Highly Scalable Web Applications

							Highly Scalable Web Applications
            Eli White
                Zend

           http://eliw.com/
                                  Scaling?


Enabling your application to grow as traffic grows


               Only do what you need but …
              Don't code yourself into a corner




  Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
                      Various aspects


                                   Web Server
                                   Database
                                   Caching




Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
               In the Beginning …


                            One Web Server:




Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
                       Load Balanced




Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
                 Numerous Options



     NetScaler


     DNS Rotation
     Apache Proxy                                                              BIG-IP
     Cloud Services

Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
                                Preparation
Ensure you don't preclude this, for example:
  If using local caching (APC / Zend Server / Other )
    Avoid assuming exclusive/single cache
  Don't rely on the filesystem
      Temporary files, Sessions, etc


If you do have code assuming one server: Encapsulate


    Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
                   Database Scaling


        Everyone starts with just one server:




 Multiple steps to take as you move forward



Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
         Step One: Master/Slave




Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
       Master/Slave Preparation



           Even with one server:
Make code write to master and read from slave




Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
                       Avoid Slave Lag


  Don't write code that would fail with slave lag:



$master->query('update users set comments += 1');
$slave->query('select comments from users');




   Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
     Step Two: Multiple Slaves




Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
   One Slave per Web Server?




                               Not as flexible

Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
       Better Solution: Random




Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
    Code to Select Random Slave
class DB {
    private static $cfg = array(
        'write' =>
            array('mysql:dbname=MyDB;host=10.1.2.3'),
        'read' =>
            array('mysql:dbname=MyDB;host=10.1.2.7',
                  'mysql:dbname=MyDB;host=10.1.2.8',
                  'mysql:dbname=MyDB;host=10.1.2.9');
        );

    public static function getConnection($pool) {
        $max = count(self::$cfg[$pool]) - 1;
        $dsn = self::$cfg[$pool][mt_rand(0, $max)];
        return new PDO($dsn, USER, PASS);
    }
}

$db = DB::getConnection('read');

    Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
         Step Three: Slave Pools


       Virtually divide your slaves into pools

      Use this to isolation high database load

            Potentially enhance query caches




Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
             Possible Pool Layout




Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
           Step Four: Partitioning



             Simplest Definition:
Break your tables or databases into smaller ones




 Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
                   Multiple Masters




Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
               Cons of Partitioning


         Loss of direct SQL support
         Increased Web Server / Application Load
         More complicated programming




Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
    Main Types of Partitioning


      Vertical                                                    Horizontal




                          Application Level



Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
                     Vertical Partitioning

“Moving various columns of your table into different tables”


Various methodologies:
●   Move rarely used columns into auxiliary table
●   Move often empty columns into auxiliary table
●   Move columns that are not used in where clauses


           Usually done within the same database/server

      Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
               Vertical Partitioning




Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
               Horizontal Partitioning

 “Moving various rows of your table into different tables”

Various methodologies:
●   Range Based
●   Date Based
●   Interlaced
●   User Based

 Can be done on one server, or break into multiple masters

     Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
          Horizontal Partitioning




Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
     Application Level Partitioning

“Moving various tables of your DB onto different servers”


Various methodologies:
●   Move single tables to specific servers
●   Move groups of related tables together to allow joining




     Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
Application Level Partitioning




Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
             Multiple Datacenters

    You thought worrying about slave lag was bad


    Data from multiple sources all needs integrated


                                    Good luck!




Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
             Brief Touch on Caching

                       Often considered performance


   Can absolutely be a scalability factor, especially when
         combined with smaller discrete DB queries


Allows you to get around DB scalability by ignoring the DB




    Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
                       Type of Caching

Single server memory caches
       For PHP: APC or Zend Server Data Cache
       Limited due to lack of sync'd cache


Distributed
       Memcached (Generic) or Zend Platform (PHP)
       Required for true scalability enhancement


   Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
           Caching Best Practices


Write through cache
Choose small, discrete, reusable data units
Don't store data you can't recreate
Store data in as close to final processed form




 Eli White — Highly Scalable Web Applications — Web Technology of Frederick Meetup — 9/8/2009
                      Questions?

For this presentation & more:
       http://eliw.com/


       Twitter: @eliw


          Zend's DevZone:
     http://dz.zend.com/