ch2
Introduction to the concepts behind relational model database systems in the 6th Edition of Database System Concepts by Silberschatz, Korth, and Sudarshan.
Data Models: Relational databases; schema and instance.
Database Design: Establishing a framework for databases.
Storage Manager: Handles data storage and retrieval.
Query Processing: How queries are interpreted and executed.
Transaction Manager: Manages database operations that require multiple steps.
Merits and Drawbacks of Database: Queries on this concept are introduced but not extensively discussed in Chapter 2.
Database System Architecture: Involves multiple layers:
View Level: Individual user views (view 1, view 2, view n).
Logical Level: Overall structure of the database.
Physical Level: How data is physically stored.
Database Schema: Outline of tables, attributes, and relationship.
Keys: Identify records uniquely in a database.
Primary Keys: A field or combination of fields that uniquely identify a table record.
Foreign Keys: A field that links to the primary key of another table, indicating relationships.
Schema Diagrams: Visual representations of database structure.
Relational Query Languages: How queries are written to manipulate data.
Relational Algebra: Mathematical structure for querying databases.
Types of Data Models:
Relational Model: Focus of this chapter, represents data in tables.
Entity-Relationship Model: Used mainly for database design.
Object-Based Models: Include Object-oriented and Object-relational.
Semi-Structured Models: Includes XML.
Older Models: Network and hierarchical models.
Attributes and Tuples:
Attributes (columns) and tuples (rows) are the primary structures in relational databases.
Each table is made up of tuples that express relationships between different pieces of data.
Domain: Set of allowable values for an attribute.
Atomic Values: Attribute values should be indivisible.
Null Values: Represents missing or unknown data, complicating operation definitions.
Relation Schema: Structure of a relation as defined by its attributes.
Current Values (Instance): A relation's present state represented in a table.
Superkey: A set of attributes that can uniquely identify tuples.
Candidate Key: A minimal superkey, necessary for primary key selection.
Foreign Key Constraints: Ensures referential integrity between tables.
Schema Diagram for University Database: Represents relationships and structures including student ID, departments, courses, etc.
Procedural vs Non-Procedural:
Procedural languages specify how to obtain a result; non-procedural focuses on what data to retrieve.
Pure Languages: Include relational algebra and relational calculus, all three are equivalent in computing power.
Focus of this chapter is on relational algebra with its six basic operations.
Operations yielding a single relation:
Select (σ): Picks tuples based on predicates.
Project (π): Retrieves selected attributes from tuples.
Union (∪): Combines tuples from similar structured tables without duplicates.
Set Difference (−): Finds tuples in one relation but not the other.
Intersection (∩): Captures common tuples across two relations.
Join Operation: Merges tuples from two relations based on matching attribute values.
Aggregate Functions: SUM, AVG, MAX, MIN can be performed, grouped by attributes (e.g. average salary by department).
This chapter focuses on the relational model's key concepts, structures, operations, and query capabilities within database systems, setting the groundwork for the advanced database concepts explored in subsequent chapters.
Introduction to the concepts behind relational model database systems in the 6th Edition of Database System Concepts by Silberschatz, Korth, and Sudarshan.
Data Models: Relational databases; schema and instance.
Database Design: Establishing a framework for databases.
Storage Manager: Handles data storage and retrieval.
Query Processing: How queries are interpreted and executed.
Transaction Manager: Manages database operations that require multiple steps.
Merits and Drawbacks of Database: Queries on this concept are introduced but not extensively discussed in Chapter 2.
Database System Architecture: Involves multiple layers:
View Level: Individual user views (view 1, view 2, view n).
Logical Level: Overall structure of the database.
Physical Level: How data is physically stored.
Database Schema: Outline of tables, attributes, and relationship.
Keys: Identify records uniquely in a database.
Primary Keys: A field or combination of fields that uniquely identify a table record.
Foreign Keys: A field that links to the primary key of another table, indicating relationships.
Schema Diagrams: Visual representations of database structure.
Relational Query Languages: How queries are written to manipulate data.
Relational Algebra: Mathematical structure for querying databases.
Types of Data Models:
Relational Model: Focus of this chapter, represents data in tables.
Entity-Relationship Model: Used mainly for database design.
Object-Based Models: Include Object-oriented and Object-relational.
Semi-Structured Models: Includes XML.
Older Models: Network and hierarchical models.
Attributes and Tuples:
Attributes (columns) and tuples (rows) are the primary structures in relational databases.
Each table is made up of tuples that express relationships between different pieces of data.
Domain: Set of allowable values for an attribute.
Atomic Values: Attribute values should be indivisible.
Null Values: Represents missing or unknown data, complicating operation definitions.
Relation Schema: Structure of a relation as defined by its attributes.
Current Values (Instance): A relation's present state represented in a table.
Superkey: A set of attributes that can uniquely identify tuples.
Candidate Key: A minimal superkey, necessary for primary key selection.
Foreign Key Constraints: Ensures referential integrity between tables.
Schema Diagram for University Database: Represents relationships and structures including student ID, departments, courses, etc.
Procedural vs Non-Procedural:
Procedural languages specify how to obtain a result; non-procedural focuses on what data to retrieve.
Pure Languages: Include relational algebra and relational calculus, all three are equivalent in computing power.
Focus of this chapter is on relational algebra with its six basic operations.
Operations yielding a single relation:
Select (σ): Picks tuples based on predicates.
Project (π): Retrieves selected attributes from tuples.
Union (∪): Combines tuples from similar structured tables without duplicates.
Set Difference (−): Finds tuples in one relation but not the other.
Intersection (∩): Captures common tuples across two relations.
Join Operation: Merges tuples from two relations based on matching attribute values.
Aggregate Functions: SUM, AVG, MAX, MIN can be performed, grouped by attributes (e.g. average salary by department).
This chapter focuses on the relational model's key concepts, structures, operations, and query capabilities within database systems, setting the groundwork for the advanced database concepts explored in subsequent chapters.