Purpose of Database Systems



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Database systems arose in response to early methods of computerized management
of commercial data. As an example of such methods, typical of the 1960s,
consider part of a university organization that, among other data, keeps information
about all instructors, students, departments, and course offerings. One
way to keep the information on a computer is to store it in operating system
files. To allow users to manipulate the information, the system has a number of
application programs that manipulate the files, including programs to:

1. Add new students, instructors, and courses

2. Register students for courses and generate class rosters

3. Assign grades to students, compute grade point averages (GPA), and generate
    transcripts

System programmers wrote these application programs to meet the needs of the
university.
New application programs are added to the system as the need arises. For
example, suppose that a university decides to create a new major (say, computer
science).As a result, the university creates a newdepartment and creates new permanent
files (or adds information to existing files) to record information about all
the instructors in the department, students in that major, course offerings, degree
requirements, etc. The university may have to write new application programs
to deal with rules specific to the new major. New application programs may also
have to be written to handle new rules in the university. Thus, as time goes by,
the system acquires more files and more application programs.
This typical file-processing system is supported by a conventional operating
system. The system stores permanent records in various files, and it needs
different application programs to extract records from, and add records to, the appropriate
files. Before database management systems (DBMSs) were introduced,
organizations usually stored information in such systems.
Keeping organizational information in a file-processing system has a number
of major disadvantages:


• Data redundancy and inconsistency: Since different programmers create
the files and application programs over a long period, the various files are
likely to have different structures and the programs may bewritten in several
programming languages. Moreover, the same information may be duplicated
in several places (files). For example, if a student has a double major (say,
music and mathematics) the address and telephone number of that student
may appear in a file that consists of student records of students in the Music
department and in a file that consists of student records of students in the
Mathematics department. This redundancy leads to higher storage and access
cost. In addition, it may lead to data inconsistency; that is, the various copies
of the same datamayno longer agree. For example, a changed student address
may be reflected in the Music department records but not elsewhere in the
system.


• Difficulty in accessing data: Suppose that one of the university clerks needs
to find out the names of all students who live within a particular postal-code
area. The clerk asks the data-processing department to generate such a list.
Because the designers of the original system did not anticipate this request,
there is no application program on hand to meet it. There is, however, an
application program to generate the list of all students. The university clerk
has now two choices: either obtain the list of all students and extract the
needed information manually or ask a programmer to write the necessary
application program. Both alternatives are obviously unsatisfactory. Suppose
that such a program is written, and that, several days later, the same clerk
needs to trim that list to include only those students who have taken at least
60 credit hours. As expected, a program to generate such a list does not
exist. Again, the clerk has the preceding two options, neither of which is
satisfactory.
The point here is that conventional file-processing environments do not
allow needed data to be retrieved in a convenient and efficientmanner. More
responsive data-retrieval systems are required for general use.


• Data isolation: Because data are scattered in various files, and files may
be in different formats, writing new application programs to retrieve the
appropriate data is difficult.


• Integrity problems: The data values stored in the database must satisfy certain
types of consistency constraints. Suppose the university maintains an
account for each department, and records the balance amount in each account.
Suppose also that the university requires that the account balance of a
department may never fall below zero. Developers enforce these constraints
in the system by adding appropriate code in the various application programs.
However, when new constraints are added, it is difficult to change
the programs to enforce them. The problem is compoundedwhen constraints
involve several data items from different files.


• Atomicity problems: A computer system, like any other device, is subject
to failure. In many applications, it is crucial that, if a failure occurs, the data
be restored to the consistent state that existed prior to the failure. Consider
a program to transfer $500 from the account balance of department A to
the account balance of department B. If a system failure occurs during the
execution of the program, it is possible that the $500 was removed from the
balance of department A butwas not credited to the balance of department B,
resulting in an inconsistent database state. Clearly, it is essential to database
consistency that either both the credit and debit occur, or that neither occur.
That is, the funds transfer must be atomic—it must happen in its entirety or
not at all. It is difficult to ensure atomicity in a conventional file-processing
system.

These Topics Are Also In Your Syllabus Purpose of Database Systems
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3 Discretionary Access Control Based on Granting and Revoking Privileges link
4 Introduction to Database Security Issues link
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• Concurrent-access anomalies: For the sake of overall performance of the system
and faster response, many systems allow multiple users to update the
data simultaneously. Indeed, today, the largest Internet retailers may have
millions of accesses per day to their data by shoppers. In such an environment,
interaction of concurrent updates is possible and may result in inconsistent
data. Consider department A, with an account balance of $10,000. If
two department clerks debit the account balance (by say $500 and $100, respectively)
of department A at almost exactly the same time, the result of the
concurrent executions may leave the budget in an incorrect (or inconsistent)
state. Suppose that the programs executing on behalf of each withdrawal read
the old balance, reduce that value by the amount beingwithdrawn, and write
the result back. If the two programs run concurrently, they may both read the
value $10,000, and write back $9500 and $9900, respectively. Depending on
which one writes the value last, the account balance of department A may
contain either $9500 or $9900, rather than the correct value of $9400. To guard
against this possibility, the system must maintain some form of supervision.
But supervision is difficult to provide because data may be accessed by many
different application programs that have not been coordinated previously.
As another example, suppose a registration program maintains a count of
students registered for a course, in order to enforce limits on the number of
students registered.When a student registers, the program reads the current
count for the courses, verifies that the count is not already at the limit, adds
one to the count, and stores the count back in the database. Suppose two
students register concurrently, with the count at (say) 39. The two program
executions may both read the value 39, and both would then write back 40,
leading to an incorrect increase of only 1, even though two students successfully
registered for the course and the count should be 41. Furthermore,
suppose the course registration limit was 40; in the above case both students
would be able to register, leading to a violation of the limit of 40 students.


• Security problems: Not every user of the database system should be able
to access all the data. For example, in a university, payroll personnel need
to see only that part of the database that has financial information. They do
not need access to information about academic records. But, since application
programs are added to the file-processing system in an ad hoc manner,
enforcing such security constraints is difficult.


These difficulties, among others, prompted the development of database systems.
In what follows, we shall see the concepts and algorithms that enable
database systems to solve the problems with file-processing systems. In most of
this book, we use a university organization as a running example of a typical
data-processing application.


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