Database management system session 5
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The document provides an overview of database normalization, detailing the various normal forms (1NF, 2NF, 3NF, BCNF, and 5NF) and their requirements aimed at minimizing redundancy and preventing anomalies in databases. It discusses the importance of lossless join decomposition and dependency preservation in maintaining data integrity when breaking relations into smaller tables. Examples illustrate how to transform tables to comply with each normal form and the implications of functional dependencies on the normalization process.
Database management system session 5
- 1. DBDA (Database Design and Applications) CH5 By: Prof. Ganesh Ingle
- 2. Session objective INTRODUCTION 3NF and BCNF Decomposition requirements Lossless join decomposition Dependency preserving decomposition Disk pack features Records and Files Ordered and Unordered files
- 3. Normalization • Normalization is the process of organizing the data in the database. • Normalization is used to minimize the redundancy from a relation or set of relations. It is also used to eliminate the undesirable characteristics like Insertion, Update and Deletion Anomalies. • Normalization divides the larger table into the smaller table and links them using relationship. • The normal form is used to reduce redundancy from the database table.
- 4. Normalization Normal Form Description 1NF A relation is in 1NF if it contains an atomic value. 2NF A relation will be in 2NF if it is in 1NF and all non-key attributes are fully functional dependent on the primary key. 3NF A relation will be in 3NF if it is in 2NF and no transition dependency exists. 4NF A relation will be in 4NF if it is in Boyce Codd normal form and has no multi-valued dependency. 5NF A relation is in 5NF if it is in 4NF and not contains any join dependency and joining should be lossless.
- 5. Normalization First Normal Form (1NF) • A relation will be 1NF if it contains an atomic value. • It states that an attribute of a table cannot hold multiple values. It must hold only single-valued attribute. • First normal form disallows the multi-valued attribute, composite attribute, and their combinations. Example: Relation EMPLOYEE is not in 1NF because of multi-valued attribute EMP_PHONE. EMP_ID EMP_NAME EMP_PHONE EMP_STATE 14 John 7272826385, 9064738238 UP 20 Harry 8574783832 Bihar 12 Sam 7390372389, 8589830302 Punjab EMP_ID EMP_NAME EMP_PHONE EMP_STATE 14 John 7272826385 UP 14 John 9064738238 UP 20 Harry 8574783832 Bihar 12 Sam 7390372389 Punjab 12 Sam 8589830302 Punjab
- 6. Second Normal Form (2NF) In the 2NF, relational must be in 1NF. In the second normal form, all non-key attributes are fully functional dependent on the primary key Example: Let's assume, a school can store the data of teachers and the subjects they teach. In a school, a teacher can teach more than one subject. TEACHER_ID SUBJECT TEACHER_AGE 25 Chemistry 30 25 Biology 30 47 English 35 83 Math 38 83 Computer 38 Normalization
- 7. Second Normal Form (2NF) In the 2NF, relational must be in 1NF. In the second normal form, all non-key attributes are fully functional dependent on the primary key Example: Let's assume, a school can store the data of teachers and the subjects they teach. In a school, a teacher can teach more than one subject. TEACHER_ID SUBJECT TEACHER_AGE 25 Chemistry 30 25 Biology 30 47 English 35 83 Math 38 83 Computer 38 Normalization TEACHER table
- 8. Normalization TEACHER_ID TEACHER_AGE 25 30 47 35 83 38 TEACHER_ID SUBJECT 25 Chemistry 25 Biology 47 English 83 Math 83 Computer TEACHER_SUBJECT table: TEACHER_DETAIL table:
- 9. Normalization Third Normal Form (3NF) • A relation will be in 3NF if it is in 2NF and not contain any transitive partial dependency. • 3NF is used to reduce the data duplication. It is also used to achieve the data integrity. • If there is no transitive dependency for non-prime attributes, then the relation must be in third normal form. • A relation is in third normal form if it holds atleast one of the following conditions for every non-trivial function dependency X → Y. • X is a super key. • Y is a prime attribute, i.e., each element of Y is part of some candidate key.
- 10. Normalization EMP_ID EMP_NAME EMP_ZIP EMP_STATE EMP_CITY 222 Harry 201010 UP Noida 333 Stephan 02228 US Boston 444 Lan 60007 US Chicago 555 Katharine 06389 UK Norwich 666 John 462007 MP Bhopal EMPLOYEE_DETAIL table: Super key in the table above: {EMP_ID}, {EMP_ID, EMP_NAME}, {EMP_ID, EMP_NAME, EMP_ZIP}....so on Candidate key: {EMP_ID} Non-prime attributes: In the given table, all attributes except EMP_ID are non-prime.
- 11. Normalization EMP_ID EMP_NAME EMP_ZIP 222 Harry 201010 333 Stephan 02228 444 Lan 60007 555 Katharine 06389 666 John 462007 EMP_ZIP EMP_STATE EMP_CITY 201010 UP Noida 02228 US Boston 60007 US Chicago 06389 UK Norwich 462007 MP Bhopal EMPLOYEE_ZIP table: EMPLOYEE table :
- 12. Normalization Boyce Codd normal form (BCNF) • BCNF is the advance version of 3NF. It is stricter than 3NF. • A table is in BCNF if every functional dependency X → Y, X is the super key of the table. • For BCNF, the table should be in 3NF, and for every FD, LHS is super key. • Example: Let's assume there is a company where employees work in more than one department. EMP_ID EMP_COUNTRY EMP_DEPT DEPT_TYPE EMP_DEPT_NO 264 India Designing D394 283 264 India Testing D394 300 364 UK Stores D283 232 364 UK Developing D283 549 EMPLOYEE table: In the above table Functional dependencies are as follows: EMP_ID → EMP_COUNTRY EMP_DEPT → {DEPT_TYPE, EMP_DEPT_NO} Candidate key: {EMP-ID, EMP-DEPT}
- 13. Normalization EMP_ID EMP_COUNTRY 264 India 264 India EMP_COUNTRY table: EMP_DEPT DEPT_TYPE EMP_DEPT_NO Designing D394 283 Testing D394 300 Stores D283 232 Developing D283 549 EMP_DEPT table: EMP_ID EMP_DEPT D394 283 D394 300 D283 232 D283 549 EMP_DEPT_MAPPING table: Functional dependencies: EMP_ID → EMP_COUNTRY EMP_DEPT → {DEPT_TYPE, EMP _DEPT_NO} Candidate keys: For the first table: EMP_ID For the second table: EMP_DEPT For the third table: {EMP_ID, EMP_DEPT}
- 14. Normalization Relational Decomposition • When a relation in the relational model is not in appropriate normal form then the decomposition of a relation is required. • In a database, it breaks the table into multiple tables. • If the relation has no proper decomposition, then it may lead to problems like loss of information. • Decomposition is used to eliminate some of the problems of bad design like anomalies, inconsistencies, and redundancy. Lossless Decomposition • If the information is not lost from the relation that is decomposed, then the decomposition will be lossless. • The lossless decomposition guarantees that the join of relations will result in the same relation as it was decomposed. • The relation is said to be lossless decomposition if natural joins of all the decomposition give the original relation.
- 15. Normalization Dependency Preserving It is an important constraint of the database. In the dependency preservation, at least one decomposed table must satisfy every dependency. If a relation R is decomposed into relation R1 and R2, then the dependencies of R either must be a part of R1 or R2 or must be derivable from the combination of functional dependencies of R1 and R2. For example, suppose there is a relation R (A, B, C, D) with functional dependency set (A->BC). The relational R is decomposed into R1(ABC) and R2(AD) which is dependency preserving because FD A->BC is a part of relation R1(ABC).
- 16. Normalization Join Dependency • Join decomposition is a further generalization of Multivalued dependencies. • If the join of R1 and R2 over C is equal to relation R, then we can say that a join dependency (JD) exists. • Where R1 and R2 are the decompositions R1(A, B, C) and R2(C, D) of a given relations R (A, B, C, D). • Alternatively, R1 and R2 are a lossless decomposition of R. • A JD ⋈ {R1, R2,..., Rn} is said to hold over a relation R if R1, R2,....., Rn is a lossless-join decomposition. • The *(A, B, C, D), (C, D) will be a JD of R if the join of join's attribute is equal to the relation R. • Here, *(R1, R2, R3) is used to indicate that relation R1, R2, R3 and so on are a JD of R.
- 17. BCNF
- 22. File Operations
- 26. THANK YOU