By Michel Léonard (auth.)
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Extra info for Database Design Theory
On the other hand, iR does not verify the jd (R 1 R2). Another difference between a decomposition of R and a jd of R may be found in their role in the definition of a database. At the level of the definition of a database structure, we will try to find decompositions of a relation R and select one from them: this is done in part 3. But the entities of R are not actually stored in the database; they can be calculated from entities of the relations ~ of the decomposition, which are in fact stored.
In particular, they have a data dictionary which brings together the database structure. It is itself managed like a small database and can often be interrogated using the same query language as that of the main database. During the course of this book, the relevance of this relational model will allow us to introduce the main aspects of the necessary cohesion between on the one hand a data model and on the other a data information structure that may or may not be taken into account by a relational DBMS.
28 Data Modelling (from e3). X = rsx. X = rsx. X = rsx; finally, rsx is an entity of Re[x] * se[x]. X = rsx. s+ = s. Rs+. R+us+ = rs and thus re is an entity of (R*S)e . Consequently, rsx is an entity of (R*S)e[X]. (f4) focus (R + S/X) =focus (R/X) +focus (S/X). focus (R + S/X) = (R + S)e[X] = (Re + se)[X]. The proof follows the same reasoning as the previous case. (f5) not focus (R/X) c focus (not R/X). If X contains R+ then there is equality. not focus (R/X) =not (Re[x]). X -:t. X = x, re'e notRe: x belongs to (not Re)[X].