Facebook Architecture

Facbook Engineering Notes

High Performance at Massive Scale – Lessons learned at Facebook

Jeff Rothschild, Vice President of Technology at Facebook gave a great presentation at UC San Diego on our favorite subject: "High Performance at Massive Scale – Lessons learned at Facebook". The abstract for the talk is:
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Facebook's Memcached Multiget Hole: More machines != More Capacity

When you are on the bleeding edge of scale like Facebook is, you run into some interesting problems. As of 2008 Facebook had over 800 memcached servers supplying over 28 terabytes of cache. With those staggering numbers it's a fair bet to think they've seen their share of Dr. House worthy memcached problems.
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Why are Facebook, Digg, and Twitter so hard to scale?

Real-time social graphs (connectivity between people, places, and things). That's why scaling Facebook is hard says Jeff Rothschild, Vice President of Technology at Facebook. Social networking sites like Facebook, Digg, and Twitter are simply harder than traditional websites to scale. Why is that? Why would social networking sites be any more difficult to scale than traditional web sites? Let's find out.
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Product: Facebook's Cassandra - A Massive Distributed Store

Update 2: Presentation from the NoSQL conference: slides, video.
Update: Why you won't be building your killer app on a distributed hash table by Jonathan Ellis. Why I think Cassandra is the most promising of the open-source distributed databases --you get a relatively rich data model and a distribution model that supports efficient range queries. These are not things that can be grafted on top of a simpler DHT foundation, so Cassandra will be useful for a wider variety of applications.
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Hive - A Petabyte Scale Data Warehouse using Hadoop

This post about using Hive and Hadoop for analytics comes straight from Facebook engineers.

Scalable analysis on large data sets has been core to the functions of a number of teams at Facebook - both engineering and non-engineering. Apart from ad hoc analysis and business intelligence applications used by analysts across the company, a number of Facebook products are also based on analytics.
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Facebook, Hadoop, and Hive

Facebook has the second largest installation of Hadoop (a software platform that lets one easily write and run applications that process vast amounts of data), Yahoo being the first.
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Strategy: Facebook Tweaks to Handle 6 Time as Many Memcached Requests

Our latest strategy is taken from a great post by Paul Saab of Facebook, detailing how with changes Facebook has made to memcached they have:
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Product: Scribe - Facebook's Scalable Logging System


In Log Everything All the Time I advocate applications shouldn't bother logging at all. Why waste all that time and code? No, wait, that's not right. I preach logging everything all the time. Doh. Facebook obviously feels similarly which is why they opened sourced Scribe, their internal logging system, capable of logging 10s of billions of messages per day. These messages include access logs, performance statistics, actions that went to News Feed, and many others.
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Some Facebook Secrets to Better Operations

Kim Nash in an interview with Jonathan Heiliger, Facebook VP of technical operations, provides some juicy details on how Facebook handles operations. Operations is one of those departments everyone runs differently as it is usually an ontogeny recapitulates phylogeny situation. With 2,000 databases, 25 terabytes of cache, 90 million active users, and 10,000 servers you know Facebook has some serious operational issues. What are some of Facebook's secrets to better operations?
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