Week 9- Normalisation PDF

CITS1402 Relational Database Management Systems Week 9/10—Normalization Dr Mehwish Nasim/ CSSE Sem1/2024 [email protected]...

CITS1402 Relational Database Management Systems Week 9/10—Normalization Dr Mehwish Nasim/ CSSE Sem1/2024 [email protected] This Photo by Unknown Author is licensed under CC BY-SA-NC  Week9\10 Contents Normalization Purpose of Normalization CITS1402 Update Anomalies Functional Dependencies Courtesy: TWL Is there something “wrong” with these tables? Alternate Representation Turn this into database tables Turn this into database tables Which column should be the primary key? Chapter 14 - Objectives The purpose of normalization. How normalization can be used when designing a relational database. The potential problems associated with redundant data in base relations. The concept of functional dependency, which describes the relationship between attributes. The characteristics of functional dependencies used in normalization. Chapter 14 - Objectives How to identify functional dependencies for a given relation. How functional dependencies identify the primary key for a relation. How to undertake the process of normalization. How normalization uses functional dependencies to group attributes into relations that are in a known normal form. Chapter 14 - Objectives 1 2 3 How to identify the most The problems associated How to represent attributes commonly used normal with relations that break the shown on a form as 3NF forms, namely First Normal rules of 1NF, 2NF, or 3NF. relations using Form (1NF), Second Normal normalization. Form (2NF), and Third Normal Form (3NF). 9 Purpose of Normalization Normalization is a technique for producing a set of suitable relations that support the data requirements of an enterprise. ER Modelling is a technique for producing a set of suitable relations that support the data requirements of an enterprise.  Purpose of Normalization Characteristics of a suitable set of relations include: the minimal number of attributes necessary to support the data requirements of the enterprise; attributes with a close logical relationship are found in the same relation; minimal redundancy with each attribute represented only once with the important exception of attributes that form all or part of foreign keys. Purpose of Normalization The benefits of using a database that has a suitable set of relations is that the database will be: easier for the user to access and maintain the data; take up minimal storage space on the computer. How Normalization Supports Database Design Project part 1 Project part 2 What is is this! Validation! Data Redundancy and Update Anomalies Major aim of relational database design is to group attributes into relations to minimize data redundancy. Potential benefits for implemented database include: Updates to the data stored in the database are achieved with a minimal number of operations thus reducing the opportunities for data inconsistencies. Reduction in the file storage space required by the base relations thus minimizing costs. 14 Data Redundancy and Update Anomalies Problems associated with data redundancy are illustrated by comparing the Staff and Branch relations with the StaffBranch relation. Data Redundancy and Update Anomalies Data Redundancy and Update Anomalies StaffBranch relation has redundant data the details of a branch are repeated for every member of staff. The branch information appears only once for each branch in the Branch relation Only the branch number (branchNo) is repeated in the Staff relation, to represent where each member of staff is located. Data Redundancy and Update Anomalies Relations that contain redundant information may potentially suffer from update anomalies. Types of update anomalies include Insertion Deletion Modification Data Redundancy and Update Anomalies Data Redundancy and Update Anomalies Insert new staff member SL52 Taylor Assistant 7000 B003 163 Main St, Swift London Data Redundancy and Update Anomalies Insert new Branch B006 111 Other St, London Primary Key? Null? Data Redundancy and Update Anomalies Delete Staff Member Ann Beech - Okay Mary Howe? – Lose details of B007 Data Redundancy and Update Anomalies Update Branch -> Ensure all details are changed for each row Data Redundancy and Update Anomalies Lossless-join and Dependency Preservation Properties Two important properties of decomposition. Lossless-join property enables us to find any instance of the original relation from corresponding instances in the smaller relations. Dependency preservation property enables us to enforce a constraint on the original relation by enforcing some constraint on each of the smaller relations. The Process of Normalization The Process of Normalization Formal technique for analyzing a relation based on its primary key and the functional dependencies between the attributes of that relation. Often executed as a series of steps. Each step corresponds to a specific normal form, which has known properties. As normalization proceeds, the relations become progressively more restricted (stronger) in format and also less vulnerable to update anomalies. The Process of Normalization UNF ER Modelling should result in a database in 3NF Unnormalized Form (UNF) A table that contains one or more repeating groups. To create an unnormalized table Transform the data from the information source (e.g. form) into table format with columns and rows. Turn this into database tables Unnormalized Form (UNF) First Normal Form (1NF) A relation in which the intersection of each row and column contains one and only one value. only one value Not in First Normal Form (1NF) Multiple values! UNF to 1NF Nominate an attribute or group of Identify the repeating group(s) in the attributes to act as the key for the unnormalized table which repeats for the unnormalized table. key attribute(s). 35 UNF to 1NF Remove the repeating group by Entering appropriate data into the empty columns of rows containing the repeating data (‘flattening’ the table). OR Placing the repeating data along with a copy of the original key attribute(s) into a separate relation. Not in First Normal Form (1NF) Multiple values! UNF to 1NF – Flattening table One value UNF to 1NF – Remove repeating data Maintain link with PK/FK Second (2NF) and Third Normal Form (3NF) 2NF: A relation that is in 1NF and every non-primary- key attribute is fully functionally dependent on the primary key. 3NF: A relation that is in 1NF and 2NF and in which no non-primary-key attribute is transitively dependent on the primary key. Functional Dependencies Functional Dependencies Important concept associated with normalization. Functional dependency describes relationship between attributes. For example, if A and B are attributes of relation R, B is functionally dependent on A (denoted A ® B), if each value of A in R is associated with exactly one value of B in R. An Example Functional Dependency An Example Functional Dependency The determinant position is functionally dependent on staffNo 1:1 relationship 1:* relationship Characteristics of Functional Dependencies About the property of the meaning or semantics of the attributes in a relation. Diagrammatic representation. The determinant of a functional dependency refers to the attribute or group of attributes on the left-hand side of the arrow. Example Functional Dependency that holds for all Time Consider the values shown in staffNo and sName attributes of the Staff relation Based on sample data, the following functional dependencies appear to hold. staffNo → sName sName → staffNo Example Functional Dependency that holds for all Time However, the only functional dependency that remains true for all possible values for the staffNo and sName attributes of the Staff relation is: staffNo → sName Characteristics of Functional Dependencies Characteristics of Functional Dependencies Determinants should have the minimal number of attributes necessary to maintain the functional dependency with the attribute(s) on the right hand- side. This requirement is called: full functional dependency Required for 2NF Violation of this property is called partial dependency Characteristics of Functional Dependencies Full functional dependency indicates that if A and B are attributes of a relation, B is fully functionally dependent on A, if B is functionally dependent on A, but not on any proper subset of A. Example Full Functional Dependency Exists in the Staff relation staffNo, sName → branchNo staffNo → branchNo True - each value of (staffNo, sName) is associated with a single value of branchNo. However, branchNo is also functionally dependent on a subset of (staffNo, sName), namely staffNo. Example above is a partial dependency. Characteristics of Functional Dependencies Main characteristics of functional dependencies used in normalization: There is a one-to-one relationship between the attribute(s) on the left-hand side (determinant) and those on the right-hand side of a functional dependency. Holds for all time. The determinant has the minimal number of attributes necessary to maintain the dependency with the attribute(s) on the right hand-side. Transitive Dependencies Important to recognize a transitive dependency because its existence in a relation can potentially cause update anomalies. Transitive dependency describes a condition where A, B, and C are attributes of a relation such that if A → B and B → C, then C is transitively dependent on A via B (provided that A is not functionally dependent on B or C). Important for 3NF Example Transitive Dependency Consider functional dependencies in the StaffBranch staffNo → sName, position, salary, branchNo, bAddress branchNo → bAddress Transitive dependency bAddress is transitively dependent on staffNo via branchNo. Transitive Dependency Update Anomalies Update Branch Address -> Ensure all details are changed for each row Identifying Functional Dependencies 09 May 2024 Identifying Functional Dependencies Identifying all functional dependencies between a set of attributes is relatively simple if the meaning of each attribute and the relationships between the attributes are well understood. This information should be provided by the enterprise in the form of discussions with users and/or documentation such as the users’ requirements specification. Identifying Functional Dependencies However, if the users are unavailable for consultation and/or the documentation is incomplete then depending on the database application it may be necessary for the database designer to use their common sense and/or experience to provide the missing information. example data Example - Identifying a set of functional dependencies for the StaffBranch relation Examine semantics of attributes in StaffBranch relation. Assume that position held and branch determine a member of staff’s salary. Example - Identifying a set of functional dependencies for the StaffBranch relation With sufficient information available, identify the functional dependencies for the StaffBranch relation as: staffNo → sName, position, salary, branchNo, bAddress branchNo → bAddress bAddress → branchNo branchNo, position → salary bAddress, position → salary Example - Using sample data to identify functional dependencies. Consider the data for attributes denoted A, B, C, D, and E in the Sample relation Important to establish that sample data values shown in relation are representative of all possible values that can be held by attributes A, B, C, D, and E. Assume true despite the relatively small amount of data shown in this relation. Example - Using sample data to identify functional dependencies. Example - Using sample data to identify functional dependencies. Function dependencies between attributes A to E in the Sample relation. A®C (fd1) C®A (fd2) B ®D (fd3) A, B ® E (fd4) Using Functional Dependencies to identify the Primary Key Identifying the Primary Key for a Relation using Functional Dependencies Main purpose of identifying a set of functional dependencies for a relation is to specify the set of integrity constraints that must hold on a relation. An important integrity constraint to consider first is the identification of candidate keys, one of which is selected to be the primary key for the relation. StaffBranch Relation Example - Identifying a set of functional dependencies for the StaffBranch relation With sufficient information available, identify the functional dependencies for the StaffBranch relation as: staffNo → sName, position, salary, branchNo, bAddress branchNo → bAddress bAddress → branchNo branchNo, position → salary bAddress, position → salary Example - Identify Primary Key for StaffBranch Relation StaffBranch relation has five functional dependencies The determinants are… staffNo → sName, position, salary, branchNo, bAddress branchNo → bAddress bAddress → branchNo branchNo, position → salary bAddress, position → salary Example - Identify Primary Key for StaffBranch Relation StaffBranch relation has five functional dependencies The determinants are staffNo → sName, position, salary, branchNo, bAddress branchNo → bAddress bAddress → branchNo branchNo, position → salary bAddress, position → salary Example - Identifying Primary Key for StaffBranch Relation Identify the attribute (or group of attributes) that uniquely identifies each tuple in this relation. candidate key(s) All attributes that are not part of a candidate key should be functionally dependent on the key. The only candidate key and therefore primary key for StaffBranch relation, is staffNo, All other attributes of the relation are functionally dependent on staffNo. Example - Using sample data to identify functional dependencies. Example - Identifying Primary Key for Sample Relation Sample relation has four functional dependencies The determinants in the Sample relation are A®C (fd1) C®A (fd2) B ®D (fd3) A, B ® E (fd4) The only determinant that functionally determines all the other attributes of the relation is (A, B). (A, B) is identified as the primary key for this relation. Using Functional Dependencies to Normalise Relations UNF to 1NF Remove the repeating group by Entering appropriate data into the empty columns of rows containing the repeating data (‘flattening’ the table). OR Placing the repeating data along with a copy of the original key attribute(s) into a separate relation. UNF to 1NF – Flattening table One value Second (2NF) and Third Normal Form (3NF) 2NF: A relation that is in 1NF and every non-primary-key attribute is fully functionally dependent on the primary key. 3NF: A relation that is in 1NF and 2NF and in which no non-primary-key attribute is transitively dependent on the primary key. Functional Dependencies Functional Dependencies Second Normal Form (2NF) Based on the concept of full functional dependency. Full functional dependency indicates that if A and B are attributes of a relation, B is fully dependent on A if B is functionally dependent on A but not on any proper subset of A. Single attribute primary keys are in 2NF Second Normal Form (2NF) A relation that is in 1NF and every non-primary-key attribute is fully functionally dependent on the primary key. Removal of partial dependencies 1NF to 2NF Identify the primary key for the 1NF relation. Identify the functional dependencies in the relation. If partial dependencies exist on the primary key remove them by placing then in a new relation along with a copy of their determinant. 1NF to 2NF clientNo, propertyNo {Primary Key} fd2 clientNo à cName {partial} fd3 propertyNo à pAddress, rent, ownderNo, oName {partial} 1NF to 2NF fd2 original fd3 Third Normal Form (3NF) Based on the concept of transitive dependency. Transitive Dependency is a condition where A, B and C are attributes of a relation such that if A ® B and B ® C, then C is transitively dependent on A through B. Third Normal Form (3NF) A relation that is in 1NF and 2NF and in which no non-primary-key attribute is transitively dependent on the primary key. 2NF to 3NF Identify the primary key in the 2NF relation. Identify functional dependencies in the relation. If transitive dependencies exist on the primary key remove them by placing them in a new relation along with a copy of their determinant. 2NF to 3NF 2NF to 3NF propertyNo {PK} fd4 propertyNo à pAddress, rent, ownerNo, oName fd4 ownerNo à oName {transitive} oName is transitively dependent on propertyNo 2NF to 3NF General Definitions of 2NF and 3NF Second normal form (2NF) A relation that is in first normal form and every non-primary-key attribute is fully functionally dependent on any candidate key. Third normal form (3NF) A relation that is in first and second normal form and in which no non-primary-key attribute is transitively dependent on any candidate key. UNF to 1NF to 2NF to 3NF remove repeating remove partial remove transitive Chapter 14 - Objectives The purpose of normalization. How normalization can be used when designing a relational database. The potential problems associated with redundant data in base relations. The concept of functional dependency, which describes the relationship between attributes. The characteristics of functional dependencies used in normalization. Chapter 14 - Objectives How to identify functional dependencies for a given relation. How functional dependencies identify the primary key for a relation. How to undertake the process of normalization. How normalization uses functional dependencies to group attributes into relations that are in a known normal form. Chapter 14 - Objectives How to identify the most commonly used normal forms, namely First Normal Form (1NF), Second Normal Form (2NF), and Third Normal Form (3NF). The problems associated with relations that break the rules of 1NF, 2NF, or 3NF. How to represent attributes shown on a form as 3NF relations using normalization.