NMEC RD_UNIT 1.ppt
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- 2. A person, place, event or item is called an entity The facts describing an entity are known as data Each entity can be described by its characteristics known as attributes All the related entities are collected together to form an entity set A database is a collection of entity sets The interaction between the entity sets are called relationships. 2
- 3. A data base is an electronic store of data. It stores information about different “things”& also contains relationships. The collection of data may be organized in the form of files or tables. Examples:- 1. Oracle 9i, 10G, 10Gi, 11G, 11Gi 2. SQL-server-2005, 2010 3. DB2,Sybase,foxpro, Ms-access2003,2007, 2010, 3
- 4. A DBMS is a software package designed to define, manipulate, retrieve and manage data in a database. It also defines rules to validate and manipulate the data. It relieves users of framing programs for data maintenance. Fourth-generation query languages, such as SQL, are used along with the DBMS package to interact with a database. 4
- 5. 1. Banking Sector 2. Universities 3. Railway Reservation 4. Finance 5. Sales 5
- 6. 1. One-to-one (1:1) : Each entity has only one matching entity in another entity set Eg: Student (1) – RollNo. (1) 2. One-to-many (1:M): Each entity of X has many matching entities in another entity set Y. Eg: Department (1) – Employees (M) 3. Many-to-many (M:M): Each entity of X has many matching entities in another entity set Y and vice versa. Eg: Students (M) – Courses (M) 6
- 7. DBMS S/W Packages – MS Access, Oracle User developed & implemented DB Custom Applications such as forms,Reports,query blocks Computer hardware – PCs, minicomputers Software – OS and Network OS Personnel- DB administrator, designer 7
- 8. User Applications DBMS Database OS Software Hardware 8
- 9. RDBMS is a DBMS i.e. based on Relational model as introduce by Dr. E.F. Codd….. Codd’s rule for RDBMS:- Dr. Codd is an IBM researcher who developed relational data base in 1970….. In 1905 Codd published 12 rules…… 1)The Information rule. 2)Granted access rule. 3)Systemic treatment of NULL values. 4)Dynamic online Catalog based on relational model. 9
- 10. 5)Comprehensive data sub-language rule. 6)View updating rule. 7)High level Insert , Update, Delete rule. 8)Physical data Independence. 9)Logical data Independence. 10)Integrity data Independence. 11)Distribution data Independence. 12)Non-subversions rule. 10
- 11. 1. It manages the data and relationships stored in the database. 2. It creates a Data Dictionary (DD) as a user creates a DB. DD stores Metadata (data about data) 3. Manages all day-to-day transactions 4. Data search can be done through DD 5. User can validate data 11
- 12. 6. Secures access through passwords, encryption etc.. 7. Backup & Recovery procedures 8. Data Sharing with data-locking capabilities 9. Import and Export Utilities from other databases 10. Users can view information stored in different tables within the database. 12
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- 14. E.F.Codd developed the relational model in 1970. The relation is represented by a table structure Each row represents an entity Each column represents an attribute DATA STRUCTURES - domain, attribute, relation, tuple, primary key, degree, cardinality. INTEGRITY CONSTRAINTS - entity integrity and referential integrity. DATA MANIPULATION OPERATIONS - defined through relational algebra and equivalent relational calculus. 14
- 15. A database consists of one or more relations. A relation is described by a name, names for one or more attributes and consists of zero or more tuples. A tuple consists of values for each attribute of the relation. An attribute takes values from a domain and there exists one value for each attribute in a tuple. A domain consists of all allowed atomic values for one or more attributes. Degree of a relation is the number of attributes of the relation. Cardinality of a relation is the number of tuples of the relation. 15
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- 19. Keys are very important part of Relational database. They are used to establish and identify relation between tables. They also ensure that each record within a table can be uniquely identified by combination of one or more fields within a table. 19
- 20. Super Key: Super Key is defined as a set of attributes within a table that uniquely identifies each record within a table. Super Key is a superset of Candidate key. Candidate Key: Candidate keys are defined as the set of fields from which primary key can be selected. It is an attribute or set of attributes that can act as a primary key for a table to uniquely identify each record in that table. 20
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- 22. The minimal set of attribute which can uniquely identify a tuple is known as candidate key. For Example, STUD_NO in STUDENT relation. The value of Candidate Key is unique and non-null for every tuple. There can be more than one candidate key in a relation. For Example, STUD_NO as well as STUD_PHONE both are candidate keys for relation STUDENT. The candidate key can be simple (having only one attribute) or composite as well. For Example, {STUD_NO, COURSE_NO} is a composite candidate key for relation STUDENT_COURSE. 22
- 23. The set of attributes which can uniquely identify a tuple is known as Super Key. For Example, STUD_NO, (STUD_NO, STUD_NAME) etc. Adding zero or more attributes to candidate key generates super key. A candidate key is a super key but vice versa is not true 23
- 24. There can be more than one candidate key in a relation out of which one can be chosen as primary key( that is most appropriate to become main key of the table) For Example, STUD_NO as well as STUD_PHONE both are candidate keys for relation STUDENT but STUD_NO can be chosen as primary key (only one out of many candidate keys). 24
- 25. The candidate key other than primary key is called as alternate key. For Example, STUD_NO as well as STUD_PHONE both are candidate keys for relation STUDENT but STUD_PHONE will be alternate key (only one out of many candidate keys). 25
- 26. If we use multiple attributes to create a Primary Key then that Primary Key is called Composite Key (also called a Compound Key or Concatenated Key). 26
- 27. A foreign key is an attribute or combination of attributes in one base table that points to the candidate key (generally it is the primary key) of another table. The purpose of the foreign key is to ensure referential integrity of the data For Example, STUD_NO in STUDENT_COURSE is a foreign key to STUD_NO in STUDENT relation. 27
- 28. It is very important that data in the underlying tables be consistent Two integrity rules: 1. Entity Integrity (feature of primary key) ◦ No column in primary key may be null ◦ Primary key provides the means of uniquely identifying a row or an entity. ◦ A null value means a value that is not known, not entered, not defined or not applicable. 28
- 29. ◦ A zero or space is not considered to be a null value ◦ RDBMS does not allow users to enter a row without a unique value in the primary key column 2. Referential Integrity(feature of foreign key) ◦ Foreign key value may be null or it must exist as a value of a primary key in the referenced table. ◦ Oracle does not allow to declare a foreign key if it does not exist as a primary key in another table 29
- 30. Relational algebra , a procedural language Relational calculus, a non-procedural language 30
- 31. 31 Relational algebra is a collection of operations to manipulate or access tables It is a procedural language with operations performed on one or more existing relations to derive resulting operations without changing the original relations. The operations can be divided into two groups SET-ORIENTED OPERATIONS NATIVE(SPECIAL)RELATIONAL OPERATIONS. Basics of Relational Algebra
- 32. 32 BASIC SET ORIENTED OPERATIONS NAME SYMBOL UNION U INTERSECTION ∩ DIFFERENCE - PRODUCT × NATIVE RELATIONAL OPERATIONS NAME SYMBOL SELECTION σ PROJECTION Π JOIN DIVISION ÷ ASSIGNMENT
- 33. 33 UNION ROLL.NO NAME 12505 SHARAN 12506 SANGEETA 12507 SHYNA A B ROLL.NO NAME 12502 PRABJOT 125O7 SHYNA 12520 POOJA 12521 RINKI ROLL.NO NAME 12502 PRABJOT 12505 SHARAN 12506 SANGEETA 12507 SHYNA 12520 POOJA 12521 RINKI R=AUB
- 34. 34 INTERSECTION ROLL.NO NAME 12502 PRABJOT 12505 SHARAN 12507 SHYNA 12521 RINKI ROLL.NO NAME 12507 SHYNA 12519 POOJA 12521 RINKI A B R=A∩B ROLL.NO NAME 12507 SHYNA 12521 RINKI
- 35. 35 DIFFERENCE B A ROLL.NO NAME 12502 PRABJOT 12505 SHARAN 12507 SHYNA 12521 RINKI ROLL.NO NAME 12507 SHYNA 12519 POOJA 12514 NEETU 12521 RINKI R=A-B ROLL.NO NAME 12502 PRABJOT 12505 SHARAN R=B-A ROLL.NO NAME 12519 POOJA 12514 NEETU
- 36. 36 CARTESIAN PRODUCT ROLL.NO NAME 12502 PRABJOT 12505 SHARAN 12507 SHYNA 12521 RINKI A ROLL.NO NAME 12507 SHYNA 12519 POOJA B R=A×B ROLL.NO NAME ROLL.NO NAME 12502 PRABJOT 12507 SHYNA 12502 PRABJOT 12519 POOJA 12505 SHARAN 12507 SHYNA 12505 SHARAN 12519 POOJA 12507 SHYNA 12507 SHYNA 12507 SHYNA 12519 POOJA 12521 RINKI 12507 SHYNA 12521 RINKI 12521 POOJA
- 37. 37 ID NAME SALARY AGE 101 AMIT 4500 30 102 AJAY 5000 35 105 JOHN 5000 36 106 ABHI 4000 28 107 ALI 4800 31 108 SUNIL 3500 33 EMPLOYEE SELECTION RESULTING TABLE σAGE >32 (EMPLOYEE) ID NAME SALARY AGE 102 AJAY 5000 35 105 JOHN 5000 36 108 SUNIL 3500 33
- 38. 38 PROJECTION EMPLOYEE ID NAME SALARY AGE 101 AMIT 4500 30 102 AJAY 5000 35 105 JOHN 5000 36 106 ABHI 4000 28 107 ALI 4800 31 108 SUNIL 3500 33 109 JOHN 4600 29 RESULTING TABLES A. π ID (EMPLOYEE) B. π NAME,AGE (EMPLOYEE) NAME AGE AMIT 30 AJAY 35 JOHN 36 ABHI 28 ALI 31 SUNIL 33 JOHN 29 ID 101 102 105 106 107 108 109 B A
- 39. 39 COURSE(C) ROLL.NO NAME COURSE 101 PIYUSH M-01 102 SUMIT M-02 103 SHEENA M-04 104 RITU M-03 S JOIN C_ID C_NAME C_DUR M-01 MBA(HR) 2 M-02 MSC(PHY) 2 M-03 MSC(IT) 2 M-04 MCA 3 ROLL.NO NAME COURSE 101 PIYUSH M-01 102 SUMIT M-02 103 SHEENA M-04 104 RITU M-03 C_ID C_NAME C_DUR M-01 MBA(HR) 2 M-02 MSC(PHY) 2 M-04 MCA 3 M-03 MSC(IT) 2 RESULTING TABLE(EQUI-JOIN) COURSE=C_ID (C) STU(S)
- 40. 40 ROLL.NO NAME COURSE 101 PIYUSH M-01 102 SUMIT M-02 103 SHEENA M-04 104 RITU M-03 C_NAME C_DUR MBA(HR) 2 MSC(PHY) 2 MCA 3 MSC(IT) 2 COURSE(C) ROLL.NO NAME COURSE 101 PIYUSH M-01 102 SUMIT M-02 103 SHEENA M-04 104 RITU M-03 C_ID C_NAME C_DUR M-01 MBA(HR) 2 M-02 MSC(PHY) 2 M-03 MSC(IT) 2 M-04 MCA 3 NATURAL JOIN ON S AND C NATURAL JOIN(INNER JOIN) STU(S)
- 41. 41 DIVISION NAME COUR SE A1 B1 A3 B2 A2 B3 A2 B1 A1 B3 A3 B3 A3 B1 COURSE B1 B3 COURS E B2 COURSE B2 B3 MAIN R1 SUB2 SUB3 RESULTING TABLES R3 R3MAIN÷SUB3 R2 NAME A1 A2 A3 NAME A3 NAME A3 R1MAIN ÷ SUB1 R2MAIN÷SUB2 SUB1 ASSIGNMENT Eg: Student enrolled in ALL the courses
- 42. Non Procedural Programmer specifies data requirement General Syntax: result=(column list):expression Example: r.Name:r in Employee and r.age<30 Result: 42 Name ABHI JOHN