaches capture provenance information by extending the underlying data model. This has the intrinsic disadvantage that the provenance must be stored and accessed using a different model than the actual data. In this paper, we present an alternative approach that uses query rewriting to annotate result tuples with provenance information. The rewritten query and its result use the same model and can, thus, be queried, stored and optimized using standard relational database techniques. In the paper we formalize the query rewriting procedures, prove their correctness, and evaluate a first implementation of the ideas using PostgreSQL. As the experiments indicate, our approach efficiently provides provenance information inducing only a small overhead on normal operations.

Citations

14 citations in Web of Science®
29 citations in Scopus®
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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Uncontrolled Keywords:provenance, relational databases, query rewrite
Language:English
Event End Date:2 April 2009
Deposited On:16 Dec 2009 07:56
Last Modified:13 Nov 2016 06:22
Publisher:IEEE Computer Society
Series Name: International Conference on Data Engineering. Proceedings
Number:25
ISSN:1084-4627
ISBN:978-0-7695-3545-6
Free access at:Official URL. An embargo period may apply.
Publisher DOI:https://doi.org/10.1109/ICDE.2009.15
Official URL:http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=4812401&tag=1

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