Chapter 1: Introduction - CS-People by full name

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Transcript Chapter 1: Introduction - CS-People by full name

CAS CS 460
Introduction to Database Systems
Thanks to Prof. George Kollios, Boston University and
Prof. Mitch Cherniack Brandeis University for lecture materials
About the course – Administrivia
 Instructor:
 Ravi Kothuri, [email protected]
Office, Hours: MCS 147, Mon/Wed 5-6PM and 7:30-8PM
 Teaching Fellow:
 Panagiotis Papapetrou, [email protected]
MCS 147, Tue/Thu 11 - 12:30 AM
 Home Page:
 http://www.cs.bu.edu/rkothuri
Check frequently! Syllabus, schedule, assignments,
announcements…
1.2
Grading
 Homeworks: 20%
 4-5 assignments
 Midterm 20%
 Final 30%
 Projects 30%
 5-6 parts
1.3
My Background
 Oracle Corporation
 PhD from University of California, Santa Barbara
 Research:
 Multi-dimensional indexing
 Mobile Databases
 Spatial, GIS systems and CAD/CAM databases
 Google Maps type of technologies for Enterprise
 Geometric algorithms for terrain management, city modeling,…
 Data Mining (spatial, financial, …)
 RFID technologies
 Semantic –web (RDF) technologies
 Book: “Pro Oracle Spatial”, Nov 2004
 Teaching on invitation from Prof. George Kollios
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Who uses Databases?
 Universities (records for students, faculty, courses,…
 Airlines (passengers, flights, luggage, …)
 Banking (customers, loans, …)
 Utilities (customers, usage history, bills); e.g. telecom, electric,..
 Any Company: human resources
 Employees, depts, facilities,…
“Data is the primary and integral part of information industry. Proper
management of the data using database technology is essential
for any large-scale company, organization.’’
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What is a Database System?
 Database:
A very large collection of related data
 Models a real world enterprise:
 Entities (e.g., teams, games / students, courses)
 Relationships (e.g., The Patriots are playing in the
Superbowl)
 Even active components (e.g. “business logic”)
 DBMS: A software package/system that can be used
to store, manage and retrieve data form databases
 Database System: DBMS+data (+ applications)
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Why Study Databases??
 Shift from computation to information
 Always true for corporate computing
 More and more true in the scientific world
 and of course, Web
 DBMS encompasses much of CS in a practical discipline
 OS, languages, theory, AI, logic
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Managing data: A naïve approach
 Why not store everything on flat files: use the file system of the
OS, cheap/simple…
Name, Course, Grade
John Smith, CS112, B
Mike Stonebraker, CS234, A
Jim Gray, CS560, A
John Smith, CS560, B+
…………………
 Yes, but not scalable…
 Filesize limitations, access/update performance is slow,..
1.8
Problem 1
 Data redundancy and inconsistency
 Multiple file formats, duplication of information in different files
(say, in different departments)
John Smith, [email protected], CS112, B
John Smith, Arts560, [email protected], B+
Smith J, [email protected], Math212, A
Why is this a problem?
 Wasted space
 Potential inconsistencies (multiple formats, John
Smith vs Smith J.)
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Problem 2
 Data retrieval:
 Find the students who took CS560
 Find the students with GPA > 3.5
For every query we need to write a program!
 Need a Query/Retrieval engine that can support
different ways to access data
 Easy to write
 Execute efficiently
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Problem 3
 Data Integrity
 No support for sharing:
 Prevent simultaneous modifications
 No coping mechanisms for system crashes
 No means of Preventing Data Entry Errors (checks must be hard-coded
in the programs)
 Security problems
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Database Systems
 Database systems offer solutions to all the mentioned problems
 Database systems:
 Support Modeling of the data
 Provide Levels of Abstraction of the data
 Provide programs to allow you to Retrieve/modify the data
 SQL
• For easy, standard specification of queries
 Query Optimizer
• To process your queries efficiently
 Ensure Integrity Maintenance
 Transaction Manager/Recovery Manager
• to ensure atomicity/integrity in concurrent transactions
• to ensure integrity after system crashes)
 …………….
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Database Systems
 Data Modeling
 Levels of Abstraction
 Data Retrieval
 Data Modification/Integrity Maintenance
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Data Model
 A framework for describing
 data
 data relationships
 data semantics
 data constraints
 Entity-Relationship model (Ch. 6)
 A set of entities to model real-world objects
 Relationships among entities
 Relational model
 Data as a set (or sets) of “records” or “tuples”
 Each tuple in the set has the same set of attributes
 Other models:
 object-oriented model: inheritance, abstraction,…
 semi-structured data models, XML: tuples in a set can have
different attributes
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Entity-Relationship Model
Example of schema in the entity-relationship model
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Entity Relationship Model (Cont.)
 E-R model of real world
 Entities (objects)
 E.g. customers, accounts, bank branch
 Relationships between entities
 E.g. Account A-101 is held by customer Johnson
 Relationship set depositor associates customers with accounts
 Widely used for database design
 Database design in E-R model usually converted to design in the
relational model (coming up next) which is used for storage and
processing
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Relational Model
Attributes
 Example of tabular data in the relational model
Customer-id
customername
192-83-7465
Johnson
019-28-3746
Smith
192-83-7465
Johnson
321-12-3123
Jones
019-28-3746
Smith
customerstreet
customercity
accountnumber
Alma
Palo Alto
A-101
North
Rye
A-215
Alma
Palo Alto
A-201
Main
Harrison
A-217
North
Rye
A-201
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Database Systems
 Data Modeling
 Levels of Abstraction
 Data Retrieval
 Data Modification/Integrity Maintenance
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Levels of Abstraction
 Data storage Involves Complex data structures
 Hide complexity from users
 Abstract views of the data (e.g., for storing a customer record)
 Physical level: how a customer record is stored as
bytes/words on disk
• Mostly hidden from database users/programmers
 Logical level: describes “types” inside the database
type customer = record
name : string;
street : string;
city : integer;
ssn; integer;
end;
 View level: application programs hide details of data types.
Views can also hide information (e.g., ssn) for security purposes.
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View of Data
A logical architecture for a database system
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Physical Level: Data Organization
 Data Storage (Ch 11)
Where can data be stored?
 Main memory
 Secondary memory (hard disks)
 Optical store
 Tertiary store (tapes)
 Move data? Determined by buffer manager
 Mapping data to files? Determined by file manager
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Database Architecture
(physical level data organization)
DBA
DDL Commands
DDL Interpreter
File Manager
Buffer Manager
Storage Manager
Data
Secondary Storage
Metadata
Schema
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Database Systems
 Data Modeling
 Levels of Abstraction
 Data Retrieval
 Data Modification/Integrity Maintenance
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Data retrieval
 Queries (Ch 3, 4)
Query = Declarative data retrieval
describes what data, not how to retrieve it
Ex. Give me the students with GPA > 3.5
vs
Scan the student file and retrieve the records with gpa>3.5
 Why?
1. Easier to write
2. Efficient to execute
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Data retrieval
Query
Query Processor
Plan
Query Optimizer
Query Evaluator
Data
 Query Optimizer
“compiler” for queries (aka “DML Compiler”)
Plan ~ Assembly Language Program
Optimizer Does Better With Declarative Queries:
1. Algorithmic Query (e.g., in C) 1 Plan to choose from
2. Declarative Query (e.g., in SQL) n Plans to choose from
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Specifying the Query using SQL
 SQL: widely used (declarative) non-procedural language
 E.g. find the name of the customer with customer-id 192-83-7465
select customer.customer-name
from customer
where customer.customer-id = ‘192-83-7465’
 E.g. find the balances of all accounts held by the customer with
customer-id 192-83-7465
select account.balance
from depositor, account
where depositor.customer-id = ‘192-83-7465’ and
depositor.account-number = account.account-number
 Procedural languages: C++, Java, relational algebra
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Data retrieval:
Indexing (Ch 12)
 How to answer fast the query: “Find the student with SID = 101”?
 One approach is to scan the student table, check every student, retrurn
the one with id=101… very slow for large databases
 Any better idea?
1st keep student record over the SID. Do a binary search…. Updates…
2nd Use a dynamic search tree!! Allow insertions, deletions, updates and at the
same time keep the records sorted! In databases we use the B+-tree (multiway
search tree)
3rd Use a hash table. Much faster for exact match queries… but cannot support
Range queries. (Also, special hashing schemes are needed for dynamic data)
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180
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156
179
120
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100
101
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30
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3
5
11
180
150
100
30
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B+Tree Example
B=4
Root
Database Architecture
(data retrieval)
DB Programmer
User
Code w/ embedded queries
DBA
Query
DDL Commands
Query Optimizer
DML Precompiler
Query Evaluator
Query Processor
File Manager
Storage Manager
Buffer Manager
Secondary Storage
Indices
Data
Statistics
Metadata
Schema
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DDL Interpreter
Database Systems
 Data Modeling
 Levels of Abstraction
 Data Retrieval
 Data Modification/Integrity Maintenance
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Data Integrity
Transaction processing (Ch 15, 16)
 Why Concurrent Access to Data must be Managed?
John and Jane withdraw $50 and $100 from a common
account…
John:
1. get balance
2. if balance > $50
3. balance = balance - $50
4. update balance
Jane:
1. get balance
2. if balance > $100
3. balance = balance - $100
4. update balance
Initial balance $300. Final balance=?
It depends…
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Data Integrity
Recovery (Ch 17)
Transfer $50 from account A ($100) to account B ($200)
1. get balance for A
2. If balanceA > $50
3. balanceA = balanceA – 50
4.Update balanceA in database
5. Get balance for B
System crashes….
6. balanceB = balanceB + 50
7. Update balanceB in database
Recovery management
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Database Architecture
DB Programmer
DBA
User
Code w/ embedded queries
DDL Commands
Query
Query Optimizer
DML Precompiler
Query Evaluator
Query Processor
File Manager
Transaction Manager
Recovery Manager
Buffer Manager
Storage Manager
Secondary Storage
DDL Interpreter
Indices
Data
Metadata
Integrity Constraints
Statistics
Schema
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Outline
 1st half of the course: application-oriented
 How to develop database applications: User + DBA
 2nd part of the course: system-oriented
 Learn the internals of a relational DBMS (Oracle..)
 Last few lectures on Oracle-specific features such as XDB….
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