This paper is a pioneer work by in relational database systems concepts of which are used to develop a sound database model even today When we study a good database model the key characteristic that defines the model is the non alteration of activities of users and application programs when changes are made to internal or external representation of data The Paper talks about the existing database models until 1970 its drawbacks by considering the problem of data dependency and subsequent solutions to fix them Ordering dependency resulted in the failure of an application program as the program failed to differentiate between the stored ordering and the presentation ordering of the data due to the changes made to the data stored indexing Indexing dependency slowed down during addition and deletion operations Since indexing is redundant indices needed to be created and destroyed accordingly The problem of Access Path dependency could be handled by not making the path as obsolete only when all the application programs using the paths have become obsolete The relational view of the data is presented well in the next section of the paper with its characteristics an array representation of relations where each row being distinct represents an n tuple in relation R and its ordering is not necessary but the ordering of columns is important as they represent the domains on which R is defined It also solves the problem which one can encounter with identical domain names and time varying relations With higher order unique domain names and relations are domain unordered relationship
This itself provided the new idea of using relationships instead of relations to interact with the relational model Next the paper discusses about the ways to establish a good relational model by the process of Normalization A domain that is unique over all the tuples in a relation is called the primary key of the relation It can be a simple domain or a combination and if there are more than one such one among them is to be selected as the primary key It is used to cross reference other elements of the same relation or elements of a different relation To cross reference elements in other relations the foreign key of a relation should be a primary key for other relation Identifying these keys and removing the redundant domains in all the relations to a simple domain normalizes the data Simple domains are those whose elements are atomic The non normalized data should satisfy the conditions to be normalized The graphs of interrelationships of the non simple domains is a collection of trees and the primary key have a simple component domain The relational model of data also permits for the development of a universal high level language based on applied predicate calculus The required arithmetic functions can be defined in the programming language and invoked in relation For an n ary relation to support symmetric exploitation it needs n factorial paths to be named and controlled To represent an n ary relation using only nested binary representation it needs 2n 1 names instead of n 1 names using n ary notation The two collections of relations are named set and expressible set where named set is a subset of expressible set A named set is a collection of relations which has a simple name A relation can be a member of a named set if declared by an authorized user
An expressible set is collection of relations designated by expressions in data language These are constructed from simple names of relations in named set Since relations are sets all usual set operations are applicable The paper lists the unusual set of operations which include Permutation Projection Join Composition and Restriction and how these are used on the relations Permutation interchanging the columns is done with n possible results Projection is when a certain column and removing from the resulting array any duplicates in the rows A Join is performed when two relations which can be joined without loss of information to form new relation is performed by using the concept of Cartesian product Composition is a projection of a join thus only joinable relations are composable and two relations need not have n composition even though there exist n joins among them Restriction is defined only if equality is applicable among the elements of the relations and is also a subset of a relation In the final section it addresses the two types of redundancies Strong and Weak redundancy According to the paper generally if a collection of operations θ in a certain order on relation R results in a particular relation S for all time then Relation R is θ derivable from set S The paper defines a set of relations strongly redundant if it contains at least one relation that possesses a projection which is derivable from the other projections of relations in the set where as a collection of relations is weakly redundant if it contains a relation that has a projection which is not derivable from other members but is at all times a projection of some join of other projections of relations in the collection Closely associated concept of consistency is also explained well in the paper When the instantaneous value of a time varying relation always gives rise to the same results it is said to be consistent Consistency checks could be performed on updates deletions and insertions and the inconsistencies could be recorded
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