Ruby performance - The low hanging fruit

Ruby Performance
The Low Hanging Fruit

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

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

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

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

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

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

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

Reduce the impact
• Optimise the application
• Optimise the environment

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

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

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

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

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"

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

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

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

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

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

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

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

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

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

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

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/

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

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

Ruby performance - The low hanging fruit

Recommended

More Related Content

What's hot (20)

Similar to Ruby performance - The low hanging fruit (20)

Recently uploaded (20)

Ruby performance - The low hanging fruit