CS162 Discussion Notes
March 31, 2011
Jorge Ortiz
ACKNOWLEDGEMENTS
Paul A. Strassmann, George Mason University
Rightscale.com
Kirk Anne, SUNY Geneseo
Randy Katz, UC Berkeley
Outline
• Cloud computing
– What is it?
• Virtualization
– Hypervisor configurations
• Amazon EC2
• Relational databases
– Entity relationship diagrams
• Data models
– Imperative versus declarative
• SQL
What is cloud computing?
• Cloud computing is Internet-based computing,
whereby shared resources, software and
information are provided to computers and
other devices on-demand, like electricity
– Wikipedia
Data Centers
Google’s
Containerized
Datacenter
Microsoft
Chicago
Datacenter
6
What runs on these machines?
• All types of applications!
• How can we make best
use of the resources?
Virtualization (2)
Virtualization (3)
Amazon EC2 Architecture
Applications
•
•
•
•
Web applications
Databases
Compute-intensive jobs
Client-Server applications
– Project 3!
• Chat Server will be in the cloud
• Clients will be outside the cloud
• Application state stored in database
Parts of a database
Record
Tables
Attribute/Field
• Records become “rows”
• Attributes/fields become “columns”
• Rules determine the relationship
between the tables and tie the data
together to form a database
Basic SQL Commands
•
•
•
•
•
•
Creating tables with CREATE
Adding data with INSERT
Viewing data with SELECT
Removing data with DELETE
Modifying data with UPDATE
Destroying tables with DROP
Creating tables with CREATE
• Generic form
CREATE TABLE tablename (
column_name data_type attributes…,
column_name data_type attributes…,
…
)
• Table and column names can’t have spaces or be
“reserved words” like TABLE, CREATE, etc.
Phone Book/Contact Table
CREATE TABLE contacts (
Name
VARCHAR(40),
Address
VARCHAR(60),
Company
VARCHAR(60),
Phone
VARCHAR(11),
URL
VARCHAR(80),
Age
INT,
Height
FLOAT,
Birthday
DATE,
WhenEntered
TIMESTAMP
);
Plan your tables very carefully!
Once created, they are difficult to change!
Data Types
• Binary
– Database specific binary objects (BLOB)
• Boolean
– True/False values (BOOLEAN)
• Character
– Fixed width (CHAR) or variable size (VARCHAR)
• Numeric
– Integer (INT), Real (FLOAT), Money (MONEY)
• Temporal
– Time (TIME), Date (DATE), Timestamp (TIMESTAMP)
Adding data with INSERT
• Generic Form
INSERT INTO tablename (column_name,…)
VALUES (value,…)
Inserting a record into ‘contacts’
INSERT INTO contacts
(contactid,name,address,company,phone,url,a
ge,height,birthday,whenentered)
VALUES
(1,‘Joe’,’123 Any St.’,’ABC’,
’800-555-1212’,‘http://abc.com’,30,1.9,
’6/14/1972’,
now());
Inserting a partial record
INSERT INTO contacts (contactid,name,phone)
VALUES (2,’Jane’,’212-555-1212’);
Automatic key generation
• CREATE SEQUENCE contactidseq;
• Change the ContactID line in the
CREATE TABLE to:
ContactID INT DEFAULT nextval(‘contactidseq’) PRIMARY KEY
• Or when inserting into a table
INSERT contacts (contactid,name,phone)
VALUES (nextval(‘contactidseq’),’Jack’,
‘716-555-1212’);
Viewing data with SELECT
• Generic Form
SELECT column,… FROM table,…
WHERE condition
GROUP BY group_by_expression
HAVING condition
ORDER BY order_expression
• The most used command
• Probably the most complicated also
• If used improperly, can cause very long waits because
complex computations
A few simple SELECTs
• SELECT * FROM contacts;
– Display all records in the ‘contacts’ table
• SELECT contactid,name FROM contacts;
– Display only the record number and names
• SELECT DISTINCT url FROM contacts;
– Display only one entry for every value of URL.
Refining selections with WHERE
• The WHERE “subclause” allows you to select
records based on a condition.
• SELECT * FROM contacts
WHERE age<10;
– Display records from contacts where age<10
• SELECT * FROM contacts
WHERE age BETWEEN 18 AND 35;
– Display records where age is 18-35
Additional selections
• The “LIKE” condition
– Allows you to look at strings that are alike
• SELECT * FROM contacts
WHERE name LIKE ‘J%’;
– Display records where the name starts with ‘J’
• SELECT * FROM contacts
WHERE url LIKE ‘%.com’;
– Display records where url ends in “.com”
Removing data with DELETE
• Generic Form
DELETE FROM table WHERE condition;
DELETE FROM contacts WHERE age<13;
Modifying data with UPDATE
• Generic Form
UPDATE table SET column=expression
WHERE condition;
UPDATE contacts SET company=‘AOL’
WHERE company=‘Time Warner’;
Destroying tables with DROP
• Generic Form
DROP TABLE tablename;
DROP TABLE contacts;
Joining together tables
•
SELECT name,phone,zip FROM people,
phonenumbers, address WHERE
people.addressid=address.addressid AND
people.id=phonenumbers.id;
PhoneNumbers
PhoneID
Id
Phone
1
1
5532
2
1
2234
3
1
3211
4
2
3421
5
3
2341
6
3
6655
People
Id
Name
AddressID
1
Joe
1
2
Jane
2
3
Chris
3
Address
AddressID
Company Address
Zip
1
ABC
123
12345
2
XYZ
456
14454
3
PDQ
789
14423
GROUP BY/HAVING
• The “GROUP BY” clause allows you to group
results together with “aggregate functions”
– AVG(), COUNT(), MAX(), MIN(), SUM()
– COUNT DISTINCT
• HAVING allows you to search the GROUP BY
results
Important links
• http://aws.amazon.com/documentation/ec2/
• http://www.mysql.com/