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Performance Testing Rails Applications
This guide covers the various ways of performance testing a Ruby on Rails application.
After reading this guide, you will know:
- The various types of benchmarking and profiling metrics.
- How to generate performance and benchmarking tests.
- How to install and use a GC-patched Ruby binary to measure memory usage and object allocation.
- The benchmarking information provided by Rails inside the log files.
- Various tools facilitating benchmarking and profiling.
Performance testing is an integral part of the development cycle. It is very important that you don't make your end users wait for too long before the page is completely loaded. Ensuring a pleasant browsing experience for end users and cutting the cost of unnecessary hardware is important for any non-trivial web application.
Performance Test Cases
Rails performance tests are a special type of integration tests, designed for benchmarking and profiling the test code. With performance tests, you can determine where your application's memory or speed problems are coming from, and get a more in-depth picture of those problems.
In a freshly generated Rails application, test/performance/browsing_test.rb
contains an example of a performance test:
require 'test_helper'
require 'rails/performance_test_help'
class BrowsingTest < ActionDispatch::PerformanceTest
# Refer to the documentation for all available options
# self.profile_options = { runs: 5, metrics: [:wall_time, :memory],
# output: 'tmp/performance', formats: [:flat] }
test "homepage" do
get '/'
end
end
This example is a simple performance test case for profiling a GET request to the application's homepage.
Generating Performance Tests
Rails provides a generator called performance_test
for creating new
performance tests:
$ rails generate performance_test homepage
This generates homepage_test.rb
in the test/performance
directory:
require 'test_helper'
require 'rails/performance_test_help'
class HomepageTest < ActionDispatch::PerformanceTest
# Refer to the documentation for all available options
# self.profile_options = { runs: 5, metrics: [:wall_time, :memory],
# output: 'tmp/performance', formats: [:flat] }
test "homepage" do
get '/'
end
end
Examples
Let's assume your application has the following controller and model:
# routes.rb
root to: 'home#dashboard'
resources :posts
# home_controller.rb
class HomeController < ApplicationController
def dashboard
@users = User.last_ten.includes(:avatars)
@posts = Post.all_today
end
end
# posts_controller.rb
class PostsController < ApplicationController
def create
@post = Post.create(params[:post])
redirect_to(@post)
end
end
# post.rb
class Post < ActiveRecord::Base
before_save :recalculate_costly_stats
def slow_method
# I fire gallzilion queries sleeping all around
end
private
def recalculate_costly_stats
# CPU heavy calculations
end
end
Controller Example
Because performance tests are a special kind of integration test, you can use
the get
and post
methods in them.
Here's the performance test for HomeController#dashboard
and
PostsController#create
:
require 'test_helper'
require 'rails/performance_test_help'
class PostPerformanceTest < ActionDispatch::PerformanceTest
def setup
# Application requires logged-in user
login_as(:lifo)
end
test "homepage" do
get '/dashboard'
end
test "creating new post" do
post '/posts', post: { body: 'lifo is fooling you' }
end
end
You can find more details about the get
and post
methods in the
Testing Rails Applications guide.
Model Example
Even though the performance tests are integration tests and hence closer to the request/response cycle by nature, you can still performance test pure model code.
Performance test for Post
model:
require 'test_helper'
require 'rails/performance_test_help'
class PostModelTest < ActionDispatch::PerformanceTest
test "creation" do
Post.create body: 'still fooling you', cost: '100'
end
test "slow method" do
# Using posts(:awesome) fixture
posts(:awesome).slow_method
end
end
Modes
Performance tests can be run in two modes: Benchmarking and Profiling.
Benchmarking
Benchmarking makes it easy to quickly gather a few metrics about each test run. By default, each test case is run 4 times in benchmarking mode.
To run performance tests in benchmarking mode:
$ rake test:benchmark
Profiling
Profiling allows you to make an in-depth analysis of each of your tests by using an external profiler. Depending on your Ruby interpreter, this profiler can be native (Rubinius, JRuby) or not (MRI, which uses RubyProf). By default, each test case is run once in profiling mode.
To run performance tests in profiling mode:
$ rake test:profile
Metrics
Benchmarking and profiling run performance tests and give you multiple metrics. The availability of each metric is determined by the interpreter being used—none of them support all metrics—and by the mode in use. A brief description of each metric and their availability across interpreters/modes is given below.
Wall Time
Wall time measures the real world time elapsed during the test run. It is affected by any other processes concurrently running on the system.
Process Time
Process time measures the time taken by the process. It is unaffected by any other processes running concurrently on the same system. Hence, process time is likely to be constant for any given performance test, irrespective of the machine load.
CPU Time
Similar to process time, but leverages the more accurate CPU clock counter available on the Pentium and PowerPC platforms.
User Time
User time measures the amount of time the CPU spent in user-mode, i.e. within the process. This is not affected by other processes and by the time it possibly spends blocked.
Memory
Memory measures the amount of memory used for the performance test case.
Objects
Objects measures the number of objects allocated for the performance test case.
GC Runs
GC Runs measures the number of times GC was invoked for the performance test case.
GC Time
GC Time measures the amount of time spent in GC for the performance test case.
Metric Availability
Benchmarking
Interpreter | Wall Time | Process Time | CPU Time | User Time | Memory | Objects | GC Runs | GC Time |
---|---|---|---|---|---|---|---|---|
MRI | yes | yes | yes | no | yes | yes | yes | yes |
REE | yes | yes | yes | no | yes | yes | yes | yes |
Rubinius | yes | no | no | no | yes | yes | yes | yes |
JRuby | yes | no | no | yes | yes | yes | yes | yes |
Profiling
Interpreter | Wall Time | Process Time | CPU Time | User Time | Memory | Objects | GC Runs | GC Time |
---|---|---|---|---|---|---|---|---|
MRI | yes | yes | no | no | yes | yes | yes | yes |
REE | yes | yes | no | no | yes | yes | yes | yes |
Rubinius | yes | no | no | no | no | no | no | no |
JRuby | yes | no | no | no | no | no | no | no |
NOTE: To profile under JRuby you'll need to run export JRUBY_OPTS="-Xlaunch.inproc=false --profile.api"
before the performance tests.
Understanding the Output
Performance tests generate different outputs inside tmp/performance
directory
depending on their mode and metric.
Benchmarking
In benchmarking mode, performance tests generate two types of outputs.
Command Line
This is the primary form of output in benchmarking mode. Example:
BrowsingTest#test_homepage (31 ms warmup)
wall_time: 6 ms
memory: 437.27 KB
objects: 5,514
gc_runs: 0
gc_time: 19 ms
CSV Files
Performance test results are also appended to .csv
files inside tmp/performance
.
For example, running the default BrowsingTest#test_homepage
will generate
following five files:
- BrowsingTest#test_homepage_gc_runs.csv
- BrowsingTest#test_homepage_gc_time.csv
- BrowsingTest#test_homepage_memory.csv
- BrowsingTest#test_homepage_objects.csv
- BrowsingTest#test_homepage_wall_time.csv
As the results are appended to these files each time the performance tests are run in benchmarking mode, you can collect data over a period of time. This can be very helpful in analyzing the effects of code changes.
Sample output of BrowsingTest#test_homepage_wall_time.csv
:
measurement,created_at,app,rails,ruby,platform
0.00738224999999992,2009-01-08T03:40:29Z,,3.0.0,ruby-1.8.7.249,x86_64-linux
0.00755874999999984,2009-01-08T03:46:18Z,,3.0.0,ruby-1.8.7.249,x86_64-linux
0.00762099999999993,2009-01-08T03:49:25Z,,3.0.0,ruby-1.8.7.249,x86_64-linux
0.00603075000000008,2009-01-08T04:03:29Z,,3.0.0,ruby-1.8.7.249,x86_64-linux
0.00619899999999995,2009-01-08T04:03:53Z,,3.0.0,ruby-1.8.7.249,x86_64-linux
0.00755449999999991,2009-01-08T04:04:55Z,,3.0.0,ruby-1.8.7.249,x86_64-linux
0.00595999999999997,2009-01-08T04:05:06Z,,3.0.0,ruby-1.8.7.249,x86_64-linux
0.00740450000000004,2009-01-09T03:54:47Z,,3.0.0,ruby-1.8.7.249,x86_64-linux
0.00603150000000008,2009-01-09T03:54:57Z,,3.0.0,ruby-1.8.7.249,x86_64-linux
0.00771250000000012,2009-01-09T15:46:03Z,,3.0.0,ruby-1.8.7.249,x86_64-linux
Profiling
In profiling mode, performance tests can generate multiple types of outputs. The command line output is always presented but support for the others is dependent on the interpreter in use. A brief description of each type and their availability across interpreters is given below.
Command Line
This is a very basic form of output in profiling mode:
BrowsingTest#test_homepage (58 ms warmup)
process_time: 63 ms
memory: 832.13 KB
objects: 7,882
Flat
Flat output shows the metric—time, memory, etc—measure in each method. Check Ruby-Prof documentation for a better explanation.
Graph
Graph output shows the metric measure in each method, which methods call it and which methods it calls. Check Ruby-Prof documentation for a better explanation.
Tree
Tree output is profiling information in calltree format for use by kcachegrind and similar tools.
Output Availability
Flat | Graph | Tree | |
---|---|---|---|
MRI | yes | yes | yes |
REE | yes | yes | yes |
Rubinius | yes | yes | no |
JRuby | yes | yes | no |
Tuning Test Runs
Test runs can be tuned by setting the profile_options
class variable on your
test class.
require 'test_helper'
require 'rails/performance_test_help'
class BrowsingTest < ActionDispatch::PerformanceTest
self.profile_options = { runs: 5, metrics: [:wall_time, :memory] }
test "homepage"
get '/'
end
end
In this example, the test would run 5 times and measure wall time and memory. There are a few configurable options:
Option | Description | Default | Mode |
---|---|---|---|
:runs |
Number of runs. | Benchmarking: 4, Profiling: 1 | Both |
:output |
Directory to use when writing the results. | tmp/performance |
Both |
:metrics |
Metrics to use. | See below. | Both |
:formats |
Formats to output to. | See below. | Profiling |
Metrics and formats have different defaults depending on the interpreter in use.
Interpreter | Mode | Default metrics | Default formats |
---|---|---|---|
MRI/REE | Benchmarking | [:wall_time, :memory, :objects, :gc_runs, :gc_time] |
N/A |
Profiling | [:process_time, :memory, :objects] |
[:flat, :graph_html, :call_tree, :call_stack] |
|
Rubinius | Benchmarking | [:wall_time, :memory, :objects, :gc_runs, :gc_time] |
N/A |
Profiling | [:wall_time] |
[:flat, :graph] |
|
JRuby | Benchmarking | [:wall_time, :user_time, :memory, :gc_runs, :gc_time] |
N/A |
Profiling | [:wall_time] |
[:flat, :graph] |
As you've probably noticed by now, metrics and formats are specified using a symbol array with each name underscored.
Performance Test Environment
Performance tests are run in the test
environment. But running performance
tests will set the following configuration parameters:
ActionController::Base.perform_caching = true
ActiveSupport::Dependencies.mechanism = :require
Rails.logger.level = ActiveSupport::Logger::INFO
As ActionController::Base.perform_caching
is set to true
, performance tests
will behave much as they do in the production
environment.
Installing GC-Patched MRI
To get the best from Rails' performance tests under MRI, you'll need to build a special Ruby binary with some super powers.
The recommended patches for each MRI version are:
Version | Patch |
---|---|
1.8.6 | ruby186gc |
1.8.7 | ruby187gc |
1.9.2 and above | gcdata |
All of these can be found on RVM's patches directory under each specific interpreter version.
Concerning the installation itself, you can either do this easily by using RVM or you can build everything from source, which is a little bit harder.
Install Using RVM
The process of installing a patched Ruby interpreter is very easy if you let RVM do the hard work. All of the following RVM commands will provide you with a patched Ruby interpreter:
$ rvm install 1.9.2-p180 --patch gcdata
$ rvm install 1.8.7 --patch ruby187gc
$ rvm install 1.9.2-p180 --patch ~/Downloads/downloaded_gcdata_patch.patch
You can even keep your regular interpreter by assigning a name to the patched one:
$ rvm install 1.9.2-p180 --patch gcdata --name gcdata
$ rvm use 1.9.2-p180 # your regular ruby
$ rvm use 1.9.2-p180-gcdata # your patched ruby
And it's done! You have installed a patched Ruby interpreter.
Install From Source
This process is a bit more complicated, but straightforward nonetheless. If you've never compiled a Ruby binary before, follow these steps to build a Ruby binary inside your home directory.
Download and Extract
$ mkdir rubygc
$ wget <the version you want from ftp://ftp.ruby-lang.org/pub/ruby>
$ tar -xzvf <ruby-version.tar.gz>
$ cd <ruby-version>
Apply the Patch
$ curl https://raw.github.com/wayneeseguin/rvm/master/patches/ruby/1.9.2/p180/gcdata.patch | patch -p0 # if you're on 1.9.2!
$ curl https://raw.github.com/wayneeseguin/rvm/master/patches/ruby/1.8.7/ruby187gc.patch | patch -p0 # if you're on 1.8.7!
Configure and Install
The following will install Ruby in your home directory's /rubygc
directory.
Make sure to replace <homedir>
with a full patch to your actual home
directory.
$ ./configure --prefix=/<homedir>/rubygc
$ make && make install
Prepare Aliases
For convenience, add the following lines in your ~/.profile
:
alias gcruby='~/rubygc/bin/ruby'
alias gcrake='~/rubygc/bin/rake'
alias gcgem='~/rubygc/bin/gem'
alias gcirb='~/rubygc/bin/irb'
alias gcrails='~/rubygc/bin/rails'
Don't forget to use your aliases from now on.
Using Ruby-Prof on MRI and REE
Add Ruby-Prof to your applications' Gemfile if you want to benchmark/profile under MRI or REE:
gem 'ruby-prof'
Now run bundle install
and you're ready to go.
Command Line Tools
Writing performance test cases could be an overkill when you are looking for one time tests. Rails ships with two command line tools that enable quick and dirty performance testing:
benchmarker
Usage:
Usage: rails benchmarker 'Ruby.code' 'Ruby.more_code' ... [OPTS]
-r, --runs N Number of runs.
Default: 4
-o, --output PATH Directory to use when writing the results.
Default: tmp/performance
-m, --metrics a,b,c Metrics to use.
Default: wall_time,memory,objects,gc_runs,gc_time
Example:
$ rails benchmarker 'Item.all' 'CouchItem.all' --runs 3 --metrics wall_time,memory
profiler
Usage:
Usage: rails profiler 'Ruby.code' 'Ruby.more_code' ... [OPTS]
-r, --runs N Number of runs.
Default: 1
-o, --output PATH Directory to use when writing the results.
Default: tmp/performance
-m, --metrics a,b,c Metrics to use.
Default: process_time,memory,objects
-f, --formats x,y,z Formats to output to.
Default: flat,graph_html,call_tree
Example:
$ rails profiler 'Item.all' 'CouchItem.all' --runs 2 --metrics process_time --formats flat
NOTE: Metrics and formats vary from interpreter to interpreter. Pass --help
to
each tool to see the defaults for your interpreter.
Helper Methods
Rails provides various helper methods inside Active Record, Action Controller
and Action View to measure the time taken by a given piece of code. The method
is called benchmark()
in all the three components.
Model
Project.benchmark("Creating project") do
project = Project.create("name" => "stuff")
project.create_manager("name" => "David")
project.milestones << Milestone.all
end
This benchmarks the code enclosed in the Project.benchmark("Creating project") do...end
block and prints the result to the log file:
Creating project (185.3ms)
Please refer to the API docs
for additional options to benchmark()
.
Controller
Similarly, you could use this helper method inside controllers.
def process_projects
benchmark("Processing projects") do
Project.process(params[:project_ids])
Project.update_cached_projects
end
end
NOTE: benchmark
is a class method inside controllers.
View
And in views
<% benchmark("Showing projects partial") do %>
<%= render @projects %>
<% end %>
Request Logging
Rails log files contain very useful information about the time taken to serve each request. Here's a typical log file entry:
Processing ItemsController#index (for 127.0.0.1 at 2009-01-08 03:06:39) [GET]
Rendering template within layouts/items
Rendering items/index
Completed in 5ms (View: 2, DB: 0) | 200 OK [http://0.0.0.0/items]
For this section, we're only interested in the last line:
Completed in 5ms (View: 2, DB: 0) | 200 OK [http://0.0.0.0/items]
This data is fairly straightforward to understand. Rails uses millisecond(ms) as the metric to measure the time taken. The complete request spent 5 ms inside Rails, out of which 2 ms were spent rendering views and none was spent communication with the database. It's safe to assume that the remaining 3 ms were spent inside the controller.
Michael Koziarski has an interesting blog post explaining the importance of using milliseconds as the metric.
Useful Links
Rails Plugins and Gems
Generic Tools
Tutorials and Documentation
- ruby-prof API Documentation
- Request Profiling Railscast - Outdated, but useful for understanding call graphs.
Commercial Products
Rails has been lucky to have a few companies dedicated to Rails-specific performance tools. A couple of those are: