Schema Evolution

Schema Evolution

Zouhaier Brahmia (University of Sfax, Tunisia), Fabio Grandi (University of Bologna, Italy), Barbara Oliboni (University of Verona, Italy) and Rafik Bouaziz (University of Sfax, Tunisia)
Copyright: © 2015 |Pages: 10
DOI: 10.4018/978-1-4666-5888-2.ch753

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In this section, we illustrate with a simple example the functioning of schema evolution, contrasting it with the lowest level of schema change support that can be embedded in a database, that is the modality of schema modification (Jensen et al., 1998). Assume that we have a relational database that contains only an AUTHOR relation with the attributes ID (primary key), NAME, PHONE, and COUNTRY. The first state of this database is as shown in Figure 1.

Figure 1.


The catalogues store information on the schema S1 of the AUTHOR relation. The table AUTHOR contains two tuples for two authors. Then consider the following schema changes:


The schema modification technique allows users to effect changes to the database schema, but neither previous schema nor its underlying data are preserved: the old schema is replaced by the new schema, which is initially empty as data populating the old schema are discarded. The effects in our example would be as shown in Figure 2.

Figure 2.


Key Terms in this Chapter

Schema Change Semantics: The effects of a schema change at schema level.

Schema Changes: Operations performed on a (populated) database schema, in order to adapt it to new application requirements.

Database Schema: The formal structure of the database, described by means of a data definition language.

Schema Evolution: A schema change modality that avoids the loss of extant data. No support is required for previous schemata.

Schema Change Propagation: The effects of a schema change at instance level, involving suitable conversions necessary to adapt extant data to the new schema.

Database Conversion/Migration: Process consisting in adapting data valid under a given schema version to another schema version.

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