A quick overview of common Ruby benchmarking tools and scenarios where they can be used

1. Ruby Performance
The Low Hanging Fruit

2. Hello, I’m
Bruce Werdschinski
Senior Lead Developer, Prezentt
!
Spent 5 years as the Technical Director
at GTP iCommerce
!
~2.5 years with Ruby, built hundreds of
ecommerce websites, loves SEO &
CRO
!
Mercedes enthusiast

3. Agenda
• Introduction to common tools
• Scenarios where we would use
those tools
• What else can we do, low
hanging fruit wise

4. From experience, look at common
expensive tasks
• Database operations
• Network access
• Incorrect algorithm
• Unnecessary work - Can we cache it?

5. Ruby benchmark
• Disable Garbage Collection first with: GC.disable
• Part of the Ruby standard library
• I prefer to use it like this:
!
time = Benchmark.realtime do
# The code I’m testing
end

6. benchmark-ips
• https://github.com/evanphx/benchmark-ips
• Benchmarks a blocks iterations/second.
• For short snippits of code, IPS automatically figures out how many
times to run the code to get interesting data
• Provides a standard deviation measure which is very cool

7. stackprof
• https://github.com/tmm1/stackprof
• For Ruby 2.1 and above
• Samples what the CPU is spending time on
• https://github.com/alisnic/stackprof-webnav is a Web UI for
stackprof dumps
• https://github.com/quirkey/stackprof-remote is middleware and CLI
for fetching and interacting with stackprof

8. How do we find expensive things?
• Experience / Knowledge
• Logs
• Ruby's own benchmark module
• External tools
• benchmark-ips, stackprof, time
• SaaS metrics tools
• Librato, Datadog, Skylight, New
Relic, Keen IO

9. Reduce the impact
• Optimise the application
• Optimise the environment

10. Optimise the Application
• Reduce heavy I/O
• ActiveRecord tweaks
• Caching

11. Reduce heavy I/O
Silly example, but it illustrates the point. Writing to the screen is more
expensive than writing to memory
!
1_000_000.times do
puts "Hello world!"
end
!
s = String.new
1_000_000.times do
s << "Hello world!n"
end
puts s
10.5 seconds vs. 6.5 seconds - But 2.28 times more memory

12. Reduce heavy I/O
• Same applies for database calls,
event processing, etc. One large
call is often much faster than many
little calls.
• I’ve been playing with Keen IO
lately, their demo app is at: http://
keen-gem-example.herokuapp.com/
• 50 calls, 1 item each: 20094ms
• 1 call with 50 items: 284ms

13. ActiveRecord
• Know your SQL
• Check logs to see what ActiveRecord is actually doing
• Lots of tools to help us

14. ActiveRecord sum example
I want to get a total of all to the orders in the database
Order.sum(&:total)
Order Load (49.3ms) SELECT "orders".* FROM "orders"
Order.sum(:total)
(4.0ms) SELECT SUM("orders"."total") AS sum_id FROM "orders"

15. ActiveRecord sum example

16. ActiveRecord sum example

17. ActiveRecord Tools
• rack-mini-profiler
• RailsPanel
• rails-footnotes
• Bullet
• Peek

18. rack-mini-profiler
• https://github.com/MiniProfiler/
rack-mini-profiler
• Middleware that shows a HTML
panel on each page

19. RailsPanel
• https://github.com/dejan/
rails_panel
• Chrome Extension that provides
information about the Rails
request. Includes Database,
rendering and total times.

20. Memoization
Memoization is a caching technique of storing a computed value to
avoid duplicated work by future calls.
1. Perform some work
2. Store the result of that work
3. Use the stored data the next time you need the result of that work

21. Memoization
A common pattern is using the conditional assignment operator: ||=
def current_user
User.find(session[:user_id])
end
Instead store the result in an instance variable by using:
def current_user
@current_user ||= User.find(session[:user_id])
end

22. identity_cache
https://github.com/Shopify/identity_cache
ActiveRecord cache for model objects
Extracted from Shopify
@user = User.fetch(id) instead of @user = User.find(id)
Uses an after_commit hook to expire the object from cache

23. Rails Cache
• Use the Dalli gem as the Rails cache store
def fetch(id)
Rails.cache.fetch("product-#{id}", expires_in: 5.minutes) do
Product.find(id)
end
end

24. Is Ruby the best tool?
• Sometimes…shock, horror…Ruby might not be the best tool for the
job.
• Where Ruby may not be the best fit:
• CPU bound
• Async I/O

25. Leibniz formula for π
1 - 1/3 + 1/5 - 1/7 + 1/9 - 1/11 … = π/4
20 million iterations
CPU bound task
• Ruby: 3.78 seconds
• Rust: 0.238 seconds

26. Optimise the Environment
• Low hanging fruit, faster server, database, more memory
• Ruby versions
• Network topology
• Caching systems
• Web performance

27. Web performance
• No point shaving 1/10th of a second off your database access time
if you’ve got a 3Mb background image.
• http://gtmetrix.com/
• http://tools.pingdom.com/fpt/

28. No more low hanging fruit
• “Ruby Under a Microscope”
by Pat Shaughnessy
• Utilization Saturation and
Errors (USE) Method

29. Thank You!
Twitter: @bwerdschinski
!
Email: bruce@werdschinski.com
!
Blog: http://www.werdschinski.com