1. DBMS SUBMITTED BY :- MADHU MADHAN Lecturer in Computer engg.
G.P. MEHAM (ROHTAK)

2. Database management concepts
Database Management Systems (DBMS)
An example of a database (relational)
Database schema (e.g. relational)
Data independence
Architecture of a DBMS
Types of DBMS
Basic DBMS types
Entity relationship model
Retrieving and manipulating data: query processing
Database views
Data integrity

3. DBMS tasks:
Managing large quantity of structured data
Efficient retrieval and modification: query processing and optimization
Sharing data: multiple users use and manipulate data
Controlling the access to data: maintaining the data integrity
An example of a database (relational):
Relations (tables)
Attributes (columns)
Tuples (rows)
Example query: Salesperson='Mary' AND Price>100.

5. Database schema (e.g. relational):
Names and types of attributes
Addresses
Indexing
Statistics
Authorization rules to access data etc.
Data independence: separation of the physical and logical data
Particularly important for distributed systems
The mapping between them is provided by the schema
Architecture of a DBMS - three levels: external, conceptual and internal schema
Types of DBMS
The data structures supported: tables (relational), trees, networks, objects
Type of service provided: high level query language, programming primitives

7. Basic DBMS types Linear files Limitation: single file
Sequence of records with a fixed format usually stored on a single file
Limitation: single file
Example query: Salesperson='Mary' AND Price>100
Hierarchical structure
Trees of records: one-to-many relationships
Limitations:
Requires duplicating records (e.g. many-to-many relationship)
Problems when updated
Retrieval requires knowing the structure (limited data independence):
traversing the tree from top to bottom using a procedural language
Network structure: similar to the hierarchical database with the implementation
of many-to-many relationships
Relational structure
Object-Oriented structure
Objects (collection of data items and procedures) and interactions between them.
Is this really a new paradigm, or a special case of network structure?
Separate implementation vs. implementation on top of a RDBMS

8. Relational structure Relations, attributes, tuples
Primary key (unique combination of attributes for each tuple)
Foreign keys: relationships between tuples (many-to-many).
Example: SUPPLIES defines relations between ITEM and SUPPLIER tuples.
Advantages: many-to-many relationships, high level declarative query language (e.g. SQL)
SQL example (retrieve all items supplied by a supplier located in Troy):
SELECT ItemName
FROM ITEM, SUPPLIES, SUPPLIER
WHERE SUPPLIER.City = "Troy" AND
SUPPLIER.Supplier# = SUPPLIES.Supplier# AND
SUPPLIES.Item# = ITEM.Item#
Programming language interfaces: including SQL queries in the code

9. Retrieving and manipulating data: query processing
Parsing and validating a query: data dictionary - a relation listing all relations and
relations listing the attributes
Plans for computing the query: list of possible way to execute the query,
estimated cost for each. Example:
SELECT ItemNames, Price
FROM ITEM, SALES
WHERE SALES.Item# = ITEM.Item# AND Salesperson="Mary"
Index: B-tree index, drawbacks - additional space, updating;
indexing not all relations (e.g. the keys only)
Estimating the cost for computing a query: size of the relation, existence/size of the indices.
Example: estimating Attribute=value with a given number of tuples and the size of the index.
Query optimization: finding the best plan (minimizing the computational cost and
the size of the intermediate results), subsets of tuples, projection and join.
Static and dynamic optimization

10. Database views Creating user defined subsets of the database
Improving the user interface
Example:
CREATE VIEW MarySales(ItemName,Price)
AS SELECT ItemName, Price
FROM ITEM, SALES
WHERE ITEM.Item#=SALES.Item# AND Salesperson="Mary"
Then the query:
SELECT ItemName
FROM MarySales
WHERE Proce>100
translates to:
WHERE ITEM.Item#=SALES.Item# AND Salesperson="Mary" AND Price>100

11. The Entity-Relationship Model
The slides for this text are organized into chapters. This lecture covers Chapter 2, on the Entity-Relationship approach to database design.
The important issue of how to map from ER diagrams to relational tables is deferred until the relational model and the integrity constraints it supports have been introduced. ER to relational mapping, together with a discussion of the related SQL commands, is discussed in Chapter 3. 1

12. Database Design Process
Requirement collection and analysis
DB requirements and functional requirements
Conceptual DB design using a high-level model
Easier to understand and communicate with others
Logical DB design (data model mapping)
Conceptual schema is transformed from a high-level data model into implementation data model
Physical DB design
Internal data structures and file organizations for DB are specified 2

13. Overview of Database Design
Conceptual design: (ER Model is used at this stage.)
What are the entities and relationships in the enterprise?
What information about these entities and relationships should we store in the database?
What are the integrity constraints or business rules that hold?
A database `schema’ in the ER Model can be represented pictorially (ER diagrams).
An ER diagram can be mapped into a relational schema. 2

14. Employees
ssn
name
lot
ER Model Basics
Entity: Real-world object distinguishable from other objects. An entity is described (in DB) using a set of attributes.
Entity Set: A collection of similar entities. E.g., all employees.
All entities in an entity set have the same set of attributes. (Until we consider ISA hierarchies, anyway!)
Each entity set has a key.
Each attribute has a domain.
The slides for this text are organized into several modules. Each lecture contains about enough material for a 1.25 hour class period. (The time estimate is very approximate--it will vary with the instructor, and lectures also differ in length; so use this as a rough guideline.) This covers Lectures 1 and 2 (of 6) in Module (5).
Module (1): Introduction (DBMS, Relational Model)
Module (2): Storage and File Organizations (Disks, Buffering, Indexes)
Module (3): Database Concepts (Relational Queries, DDL/ICs, Views and Security)
Module (4): Relational Implementation (Query Evaluation, Optimization)
Module (5): Database Design (ER Model, Normalization, Physical Design, Tuning)
Module (6): Transaction Processing (Concurrency Control, Recovery)
Module (7): Advanced Topics 3

15. ER Model Basics Key and key attributes:
Employees
ssn
name
lot
ER Model Basics
Key and key attributes:
Key: a unique value for an entity
Key attributes: a group of one or more attributes that uniquely identify an entity in the entity set
Super key, candidate key, and primary key
Super key: a set of attributes that allows to identify and entity uniquely in the entity set
Candidate key: minimal super key
There can be many candidate keys
Primary key: a candidate key chosen by the designer
Denoted by underlining in ER attributes
The slides for this text are organized into several modules. Each lecture contains about enough material for a 1.25 hour class period. (The time estimate is very approximate--it will vary with the instructor, and lectures also differ in length; so use this as a rough guideline.) This covers Lectures 1 and 2 (of 6) in Module (5).
Module (1): Introduction (DBMS, Relational Model)
Module (2): Storage and File Organizations (Disks, Buffering, Indexes)
Module (3): Database Concepts (Relational Queries, DDL/ICs, Views and Security)
Module (4): Relational Implementation (Query Evaluation, Optimization)
Module (5): Database Design (ER Model, Normalization, Physical Design, Tuning)
Module (6): Transaction Processing (Concurrency Control, Recovery)
Module (7): Advanced Topics 3

16. ER Model Basics (Contd.)
name
ER Model Basics (Contd.)
ssn
lot
Employees
since
name
dname
super-visor
subor-dinate
ssn
lot
did
budget
Reports_To
Employees
Works_In
Departments
Relationship: Association among two or more entities. e.g., Jack works in Pharmacy department.
Relationship Set: Collection of similar relationships.
An n-ary relationship set R relates n entity sets E1 ... En; each relationship in R involves entities e1 in E1, ..., en in En
Same entity set could participate in different relationship sets, or in different “roles” in same set. 4

17. Key Constraints
since
lot
name
ssn
dname
did
budget
Manages
Consider Works_In: An employee can work in many departments; a dept can have many employees.
In contrast, each dept has at most one manager, according to the key constraint on Manages.
Employees
Departments
1-to-1
1-to Many
Many-to-1
Many-to-Many 6

18. Example ER
major
Department
offers
An ER diagram represents several assertions about the real world. What are they?
When attributes are added, more assertions are made.
How can we ensure they are correct?
A DB is judged correct if it captures ER diagram correctly.
faculty
Courses
teaches
Professor
advisor
enrollment
Students 2

19. Exercises Is double major allowed?
Department
offers
Is double major allowed?
Can a student have more than 1 advisor?
Is joint appointment of faculty possible?
Can two profs share to teach the same course?
Can a professor teach more than one course?
Can a professor stay without affiliated with a department?
faculty
Courses
teaches
Professor
advisor
enrollment
Students 2

20. Participation Constraints
Does every department have a manager?
If so, this is a participation constraint: the participation of Departments in Manages is said to be total (vs. partial).
Every Departments entity must appear in an instance of the Manages relationship.
since
since
name
name
dname
dname
ssn
lot
did
did
budget
budget
Employees
Manages
Departments
Works_In
since 8

21. Weak Entities
A weak entity can be identified uniquely only by considering the primary key of another (owner) entity.
Owner entity set and weak entity set must participate in a one-to-many relationship set (one owner, many weak entities).
Weak entity set must have total participation in this identifying relationship set.
name
cost
ssn
pname
lot
age
Employees
Policy
Dependents 10

22. ISA (`is a’) Hierarchies
name
ISA (`is a’) Hierarchies
ssn
lot
Employees
As in C++, or other PLs, attributes are inherited.
If we declare A ISA B, every A entity is also considered to be a B entity.
hourly_wages
hours_worked
ISA
contractid
Hourly_Emps
Contract_Emps
Overlap constraints: Can Joe be an Hourly_Emps as well as a Contract_Emps entity? (default: disallowed; A overlaps B)
Covering constraints: Does every Employees entity also have to be an Hourly_Emps or a Contract_Emps entity? (default: no; A AND B COVER C)
Reasons for using ISA:
To add descriptive attributes specific to a subclass.
To identify entities that participate in a relationship. 12

23. name
Aggregation
ssn
lot
Employees
Used when we have to model a relationship involving (entitity sets and) a relationship set.
Aggregation allows us to treat a relationship set as an entity set for purposes of participation in (other) relationships.
Monitors
until
started_on
since
dname
pid
pbudget
did
budget
Projects
Sponsors
Departments
Aggregation vs. ternary relationship:
Monitors is a distinct relationship,
with a descriptive attribute.
Also, can say that each sponsorship
is monitored by at most one employee. 2

24. Conceptual Design Using the ER Model
Design choices:
Should a concept be modeled as an entity or an attribute?
Should a concept be modeled as an entity or a relationship?
Identifying relationships: Binary or ternary? Aggregation?
Constraints in the ER Model:
A lot of data semantics can (and should) be captured.
But some constraints cannot be captured in ER diagrams. 3

25. Entity vs. Attribute
Should address be an attribute of Employees or an entity (connected to Employees by a relationship)?
Depends upon the use we want to make of address information, and the semantics of the data:
If we have several addresses per employee, address must be an entity (since attributes cannot be set-valued).
If the structure (city, street, etc.) is important, e.g., we want to retrieve employees in a given city, address must be modeled as an entity (since attribute values are atomic).

26. Entity vs. Attribute (Contd.)
from to
name
Employees
ssn
lot
Works_In4 does not allow an employee to work in a department for two or more periods.
Similar to the problem of wanting to record several addresses for an employee: We want to record several values of the descriptive attributes for each instance of this relationship. Accomplished by introducing new entity set, Duration.
dname
did
budget
Works_In4
Departments
name
dname
budget
did
ssn
lot
Employees
Works_In4
Departments
Duration
from to 5

27. Entity vs. Relationship
First ER diagram OK if a manager gets a separate discretionary budget for each dept.
What if a manager gets a discretionary budget that covers all managed depts?
Redundancy: dbudget stored for each dept managed by manager.
Misleading: Suggests dbudget associated with department-mgr combination.
since
dbudget
name
dname
ssn
lot
did
budget
Employees
Manages2
Departments
name
ssn
lot
since
dname
Employees
did
budget
Manages2
Departments
ISA
This fixes the
problem!
Managers
dbudget 6

28. Summary of Conceptual Design
Conceptual design follows requirements analysis,
Yields a high-level description of data to be stored
ER model popular for conceptual design
Constructs are expressive, close to the way people think about their applications.
Basic constructs: entities, relationships, and attributes (of entities and relationships).
Some additional constructs: weak entities, ISA hierarchies, and aggregation.
Note: There are many variations on ER model. 11

29. Summary of ER (Contd.)
Several kinds of integrity constraints can be expressed in the ER model: key constraints, participation constraints, and overlap/covering constraints for ISA hierarchies. Some foreign key constraints are also implicit in the definition of a relationship set.
Some constraints (notably, functional dependencies) cannot be expressed in the ER model.
Constraints play an important role in determining the best database design for an enterprise. 12

30. Summary of ER (Contd.)
ER design is subjective. There are often many ways to model a given scenario! Analyzing alternatives can be tricky, especially for a large enterprise. Common choices include:
Entity vs. attribute, entity vs. relationship, binary or n-ary relationship, whether or not to use ISA hierarchies, and whether or not to use aggregation.
Ensuring good database design: resulting relational schema should be analyzed and refined further. FD information and normalization techniques are especially useful. 13

31. Exercise
name
Customer
ssn
addr
acct#
balance
What can you say about policy of the bank from the ER diagram?
What can you say about the policy of the company?
CustAcct
Account
name
Employees
ssn
lot
Manages
deptid
budget
Dept 7

32. Design Exercise
Design a DB using ER, and sketch the resulting diagram. State any important assumptions you made in reaching the design. Show explicitly whether relationships are 1-1, 1-M, or N-M.
UVA registrar’s office: It maintains data about each class, including the instructor, students, enrollment, time and place of the class meetings. For each student-class pair, a grade is recorded.
Hospital: It maintains all patients visited, including age and address. It also keeps track of the information about billing, visits, data, reason for visit, and treatment. 12

33. Data integrity Integrity constraints: semantic conditions on the data
Individual constraints on data items
Uniqueness of the primary keys
Dependencies between relations
Concurrency control
Steps in executing a query
Concurrent users of the database, interfering the execution of one query by another
Transaction: a set of operations that takes the database from one consistent state to another
Solving the concurrency control problem: making transactions atomic operations (one at a time)
Concurrent transactions: serializability theory (two-phase locking), read lock (many), write lock (one).
Serializible transactions: first phase - accumulating locks, second phase - releasing locks.
Deadlocks: deadlock detection algorithms.
Distributed execution problems:
release a lock at one node (all locks accumulated at the other node?)
strict two-phase locking

34. The Transaction Model Examples of primitives for transactions.
Description
BEGIN_TRANSACTION
Make the start of a transaction
END_TRANSACTION
Terminate the transaction and try to commit
ABORT_TRANSACTION
Kill the transaction and restore the old values
READ
Read data from a file, a table, or otherwise
WRITE
Write data to a file, a table, or otherwise
Examples of primitives for transactions.

35. The Transaction Model Transaction to reserve three flights commits
BEGIN_TRANSACTION reserve WP -> JFK; reserve JFK -> Nairobi; reserve Nairobi -> Malindi; END_TRANSACTION
(a)
BEGIN_TRANSACTION reserve WP -> JFK; reserve JFK -> Nairobi; reserve Nairobi -> Malindi full => ABORT_TRANSACTION
(b)
Transaction to reserve three flights commits
Transaction aborts when third flight is unavailable

36. Distributed Transactions
A nested transaction
A distributed transaction

37. Concurrency Control (1)
General organization of managers for handling transactions.

38. Data integrity Backup and recovery Security and access control
The problem of keeping a transaction atomic: successful or failed
What if some of the intermediate steps failed?
Log of database activity: use the log to undo a failed transaction.
More problems: when to write the log, failure of the recovery system executing the log.
Security and access control
Access rules for relations or attributes. Stored in a special relation (part of the data dictionary).
Content-independent and content-dependent access control
Content-dependent control: access to a view only or query modification
(e.g. and-ing a predicate to the WHERE clause)
Discretionary and mandatory access control

39. THANK YOU