RDBMS

A relation Schema denoted by R(A1, A2, ?, An) is made up of the relation name R and the list of attributes Ai that it contains. A relation is defined as a set of tuples. Let r be the relation which contains set tuples (t1, t2, t3, ..., tn). Each tuple is an ordered list of n-values t=(v1,v2, ..., vn).

This language that enable user to access or manipulate data as organised by appropriate data model.

► Procedural DML or Low level: DML requires a user to specify what data are needed and how to get those data.

► Non-Procedural DML or High level: DML requires a user to specify what data are needed without specifying how to get those data.

It is a particular property, which describes the entity.

The collections of entities of a particular entity type are grouped together into an entity set.

A view may be thought of as a virtual table, that is, a table that does not really exist in its own right but is instead derived from one or more underlying base table. In other words, there is no stored file that direct represents the view instead a definition of view is stored in data dictionary.

Growth and restructuring of base tables is not reflected in views. Thus the view can insulate users from the effects of restructuring and growth in the database. Hence accounts for logical data independence.

Data independence means that ?the application is independent of the storage structure and access strategy of data?. In other words, The ability to modify the schema definition in one level should not affect the schema definition in the next higher level.

Two types of Data Independence are:

► Physical Data Independence: Modification in physical level should not affect the logical level.

► Logical Data Independence: Modification in logical level should affect the view level.

NOTE: Logical Data Independence is more difficult to achieve.

A collection of conceptual tools for describing data, data relationships data semantics and constraints.

Unlike Relational systems in System R

► Domains are not supported

► Enforcement of candidate key uniqueness is optional

► Enforcement of entity integrity is optional

► Referential integrity is not enforced

A Relation schema R is said to be 5NF if for every join dependency {R1, R2, ..., Rn} that holds R, one the following is true

► Ri = R for some i.

► The join dependency is implied by the set of FD, over R in which the left side is key of R.

An entity set may not have sufficient attributes to form a primary key, and its primary key compromises of its partial key and primary key of its parent entity, then it is said to be Weak Entity set.

Extension - It is the number of tuples present in a table at any instance. This is time dependent.

Intension - It is a constant value that gives the name, structure of table and the constraints laid on it.

System R was designed and developed over a period of 1974-79 at IBM San Jose Research Center. It is a prototype and its purpose was to demonstrate that it is possible to build a Relational System that can be used in a real life environment to solve real life problems, with performance at least comparable to that of existing system.

Its two subsystems are

► Research Storage

► System Relational Data System.

It is a program module, which manages the allocation of space on disk storage and data structure used to represent information stored on a disk.

PL/SQL uses cursors for all database information accesses statements. The language supports the use two types of cursors

► Implicit

► Explicit

It is a program module, which is responsible for fetching data from disk storage into main memory and deciding what data to be cache in memory.

It is a program module that provides the interface between the low-level data stored in database, application programs and queries submitted to the system.

a) on the N side in a 1 : N relationship

b) on the 1 side in a 1 : N relationship

c) on either side in a 1 : 1 relationship

d) nothing to do with 1 : 1 or 1 : N relationship

(b) on the 1 side in a 1 : N relationship

a) entities in ERD should correspond to an existing entity/store in DFD

b) entity in DFD is converted to attributes of an entity in ERD

c) relations in ERD has 1 to 1 correspondence to processes in DFD

d) relationships in ERD has 1 to 1 correspondence to flows in DFD

(a) entities in ERD should correspond to an existing entity/store in DFD

The well-known inference rules for FDs

? Reflexive rule :

If Y is subset or equal to X then X Y.

► Augmentation rule:

If X Y then XZ YZ.

► Transitive rule:

If {X Y, Y Z} then X Z.

► Decomposition rule :

If X YZ then X Y.

► Union or Additive rule:

If {X Y, X Z} then X YZ.

► Pseudo Transitive rule :

If {X Y, WY Z} then WX Z.

Of these the first three are known as Amstrong Rules. They are sound because it is enough if a set of FDs satisfy these three. They are called complete because using these three rules we can generate the rest all inference rules.

It is the program module, which tests for the satisfaction of integrity constraint and checks the authority of user to access data.