Lessons Learnedwhile building

How To Run Your Big App on OneAndAHalf Server

or...

Menno van der SmanDeveloper at Wakoopa

since May 2007

Wakoopa is about software

MacPC

Linux

200GB

Does it scale?

Scaling the front is easy

Scaling the back is harder

Limits spawn creativity

Serversat Railsmachine

16GB RAM8 Cores

5GB RAM4 Cores

dedicatedstaging

productiondatabase

sharedarchiving

Keeping Your Database Happy

or...

Queuing

DelayedJob for anything else

processing multiple items at a time

efficient cache update

Smart queries

INSERT INTO hourly_usage (...) VALUES (...) ON DUPLICATE KEY UPDATE active_seconds = active_seconds + ..., idle_seconds = idle_seconds + ...

UPDATE developers SET active_seconds = active_seconds + ...

Allows for concurrency

Aim for a Small Rowsize

choose a correct datatype

pick the right indexes

sometimes `id` shouldn’t be the PK

Allows efficient PK

Original implementation by Dr NicMaintained by Darrin Holst

http://github.com/drnic/composite_primary_keys

class HourlyUsage < ActiveRecord::Base set_primary_keys :user_id, :software_id, :used_at ...end

composite_primary_keys

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

Archive old datathat’s not frequently used

Alternative solutionPartitioning

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);

Didn’t work for us

Makes ‘WHERE software_id = ...’ very fast

Rails 2.3Apache

PassengerREE 1.8.7

MySQL 5.0Memcached

SphinxAmazon EC2

Other Techologies

Our REE settings

#!/bin/shRUBY_HEAP_MIN_SLOTS=500000RUBY_HEAP_SLOTS_INCREMENT=250000RUBY_HEAP_SLOTS_GROWTH_FACTOR=1RUBY_GC_MALLOC_LIMIT=50000000exec "/opt/ruby-enterprise/bin/ruby" "$@"

Questions?or suggestions?