Database schema change has long been recognized as a complex, time-consuming and risky process. It requires not only the modification of database structures and contents, but also the joint evolution of related application programs. This coevolution process mainly consists in converting database queries expressed on the source database schema, into equivalent queries expressed on the target database schema. Several approaches, techniques and tools have been proposed to address this problem, by considering software systems relying on a single database. In this paper, we propose an automated approach to query adaptation for schema changes in hybrid polystores, i.e., data-intensive systems relying on several, possibly heterogeneous, databases. The proposed approach takes advantage of a conceptual modeling language for representing the polystore schema, and considers a generic query language for expressing queries on top of this schema. Given a source polystore schema, a set of input queries and a list of schema change operators, our approach (1) identifies those input queries that cannot be transformed into equivalent queries expressed on the target schema, (2) automatically transforms those input queries that can be adapted to the target schema, and (3) generates warnings for those output queries requiring further manual inspection.
|titre||Proceedings of the 20th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM 2020)|
|Editeur||IEEE Computer Society Press|
|Nombre de pages||5|
|Etat de la publication||Publié - sept. 2020|
Série de publications
|Nom||Proceedings - 20th IEEE International Working Conference on Source Code Analysis and Manipulation, SCAM 2020|
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Best New Idea and Emerging Results (NIER) Paper Award at the 20th IEEE Working Conference on Source Code Analysis and Manipulation (SCAM 2020)
Prix: Prix (y compris les médailles et récompenses)