Event-Driven Programming
Vivek Pai
Dec 4, 2001
GedankenEvents
Enron
– bad news all around
What
Korean
are these numbers: $1B, $100B, $80B, $200M
facts
Largest
on-line game has 3M+ subscribers
What’s the comparable figure for the US?
What are the populations of the two countries?
How
many albums does the Wu Tang Clan have?
What is Ginger?
2
A Random Aside
What do
these companies have in common
VA Linux, Penguin Computing
RLX Technologies, Fibercycle
HP, Compaq
Dell, IBM
3
Mechanics
Project 3
grading in progress
Project 4 grading in progress
All feedback questions answered
One mail dropped – extra project proposals
Speaking of which
We
need to agree on a one-page proposal
4
Project 5
Tyranny of
the majority
Several goals
Performance
improvement via caching
Dynamic adjustment to load
Master/slave or symmetric programming
Probably due
on Dean’s Date
Extra credit: 6 points (15 base)
5
Another Random Aside
You
may want to read
Flash: An
Efficient and Portable Web Server
Available from my home page
Caveat: far more
complicated than Project 5
6
Official Goals
Discuss the
difference between standard
programming styles and event-driven
programming
Show the difference between structuring servers
using processes and application-level
multiplexing
Discuss the benefits and drawbacks of each
approach
7
What Is An Event?
Some
kind of notification
Interrupts
Signals
Polling
(via poll/select/etc)
Callback (via function pointer)
Similarities?
8
“Reactive” Environments
Windowing systems
Network-aware programs
Drivers of
all sorts
9
Traditional Environments
One
thing going on at a time
Finish that thing, go on to next
Any step can block indefinitely
Resumption from blocking is simple – OS
provided
10
What Goes On In A Web Browser?
Drawing
the current page
Inline images
Translating
machine names to IP addresses
Launching connections
Sending requests
Getting piecemeal responses, drawing images
User
clicking to next link
11
Threads Versus Events
One
stack versus many stacks
What happens on blocking operations
Parallelism
Shared variables
State
12
Let’s Think Of States
How
many possible states are there?
Take
all pieces of information
Decide valid range for all pieces
Enumerate
Can
we reduce states?
Some
combinations invalid
Still, lots of states
13
Really Reducing States
Take all
major pieces of program
Add extra tags to state
What do tags look like?
Position
Count
#
14
State Examples
If-then-else
3
For
1
states: start, then-clause, else-clause
loop
state + count
Why do
we care?
Resuming
at the right state
15
Remember This Diagram?
Accept
Conn
Read
Request
Find
File
Send
Header
Read File
Send Data
end
16
Structure of Event-Driven
Programs
Lots of
state machines
Maintaining information about each one
Some way of moving through states
As few restrictions as possible on timing
17
The Real Structure
While (1)
Get event
Dispatch event
Or,
while loop in library
Event
handlers in main program
18
Delays
Are
delays possible?
Interrupt
handlers – generally not
Otherwise? Depends on event rate
How
to avoid delays?
More
events – asynchronous operations
What happens if no async support?
 Fake
it
19
Blocking Steps
Disk Blocking
Accept
Conn
Read
Request
Find
File
Send
Header
Read File
Send Data
end
Network Blocking
20
Overcoming Disk Blocking States
Accept
Conn
Read
Request
Find
File
Helper
Send
Header
Read File
Send Data
end
Helper
21
New Architecture - AMPED
Asymmetric Multiple Process Event Driven
Accept
Conn
Read
Request
Find
File
Send
Header
Read File
Send Data
Event Dispatcher
Helper 1
Helper 2
Helper N
Helpers are threads or processes
22
Caches in Flash Web Server
Accept
Conn
Read
Request
Find
File
Send
Header
Read File
Send Data
end
Pathname Response Mapped
Translation Header
File
Cache
Cache
Cache
Helper
Helper
23