Download - L1: Course Overview & Review
H.Lu/HKUST
L1: Course Overview & Review
H.Lu/HKUST L01: RDBMS REVIEW -- 2
The Teaching Staff Instructor: Lu Hongjun
Office: 3543 (Lift 25-26), HKUST E-Mail: [email protected] URL: http://www.cs.ust.hk/~luhj Research Interests:
• Data/Knowledge base management with emphasis on query processing and optimization
• Data warehousing and data mining• Applied performance evaluation• Database application development • Parallel and distributed database systems
TA: Name Jiang Haifeng Liu Guimei Office: 4212 (DB Lab) HKUST E-Mail: [email protected] [email protected] URL: http://ihome.ust.hk/~jianghf http://ihome.ust.hk/~cslgm
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References
R.Ramakrishnan & J. Gehrke. Database Management Systems, 3rd Ed. McGraw Hill, 2000
D. Shasha & P. Bonnet. Database Tuning: Principles, Experiments, and Troubleshooting Techniques, Revised edition , Morgan Kaufmann, 2002
Related papers
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Course Contents
Part I: Issues in database administration Database design Principles of database performance tuning Database security
Part II: Emerging DB-related technology OLAP and data warehouse XML data management Data stream processing
Course Web Page: http://course.cs.ust.hk/comp334/
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Grading
Written assignment (20%) Exams (25%) Course project (50 %) Class participation (5%)
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Course Project Requirements Carried in teams of two or four Database related projects
You propose your own project, and get approve from the instructor
Topic: database related The amount of work : it accounts for 50% of your final
grade Required documents (double-spaced)
Project proposal (1-2 pages)• due date: 23-24/02
Status report (4-6 pages)• due date: 28-29/03
Final report (8-10 pages)• due date: 10-11/05
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Summary
It is a graduate level course Not a DBA course Not an introductory database course Not a programming course, but you need to know
how to write programs Hopefully, you will leave with
A good grade A good understanding of studied topics
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Review -- RDBMS
Relational database systems The basic concepts in database systems Relational data model Relational languages
Database design Previous course: conceptual and logic design This course: physical database design
Database management systems The basic components of DBMS Storage management Transaction management Query processing & optimization
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What Is Database & DBMS?
Database: a very large, integrated, persistent collection of data. Models real-world enterprise.
• Entities (e.g., students, courses)
• Relationships (e.g., James is taking CSIT530)
A Database Management System (DBMS) is a software package designed to store and manage databases.
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Data Models
A data model is a collection of concepts for describing data and related operations, semantics of data, relationship among data, and constraints on data
Two types of data models Conceptual models: emphasize semantics of data
• Entity-Relationship model, Object-Oriented model
Logical models: ways how the data is organized in the logical level
• Hierarchical model, Network model, Relational model
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Instances and Schemas
A schema is a description of a particular collection of data, using a given data model - the logical structure of the database (e.g., set of customers and accounts and the relationship between them)
Schema Instance - the actual content of the database at a particular point in time
Similar to types and variables in programming languages
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Levels of Abstraction
ANSI-SPARC three-level architecture
Many views, single conceptual (logical) schema and physical schema. Views describe how users
see the data.
Conceptual schema defines logical structure
Physical schema describes the files and indexes used.
View
Conceptual Schema
Physical Schema
ViewView
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Data Independence
Applications insulated from how data is structured and stored. Ability to modify a schema definition in one level without
affecting a schema definition in the next higher level. The interfaces between the various levels and components
should be well defined so that changes in some parts do not seriously influence others.
Logical data independence: Protection from changes in logical structure of data.
Physical data independence: Protection from changes in physical structure of data.
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Database Environment
ProceduresAnd standards
Data
DBMS
Hardware
ApplicationPrograms
Systemadministrator
DatabaseAdministrator
Analysts &Programmers
DatabaseDesigner
designs
manages
designs
writeuse
Specifies & enforces
End Users
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DBMS Related Languages
Data Definition Language (DDL) Specification notation for defining the database schema Data storage and definition language - special type of
DDL in which the storage structure and access methods used by the database system are specified
Data Manipulation Language (DML) Language for accessing and manipulation the data
organized by the appropriate data model Two classes of languages
• Procedural - user specifies what data is required and how to get those data.
• Nonprocedural - user specifies what data is required without specifying how to get those data
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DBMS Related Languages
Programming
Language for
DBMS Applications
Host Language
Data Sublanguage
DDL
DML
Query Language
Procedural
Non-Procedural
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Evolution of Database Technology
1960s: Hierarchical (IMS) & network (CODASYL) DBMS.
1970s: Relational data model, relational DBMS implementation.
1980: RDBMS rules the earth 1985-: Advanced data models (extended-relational,
OO, deductive, etc.)
Application-oriented DBMS (spatial, scientific, engineering, etc.).
1990s: ORDB, OLAP, Data mining, data warehousing, multimedia databases, and network databases.
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What is an RDBMS
A piece of software that manages data based on the relational model Relational data, SQL queries
Commercial products Oracle, IBM DB2, IBM Informix, Sybase,
Microsoft SQL Server Each has ~10 million lines of C/C++ code
Smaller packages – MySQL, PostgresSQL
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Relational Data Model
Main concept: relation A table with rows and columns
Every relation has a schema Description of the columns, or fields
Relational data – rows in a table No order among the rows in a table
The most widely used data model!
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University Database
Conceptual schema: Students (sid: string, name: string, login: string, age:
integer, gpa:real)
Cardinality = 3, degree = 5 , all rows distinct Courses (cid: string, cname:string, credits:integer) Enrolled (sid:string, cid:string, grade:string)
sid name login age gpa
53666 Jones jones@cs 18 3.4 53688 Smith smith@eecs 18 3.2 53650 Smith smith@math 19 3.8
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Relational Languages
Formal languages Relational algebra Relational calculus
Commercial language: SQL DDL (Data Definition Language)
• Create Table, Create Index, Create View … DML (Data Manipulation Language)
• Queries– Select
• Updates– Insert, Delete, Update
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Creating Tables
CREATE TABLE Students
(sid: CHAR(20), name: CHAR(20), login: CHAR(10), age: INTEGER, gpa: REAL)
CREATE TABLE Enrolled
(sid: CHAR(20), cid: CHAR(20), grade: CHAR(2))
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Primary Key Constraints
A set of fields is a key for a relation if : 1. Any two distinct tuples differ in some fields of
the set, and 2. This is not true for any subset of the set.
A superkey: Condition 1 true and 2 false. E.g., sid is a key for Students. {sid, gpa} is a
superkey. One primary key can be set per relation.
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Primary and Candidate Keys
CREATE TABLE Students
(sid: CHAR(20), name: CHAR(20), login: CHAR(10), age: INTEGER, gpa: REAL,PRIMARY KEY (sid),UNIQUE (login))
CREATE TABLE Enrolled (sid CHAR(20) cid CHAR(20), grade CHAR(2), PRIMARY KEY (sid,cid))
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Foreign Key Constraints
Foreign key : a set of fields in a relation Refers to the primary key of another relation
Referential integrity No dangling references
CREATE TABLE Enrolled (sid CHAR(20), cid CHAR(20), grade CHAR(2), PRIMARY KEY (sid,cid), FOREIGN KEY (sid) REFERENCES Students )
sid name login age gpa
53666 Jones jones@cs 18 3.453688 Smith smith@eecs 18 3.253650 Smith smith@math 19 3.8
sid cid grade53666 Carnatic101 C53666 Reggae203 B53650 Topology112 A53666 History105 B
EnrolledStudents
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Integrity Constraints (ICs)
IC: condition that must be true for any db instance Domain constraints Primary constraints Foreign key constraints
ICs are specified when a schema is defined. ICs are checked when relations are modified. A legal instance of a relation
Satisfies all specified ICs
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Adding and Deleting Tuples
INSERT INTO Students (sid, name, login, age, gpa)VALUES (53688, ‘Smith’, ‘smith@ee’, 18, 3.2)
DELETE FROM Students SWHERE S.name = ‘Smith’
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Queries
SELECT *FROM Students SWHERE S.sid = 53688
sid name login age gpa
53666 Jones jones@cs 18 3.453688 Smith smith@eecs 18 3.253650 Smith smith@math 19 3.8
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Querying Multiple Tables
SELECT S.name, E.cidFROM Students S, Enrolled EWHERE S.sid=E.sid AND E.grade=“A”
S.name E.cid
Smith Topology112
sid name login age gpa
53666 Jones jones@cs 18 3.453688 Smith smith@eecs 18 3.253650 Smith smith@math 19 3.8
sid cid grade53666 Carnatic101 C53666 Reggae203 B53650 Topology112 A53666 History105 B
EnrolledStudents
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Functional Components of DBMS
Statistics
Metadata
Indexes
User data
Storage Manager
Buffer Management
Index/file/record
Management
Execution Engine
Query Processing & Optimization
Buffer
DDL Compiler
Transaction Management
Recovery
Log
Concurrency Control
Lock Table
Query Plan
DDL Command
User/Application Database Administrator
Security Control
Storage Management
DML Stmt.
Query Processing
Transaction Manager
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Query Optimization
A major strength of RDBMS SQL queries are declarative Optimizer figures out how to answer them
Re-order operations Pick among alternatives of one operation Ensure that the answer is correct!
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Transaction
A key concept in databases An atomic sequence of actions (read/write) Brings DB from a consistent state to another ACID
Atomicity Consistency Isolation Durability
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Concurrency Control & Recovery
Concurrency Control Essential for good DBMS performance Run several user programs concurrently Interleave actions of different users Ensure the correctness
• Users may think it is a single-user system.
Recovery Essential for durability of transactions
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RDBMS Features
Effective and efficient access Easier application development Data independence Data integrity and security Concurrent access Recovery from crashes Uniform data administration
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Summary
DBMS used to maintain, query large datasets. Benefits include recovery from system crashes,
concurrent access, quick application development, data integrity and security.
Levels of abstraction give data independence. A DBMS typically has a layered architecture. DBAs hold responsible jobs and are well-paid! DBMS R&D is one of the broadest, most exciting areas in CS.