Functionality of a DBMS

Slides adapted from Rao (ASU) & Franklin (Berkeley)

Functionality of a DBMS• Data Dictionary Management• Storage management

– Data storage Definition Language (DDL)• High level query and data manipulation language

– SQL/XQuery etc.– May tell us what we are missing in text-based search

• Efficient query processing– May change in the internet scenario

• Transaction processing• Resiliency: recovery from crashes,• Different views of the data, security

– May be useful to model a collection of databases together• Interface with programming languages


Building an Application with a Database System

• Requirements modeling (conceptual, pictures)– Decide what entities should be part of the application and

how they should be linked.• Schema design and implementation

– Decide on a set of tables, attributes.– Define the tables in the database system.– Populate database (insert tuples).

• Write application programs using the DBMS– Now much easier, with data management API


ssn

address name field

Professor

Advises

Takes

Teaches

CourseStudent

name category

quarter

name

Conceptual Modeling


Data Models• A data model is a collection of concepts for

describing data.

• A schema is a description of a particular collection of data, using a given data model.

• The relational model of data is the most widely used model today.– Main concept: relation, basically a table with rows and

columns.– Every relation has a schema, which describes the columns, or

fields.


Levels of Abstraction

• Views describe how users see the data.

• Conceptual schema

defines logical structure

• Physical schema describes the files and indexes used.

Physical Schema

Conceptual Schema

View 1 View 2 View 3

DB


Example: University Database• Conceptual schema:

– Students(sid: string, name: string, login: string, age: integer, gpa:real)

– Courses(cid: string, cname:string, credits:integer)

• External Schema (View): – Course_info(cid:string,enrollment:in

teger)

• Physical schema:– Relations stored as unordered files. – Index on first column of Students.

Physical Schema

Conceptual Schema


DB

If five people are asked to come up with a schema for the data, what are the odds that they will come up with the same schema?


Data Independence• Applications insulated from

how data is structured and stored.

• Logical data independence: Protection from changes in logical structure of data.

• Physical data independence: Protection from changes in physical structure of data.

• Q: Why are these particularly important for DBMS?

Physical Schema

Conceptual Schema


DB


Schema Design & Implementation

• Table Students

• Separates the logical view from the physical view of the data.

Student Course Quarter

Charles CS 444 Fall, 1997

Dan CS 142 Winter,1998

… … …


Terminology

tuples

Attribute names Students

(Arity=3)

Student Course Quarter

Charles CS 444 Fall, 1997

Dan CS 142 Winter,1998

… … …


Querying a Database

• Find all the students taking CSE594 in Q1, 2004

• S(tructured) Q(uery) L(anguage)select E.namefrom Enroll Ewhere E.course=CS490i and E.quarter=“Winter, 2000”

• Query processor figures out how to answer the query efficiently.


Example: Projection Onto SSN, Name

EmployeeSSN Name DepartmentID Salary999999999 John 1 30,000777777777 Tony 1 32,000888888888 Alice 2 45,000

SSN Name999999999 John777777777 Tony888888888 Alice


Cartesian Product X • Binary Operation• Result is set of tuples

combining all elements of R1 with all elements of R2, for R1 R2

• Schema is union of Schema(R1) & Schema(R2)

• Notice we could do selection on result to get meaningful info!

3/19/2001 12:13 PM 14Copyright © 2000 D.S.Weld (modified by Rao)

EmployeeName SSNJohn 999999999Tony 777777777DependentsEmployeeSSN Dname999999999 Emily777777777 Joe

Employee_DependentsName SSN EmployeeSSN DnameJohn 999999999 999999999 EmilyJohn 999999999 777777777 JoeTony 777777777 999999999 EmilyTony 777777777 777777777 Joe

Cartesian Product Example


EmployeeName SSNJohn 999999999Tony 777777777DependentsEmployeeSSN Dname999999999 Emily777777777 Joe

Employee_DependentsName SSN EmployeeSSN DnameJohn 999999999 999999999 EmilyJohn 999999999 777777777 JoeTony 777777777 999999999 EmilyTony 777777777 777777777 Joe

Cartesian Product Example


Join• Most common (and exciting!) operator…• Combines 2 relations

– Selecting only related tuples• Result has all attributes of the two relations• Equivalent to

– Cross product followed by selection followed by Projection• Equijoin

– Join condition is equality between two attributes• Natural join

– Equijoin on attributes of same name– result has only one copy of join condition attribute


Example: Natural JoinEmployeeName SSNJohn 999999999Tony 777777777DependentsSSN Dname999999999 Emily777777777 Joe

Employee DependentsEmployee_DependentsName SSN DnameJohn 999999999 EmilyTony 777777777 Joe


Complex Queries

Product ( pname, price, category, maker)Purchase (buyer, seller, store, prodname)Company (cname, stock price, country)Person( per-name, phone number, city)

Find phone numbers of people who bought gizmos from Fred.

Find telephony products that somebody bought


Exercises Product ( pname, price, category, maker)Purchase (buyer, seller, store, prodname)Company (cname, stock price, country)Person( per-name, phone number, city)

Ex #1: Find people who bought telephony products.Ex #2: Find names of people who bought American productsEx #3: Find names of people who bought American products and did not buy French productsEx #4: Find names of people who bought American products and they live in Seattle.Ex #5: Find people who bought stuff from Joe or bought products from a company whose stock prices is more than $50.


SQL IntroductionStandard language for querying and manipulating data

Structured Query Language

Many standards out there: SQL92, SQL2, SQL3, SQL99Vendors support various subsets of these

(but we’ll only discuss a subset of what they support)Basic form = syntax on relational algebra (but many other features too)

Select attributes From relations (possibly multiple, joined) Where conditions (selections)


Selections s SELECT * FROM Company WHERE country=“USA” AND stockPrice > 50

You can use: Attribute names of the relation(s) used in the FROM. Comparison operators: =, <>, <, >, <=, >= Apply arithmetic operations: stockprice*2 Operations on strings (e.g., “||” for concatenation). Lexicographic order on strings. Pattern matching: s LIKE p Special stuff for comparing dates and times.


Projection p

SELECT name AS company, stockprice AS price FROM Company WHERE country=“USA” AND stockPrice > 50

SELECT name, stock price FROM Company WHERE country=“USA” AND stockPrice > 50

Select only a subset of the attributes

Rename the attributes in the resulting table


Ordering the Results

SELECT name, stock price FROM Company WHERE country=“USA” AND stockPrice > 50 ORDERBY country, name

Ordering is ascending, unless you specify the DESC keyword.

Ties are broken by the second attribute on the ORDERBY list, etc.


Join

SELECT name, store FROM Person, Purchase WHERE per-name=buyer AND city=“Seattle” AND product=“gizmo”

Product ( pname, price, category, maker)Purchase (buyer, seller, store, product)Company (cname, stock price, country)Person( per-name, phone number, city)


Tuple Variables

SELECT product1.maker, product2.maker FROM Product AS product1, Product AS product2 WHERE product1.category = product2.category AND product1.maker <> product2.maker

Product ( name, price, category, maker)

Find pairs of companies making products in the same category


Defining Views(Virtual) Views are relations, except that they are not physically stored.

They are used mostly in order to simplify complex queries andto define conceptually different views of the database to differentclasses of users.

View: purchases of telephony products:

CREATE VIEW telephony-purchases AS SELECT product, buyer, seller, store FROM Purchase, Product WHERE Purchase.product = Product.name AND Product.category = “telephony”


A Different ViewCREATE VIEW Seattle-view AS

SELECT buyer, seller, product, store FROM Person, Purchase WHERE Person.city = “Seattle” AND Person.name = Purchase.buyer

We can later use the views: SELECT name, store FROM Seattle-view, Product WHERE Seattle-view.product = Product.name AND Product.category = “shoes”

What’s really happening when we query a view??


Updating ViewsHow can I insert a tuple into a table that doesn’t exist?

CREATE VIEW bon-purchase AS SELECT store, seller, product FROM Purchase WHERE store = “The Bon Marche”

If we make the following insertion:

INSERT INTO bon-purchase VALUES (“the Bon Marche”, Joe, “Denby Mug”)

We can simply add a tuple (“the Bon Marche”, Joe, NULL, “Denby Mug”)to relation Purchase.


Non-Updatable Views

CREATE VIEW Seattle-view AS SELECT seller, product, store FROM Person, Purchase WHERE Person.city = “Seattle” AND Person.name = Purchase.buyer

How can we add the following tuple to the view?

(Joe, “Shoe Model 12345”, “Nine West”)

Given Purchase (buyer, seller, store, product) Person( name, phone-num, city)


Materialized Views• Views whose corresponding queries have been executed

and the data is stored in a separate database– Uses: Caching

• Issues– Using views in answering queries

• Normally, the views are available in addition to database– (so, views are local caches)

• In information integration, views may be the only things we have access to. – An internet source that specializes in woody allen movies can be seen as a view

on a database of all movies. Except, there is no database out there which contains all movies..

– Maintaining consistency of materialized views


Query Optimization

Imperative query execution plan:Declarative SQL query

Ideally: Want to find best plan. Practically: Avoid worst plans!

Goal:

(Simple Nested Loops)

Purchase Person

Buyer=name

City=‘seattle’ phone>’5430000’

buyer

s

(Table scan) (Index scan)

SELECT S.buyerFROM Purchase P, Person QWHERE P.buyer=Q.name AND Q.city=‘seattle’ AND Q.phone > ‘5430000’

Inputs:• the query• statistics about the

data (indexes, cardinalities, selectivity factors)

• available memory

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Functionality of a DBMS