Mysql 2007 Tech At Digg V3
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Mysql 2007 Tech At Digg V3






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    Mysql 2007 Tech At Digg V3 Mysql 2007 Tech At Digg V3 Presentation Transcript

        • Technology at
        • Elliott White III - Eli
        • Tim Ellis - Time
    • What's all this then?
      • History of Tech at Digg
      • Standard Setup
      • Memcached
      • Purpose Driven MySQL Server Pools
      • Sharding
      • Other MySQL details
    • History of Tech at Digg
      • Initially one Linux server with Apache 1.3 and PHP 4.x
      • MySQL 4.0 and myisam tables & MySQL full-text search
      • Started with as many open source packages as possible for rapid development.
        • ImageMagick, Ispell, prototype/scriptaculous, etc
      • Grew quick. One server became two. myisam become innodb. We moved to 3 servers, Apache 2.x, MySQL master-slave replication, started using memcached, moved to PHP 5.x & hired a dba
      • And then the pace picked up yet again...
    • A Standard Setup Many PHP Servers behind a load balancer:
    • A Standard Setup Many MySQL slaves, talking to a master
    • A Standard Setup Randomized PHP to MySQL relations
    • Memcached What is it & Why use it? Why not just pregenerate pages of content?
      • Performance gains:
      • Caching certain chunks of data that may be used on many different pages.
      • From that, still being able to dynamically create the page, but using cached data.
    • Memcached Server Farm
      • Issues to be solved:
      • Allowing for Failover and Redundancy
      • Removing or ignoring stale data upon machine failure
      • Stopping perpetuation of database slave lag
      • Making the actual decisions of what and when to cache
      • Solution: Write generic code that understands your data.
    • Purpose Driven MySQL Pools Creating separate slave pools, that are close to identical in order to isolate high database load.
    • Purpose Driven Pool Example
    • Sharding Simplest Definition: Breaking up your database into a number of smaller ones.
      • Pros
        • Greater performance
        • Tweakable / Scalable
      • Cons
        • Loss of SQL support (JOIN)
        • Increased PHP load
        • Complicated programming
    • Possible Types of Sharding Table-based Range-based Date-based Hashed Partial Sharding
    • How MySQL Can Do Sharding
      • Partition tables
      • Federated tables
      • MySQL Cluster (NDB)
        • Which of these technologies does Digg use?
          • None of them
          • They weren't ready when we needed them
    • Digg MySQL Specifics
      • Mix of MySQL 5.0 versions: 5.0.22, 5.0.27, 5.0.30, 5.0.32
      • A single MySQL 4.1 supporting Cacti
      • MySQL installation & patching done via Debian apt
      • 5.0 performs fine for us compared to 4.1
      • OLTP DBs are InnoDB & OLAP DB is MyISAM
      • InnoDB backup DB for dumps and slave creation
      • InnoDB recovery faster after slave hardware dies
      • MyISAM great for loads and date-versioned DBs
    • Current DB Challenges
      • Scaled via “buy more RAM,” can't afford that anymore
      • Physical I/O common, so rewrite queries
      • Convincing site architects to change features to more scalable alternatives
      • MySQL debug binary testing
      • Schema cruft
      • Managing monitoring & alerting systems (Cacti)
      • Master is a single point of failure (not as bad as it sounds)
      • Why are our disks lying? Use from:
    • Any Questions?
        • For this presentation and more: