Lessons Learned
while building

or...
How To Run Your Big
App on One Server
AndAHalf

Menno van der Sman
Developer at Wakoopa
since May 2007

Wakoopa is about
software

PC Mac
Linux

200
GB

Does it scale?

Scaling the front is easy

Scaling the back is
harder

Limits spawn creativity

Servers
at Railsmachine
16GB RAM 5GB RAM
8 Cores 4 Cores
dedicated shared
staging archiving
production
database

or...
Keeping Your Database
Happy

Queuing
processing multiple items at a time
efficient cache update
DelayedJob for anything else

Smart queries
UPDATE developers SET active_seconds = active_seconds + ...
INSERT INTO hourly_usage (...) VALUES (...) ON DUPLICATE KEY UPDATE
active_seconds = active_seconds + ..., idle_seconds = idle_seconds + ...
Allows for concurrency

Aim for a Small Rowsize
choose a correct datatype
pick the right indexes
sometimes `id` shouldn’t be the PK

composite_primary_keys
Allows efficient PK
class HourlyUsage < ActiveRecord::Base
set_primary_keys :user_id, :software_id, :used_at
...
end
Original implementation by Dr Nic
Maintained by Darrin Holst
http://github.com/drnic/composite_primary_keys

Archive old data
that’s not frequently used
SELECT ... FROM hourly_usage WHERE used_at < '...' INTO OUTFILE '/path/to/file'
LOAD DATA LOCAL INFILE '/path/to/file' REPLACE INTO TABLE hourly_usage_storage
avoids long locks

Alternative solution
Partitioning
CREATE TABLE hourly_usage_storage ( ... )
PARTITION BY RANGE (software_id) (
PARTITION p0 VALUES LESS THAN (...),
PARTITION p1 VALUES LESS THAN (...),
PARTITION p2 VALUES LESS THAN (...),
PARTITION p3 VALUES LESS THAN (...),
....
PARTITION pn VALUES LESS THAN MAXVALUE
);
Makes ‘WHERE software_id = ...’ very fast
Didn’t work for us

Other Techologies
Rails 2.3
Apache
Passenger
REE 1.8.7
MySQL 5.0
Memcached
Sphinx
Amazon EC2

Our REE settings
#!/bin/sh
RUBY_HEAP_MIN_SLOTS=500000
RUBY_HEAP_SLOTS_INCREMENT=250000
RUBY_HEAP_SLOTS_GROWTH_FACTOR=1
RUBY_GC_MALLOC_LIMIT=50000000
exec "/opt/ruby-enterprise/bin/ruby" "$@"

Questions?
or suggestions?