20-Jan - SEAS - University of Pennsylvania

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Server Architectures and Web Servers
Zachary G. Ives
University of Pennsylvania
CIS 455 / 555 – Internet and Web Systems
January 20, 2010
Today
 Brief discussion of the Butler Lampson paper handed
out on Monday
 Server architecture (internal)
 If time: Web (HTTP) servers
 Read:
 “HTTP Made Really Easy” link on the Schedule page
 Krishnamurthy / Rexford Ch 4 (handed out)
2
Some Context
 To this point, you’ve probably had significant
experience designing programs to solve specific,
relatively small tasks
 It’s often a very difficult job to build a system
 (What is a computing system?)
 (Why is it harder to build?)
 We will consider in this course:
 Architectural aspects [Butler Lampson article]
 Algorithmic aspects [e.g., two-phase commit]
 Engineering aspects [e.g., build management]
3
Butler Lampson
(Abbreviated Biography from His Page)
 Butler Lampson is an Architect at Microsoft Corporation and
an Adjunct Professor of Computer Science and Electrical
Engineering at MIT.
 He was one of the designers of the SDS 940 time-sharing
system, the Alto personal distributed computing
system, the Xerox 9700 laser printer, two-phase commit
protocols, ...
 He received the ACM’s Software Systems Award in 1984 for
his work on the Alto, the IEEE Computer Pioneer award in
1996, and the Turing Award in 1992.
4
Historical Note: Xerox Alto
1972-78
 Personal computer for
research
 The first GUI-based
computer (note the mouse!)
 128KB RAM, 2.5MB hard disk
 Ethernet
In many ways, the forerunner
to the Xerox Star
 … Which begat the Apple
Lisa, and the rest is history!
5
Lampson’s Advice
6
Designing Servers: Systems for
Handling Many Client Requests
Major issues:
 Concurrency
 How do we handle multiple simultaneous requests?
 Statefulness and sessions
 Are requests self-contained, or do they require the server to
keep around state?
 Communication and consistency
 What state is shared across requests?
 Do all requests need the same view?
 … And, of course, security!!!
(Note that servers today are typically replicated)
7
Toy Example
 Suppose we want to build an “arithmetic” server





Takes a request for a computation
Parses the computation request
Performs the computation
Generates an HTML document with the result
Returns the result to the requestor
 Suppose we can build on TCP…
8
Concurrency
One approach: a separate server for each request
 Obviously this doesn’t work
Alternative: context-switching using shared resources
One, or a few, CPUs/disks/etc., multiplexing across
jobs





Threads and processes
Events
Cooperative scheduling
Thread pools
Staged events
9
Review: Threads and Processes
 Threads/processes are each written as if they are
sequential programs
 But threads may also yield or wait on condition variables
 Preemptive switching, based on time slicing
according to quanta (usu. 10-100msec)
 States of threads: ready, running, and blocked
 Different levels of sharing and overhead between the
two
10
Example with Threads
 “Arithmetic” server divided into several components
 Daemon thread:
 Takes a request for a computation
 Parses the computation request
 Handler thread invoked on the results:
 Performs the computation
 Generates an HTML document with the result
 Returns the result to the requestor
11
Necessary Java Constructs
 Each handler may subclass Thread
 Implement the run() method
 Invoke via Handler h = new Handler(); h.start()
 Or the handler may implement Runnable
 Implement the run() method
 Invoke via Thread t = new Thread(myHandler); t.start()
12
Shared Resources
 Suppose we share a resource such as an output
logfile across threads
 How do we ensure that each thread’s modifications
to the file are compatible (e.g., log interleaves one
status msg at a time)?
 For shared resources, use synchronized to gain a monitor
on an object to be “locked”
 synchronized methods lock the entire object
 synchronized (obj) { … } blocks lock their argument
13
Issues with Threads and Shared
Resources
 Deadlock: nothing happens because locks are held
in a way that all threads are waiting on other threads
 Livelock: system grinds to a halt because each
thread is responding to requests from the other
threads, but not making progress
 Starvation: a thread never gets scheduled
14
Event Handlers
 Basically, a programmer-specified way of breaking up
tasks
 You’ve probably seen it if you’ve done any sort of GUI
programming
 But it’s also used to multitask
 Based on an event queue and a notion of an event
handler loop
 Each task is broken into a series of events
 Each event has a handler that does some work and
potentially enqueues another event
 “Local state” is generally kept in the event
15
Shared Resources in Event
Handlers
 Generally don’t need true synchronized blocks or
the equivalent here
 We control when each event handler gives up a resource,
hence we control interleaving of requests and their
modification to shared resource
 But still may need to maintain flags or other
information for situations when a resource is used
across events
16
Example with Events
17
Thread Pools
 Very commonly used (e.g., in many Apache products
including some versions of the Web server)
 Fixed number of threads – say 100 or 200
 As requests come in, they’re put onto a queue
 Handler threads dequeue items and process them
18
A Key Aspect of the Thread Pool:
the Queue
 The daemon thread doesn’t spawn threads: instead,
it enqueues requests
 The handler threads dequeue and handle requests
 What to do when the system is not fully saturated,
i.e., some threads in the pool are idle?
 object.wait(), notify(), notifyAll()
 MUST use these when a synchronized on the object!
19
Example with Thread Pools
20
Other Ideas
 Cooperative scheduling
 “Non-preemptive multitasking”: threads execute for a
while, save state, and explicitly yield
 Examples of where used: old Mac OS, Windows 2.x
 Why is it bad?
 Staged events (SEDA – Welsh, UCB)
 Tasks are broken into explicit sub-components with
different triggering events
 Better for cache behavior, etc.
 Scales to thousands of tasks
21
Concurrency and Debugging
 A critical issue: how do we debug concurrent apps?
 Consider:
 Threads – pros and cons
 Events – pros and cons
 There’s no free lunch!
22
Statefulness and Sessions
Very early HTTP
 Essentially stateless
 Make a request; the response is a page that is named by the URL
More recent HTTP, and other protocols:
 Some amount of state is maintained
 In HTTP, this requires cookies (more later)
 In many other protocols, the connection is kept open and all state is
preserved on both ends
Pros and cons of statefulness?
 (Does this look at all like the threads vs. events discussion?)
23
Communication and Consistency
 A key question: how much interaction is there
among server processes / requests?
 Let’s consider:





Amazon.com
EBAY
Blogger.com
iTunes
Google
24
Shared, Persistent State
 Generally a database back-end
 Recovery and reliability features
 Transaction support
 Simple query interface
 Often the database is on a different server from the
executing code
AJAX game
 This is what Enterprise JavaBeans are
designed to support: distributed
 transactions
 “Model view controller” pattern
is the most common
Controller
Client-side
JScript
View
XML view
Model
Database
25
Web (HTTP) Servers
 Processes HTTP requests,
generally over TCP Port 80
HTTP
request
 Response uses another port
Port 80
Processing
Response Other port
 May involve:
 Returning a document, with
its (MIME) type info
 e.g., HTML document, TXT
document
 Invoking a program or
module, returning its output
 Submitting form data to a
program or module,
returning its output
 Resources are described
using URLs
26
The URL
URL: Uniform Resource Locator
 A way of encoding protocol, login, DNS (or IP) address,
path info in one string
 Special case of Uniform Resource Identifer (URI)
URL is a URI for a location from which something can be retrieved
URN is a URI for a name
General syntax:




{partition/protocol}://{userid}:{password}@{domain:port}/{path}
http://me:too@my.com/index.html
news://nntp.upenn.edu
imap://email:me@my.com/folder1
27
Handling a Web (HTTP) Request
1. Read and parse the request message

Most commonly, GET the contents of a URL
2. Translate the URL


Extract the “path” that is being requested
Determine if this is:



A “virtual directory” that’s an alias for something else
A reference to a file (HTML or SSI)
A reference to a script or servlet
3. Verify authorization / access rights
4. Generate the response (may be an error code)
28
HTTP: HyperText Transfer Protocol
A very simple, stateless protocol for sessionless
exchanges
 Browser creates a new connection each time it wants to
make a new request (for a page, image, etc.)
 What are the benefits of this model? Drawbacks?
Exceptions:
 HTTP 1.1 added optional support for persistent
connections and pipelining
 Clients + servers might keep state information
 Cookies provide a way of recording state
29
HTTP Overview
Requests:
 A small number of request types (GET, POST, PUT,
DELETE)
 Request may contain additional information, e.g. client
info, parameters for forms, etc.
Responses:
 Response codes: 200 (OK), 404 (not found), etc.
 Metadata: content’s MIME type, length, etc.
 The “payload” or data
30
A Simple HTTP Request
GET /~cis455/index.html HTTP/1.1
If-Modified-Since: Sun, 7 Jan 2007 11:12:23 GMT
Referer: http://www.cis.upenn.edu/index.html
 Requests data at a path using HTTP 1.1 protocol
 Example response:
HTTP/1.1 200 OK
Date: Sun, 7 Jan 2007 11:12:26 GMT
Last-Modified: Wed, 14 Jan 2004 8:30:00 GMT
Content-Type: text/html
Content-Length: 3931
…
31
Request Types
GET
Retrieve the resource at a URL
PUT
Publish the specified data at a URL
DELETE
(Self-explanatory; not always supported)
POST
Submit form content
32
Forms: Returning Data to the Server
 HTML forms allow assignments of values to variables
 Two means of submitting forms to apps:
 GET-style – within the URL:
GET /home/my.cgi?param=val&param2=val2
 POST-style – as the data:
POST /home/second.cgi
Content-Length: 34
searchKey Penn
where www.google.com
33
Authentication and Authorization
 Authentication
 At minimum, user ID and password – authenticates requestor
 Client may wish to authenticate the server, too!
 SSL (we’ll discuss this more later)
 Part of SSL: certificate from trusted server, validating machine
 Also: public key for encrypting client’s transmissions
 Authorization
 Determine what user can access
 For files, applications: typically, access control list
 If data from database, may also have view-based security
 We’ll talk about these in more detail later in the semester
34
Programming Support in Web Servers
 Several means of supporting custom code:
 CGI – Common Gateway Interface – the oldest:
 A CGI is a separate program, often in Perl, invoked by the server
 Certain info is passed from server to CGI via Unix-style
environment variables
 QUERY_STRING; REMOTE_HOST, CONTENT_TYPE, …
 HTTP post data is read from stdin
 Interface to persistent process:
 In essence, how communication with a database is done – Oracle
or MySQL is running “on the side”
 Communicate via pipes, APIs like ODBC/JDBC, etc.
 Server module running in the same process
35
Two Main Types of Server Modules
 Interpreters:
 JavaScript/JScript, PHP, ASP, …
 Often a full-fledged programming language
 Code is generally embedded within HTML, not stand-alone
 Custom runtimes/virtual machines:
Most modern Perl runtimes; Java servlets; ASP.NET
A virtual machine runs within the web server process
Functions are invoked within that JVM to handle each request
Code is generally written as usual, but may need to use HTML to
create UI rather than standard GUI APIs
 Most of these provide (at least limited) protection mechanisms




36
Interfacing with a Database
A very common operation:
 Read some data from a database, output in a web form
 e.g., postings on Slashdot, items for a product catalog, etc.
Three problems, abstracted away by
ODBC/ADO/JDBC:
 Impedance mismatch from relational DBs to objects in Java
(etc.)
 Standard API for different databases
 Physical implementation for each DB
37
(Cross-)Session State: Cookies
 Major problem with sessionless nature of HTTP:
how do we keep info between connections?
 Cookie: an opaque string associated with a web site,
stored at the browser
 Create in HTTP response with “Set-Cookie: xxx”
 Passed in HTTP header as “Cookie: xxx”
 Interpretation is up to the application
 Usually, object-value pairs; passed in HTTP header:
 Cookie: user=“Joe” pwd=“blob” …
 Often have an expiration
 Very common: “session cookies”
38
Common Web Server Architectures
 How do we handle many concurrent requests?
 Approach 1 – use what the OS provides:
 Fork a separate process for each request
 Or spawn a separate thread
 Approach 2 – write your own task switcher
 Break every response into small steps
 Schedule with custom event-driven dispatcher
 Approach 3 – pool of handlers:
 Create a thread pool that switches among requests or steps
39
Content Management Systems
 Generally, a “middleware” that runs under the web
server (or provides its own)
 Provides content integration from multiple sources
 Perhaps SQL or XML databases
 Perhaps text files, RSS feeds, etc.
 Often provides content authoring & assembly tools
 Typically, provides templates or other similar features for
describing how to assemble the site
 Common examples:
 MS Content Management Server; Slash; Apache Cocoon
40
Ways of Handling Many Requests
 Web server “listens” on port 80 – “daemon” task
 Upon a request, it needs to invoke a response
 How should that response task get executed?
41
Readings
 Please read for further depth:
 “HTTP Made Really Easy”
 Rexford/Krishnamurthy chapter on HTTP servers
 You will need to learn:
 Enough about HTTP to handle GET, POST, cookies, etc.
 Enough about Java threads to write your own thread
pools for a Web server
 Enough about servlets to run them (including sessions)
42
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