Scaling the Facebook data warehouse to 300 PB
At Facebook, we have unique storage scalability challenges when it comes to our data warehouse. Our warehouse stores upwards of 300 PB of Hive data, with an incoming daily rate of about 600 TB. In the last year, the warehouse has seen a 3x growth in the amount of data stored. Given this growth trajectory, storage efficiency is and will continue to be a focus for our warehouse infrastructure.
Anyone who says that MySQL is not scalable has no idea. Â Facebook is one of the examples for a large deployment of MySQL:
How big is Facebook’s Internet infrastructure? Facebook VP of Technology Jeff Rothschild provided some details in a panel at the recent MySQL user conference. Rothschild says Facebook is now running 10,000 servers, including 1,800 MySQL servers that are overseen by just two database administrators.
Facebook recently surpassed 500,000,000 users – half a billion!
Steve Yegge has posted yet another of his excellent (and long) rants. This time he talks about the size of code and why one should jump out of its skin to keep it minimal.
 Most programmers have successfully compartmentalized their beliefs about code base size. Java programmers are unusually severe offenders but are by no means the only ones. In one compartment, they know big code bases are bad. It only takes grade-school arithmetic to appreciate just how bad they can be. If you have a million lines of code, at 50 lines per “page”, that’s 20,000 pages of code. How long would it take you to read a 20,000-page instruction manual? The effort to simply browse the code base and try to discern its overall structure could take weeks or even months, depending on its density. Significant architectural changes could take months or even years.
As I said, it’s a long piece. But it’s worth every paragraph. Even though some Java programmers might be slightly offended by the article, I’m sure it’s not intentional.