Transcript PPT
Chapter 2: Intro to Relational Model
Database System Concepts, 6th Ed.
©Silberschatz, Korth and Sudarshan
See www.db-book.com for conditions on re-use
Database System Concepts
Chapter 1: Introduction
Part 1: Relational databases
Chapter 2: Introduction to the Relational Model
Chapter 3: Introduction to SQL
Chapter 4: Intermediate SQL
Chapter 5: Advanced SQL
Chapter 6: Formal Relational Query Languages
Part 2: Database Design
Chapter 7: Database Design: The E-R Approach
Chapter 8: Relational Database Design
Chapter 9: Application Design
Part 3: Data storage and querying
Chapter 10: Storage and File Structure
Chapter 11: Indexing and Hashing
Chapter 12: Query Processing
Chapter 13: Query Optimization
Part 4: Transaction management
Chapter 14: Transactions
Chapter 15: Concurrency control
Chapter 16: Recovery System
Part 5: System Architecture
Chapter 17: Database System Architectures
Chapter 18: Parallel Databases
Chapter 19: Distributed Databases
Database System Concepts - 6th Edition
Part 6: Data Warehousing, Mining, and IR
Chapter 20: Data Mining
Chapter 21: Information Retrieval
Part 7: Specialty Databases
Chapter 22: Object-Based Databases
Chapter 23: XML
Part 8: Advanced Topics
Chapter 24: Advanced Application Development
Chapter 25: Advanced Data Types
Chapter 26: Advanced Transaction Processing
Part 9: Case studies
Chapter 27: PostgreSQL
Chapter 28: Oracle
Chapter 29: IBM DB2 Universal Database
Chapter 30: Microsoft SQL Server
Online Appendices
Appendix A: Detailed University Schema
Appendix B: Advanced Relational Database Model
Appendix C: Other Relational Query Languages
Appendix D: Network Model
Appendix E: Hierarchical Model
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Chapter 2: Intro to Relational Model
2.1 Structure of Relational Databases
2.2 Database Schema
2.3 Keys
2.4 Schema Diagrams
2.5 Relational Query Languages
2.6 Relational Operations
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In The Beginning...
Everything in Table
Set-oriented Query Language
E.F. Codd
-- 1970 CACM Paper
-- Turing Award
1970
4
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6th
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Example of a Relation
attributes
(or columns)
tuples, records
(or rows)
The set of allowed values for each attribute is called the domain of the attribute
Attribute values are (normally) required to be atomic; that is, indivisible
The special value null is a member of every domain
The null value causes complications in the definition of many operations
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Relation Schema and Instance
A1, A2, …, An are attributes
R = (A1, A2, …, An ) is a relation schema
Example: instructor = (ID, name, dept_name, salary)
Formally, given sets D1, D2, …. Dn a relation r is a subset of D1 x D2 x … x Dn
Thus, a relation is a set of n-tuples (a1, a2, …, an) where each ai Di
The current values (relation instance) of a relation are specified by a table
An element t of r is a tuple, represented by a row in a table
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Relations are Unordered
Order of tuples is irrelevant (tuples may be stored in an arbitrary order)
Relations are basically set!
Example: the instructor relation with unordered tuples
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Database
A database consists of multiple relations
Information about an University enterprise is broken up into parts
instructor
student
advisor
Bad design:
university (instructor -ID, name, dept_name, salary, building, budget..)
results in
repetition of information (e.g., two students have the same instructor)
the need for null values (e.g., represent an student with no advisor)
Normalization theory (Chapter 7) deals with how to design “good” relational
schemas
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University Relation
(instructor -ID, name, dept_name, salary, building, budget)
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Keys
Let K R
K is a superkey of R if values for K are sufficient to identify a unique tuple of
each possible relation r(R)
Example: {ID} and {ID,name} are both superkeys of instructor.
Superkey K is a candidate key if K is minimal
Example: {ID} is a candidate key for Instructor
One of the candidate keys is selected to be the primary key.
which one?
Foreign key constraint: Value in one relation must appear in another
Referencing relation
Referenced relation
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Schema Diagram for University Database
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Figure 2.02: The Course relation
Figure 2.05: The Department Relation
Figure 2.03: The Pre-requisite relation
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Figure 2.04: The Instructor relation
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Figure 2.06: The Section relation
Figure 2.07: The Teaches relation
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Relational Query Languages
Procedural vs. non-procedural (declarative)
“Pure” formal query languages:
Relational algebra
Tuple relational calculus
Domain relational calculus
Relational operators
Select
Project
Cartesian Product
Set Union
Set Minus
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Selection ( σ ) of tuples
Relation r
Select tuples with A=B and D > 5
σ
A=B and D > 5
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(r)
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Projection (Π) of Columns (Attributes)
Relation r:
Select A and C
Projection
Π A, C (r)
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Cartesian Product ( x ):
Cross-Product two relations
Relations r, s:
r x s:
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Union ( ) of two relations
Relations r, s:
r s:
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Set difference ( – ) of two relations
Relations r, s:
r – s:
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Set Intersection ( ) of two relations
Relation r, s:
rs
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Natural Join ( ) : Joining two relations
Let r and s be relations on schemas R and S respectively.
The “natural join” of relations R and S is a relation on schema R S obtained as
follows:
Consider each pair of tuples tr from r and ts from s.
If tr and ts have the same value on each of the attributes in R S,
add a tuple t to the result, where
t has the same value as tr on r
t has the same value as ts on s
Relations r, s:
Natural Join
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r
s
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Some of Relational Algebra Operators: Figure in-2.1
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Figure 2.02: The Course relation
Figure 2.05: The Department Relation
Figure 2.03: The Pre-requisite relation
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Figure 2.04: The Instructor relation
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Figure 2.06: The Section relation
Figure 2.07: The Teaches relation
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Figure 2.13: selecting attributes
ID and salary of instructors with
salary greater than $85000
Figure 2.10: selecting instructors
with salary greater than $85000
Figure 2.11: selecting ID and salary
attributes from the instructor relations
Figure 2.12: Natural Join of the
instructor and department relations
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End of Chapter 2
Database System Concepts, 6th Ed.
©Silberschatz, Korth and Sudarshan
See www.db-book.com for conditions on re-use