Relational Model: Relational model represents data in the form of relations or tables.
Relational Schema: Schema represents structure of a relation. e.g.; Relational Schema of STUDENT relation can be represented as:
STUDENT (STUD_NO, STUD_NAME, STUD_PHONE, STUD_STATE, STUD_COUNTRY, STUD_AGE)
Relational Instance: The set of values present in a relation at a particular instance of time is known as relational instance as shown in Table 1 and Table 2.
Attribute: Each relation is defined in terms of some properties, each of which is known as attribute. For Example, STUD_NO, STUD_NAME etc. are attributes of relation STUDENT.
Domain of an attribute: The possible values an attribute can take in a relation is called its domain. For Example, domain of STUD_AGE can be from 18 to 40.
Tuple: Each row of a relation is known as tuple. e.g.; STUDENT relation given above has 4 tuples.
NULL values: Values of some attribute for some tuples may be unknown, missing or undefined which are represented by NULL. Two NULL values in a relation are considered different from each other.
Table 1 and Table 2 represent relational model having two relations STUDENT and STUDENT_COURSE.
Codd rules were proposed by E.F. Codd which should be satisfied by relational model.
- Information Rule: Data stored in Relational model must be a value of some cell of a table.
- Guaranteed Access Rule: Every data element must be accessible by table name, its primary key and name of attribute whose value is to be determined.
- Systematic Treatment of NULL values: NULL value in database must only correspond to missing, unknown or not applicable values.
- Active Online Catalog: Structure of database must be stored in an online catalog which can be queried by authorized users.
- Comprehensive Data Sub-language Rule: A database should be accessible by a language supported for definition, manipulation and transaction management operation.
- View Updating Rule: Different views created for various purposes should be automatically updatable by the system.
- High level insert, update and delete rule: Relational Model should support insert, delete, update etc. operations at each level of relations. Also, set operations like Union, Intersection and minus should be supported.
- Physical data independence: Any modification in the physical location of a table should not enforce modification at application level.
- Logical data independence: Any modification in logical or conceptual schema of a table should not enforce modification at application level. For example, merging of two tables into one should not affect application accessing it which is difficult to achieve.
- Integrity Independence: Integrity constraints modified at database level should not enforce modification at application level.
- Distribution Independence: Distribution of data over various locations should not be visible to end-users.
- Non-Subversion Rule: Low level access to data should not be able to bypass integrity rule to change data.
Given the basic ER and relational models, which of the following is INCORRECT? [GATE CS 2012]
A. An attribute of an entity can have more than one value
B. An attribute of an entity can be composite
C. In a row of a relational table, an attribute can have more than one value
D. In a row of a relational table, an attribute can have exactly one value or a NULL value
Answer: In relation model, an attribute can’t have more than one value. So, option C is the answer.
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- DBMS | Anomalies in Relational Model
- Database Management System | ER Model
- Database Management system | Relational Algebra
- DBMS | Concurrency Control Protocol | Multiple Granularity Locking
- DBMS | Concurrency Control Protocol | Thomas Write Rule
- Database File Indexing – B+ Tree (Introduction)
- PL/SQL Introduction
- DBMS | Concurrency Control Protocols | Timestamp Ordering Protocols