Database Normalization is the process of efficiently organizing data in a database. There are two goals of the normalization process:

Transcription

1 NORMAL FORMS INTRODUCTION Normal Forms can be simply defined as database normalization rules/conditions. It is a condition of using keys and functional dependencies (FDs) of a relation to certify whether a relation schema is in a particular normal form. Database Normalization is the process of efficiently organizing data in a database. There are two goals of the normalization process: i. Eliminating redundant data (for example, storing the same data in more than one table), and, ii. Ensuring data dependencies make sense (only storing related data in a table). Normalization rule is divided into the following normal forms:- 1. First Normal Form (1NF), and 2. Second Normal Form (2NF) 3. Third Normal Form (3NF) 4. Boyce Codd Normal Form (BCNF) Normal forms are simply the steps taken to normalize a database: DEFINITION OF SOME TERMS 1. FD (Functional Dependence): This is a constraint (limit/restrictions)) that describes the relationship between attribute in a reaction. In otherwords, FD is a relationship that exists when one atribute uniquely determines another attribute e.g. An FD X Y says that if two turples agree on the values in attribute X, they must also agree on the values in attribute Y. 2. Attributes: This means the field or column of a table 3. Turples: A turple is one record or row of a table 4. Relation: This refers to a table of database 5. Unformalized Form Database (UNF): This is a database that has not gone through the process of normalization. 6. Keys: A key is an attribute or set of attribute that has not gone through the process of normalization.

2 First Normal Form (1NF):- a table is said to be in 1NF if there are no repeating attributes (fields/columns) in it. To achieve 1NF from UNF table:- (1) Every repeating fields must be separated into a new table along with the key from UNF (2) Primary Key from the new table could be composite. Second Normal Form (2NF):-A table is said to be in 2NF if both the following conditions hold: (a) Table is in 1NF (b) Contains only field/columns that are functionally dependent on the primary key. Table 1.1 Emp_Id Emp_name Emp_address Emp_dept 101 John Lagos Dept John Lagos Dept James Abuja Dept Cane Jos Dept Cane Jos Dept 004 Table 1 Employee s Table Emp_Id Emp_name Emp_address Emp_mobile 101 Kingsley Ibadan John Ibadan Deborah Ile-Ife Lester Osogbo RELATIONAL MODEL Relational Model of belongs to the database model type.it is the most popular form of database where different tables are linked together by the means of keys. It has in-built functions that help to create, modify, manipulate and query the database. Representation of data in relational model of database There are three key terms used in relational model.they include; RELATIONS,ATTRIBUTES and DOMAINS

3 A RELATION: A relation refers to a table of rows and column. A relation is the way of representing the relational model.it comprises of two aspects; Relation Schema and Relation Instance 1. The relation schema specifies the relation s name, the name of each attributes (field or column), the domain of each field Example of Relation Schema is shown in the student s information below Students (Sid: String, Name: String, Login: String, Age: Integer, Gpa: real) 2. Relation Instance: This is a set of turples (records or rows), in which each turple has the same number of fields as the relation schema Field names TUPLES (RECORDS OR ROWS) Sid Name Login Age Gpa Aci501 James eng.ng Aci502 Dave music.ng Aci503 Smith cs.ng Aci504 Smith math.ng Aci507 Gladys math.ng Aci506 John cs.ng The number of fields in a relation is called the Degree or the Arity of a relation. The number of turples is called Cardinality of a relation. ATTRIBUTE: An attribute is a named column of a relation DOMAIN: This is a set of value the attribute are allowed to take or accommodate. CREATING AND MODIFYING RELATION (using SQL) SQL is a DBMS used for creating and manipulating relations. DDL is a subset of SQL that supports the creation, deletion and modification of relations. Some Statement/Commands in SQL 1. Create Table Statement: This is used to create a new relation.the format is create table Students (sid char (20),name char (30),login char (20),age Int,gpa Real ) 2. Insert Statement: This is used to insert turple into the table,e.g to insert a single turple into the students table, we have; Insert Into students (sid,name,login,age,gpa) Values (Aci503, Smith, smith@cs.ng,17,3.2)

4 3. Delete Command :Used to delete a turple from the relation e.g. to delete any tuple with the name smith, we use Delete From students S Where S. Name = Smith 4. Update Command: This is used to modify values in an existing row. If we want to increment the gpa of the student with Sid Aci502, we have; Update Set S.gpa=S.gpa+1 Where S.sid=Aci502 QUERYING RELATIONAL MODEL DATABASE Querying is the act of questioning the database for some information based on a given criterial. For instance we may want to know from our relational database how many of the students in a class are female; the result will be represented in another relation. Select command is used to query a relational database, the format is Select* Primary Key: This is a column/field/attribute and it can also be more than one in a table that uniquely identifies the rows/turples in that table. Foreign Key: This is the field of a table which refers to the primary key in other tables. Foreign keys are used to provide the link (relationship) between the tables. The foreign key (Doctor Id in the patient table) can then be used to match to the primary key (Doctor Id in the doctor table) and share the correct data. Candidate Key: This is a field that meets all the requirement of a primary key i.e. has the potential to be used as a primary key. Composite Key: When more than one primary key are needed to uniquely identify an entity in a relation, the combination of these keys is used and is known as the composite key.

5 PARALLEL AND DISTRIBUTED DATABASE A distributed database is a database in which storage devices are not all attached to a common processing unit such as the CPU and which is controlled by a distributed (together sometimes called a distributed database system). It may be stored in multiple computers, located in the same physical location; or may be dispersed over a network of interconnected computers. Unlike parallel systems, in which the processors are tightly coupled and constitute a single database system, a distributed database system consists of loosely coupled sites that share no physical components. System administrators can distribute collections of data (e.g. in a database) across multiple physical locations. A distributed database can reside on network servers on the Internet, on corporate intranets or extranets, or on other company networks. Because they store data across multiple computers, distributed databases can improve performance at end-user worksites by allowing transactions to be processed on many machines, instead of being limited to one. Two processes ensure that the distributed databases remain up-to-date and current: replication and duplication. 1. Replication involves using specialized software that looks for changes in the distributive database. Once the changes have been identified, the replication process makes all the databases look the same. 2. Duplication, on the other hand, has less complexity. It basically identifies one database as a master and then duplicates that database. The duplication process is normally done at a set time after hours. This is to ensure that each distributed location has the same data Both replication and duplication can keep the data current in all distributive locations. A distributed database is a database in which portions of the database are stored on multiple computers within a network. Users have access to the portion of the database at their location so that they can access the data relevant to their tasks without interfering with the work of others. Distributed computing comes from the business world where you have distributed systems such as airline reservation systems, where many people access and modify the same data at the same time. In distributed data bases Data is stored in multiple places (each is running a DBMS) Examples of distributed databases 1. Bank with many branches 2. Chain of retail stores with many locations 3. Library with many branches 4. Telecommunication companies like MTN,GLO etc

6 A Parallel database is a database that can do multiple tasks in parallel allowing the database to make use of multiple CPU cores and multiple disks that are standard for modern database servers. Parallel computing means that different activities happen at the same time Data is located in one place (one server). Motherboard that has more than one CPU slots is recommended for parallel database. It's not common and mainly for professional uses Server or workstation motherboard that support multiple CPUs are shown below. Differences between parallel and distributed databases s/n Parallel Distributed 1 Machines are physically close to each other, e.g. same server room Machines are far from each other, e.g., in different continent 2 3 Machines are connected with dedicated high-speed LANs and switches. Make use of multiple CPU Are connected using public-purpose network, e.g., Internet Data is distributed across multiple hosts.

7 Advantages of Parallel Databases 1. High Performance 2. Increased Availability Disadvantages of Parallel Databases 1. It is expensive to set up 2. Managing parallel databases simultaneously is difficult Advantages of Distributed Databases 1. Reliabity 2. It is easy to expand 3. Protection of valuable data 4. Modularity 5. Improved performance 6. Continuous operation, even if some nodes go offline Disadvantages of Distributed Databases 1. Complexity 2. Difficult to maintain integrity 3. Security 4. Extra labour cost Storing data in distributed database (DDBS) Data storage in distributed database involved 2 concepts 1. Fragmentation: This consists of breaking a relation into smaller relation and fragments and storing the fragments in different location. There are two types of fragmentation; they are horizontal fragmentation and vertical fragmentation. In horizontal fragmentation, each fragment consists of a subset of rows of the original relation In vertical fragmentation, each fragment consists of a subset of columns of the original relation 2. Replication: Replication involves using specialized software that looks for changes in the distributive database. Once the changes have been identified, the replication process makes all the databases look the same.