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Lecture notes

Database

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A complete guide in point form to understand the basics of Databases, required in all computer science course, in order to achieve a 1st. Database is the foundation to data entries and data, which is a crucial item in today's age.

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  • March 26, 2019
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  • 2017/2018
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By: nganozov • 1 year ago

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gohmegan
CS2855 Databases Relational Model
Reading = Database System Concepts, 6th edition, Avi  Model = collection of tables
Silberschatz  lower level than ER Model
Coursework:  ER Design -> Relational model
 3 coursework assignments (15%) Data Definition Language (DDL)
 Mini-project (25%)  defines schema
 Exam (60%)  DDL compiler = generates set of tables (into data
Text -> ER Diagram -> Relational Model -> Relational dictionary)
Algebra -> SQL  Data Dictionary = contains metadata (schema,
 DBMS: storage structure, access, integrity constraints,
o Database (collection of interrelated data) authorization)
o programs to access them Data Manipulation Language (DML)
o env = convenient + efficient  Access + manipulate
 Database Application:  query + update
o banking, airlines....  Procedural (what data, how)
 Database = fundamental to ~all systems  Declarative (what data is required)
Purpose:  “Pure languages” = relational algebra
 Drawbacks of file: Extensible Markup Language (XML)
o Data redundancy + inconsistency  general purpose, user defines tag
o difficult in accessing Not separated (SQL will consist of both)
o atomicity of updates Relational Algebra
 failure = inconsistent = partial
updates
o concurrent access
o security (constraints) SQL (Standard SQL examples)
o No data independence
Level of "Abstraction"
1. Physical (how it's stored)
2. Logical (how data (type) stored in database,
relationship between data)
3. View (app hide details of data type, hide info for
security)
Data Model
 Data Part 2: ER Model
 Relationship ER Model = high level data model
 semantics - collection of entities
 constraints - relationships
1. ER Data Model for DB Design - constraints
2. Relational Model - attributes
3. Semistructured Data Model (XML) Entities: thing
Data Schemas VS Instances - have attributes
 schema = overall logical design of DB - entity set = set of entities of same type, same kind
 instance = snapshot of the DB, the actual data in of attributes
the DB at that time - entity has value for each attributes
 instances changes, schema almost never do Relationship: association among several entities
ER Model - Relationship-set = set of tuples (relationships)
 Model = entities + relationships Role: function that an entity plays in a R
o entity = thing or object (distinguishable E.g. R = Joan is father of Sean. E = Joan, Sean.
from other objects) Role: parent-child relationship. Can have 2 roles
o attributes = entities Descriptive attribute: an attribute of a relationship set
Degree = no. of entity sets in relationship set
o relationship = association among several
- binary = 2
entities

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