Semantics of Relations
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More often we remove the nested group to another relation In Fig 7-4 this is done with the nests of supervised employees, the no of supervisees can range from 0 for the janitor to n 1 for the company president A new relation Supervision is used to capture all the nested supervisees lists for all employees The repetition of the supervising employee s name in the super eld provides the linkage from the tuples in the new Employee 1 relation, so that the information about who supervises whom is not lost The process of removing nested groups is called normalization, and the resulting relations are designated to be in rst normal form When relationships are expressed through common domains in separate relations rather than by being in the same tuples of one relation, the structure is less tightly bound Searching the databases for a relationship takes more e ort when binding is weaker, but exibility increases Some binding can be provided in the relation-schema The schema of the Employee 1 relation indicates that there exists a connected relation Supervision Relations throughout the remainder of this chapter are in rst normal form Schemas are the subject of Chap 8
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354 7-2 SEMANTICS OF RELATIONS
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In order to build a model we have to de ne the internal structure of the relations and the relationships between the relations In this section we present the underlying formalisms and in Sec 7-3 we will employ them to create building blocks for database design 7-2-1 Ruling and Dependent Parts A tuple of a relation can be considered to be a partial description of an entity or a real-world object Entities used in earlier examples were people, invoices, payments, and creditors Within one relation we distinguish the set of attributes which de ne the object described by the tuples - the ruling part - and those which provide data regarding the object - the dependent part In most our view models relations should have ruling parts which are unique, since we wish to have only one descriptive tuple per object This immediately makes the tuples themselves unique The ruling part should not contain redundant attributes; that is, it should not contain attributes, which when removed, would still leave a ruling part with the property of uniqueness When an employee number is in the ruling part of a relation, the employee name is not also in the ruling part, since employee numbers are assigned uniquely As a notational convenience in the examples that follow, we will in relation-schemas place the ruling part before the dependent part and separate them with the symbol :
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Relation-schema for a automobile registry
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Automobile: RELATION state, license number
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: make, model, year manufactured, owner;
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Since rst-normal-form relations are also mathematical sets, the tuples of a relation must be unique Given this constraint it is always possible to nd a unique ruling part; in the worst case, it includes all the attributes and the dependent part is null
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Structure versus Meaning Finer distinctions among relationships can be made A single concept, dependent attribute, is used to convey all the shades of meaning available through expressions such as belongs to , being , married to , possessed by , purchased by , and having A model connection to another relation can describe the employees with whom a person works, the department, the position held, or the product produced Knowledge of the semantic structure supplements in an essential manner the contents of the database itself We treat the semantics in a simpli ed manner, discussing meaning only to the extent that the semantic relationships a ect the structure of a view or database model
Dependent part attributes of a relation depend on the ruling part of the relation for their de nition and existence Similarily we nd that attributes in one, secondary relation may depend on attributes in another, primary relation If the dependent attributes are in the ruling part of the secondary relation, the existence of tuples in that relation becomes dependent on attributes of the primary relation