Practical Database Programming With Java

6 Chapter 1 Introduction

INSTRUCTOR AND CUSTOMER SUPPORT

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Instructor materials are available upon request from the book’s listing on www.wiley.com

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Figure 1.2. Book related materials on the Web sites.

Homework Solutions 7

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10Chapter 2 Introduction to Databases

•What are databases and database programs?

•File processing system

•Integrated databases

•Various approaches to developing a database

•Relational data model and entity-relationship model (ER)

•Identifying keys

•Primary keys, foreign keys and referential integrity

•Defining relationships

•Normalizing the data

•Implementing the relational database

•Create a Microsoft Access sample database

•Create a Microsoft SQL Server 2008 sample database

•Create an Oracle sample database

2.1 WHAT ARE DATABASES AND DATABASE PROGRAMS?

A modern-day database is a structured collection of data stored in a computer. The term structured implies that each record in the database is stored in a certain format. For example, all entries in a phone book are arranged in a similar fashion. Each entry contains a name, an address, and a telephone number of a subscriber. This information can be queried and manipulated by database programs. The data retrieved in answer to queries become information that can be used to make decisions. The databases may consist of a single table or related multiple tables. The computer programs used to create, manage, and query databases are known as database management systems (DBMS). Just like the databases, the DBMS vary in complexity. Depending on the need of a user, one can use either a simple application or a robust program. Some examples of these programs were given earlier.

2.1.1 File Processing System

The file processing system is a precursor of the integrated database approach. The records for a particular application are stored in a file. An application program is needed to retrieve or manipulate data in this file. Thus, various departments in an organization will have their own file processing systems with their individual programs to store and retrieve data. The data in various files may be duplicated and not available to other applications. This causes redundancy and may lead to inconsistency, meaning that various files that supposedly contain the same information may actually contain different data values.Thus, duplication of data creates problems with data integrity. Moreover, it is difficult to provide access to multiple users with the file processing systems without granting them access to the respective application programs, which manipulate the data in those files.

The file processing system may be advantageous under certain circumstances. For example, if data is static and a simple application will solve the problem, a more expensive DBMS is not needed. For example, in a small business environment, you want to keep

2.1 What Are Databases and Database Programs? 11

track of the inventory of the office equipment purchased only once or twice a year. The data can be kept in an Excel spreadsheet and manipulated with ease from time to time. This avoids the need to purchase an expensive database program and hiring a knowledgeable database administrator. Before the DBMS became popular, the data was kept in files, and application programs were developed to delete, insert, or modify records in the files. Since specific application programs were developed for specific data, these programs lasted for months or years before modifications were necessitated by business needs.

2.1.2 Integrated Databases

A better alternative to a file processing system is an integrated database approach. In this environment, all data belonging to an organization is stored in a single database. The database is not a mere collection of files; there is a relation between the files. Integration implies a logical relationship, usually provided through a common column in the tables. The relationships are also stored within the database. A set of sophisticated programs known as DBMS is used to store, access and manipulate the data in the database. Details of data storage and maintenance are hidden from the user. The user interacts with the database through the DBMS. A user may interact either directly with the DBMS or via a program written in a programming language, such as C++, Java, or Visual Basic. Only the DBMS can access the database. Large organizations employ Database Administrators (DBAs) to design and maintain large databases.

There are many advantages to using an integrated database approach over that of a file processing approach:

1.Data Sharing: The data in the database is available to a large numbers of users who can access the data simultaneously and create reports and manipulate the data given proper authorization and rights.

2.Minimizing Data Redundancy: Since all the related data exists in a single database, there is a minimal need of data duplication. The duplication is needed to maintain relationship between various data items.

3.Data Consistency and Data Integrity: Reducing data redundancy will lead to data consistency. Since data is stored in a single database, enforcing data integrity becomes much easier. Further more, the inherent functions of the DBMS can be used to enforce the integrity with minimum programming.

4.Enforcing Standards: DBAs are charged with enforcing standards in an organization. DBA takes into account the needs of various departments and balances it against the overall need of the organization. DBA defines various rules, such as documentation standards, naming conventions, update and recovery procedures, and so on. It is relatively easy to enforce these rules in a Database System, since it is a single set of programs that is always interacting with the data files.

5.Improving Security: Security is achieved through various means, such as controlling access to the database through passwords, providing various levels of authorizations, data encryption, providing access to restricted views of the database, and so on.

6.Data Independence: Providing data independence is a major objective for any database system. Data independence implies that even if the physical structure of a database changes, the applications are allowed to access the database as before the changes were implemented.

12 Chapter 2 Introduction to Databases

In other words, the applications are immune to the changes in the physical representation and access techniques.

The downside of using an integrated database approach has mainly to do with exorbitant costs associated with it.The hardware, the software, and maintenance are expensive. Providing security, concurrency, integrity, and recovery may add further to this cost. Furthermore, since DBMS consists of a complex set of programs, trained personnel are needed to maintain it.

2.2 DEVELOP A DATABASE

Database development process may follow a classical Systems Development Life Cycle.

1.Problem Identification: Interview the user, identify user requirements. Perform preliminary analysis of user needs.

2.Project Planning: Identify alternative approaches to solving the problem. Does the project need a database? If so, define the problem. Establish scope of the project.

3.Problem Analysis: Identify specifications for the problem. Confirm the feasibility of the project. Specify detailed requirements.

4.Logical Design: Delineate detailed functional specifications. Determine screen designs, report layout designs, data models, and so on.

5.Physical Design: Develop physical data structures.

6.Implementation: Select DBMS. Convert data to conform to DBMS requirements. Code programs; perform testing.

7.Maintenance: Continue program modification until desired results are achieved.

An alternative approach to developing a database is through a phased process, which will include designing a conceptual model of the system that will imitate the real-world operation. It should be flexible and change when the information in the database changes. Furthermore, it should not be dependent upon the physical implementation. This process follows the following phases:

1.Planning and Analysis: This phase is roughly equivalent to the first three steps mentioned above in the Systems Development Life Cycle. This includes requirement specifications, evaluating alternatives, determining input, output, and reports to be generated.

2.Conceptual Design: Choose a data model and develop a conceptual schema based on the requirement specification that was laid out in the planning and analysis phase. This conceptual design focuses on how the data will be organized without having to worry about the specifics of the tables, keys, and attributes. Identify the entities that will represent tables in the database; identify attributes that will represent fields in a table; and identify each entity attribute relationship. Entity–relationship diagrams provide a good representation of the conceptual design.

3.Logical Design: Conceptual design is transformed into a logical design by creating a roadmap of how the database will look before actually creating the database. Data model is identified; usually it is the relational model. Define the tables (entities) and fields (attributes). Identify primary and foreign key for each table. Define relationships between the tables.

2.3 Sample Database 13

4.Physical Design: Develop physical data structures; specify file organization, and data storage and so on. Take into consideration the availability of various resources, including hardware and software. This phase overlaps with the implementation phase. It involves the programming of the database taking into account the limitations of the DBMS used.

5.Implementation: Choose the DBMS that will fulfill the user needs. Implement the physical design. Perform testing. Modify if necessary or until the database functions satisfactorily.

2.3 SAMPLE DATABASE

We will use CSE_DEPT database to illustrate some essential database concepts. Tables

2.1–2.5 show sample data tables stored in this database.

The data in CSE_DEPT database is stored in five tables—LogIn, Faculty, Course, Student, and StudentCourse. A table consists of row and columns (Fig. 2.1). A row represents a record and the column represents a field. A row is called a tuple and a column is called an attribute. For example, the Student table has seven columns or fields— student_id, name, gpa, major, schoolYear, and email. It has five records or rows.

2.3 Sample Database 15

Table 2.5. StudentCourse table

2.3.1 Relational Data Model

A data model is like a blue print for developing a database. It describes the structure of the database and various data relationships and constraints on the data. This information is used in building tables, keys, and defining relationships. Relational model implies that a user perceives the database as made up of relations, a database jargon for tables. It is imperative that all data elements in the tables are represented correctly. In order to achieve these goals, designers use various tools. The most commonly used tool is entity– relationship model (ER). A well-planned model will give consistent results and will allow changes if needed later on. The following section further elaborates on the ER Model.

16 Chapter 2 Introduction to Databases

Table

Field

Figure 2.1. Records and fields in a table.

2.3.2 Entity–Relationship Model

The ER model was first proposed and developed by Peter Chen in 1976. Since then, Charles Bachman and James Martin have added some refinements; the model was designed to communicate the database design in the form of a conceptual schema. The ER model is based on the perception that the real world is made up of entities, their attributes, and relationships. The ER model is graphically depicted as entity–relationship diagrams (ERD). The ERD are a major modeling tool; they graphically describe the logical structure of the database. ERD can be used with ease to construct the relational tables, and are a good vehicle for communicating the database design to the end user or a developer. The three major components of ERD are entities, relationships, and the attributes.

Entities: An entity is a data object, either real or abstract, about which we want to collect information. For example, we may want to collect information about a person, a place, or a thing. An entity in an ER diagram translates into a table. It should preferably be referred to as an entity set. Some common examples are departments, courses, and students. A single occurrence of an entity is an instance. There are four entities in the CSE_Dept database, LogIn, Faculty, Course, and Student. Each entity is translated into a table with the same name. An instance of the Faculty entity will be Alice Brown and her attributes.

Relationships: A database is made up of related entities.There is a natural association between the entities; it is referred to as relationship. For example,

•Students take courses

•Departments offer certain courses

•Employees are assigned to departments

The number of occurrences of one entity associated with single occurrence of a related entity is referred to as cardinality.

Attributes: Each entity has properties or values called attributes associated with it. The attributes of an entity map into fields in a table. Database processing is one attribute of an entity called Courses. The domain of an attribute is a set of all possible values from which an attribute can derive its value.