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									                                        Assignment – SET 1
                          Subject – Database Management System
                                        Code: MI0034



Q1. Differentiate between Traditional File System & Modern Database System? Describe the
properties of Database & the Advantage of Database?



Traditional File Systems Vs Modern Database Management Systems


Traditional File System                                      Modern Database Management Systems


Traditional File system is the system that was followed This is the Modern way which has replaced the
before the advent of DBMS i.e., it is the older way.         older concept of File system.


In Traditional file processing, data definition is part of   Data definition is part of the DBMS
the application program and works with only specific
                                                             Application is independent and can be used with
application.
                                                             any application.


File systems are Design Driven; they require                 One extra column (Attribute) can be added
design/coding change when new kind of data occurs.           without any difficulty

E.g.: In a traditional employee the master file has          Minor coding changes in the Application
Emp_name, Emp_id, Emp_addr, Emp_design,                      program may be required.
Emp_dept, Emp_sal, if we want to insert one more
column Emp_Mob number then it requires a complete
restructuring of the file or redesign of the application
code, even though basically all the data except that in
one column is the same.


Traditional File system keeps redundant [duplicate]          Redundancy is eliminated to the maximum
information in many locations. This might result in the      extent in DBMS if properly defined.
loss of Data Consistency.

For e.g.: Employee names might exist in separate files
like Payroll Master File and also in Employee Benefit
Master File etc. Now if an employee changes his or her
last name, the name might be changed in the pay roll
master file but not be changed in Employee Benefit
Master File etc. This might result in the loss of Data
Consistency.


In a File system data is scattered in various files, and     This problem is completely solved here.
each of these files may be in different formats, making
it difficult to write new application programs to retrieve
the appropriate data.


Security features are to be coded in the Application         Coding for security requirements is not required
Program itself.                                              as most of them have been taken care by the
                                                             DBMS.


Hence, a data base management system is the software that manages a database, and is responsible for its
storage, security, integrity, concurrency, recovery and access.

The DBMS has a data dictionary, referred to as system catalog, which stores data about everything it
holds, such as names, structure, locations and types. This data is also referred to as Meta data.

Properties of Database

The following are the important properties of Database:

1. A database is a logical collection of data having some implicit meaning. If the data are not related then
it is not called as proper database.
E.g. Student studying in class II got 5th rank.


Stud_name                              Class                               Rank obtained
Vijetha                              Class II                             5th


2. A database consists of both data as well as the description of the database structure and constraints.

E.g.


Field Name                     Type                                   Description


Stud_name                      Character                              It is the students name


Class                          Alpha numeric                          It is the class of the student




3. A database can have any size and of various complexity. If we consider the above example of
employee database the name and address of the employee may consists of very few records each with
simple structure. E.g.


Emp_name           Emp_id        Emp_addr                                   Emp_desig           Emp_Sal


Prasad             100           Shubhodaya, Near Katariguppe Big           Project Leader      40000
                                 Bazaar, BSK II stage, Bangalore


Usha               101           #165, 4th main Chamrajpet, Bangalore       Software            10000
                                                                            engineer


Nupur              102           #12, Manipal Towers, Bangalore             Lecturer            30000


Peter              103           Syndicate house, Manipal                   IT executive        15000




Like this there may be n number of records.
4. The DBMS is considered as general-purpose software system that facilitates the process of defining,
constructing and manipulating databases for various applications.

5. A database provides insulation between programs, data and data abstraction. Data abstraction is a
feature that provides the integration of the data source of interest and helps to leverage the physical data
however the structure is.

6. The data in the database is used by variety of users for variety of purposes. For E.g. when you consider
a hospital database management system the view of usage of patient database is different from the same
used by the doctor. In this case the data are stored separately for the different users. In fact it is stored in a
single database. This property is nothing but multiple views of the database.

7. Multiple user DBMS must allow the data to be shared by multiple users simultaneously. For this
purpose the DBMS includes concurrency control software to ensure that the updating done to the database
by variety of users at single time must get updated correctly. This property explains the multiuser
transaction processing.

Advantages of using DBMS

1. Redundancy is reduced

2. Data located on a server can be shared by clients

3. Integrity (accuracy) can be maintained

4. Security features protect the Data from unauthorized access

5. Modern DBMS support internet based application.

6. In DBMS the application program and structure of data are independent.

7. Consistency of Data is maintained

8. DBMS supports multiple views. As DBMS has many users, and each one of them might use it for
different purposes, and may require to view and manipulate only on a portion of the database, depending
on requirement.



Q2. What is the disadvantage of sequential file organization? How do you overcome it? What are the
advantages & disadvantages of Dynamic Hashing?
In this file organization, the records of the file are stored one after another both physically and logically.
That is, record with sequence number 16 is located just after the 15th record.

A record of a sequential file can only be accessed by reading all the previous records.

The records are discriminated from one another using the record length declared in the associated FD
statement of the FILE-SECTION. For example, If the record structure that the programmer has declared
is 52 bytes, blocks of 52 byte data (records) are assumed to placed one after another in the file. If the
programmer is reading the data in a sequential file, every READ statement brings 52 bytes into the
memory.

If the file contains, say, 52 byte records; but the programmer tries to read this file with a program which
has declared 40 byte records (i.e the total length of the FD structure is 40 bytes), the program will
certainly read some pieces of information into the memory but the after the first READ statement, some
meaningless pieces of records will be brought into memory and the program will start processing some
physical records which contain logically meaningless data.

It is the programmer's responsibility to take care of the record sizes in files. You must be careful when
declaring record structures for files. Any mistake you make in record sizes will cause your program to
read/write erroneous information. This is especially dangerous if the file contents are being altered
(changed, updated).

Since the records are simply appended to each other when building SEQUENTIAL files, you simply end
up with a STREAM of byte. If this string does not contain any "Carriage Return/Line Feed" control
characters in it, the whole file will appear as a single LINE of character and would be impsossible to
process with regular text editors. As you should know by now, text editors are good in
reading/writing/modifying text files. These programs will assume that the file consists of LINES and
expect the lines to separated from each other by a pair of control characters called "Carriage Return/Line
Feed" (or CR/LF).

COBOL has a special type of sequential file organization, which is called the LINE SEQUENTIAL
ORGANIZATION which places a CR/LF pair at the end of each record while adding records to a file and
expect such a pair while reading. LINE SEQUENTIAL files are much easier to use while developing
programs because you can always use a simple text editor to see the contents of your sequential file and
trace/debug your program.

Please note that LINE SEQUENTIAL files have two extra characters for each record. For files, which
have millions of records, this might use up a significant amount of disk space.

SEQUENTIAL files have only one ACCESS MODE and that is "sequential access". Therefore you need
not specify an ACCESS MODE in the SELECT statement. Typical SELECT statements for
SEQUENTIAL files are :

  SELECT MYFILE ASSIGN TO DISK "MYFILE.DAT"
     ORGANIZATION IS SEQUENTIAL.
     SELECT MYFILE-2 ASSIGN TO DISK "C:\DATADIR\MYFILE2.TXT"
     ORGANIZATION IS LINE SEQUENTIAL.
In the FILE-SECTION, you must provide FD blocks for each file; hence for a sequential file you could
have something like :

 FD MYFILE.
   01 MYFILE-REC.
     02 M-NAME PIC X(16).
     02 M-SURNAME PIC X(16).
     02 M-BIRTHDATE.
       03 M-BD-YEAR PIC 9999.
       03 M-BD-MONTH PIC 99.
       03 M-BD-DAY PIC 99.


Note : You must NOT provide record fields for the extra two CR/LF bytes in record descriptions of LINE
SEQ files. Once you declare the file to be a LINE SEQ file, these two extra bytes are automatically taken
in consideration and added for all new records that are added to a file.

It is NOT possible to delete records of a seq file. If you do not want a specific record to be kept in a seq
file any more, all you can do is to modify the contents of the record so that it contains some special values
that your program will recognize as deleted (remember to open the file in I-O mode and REWRITE a
new record).

Can be only processed sequentially. If you need to read record number N, you must first read the previous
N-1 records. Especially no good for programs that make frequent searches in the file.


To overcome these disadvantages some of the following hashing techniques are in use:

One disadvantage of sequential file organization is that we must use linear search or binary search to
locate the desired record and that results in more i/o operations. In this there are a number of unnecessary
comparisons. In hashing technique or direct file organization, the key value is converted into an address
by performing some arithmetic manipulation on the key value, which provides very fast access to records.



Let us consider a hash function h that maps the key value k to the value h(k). The VALUE h(k) is used as
an address.

The basic terms associated with the hashing techniques are:

1) Hash table: It is simply an array that is having address of records.

2) Hash function: It is the transformation of a key into the corresponding location or address in the hash
table (it can be defined as a function that takes key as input and transforms it into a hash table index).

3) Hash key: Let 'R' be a record and its key hashes into a key value called hash key.
The different hashing techniques are:

             Internal Hashing

             Dynamic hashing
             Extendable hashing

Dynamic Hashing Technique

A major drawback of the static hashing is that address space is fixed. Hence it is difficult to expand or
shrink the file dynamically.

In dynamic hashing, the access structure is built on the binary representation of the hash value. In this, the
number of buckets is not fixed [as in regular hashing] but grows or diminishes as needed. The file can
start with a single bucket, once that bucket is full, and a new record is inserted, the bucket overflows and
is slit into two buckets. The records are distributed among the two buckets based on the value of the first
[leftmost] bit of their hash values. Records whose hash values start with a 0 bit are stored in one bucket,
and those whose hash values start with a 1 bit are stored in another bucket. At this point, a binary tree
structure called a directory is built. The directory has two types of nodes.

1. Internal nodes: Guide the search, each has a left pointer corresponding to a 0 bit, and a right pointer
corresponding to a 1 bit.

2. Leaf nodes: It holds a pointer to a bucket a bucket address.

Each leaf node holds a bucket address. If a bucket overflows, for example: a new record is inserted into
the bucket for records whose hash values start with 10 and causes overflow, then all records whose hash
value starts with 100 are placed in the first split bucket, and the second bucket contains those whose hash
value starts with 101. The levels of a binary tree can be expanded dynamically.

Advantages of dynamic hashing:

1. The main advantage is that splitting causes minor reorganization, since only the records in one bucket
are redistributed to the two new buckets.

2. The space overhead of the directory table is negligible.

3. The main advantage of extendable hashing is that performance does not degrade as the file grows. The
main space saving of hashing is that no buckets need to be reserved for future growth; rather buckets can
be allocated dynamically.
Disadvantages:

1. The index tables grow rapidly and too large to fit in main memory. When part of the index table is
stored on secondary storage, it requires extra access.

2. The directory must be searched before accessing the bucket, resulting in two-block access instead of
one in static hashing.

3. A disadvantage of extendable hashing is that it involves an additional level of indirection.



Q3. What is relationship type? Explain the difference among a relationship instance, relationship type
& a relation set?


Answer later

Q4. What is SQL? Discuss.

SQL stands for Structured Query language

The Structured Query language is used for programming the database. The history of SQL began in an
IBM laboratory in San Jose, California, where SQL was developed in the late 1970's. SQL stands for
structured Query Language. It is a non-procedural language, meaning that SQL describes what data to
retrieve delete or insert, rather than how to perform the operation. It is the standard command set used to
communicate with the RDBMS.


A SQL query is not-necessarily a question to the database. It can be command to do one of the
following.

Create or delete a table.

Insert, modify or delete rows.

Search several rows for specifying information and return the result in order.

Modify security information.

THE SQL STATEMENT CAN BE GROUPED INTO FOLLOWING CATEGORIES.

1. DDL(Data Definition Language)

2. DML(Data Manipulation Language)

3. DCL(Data Control Language)
4. TCL(Transaction Control Language)

DDL: Data Definition Language

DML: (Data Manipulation Language)

The DML statements are used to alter the database tables in someway. The UPDATE, INSERT and
DELETE statements alter existing rows in a database tables, insert new records into a database table, or
remove one or more records from the database table.

DCL: (Data Control Language)

The Data Control Language Statements are used to Grant permission to the user and Revoke permission
from the user, Lock certain Permission for the user.

SQL DBA>Revoke Import from Akash;

SQL DBA>Grant all on emp to public;

SQL DBA>Grant select, Update on EMP to L.Suresh;

SQlDBA>Grant ALL on EMP to Akash with Grant option;

Revoke: Revoke takes out privilege from one or more tables or views.

SQL DBA>rEOKE UPDATE, DELETE FROM l.sURES;

SQL DBA>Revoke all on emp from Akash

TCL: (Transaction Control Language)

It is used to control transactions.

Eg: Commit

The DDL statement provides commands for defining relation schema i,e for creating tables, indexes,
sequences etc. and commands for dropping, altering, renaming objects.

SQL* COMMANDS:

This subsection discusses the often used commands in sql environment. For example, if your SQL
commands are saved in a file (typically in note pad) you can execute this file using an "at" @command,
similarly there are a number of such commands:
@<filename> Runs the command file stored in <filename>




DATA TYPES IN ORACLE 8i SQL:

The fig. shows the complete listing of the data types allowed in oracle.


DATA TYPE                      DESCRIPTION


CHAR (sizs)                    Fixed length character. Max = 2000


VARCHAR2(size)                 Variable length character. Max=4000


DATE                           Date, valid range is from jan1,4712 B.C to.
                               DEC 31,4712 A.D.


BLOB                           Binary large object Max =4GB


CLOB                           Character large object Max=4G.B.




BFILE                          Pointer to binary OS file
LONG                            Character data of variable size, Max=2G.B.


LONG RAW                        Raw binary data. Rest is same as long


NUMBER (size)                   Numbers. Max. size =40 digits


NUMBER(size,d)                  Numbers, range=1.0E-130 to 9.9E125


DECIMAL                         Same as NUMBER. Size /d can't be specified


FLOAT                           Same as NUMBER


INTEGER                         Same as NUMBER Size /d can't be specified


SMALLINT                        Same as NUMBER




Q5. What is Normalization? Discuss various types of Normal Forms?

Introduction to Normalization

In Unit 8 you learnt about how to create database using SQL. In this unit we will study how to normalize
the data in the database. Normalization is the process of building database structures to store data, because
any application ultimately depends on its data structures. If the data structures are poorly designed, the
application will start from a poor foundation. This will require a lot more work to create a useful and
efficient application. Normalization is the formal process for deciding which attributes should be grouped
together in a relation. Normalization serves as a tool for validating and improving the logical design, so
that the logical design avoids unnecessary duplication of data, i.e. it eliminates redundancy and promotes
integrity. In the normalization process we analyze and decompose the complex relations into smaller,
simpler and well-structured relations.

Normal forms Based on Primary Keys
A relation schema R is in first normal form if every attribute of R takes only single atomic values. We can
also define it as intersection of each row and column containing one and only one value. To transform the
un-normalized table (a table that contains one or more repeating groups) to first normal form, we identify
and remove the repeating groups within the table.

E.g.

Dept.


D.Name                         D.No                        D. location


R&D                            5                           [England, London, Delhi)


HRD                            4                           Bangalore


Figure A

Consider the figure that each dept can have number of locations. This is not in first normal form because
D.location is not an atomic attribute. The dormain of D location contains multivalues.

There is a technique to achieve the first normal form. Remove the attribute D.location that violates the
first normal form and place into separate relation Dept_location




Functional dependency: The concept of functional dependency was introduced by Prof. Codd in 1970
during the emergence of definitions for the three normal forms. A functional dependency is the constraint
between the two sets of attributes in a relation from a database.

Given a relation R, a set of attributes X in R is said to functionally determine another attribute Y, in R,
(X->Y) if and only if each value of X is associated with one value of Y. X is called the determinant set
and Y is the dependant attribute.

For eg.: Consider the example of STUDENT_COURSE database.
STUDENT_COURSE




In the STUDENT_COURSE database (Sid) student id does not uniquely identifies a tuple and therefore it
cannot be a primary key. Similarly (Cid) course id cannot be primary key. But the combination of (Sid,
Cid) uniquely identifies a row in STUDENT_COURSE. Therefore (Sid, Cid) is the primary key which
uniquely retrieves Sname, address, course, marks, which are dependent on the primary key.




Second Normal Form (2 NF)

A second normal form is based on the concept of full functional dependency. A relation is in second
normal form if every non-prime attribute A in R is fully functionally dependent on the Primary Key of R.
Emp_Project:Emp_ProjectFigure 9.2: 2NF and 3 NF, (a) Normalizing EMP_PROJ into 2NF relations




Normalizing EMP_DEPT into 3NF relations

A Partial functional dependency is a functional dependency in which one or more non-key attributes are
functionally dependent on part of the primary key. It creates a redundancy in that relation, which results
in anomalies when the table is updated.

Third Normal Form (3NF)

This is based on the concept of transitive dependency. We should design relational schema in such a way
that there should not be any transitive dependencies, because they lead to update anomalies. A functional
dependence [FD] x->y in a relation schema 'R' is a transitive dependency. If there is a set of attributes 'Z'
Le x->, z->y is transitive. The dependency SSN->Dmgr is transitive through Dnum in Emp_dept relation
because SSN->Dnum and Dnum->Dmgr, Dnum is neither a key nor a subset [part] of the key.
According to codd's definition, a relational schema 'R is in 3NF if it satisfies 2NF and no no_prime
attribute is transitively dependent on the primary key. Emp_dept relation is not in 3NF, we can normalize
the above table by decomposing into E1 and E2.

Note: Transitive is a mathematical relation that states that if a relation is true between the first value and
the second value, and between the second value and the 3rd value, then it is true between the 1st and the 3rd
value.

Example 2:

Consider a relation schema 'Lots' which describes the parts of land for sale in various countries of a state.
Suppose there are two candidate keys: property_ID and {Country_name.lot#}; that is, lot numbers are
unique only within each country, but property_ID numbers are unique across countries for entire state.

Based on the two candidate keys property_ID and {country name,Lot} we know that functional
dependencies FD1 and FD2 hold. Suppose the following two additional functional dependencies hold in
LOTS.

FD3: Country_name -> tax_rate

FD4: Area -> price

Here, FD3 says that the tax rate is fixed for a given country                            , FD4 says that price

of a Lot is determined by its area,               . The Lots relation schema violates 2NF, because tax_rate
is partially dependent upon candidate key { Country_namelot#} Due to this, it decomposes lots relation
into two relations - lots1 and lots 2.
Lots1 violates 3NF, because price is transitively dependent on candidate key of Lots1 via attribute area.
Hence we could decompose LOTS1 into LOTS1A and LOTS1B.

A relation schema R is in 3NF when it satisfies the conditions below.

1. It is fully functionally dependent on every key of 'R'

2. It is non_transitively dependent on every key of 'R'

Fourth Normal Form (4NF)

Multi valued dependencies are based on the concept of first normal form, which prohibits attributes
having a set of values. If we have two or more multi valued independent attributes in the same relation,
we get into a situation where we have to repeat every value of one of the attributes, with every value of
the other attributes to keep the relation state consistent, and to maintain independence among the
attributes involved. This constraint is specified by a Multi valued dependency.

Consider a table employee that has the attribute name, project and hobby.

An employee can work in more than one project and can have more than one hobby.

The employees projects and hobbies are independent of one another.

A given project or hobby is associated with any number of employees.

To keep the Relation State consistent we must have separate tuples to represent every combination of
employee's project and employees hobbies.

The drawback of EMPLOYEE relation is redundant data. This redundant data leads to update anomaly.
For example, if we wish to add one more project on Sybase, so that employ B is handling, then we must
add two more tuples for each hobby. The values Reading and Movie of hobby are repeated with each
value of project. This redundancy is undesirable. One way to remove redundancy is to decompose
EMPLOYEE relation into two relations PROJECT AND HOBBY.

NOW, if we wish to insert Sybase in PROJECT relation, then there is only one entry required.


Definition (MVD): A relation R(X.Y.Z) is said to have multivalued dependency                if the set of Y

values for a given [X,Z] pair does not depend on Z, but depends only on X, then we say               "X
multi-determines y" or "y is multi-dependent on x". Then such FD is called Multivalued Dependency
(MVD) and is represented by double arrows
We can also define MVD as, for each value of X there is a set of values for Y, and a set of values for Z.
However, the set of values for Y and Z are independent of each other.

So wherever two independent one_to_many relationships (A:B and A:C) are mixed on the same relation,
a multivalued dependency arises. Multivalued dependency can be avoided using the fourth normal form.

EMPLOYEE


NAME                             PROJECT                                HOBBY


A                                Microsoft                              Cricket


A                                Oracle                                 Music


A                                Microsoft                              Music


A                                Oracle                                 Cricket


B                                INTEL                                  Movies


B                                Sybase                                 Reading


B                                INTEL                                  Reading


B                                Sybase                                 Movies



Decomposed relation to reduce redundancy

PROJECT


NAME                                              PROJECT
A                                                 Microsoft


A                                                 Oracle


B                                                 Intel


B                                                 Sybase


HOBBY


NAME                                              PROJECT


A                                                 Cricket


A                                                 Music


B                                                 Movie


B                                                 Reading


Fourth Normal Form (4NF): The definition of 4NF is violated when a relation has undesirable
multivalued dependencies, and hence identify such relations and decompose into 4NF relations.


Alternate definition: A relation R is said to be in 4NF if for every MVD       that holds over R, one
of the following is true:

B     A (trivial), or

AB = R or

A is a super key
The Employee relation is not in 4NF because of the non-trivial MVDs (project and hobby attributes of
employee relation are independent of each other) and NAME is not a super key of EMPLOYEE. To make
this relation into 4NF you have to decompose EMPLOYEE to PROJECT AND HOBBY.




Q6. What do you mean by Shared Lock & Exclusive lock? Describe briefly two phase locking protocol?




Shared Locks: It is used for read only operations, i.e., used for operations that do not change or update
the data.

E.G., SELECT statement:,

Shared locks allow concurrent transaction to read (SELECT) a data. No other transactions can modify the
data while shared locks exist. Shared locks are released as soon as the data has been read.

Exclusive Locks: Exclusive locks are used for data modification operations, such as UPDATE, DELETE
and INSERT. It ensures that multiple updates cannot be made to the same resource simultaneously. No
other transaction can read or modify data when locked by an exclusive lock.

Exclusive locks are held until transaction commits or rolls back since those are used for write operations.

There are three locking operations: read_lock(X), write_lock(X), and unlock(X). A lock associated with
an item X, LOCK(X), now has three possible states: "read locked", "write-locked", or "unlocked". A
read-locked item is also called share-locked, because other transactions are allowed to read the item,
whereas a write-locked item is called exclusive-locked, because a single transaction exclusive holds the
lock on the item.

Each record on the lock table will have four fields: <data item name, LOCK, no_of_reads,
locking_transaction(s)>. The value (state) of LOCK is either read-locked or write-locked.

read_lock(X):

B, if LOCK(X)='unlocked'

Then begin LOCK(X)"read-locked"
No_of_reads(x)1

end

else if LOCK(X)="read-locked"

then no_of_reads(X)no_of_reads(X)+1

else begin wait(until)LOCK(X)="unlocked" and

the lock manager wakes up the transaction);

goto B

end;

write_lock(X):

B: if LOCK(X)="unlocked"

Then LOCK(X)"write-locked";

else begin

wait(until LOCK(X)="unlocked" and

the lock manager wkes up the transaction);

goto B

end;

unlock(X):

if LOCK(X)="write-locked"

Then begin LOCK(X)"un-locked";

Wakeup one of the waiting transctions, if any

end

else if LOCK(X)=read-locked"

then begin
no_of_reads(X)no_of_reads(X)-1

if no_of_reads(X)=0

then begin LOCK(X)=unlocked";

wakeup one of the waiting transactions, if any

end

end;

The Two Phase Locking Protocol

The two phase locking protocol is a process to access the shared resources as their own without creating
deadlocks. This process consists of two phases.

1. Growing Phase: In this phase the transaction may acquire lock, but may not release any locks.
Therefore this phase is also called as resource acquisition activity.

2. Shrinking phase: In this phase the transaction may release locks, but may not acquire any new locks.
This includes the modification of data and release locks. Here two activities are grouped together to form
second phase.

IN the beginning, transaction is in growing phase. Whenever lock is needed the transaction acquires it. As
the lock is released, transaction enters the next phase and it can stop acquiring the new lock request.
                                      Assignment – SET 2
                        Subject – Database Management System
                                      Code: MI0034


Q1.Define Data Model & discuss the categories of Data Models? What is the difference between
logical data Independence & Physical Data Independence?


A database model is a theory or specification describing how a database is structured and used. Several
such models like Hierarchical model, Network model, Relational model etc., have been suggested.

Data Model, Schemas and Instances:


Data Model             It is a set of Concepts for viewing a set of data in a structured way.

                       This can be easily understood by professionals and non-technical users.

                       It can explain the way in which the organization uses and manages the
                       information.


Concepts used in a     Entity
Data Model
                       An entity is something that has a distinct, separate existence, though it need not be
                       of a material existence.

                       E.g. - Employee.

                       Attribute

                       It is the property that describes an entity

                       It is a characteristic or property of an object, such as weight, size, or color

                       Relationship

                       Describes the relationship between two or more entities
Schemas                 The description of the data base means defining the names, data type, size of a
                        column in a table and database [actual data in the table] itself.

                        The description of a database is called the database schema [or the Meta data].

                        Description of a database is specified during database design and is not frequently
                        changed.

                        Roll No.

                        Name

                        Semester

                        Branch


Instances               The collection of data stored in the database at a particular moment is a database
                        instance or database state or snapshot.

                        These changes very frequently due to addition, deletion and modification.

                        Roll No.

                        Name

                        Semester

                        Branch

                        1

                        Rajesh Prabhu

                        ii

                        E&C



Data independence is defined as the ability to modify a schema definition in one level without affecting a
schema definition in a higher level.
Physical data independence                           Logical data independence


This is the ability to modify the physical           This is the ability to modify the conceptual
scheme without causing application programs          scheme without causing application programs
to be rewritten. Modifications at this level are     to be rewritten. This is usually done when the
usually to improve performance.                      logical structure of database is altered. Logical
                                                     data independence is harder to achieve, as the
                                                     application programs are usually heavily
                                                     dependent on the logical structure of the data.
                                                     An analogy is made to abstract data types in
                                                     programming languages.




Q2. What is a B+Trees? Describe the structure of both internal and leaf nodes of a B+Tree?


Indexes are used to speed up the retrieval of records.

Indexes can be created using one or more columns, providing the basis for both rapid random lookups and
efficient ordering of access to records.

The disk space required to store the index is typically less than the storage of the table (since indexes
usually contain only the key-fields according to which the table is to be arranged, and exclude all the
other details in the table).

Index file consists of two fields, the first field contains the value and second field contains the list of
pointers to address values in the disk block

Searching an index is much faster than searching the table because the index is sorted and its rows are
very small.

Index access structure is usually defined on a single field of a file, called an indexing field.
B + Tree Index Files

The main disadvantage of the index-sequential file organization is that performance degrades as the file
grows. A B+-tree index takes the form of a balanced tree in which every path from the root of the tree to a
leaf of the tree is of the same length.

In a B- tree every value of the search field appears once at some level in the tree, along with a data pointer
[may be in internal nodes also]. In a B+-tree, data pointers [address of a particular search value] are stored
only at the leaf nodes of the tree; hence, the structure of leaf nodes differs from the structure of internal
nodes. The leaf nodes have an entry for every value of the search field, along with a data pointer to the
record.

A B+ tree is a multilevel index, but it has got different a structure. A typical node of the B+ tree contains
upto n-1 search key values such as k1,k2.n-1 and n pointers p1,p2..pn. The search key values within a
node are kept in sorted order, ki < kj.

The number of pointers in a node is called the fan out of the node.

The structure of a non-leaf node is the same as leaf nodes, except that all pointers are pointers to tree
nodes.

Each internal node is of the form >p1, k1,p2,k2.pq-1, kq-1, pq>

The root node has at least 2 tree pointers.

Each leaf node is of the form

<<k1, pr1>,<k2, pr2><kn-1, prn-1>, pnext>

each pri is a data pointer, and pnext points to the next leaf node of the B+ tree

All leaf nodes are at the same level.

Consider an example, assume that we wish to insert a record in a B+ tree of order n=3 and pleaf=2, first
we observe that root is the only node in the tree, so it is also a leaf node. As soon as more than one level is
created, the tree is divided into internal nodes and leaf nodes. Notice that every value must exist at the
leaf level, because all the data pointers are at the leaf level. However, only some values exist in internal
nodes to guide the search. Notice also that every value appearing in an internal node also appears in the
sub tree as the rightmost value.
Say for example, to insert 12, the node is split into two nodes.

The figure shows the two leaf nodes that result from inserting 12. An existing node contains 7 and 8 and
remaining value 12 in a new node. The first J = [((Pleaf + 1)1/2)] = 3/2 = 2 entries in the original node are
kept there and the remaining entries are moved to a new leaf node. The Jth search value is replicated in the
parent internal node, and an extra pointer to the new node is created in the parent. If the parent internal
node is full, it must be split. This splitting can propagate all the way up to create a new root node.




Figure 4.5: An example of insertion in a B+ tree with p=3 and Pleaf=2
Q3. Describe Projection operation, Set theoretic operation & join operation?


Project operation:

Projection operation is used to select only few columns from a table. the mathematical symbol
p<ATTRIBUTE LIST>(<relation>)

Here, <attribute list> is a list of attributes from the relation r hence the degree (number of columns) of the
result is equal to the number of attributes specified in the attribute list.

Eg 1. Select the name and salary of all the employees.

pNAME. SALARY (EMPLOYEE).

This query selected only name and salary attributes from relation EMPLOYEE

Eg. 2. Select names and addresses of all employees working for department 10.

pNAME, ADDRESS (DNO=10(EMPLOYEE)

Set theoretic operations:

These are used to merge the elements of two sets in various ways, including union, intersection and
difference. Three of these operations require the table to be union compatible. The two relations are said
to require the table to be union compatible. The two relations are said to be union compatible if the
following conditions are satisfied.

1. The two relation/tables (say R & S) that have the same number of columns (have the same degree)

2. Each column of the first relation/table must be either the same data type as the corresponding column
of the second relation/table(s).

Relations R & S
Intersection (?):

The intersection operation selects the common tuples from the two relations.

The result of the operation R?S is




Union (    ):

The result of this operation denoted by RS, is a relation that includes all tuples that are either in R or in S
or in both. Duplicate tuples will not appear in the output.




Difference ( ):

The result of the difference consists of all tuples in R but not in S




Cartesian products (X):
The Cartesian product or cross-product is a binary operation that is used to combine two relations.
Assuming R & S as relations with n and m attributes respectively, the Cartesian products R x S can be
written as,

R (A1, A2..An) x S (B1, B2.Bn)

The result of the above set operation is

Q (A1, A2..An, B1, B2.Bn)

Total number of columns in Q: degree (Q) = n + m

Total number of tuples in Q: count (Q) = Number of tuples in R* Number of tuples in S




Cartesian product of R and S can be written as,




The relation R has 2 columns and 3 tuples. The relation S has 2 columns and 3 tuples. So the Cartesian
product has 4

columns (2+2) and 6 tuples
(3 x 2).

The Cartesian product operation applied by itself is generally meaningless. It is useful only when
followed by selection and projection operations.
Renaming r (rho):

This operation is used to rename the relations or attributes. The symbol r(rho) is used to denote the
rename operator. In some situations, it is better to break down a complex query into two or more simple
querys. We must rename the relations that hold the intermediate result relations. It improves the
readability and facilitates better understanding.

The syntax is as follows:

Rename <OLD TABLE> to <NEW TABLE>




                                                                                        Here S is new
new relation and R is original relation.




                                                                                        6.4.4 The Join
Operation

Join (   ): The capability of retrieving data from multiple tables using a single SQL statement is one of
the most powerful and useful features of RDBMS. It is the availability of join operation. We know that
one table may not give all the information about a particular entity.

The join operation, denoted by     is used to combine two relations to retrieve useful information. A join
operation matches data from two or more tables; based on the values of one or more columns in each
table, it allows us to process more than one table at a time.
For e.g.: The employee table gives only the department id's, if we want to know the department name,
then we have to get the information by joining employee table and dept. table.

In join, only combinations of tuples satisfying the join condition appear in the result.

The general form of a Join operation is

R<join condition>S

For example by joining employee and department relations, we can get the name of the department in
which the employee is working (department name exists in department table).

Select emp_no, ename, dept.dname from emp.dept

Where emp.deptno = dept.dept_no and

emp_no = &emp_no.

Emp_dept<--employee e.deptno=d.deptnoDEPT

Result<-IIemp.enam,dname)emp_dept)

The first operation in the joint operation will combine the tuples of the employee and department relations
on the basis of the dept no.to form a relation called emp_dept. Then the PROJECT operation will create a
relation RESULT with the attributes eno. Ename, and dname. To perform join between two relations,
there should be a common field between them.

Theta Join: A join condition is of the form

<Condition>and<condition>and<condition>

Where each condition is of the form Ai 0 Bj (dept.deptno = emp.dept_no). Ai is an attribute of R and Bj is
an attribute of S. Ai and Bj have the same domain (same values) and 0 is one of the comparison operators
(=,<,<=,>,>=,!=).

A join operation with such a general join condition is called a "Theta join".

Equi Join: While joining if the comparison operator is = then it is equijoin.

Eg. Select emp_no.ename.dept.dname from emp.dept.

Where emp.deptno = dept.dept_no.
Natural Join: It is denoted by          symbol. The standard definition of natural join requires that the join
attributes have the same name in both relations. In general, natural join is performed by equating all
attribute pairs that have the same name in the two relations. The general format is:



Here list l specifies list of attributes from R and list2 specifies a list of attributes from S.




Here, the joining is done over the attribute DNumber of Department relation and DNum of Project
relation. In fact, DNum of Project is a foreign key which references DNumber of Department. Generally,
in a natural join, the joining attribute is implicitly considered. Suppose the two relations have no

attribute(s) in common,               is simply the cross product of these two relations. Joining can be done
between any set of attributes and need not be always with respect to the primary key and foreign key
combinations.

The expected size of the join result divided by maximum size i.e.                    leads to a relation called
join selectively.

Outer join:
It returns both matching and non matching rows. It differs from the inner join, in that the rows in one
table having no matching rows in the other table will also appear in the results table, with nulls in the
other attribute position, instead of being ignored as in the case with the inner join. It outputs rows even if
they do not satisfy the join condition; the outer join operator is used with the table having n matching
rows.




In the above example even though there is no matching row with B name, all workers are listed along
with age and skill. If there is no match, simply get an empty skill column. The outer join can be used
when we want to keep all the tuples in R or in S; those in both relations, whether or not they have
matching tuples in the other relation.

Left outer join: It is denoted by          . The left outer join operation keeps every tuple in the first or left

relation R in relation              . If no matching tuple is found in S in the join, result is filled with null
values.
Right outer join: It is denoted by          , and keeps every tuple in the second or right relation S in the
result of R

Full outer join: It is denoted by         and keeps all tuples in both the left and right relations and when no
matching tuples are found, filled with null values as needed.

Division

A division operation (denoted by ) is useful for a special kind of query; occasionally it may be used to
solve certain kind of problems.

Consider the relations P (P) and Q (Q) as shown in the figure. The result of dividing P by Q is the relation
R and it has two tuples. For each tuple in R, its product with the tuples of Q must be in P. In our example
(a1, b1) must both be tuples in P: the same is true for (a5, b1) and (a5, b2)

Examples of the division operations R = P + Q:




For e.g.: To retrieve the names of employees who work on all the projects that 'John Smith' works on.

1. Retrieve the list of project numbers that John Smith works on the intermediate relation SMITH_PNOS:




2. create a relation that includes a tuple < PNO,ESSN> whenever the employee whose social security
number is ESSN works on the project whose number is PNO in the intermediate relation SSN_PNOS.

SSN_PNOS < ESSN.PNO(WORKS_ON)

3. Apply the DIVISION operation to the two relations which gives the desired employees social security
numbers.
TABLES




Notice here that 123,453 appear in SSN_PNOS in combination with all two tuples in SMITH_PNOS; that
is why they appear in the resulting relation SSNS.

Q 4. Discuss Multi Table Queries?
Multi Table Queries

So far the queries that we have discussed were containing only one table in the clause. There are many
occasions in the database applications where we need to retrieve data from more than one table. This
section addresses these kinds of queries.

SIMPLE EQUI-JOINS:

When two tables are joined together we must follow these guidelines:

Table names in the FROM clause are separated by commas.

Use appropriate joining condition. This means that the foreign key of table 1 will be made equal to the
primary key of table 2. This column acts as the joining attribute. For example, dno of employee table and
dno of department will be involved in the joining condition of WHERE clause.

EXAMPLE-1: This example demonstrates the equijoin and the purpose is to display the employee names
and the department names for which they work.

SELECT NAME, DNAME

FROM Employee, Department

WHERE employe.Dno = department.Dno;
OUTPUT:

NAME DNAME

Prasad Accounts

Reena Accounts

Deepak Admin

Venkat Accounts

Pooja Research

EXAMPLE 2:

Let us now try to display only employees working for Accounts department.

SELECT Name, salary, Dname

FROM Employee, department

WHERE (Emplyee.DNO = Department.DNO)

AND (Dname = 'Accounts');

OUT PUT:

NAME SALARY DNAME

Prasad 32000 Accounts

Reena 8000 Accounts

Venkat 30000 Accounts

SELF JOIN and TABLE ALIASES:

The self-join is one where you involve the same table in the join. This is illustrated in the following
example. This technique is used fully to solve many queries.

To find the employee who earns more than venkat

SELECT e1.name, e1.salary

FROM Employee e1, Employee e2
WHERE (e1.salary > e2.salary) AND (e2.name = 'venkat')

OUT PUT:

NAME SALARY

Prasad 32000

OUTER JOINS:

Outer joins are used to display rows that do not meet the join condition. For left outer join use a plus sign
(+) to left condition and for right outer join use the plus sign to the right condition. The syntax for left and
right outer joins is given below:

Left outer join

SELECT table1.col, table2.col

FROM table1 t1, table2 t2

WHERE t1.col (+) = t2.col;

Notice that the plus sign cannot be placed on both sides of the condition.

EXAMPLE 1: This example demonstrates the right outer join by retaining the right side table
(department) tuples and giving null values for the tuples that do not match the left side table (employee).

SELECT Name, Dname

FROM Employee E, Department D

WHERE E.Name(+) =D.Dname;

OUTPUT::

NAME DNAME

Accounts

Admin

EXAMPLE 2: This is same as ex.1, but the only difference is that it is a left outer join. So all the left
table (employee) rows are kept, and if no match occurs with the right side table (department) a null is
shown.
SELECT Name, Dnaem

FROM Employee E, Department D

WHERE E.Name = D.Dname(+);

OUT PUT:

NAME DNAME

Deepak

Venkat

Pooja

Prasad

Reena

Q 5. Discuss Transaction Processing Concept? 10.2 Describe properties of Transactions?
Transaction management is the ability of a database management system to manage the various
transactions that occur within the system. Transaction is a set of program statements or collections of
operations that form a single logical unit of work. A database management system should ensure that the
transactions are executed properly, either the entire transaction should execute or none of the operations
should have been executed. This is also called atomic cooperation. The DBMS should execute this task or
transaction in total to avoid inconsistency.

Transaction Processing Concepts

Definition: A transaction is an atomic unit comprised of one or more SQL statements. A transaction
begins with the first executable statement and ends when it is committed or rolled back.

Single User V/S Multi User systems: A DBMS is used if at most one user at a time can use the system.
It is multi-user if many users can use the system and have access to the DB concurrently. For e.g.: An air
line reservation system is used by 100's of travel agency and clerks concurrently.

Multiple users can access databases and use computer systems simultaneously. Because of the concept of
multiprogramming, this system executes some commands from one process than suspend that process,
and executes some command from the next process. Therefore it is inter leaved.
In a single user system one can execute at most one process at a time.


Interleaved concurrency of operators A and B




operators A and B




Figure 10.1: Interleaved concurrency versus parallel execution

The Read and Write operations and DBMS Buffers:

A transaction is a logical unit of database processing that includes one or more database access operations
(insertion, delete etc). Only retrieving of data is called read only transaction.

The basic database access operations are

1) Read-item         It reads a database item named 'x' into a program variable.

2) Write-item         writes the value of the program variable x into the database.




Read-item (x) includes the following steps:

1. Find the address of the disk block that contains item 'x'.

2. Copy that disk block into a bugger in main memory.
3. Copy item x from the buffer to the program variable x.

Executing the write-item (x) includes the following steps.

1. Find the address of the disk block that contains item (x).

2. Copy that disk block into a buffer in main memory.

3. Copy item x from the program variable into its current location in the buffer

4. Store the updated block from the buffer back to disk.

a. b.

T1 T2

Read_item (X) Read_item(X);

X=X-N' X:=X+M

Write_item(X); Write_item(X)

Read_item(Y)

Y=Y+N;

Write_item(Y)

Concurrent control: The data in the database must perform their transactions concurrently without
violation the ACID (Atomicity, Consistency, Integrity and Durability) properties of a database. It takes
place during the progression of an activity. It involves the regulation of ongoing activities that are part of
transformation process to ensure that they conform to organizational standards. Concurrency control
solves the major issues involved with allowing multiple people simultaneous access to shared entities, and
their object representations...

Why concurrency control is needed: In a multiuser database, transactions submitted by the various
users may execute concurrently and may update the same data. Concurrently executing transactions must
be guaranteed to produce the same effect as serial execution of transactions [one by one]. Several
problems can occur when concurrent transactions execute in an uncontrolled manner, therefore the
primary concern of a multiuser database includes how to control data concurrency and consistency.
Data concurrency: Access to data concurrently (simultaneously) used by many users must be co-
ordinates.

Data consistency: A user always sees a consistent (accurate) view of all data committed by other
transactions as of that time and all changes made by the user up to that time. Several problems can occur
when concurrent transactions execute in an uncontrolled manner.

For e.g.: Airline reservation database in which a record is stored for each flight. Each record includes the
number of reserved seats on that flight. Fig..a shows a Transaction "T1" that transfers N reservations from
one flight, whose number of reserved seats is 'x', to another flight whose number of reserved seats is 'y'.
Fig.b shows a transaction T2 that reserves m seats on the first flight. We now discuss the types of
problems we may encounter when these two transactions run concurrently.

1. The lost update problem: Suppose transactions T1 and T2 are submitted at the same time, when these
two transactions are executed concurrently as shown in fig. a, then the final value of x is incorrect.
Because T2 reads the value of x before T1 changes it in the database, and hence the updated value
resulting from T1 is lost. For e.g.: x=80 at the start (80 reservation at the beginning), n=5 (T1 transfers 5
seat reservation from the flight x to y), and m=4 (T2 reserves 4 seats on x), the final result should be x=79
but due to interleaving of operations x=84, because updating T1 that removed the 5 seats from x was lost.




2. Dirty read problem: This problem occurs when one transaction updates a database item and then the
transaction fails for some reason. The updated item is accessed by another transaction before it is changed
back to its original value.

For e.g.: T1 updates item x and then fails before completion, so the system must change x back to original
value. Before it can do so, however, transaction T2 reads the temporary value of x, which will not be
recorded permanently in the database, because of the failure of T1. The value of item x that is read by T2
is called Dirty Data, because it has been created by a transaction that has not been completed and
committed yet. Hence this problem is also known as the temporary update problem.




3. Incorrect Summary Problem: If one transaction is calculating an aggregate summary function on a
number of records, while other transactions are updating some of these records, the aggregate function
may calculate some values before they are updated and others after they are updated.

For ex: Transaction T3 is calculating the total no. of reservations on all the flights, meanwhile transaction
T1 is executing. The T3 reads the values of x after n seats have been subtracted from it, but reads the
value of y before those n seats have been added to it.




Why is recovery needed?

A major responsibility of the data base administrator is to prepare for the possibility of hardware,
software, network and system failure. It is usually desirable to recover the databases and return to normal
operation as quickly as possible. Recovery should proceed in such a manner to protect the database and
users from unnecessary problems.
Whenever a transaction is submitted to a DBMS for execution, the system is responsible for making
sure that either.

1. All the operations in the transactions are completed successfully and their effects are recorded
permanently in the DB or

2. The transaction has no effect on the DB; this may happen if a transaction fails after executing some of
it's operations, but before executing all of them.

Types of failures:

1. A computer failure (System Crash):

Hardware, software, network error occurs in the computer system during transaction

2. Transaction or system error:

Some operation in the transaction may cause it to fail, such as integer overflow or division by 'Zero' etc.

3. Local errors or exception conditions detected by the transaction:

During transaction execution, certain conditions may occur that perform cancellation of the transaction.
For ex. Data for the transaction my not be found.

4. Concurrency control enforcement:

The concurrency control method may decide to abort the transactions, to be restarted later, because
several transactions are in a state of deadlock.

5. Disk failure:

Some disk blocks may lose their data because of read or write malfunctions

6. Physical problems and catastrophes:

This refers to a list of problems that includes power or air conditioning failure, fire, theft, overwriting
disks etc.

Transaction states and additional operations: A transaction is an atomic unit of work that is entirely
completed or not done at all. For recovery purpose the system needs to keep track of when the transaction
starts, terminates, commits or aborts. Hence the recovery manager keeps track of the following
operations.
1. Begin transaction: This marks the beginning of transaction execution,

2. Read/Write: These specify read/write operation execution.

3. End transaction: This specifies that the read and write transaction operations have ended, and marks
the end of the transaction execution. At this point it maybe necessary to check whether the changes can be
permanently applied to the DB or aborted.

4. Commit transaction: This signals a successful end of the transaction, so that any changes executed by
the transaction can be committed to the DB.

5. Roll Back: This signals that the transactions has ended unsuccessfully, so that any changes that the
transaction may have applied to the database must be undone.




Fig. 10.2: State transition diagram illustrating the states for transaction execution

Figure 10.2 shows a state transition diagram that describes how a transaction moves through its execution
states. A transaction goes into an active state immediately after it starts execution, where it can issue Read
and Write operations. When the transaction ends, it moves to the partially committed state. At this point
some recovery protocols need to ensure that there is no system failure. Once this check is successful, the
transaction is said to have reached its commit point and enters the committed state.

However, a transaction can go to the failed state if one of the checks fails or if the transaction is aborted
during its active state. The transaction may then have to be rolled back to undo the effect of its Write
operations on the database. The terminated state corresponds to the transaction leaving the system or end
of the transaction.

Desirable Properties of Transactions
To ensure data integrity, the database management system should maintain the following transaction
properties. These are often called the ACID properties.

1. Atomicity: A transaction is an atomic unit of processing. It is either performed in its entirety
(completely) or not performed at all.

2. Consistency: The basic idea behind ensuring atomicity is as follows. The database system keeps back
of the old values of any data on which a transaction performs a write, and if the transaction does not
complete its execution, the old values are restored to make it appear as though the transaction was never
executed.

For Ex: Let Ti be a transaction that transfers 850 from account A to account B. This transaction can be
defined as

Ti ; read(A)

A :=A-50;

Writ (A);

Read(B);

B:=B+50;

Write (B).

Suppose that before execution of transactions Ti the values of accounts A and B are Rs.1000 and Rs.2000
respectively. Now suppose that, during the execution of transaction Ti, a failure has occurred after
write(A) operation, that prevents Ti from completing its execution successfully. But before the write of B
operation was executed values of A and B in database are Rs.950 and`Rs.2000. We have lost Rs.50 which
is executed in a sequential fashion.

3. Durability: Once a transaction changes the database and the changes are committed, these changes
must never be lost because of subsequent failures. The users need not worry about the incomplete
transactions. Partially executed transactions can be rolled back to the original state, ensuring durability is
the responsibility of the recovery management component of the DBMS.

Q 6. Describe the advantage of Distributed database? What is Client/server Model? Discuss briefly the
security and Internet violation?
In a centralized database system, all system components such as data, DBMS software, storage devices
reside at a single computer or site, where as in distributed database system data is spread over one or more
computer connected by a network.

Distributed database is thus a set of databases stored on multiple computers but it appears to a user as a
single database. The data on several computers can be simultaneously accessed and modified (data from
local and remote databases) using a network. Each database server in the DDB is controlled by its local
DBMS, and each cooperates to maintain the consistency of the global database.

As a general goal, distributed computing systems divide a big, unmanageable problem into smaller pieces
and solve it efficiently in a coordinated manner.

Advantages of Distributed Databases

1. Increased reliability and availability: Reliability is broadly defined as the probability that a system is
running at a certain time point, whereas reliability is defined as the system that is continuously available
during a time interval. When the data and DBMS software are distributed over several sites, one site may
fail while other sites continue to operate. Only the data and software that exist at the failed site cannot be
accessed. In a centralized system, failure at a single site makes the whole system unavailable to all users.

2. Improved performance: Large database is divided into smaller databases by keeping the necessary
data where it is needed most. Data localization reduces the contention for CPU and I/O services, and
simultaneously reduces access delays involved in wide area network. When a large database is distributed
over multiple sites, smaller databases exist at each site. As a result, local queries and transactions
accessing data at a single site have better performance because of the smaller local databases. To improve
parallel query processing a single large transaction is divided into a number of smaller transactions and
executes multiple transactions at different sites.

3. Data sharing: Data can be accessed by users at other remote sites through the distributed database
management system (DDBMS) Software.




Client-Server Model

The Client-Server model is basic to distributed systems; it allows clients to make requests that are routed
to the appropriate server in the form of transactions. The client-server model consists of three parts.
1. Client The client is the machine (workstation or pc) running the front and applications. It interacts with
a user through the keyboard, display and mouse. The client has no direct data access responsibilities. The
client machine provides front-end application software for accessing the data on the server. The clients
initiates transactions, the server processes the transactions.

Interaction between client and server might be processed as follows during processing of an SQL
query.

1. The client passes a user query and decomposes it into a number of independent site queries. Each site
query is sent to the appropriate server site.

2. Each server processes the local query and sends the resulting relation to the client site.

3. The client site combines the results of the queries to produce the result of the originally submitted
query.

So the server is called database processor or back end machine, where as the client is called application
processor or front end machine.

Another function controlled by the client is that of ensuring consistency of replicated copies of a data item
by using distributed concurrency control techniques. The client must also ensure the atomicity of global
transactions by performing global recovery when certain sites fail. It provides distribution transparency,
which is the client hides the details of data distribution from the user.

1. Server The server is the machine that runs the DMS software. It is referred to as back end. The server
processes SQL and other query statements received from client applications. It can have large disk
capacity and fast processors.

2. Network The network enables remote data access through client server and server-to-server
communication.

Each computer in a network is a node, acts as a client, a server, or both, depending on the situation.

Advantages:

Client applications are not dependent on physical location of the data. If the data is moved or distributed
to other database servers, the application continues to function with little or no modification.
It provides multi-tasking and shared memory facilities; as a result they can deliver the highest possible
degree of concurrency and data integrity.

In networked environment, shared data is stored on the servers, rather than on all computers in the system.
This makes it easier and more efficient to manage concurrent access. Inexpensive, low-end client work
stations can access the remote data of the server effectively.

Security and Integrity Violations

Misuse of database can be categorized as being either intentional or accidental.

Accidental loss of data consistency:

1. System crashes during transaction processing

2. Due to multi-users accessing the database.

3. Distribution of data over several computers.

Intentional loss of data may be due to reading, writing or destruction of data by unauthorized users.

Database security usually protects data by several techniques.

Certain portion [selected columns] of a database is available only to those persons who are authorized to
access it. This ensures that the confidentiality of data is maintained.

For e.g.: In large organizations, where different users may use the same database, sensitive information
such as employees salaries should be kept confidential from most of the other users.

To protect database we must take security measures at several levels. Network security is also important
as database security.

Security within the operating system is implemented by providing a password for the user accounts. It
Protects data in primary memory by avoiding direct access to the data.

								
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