From 2c2824a967a18d7f7a7622f24a9e3be4db851bf8 Mon Sep 17 00:00:00 2001 From: Pratik Naik Date: Thu, 8 Jan 2009 15:57:19 +0000 Subject: [PATCH] Update performance testing guide stuff --- .../html/benchmarking_and_profiling.html | 1003 ----------------- railties/doc/guides/html/index.html | 2 +- .../doc/guides/html/performance_testing.html | 577 ++++++++++ .../benchmarking_and_profiling/appendix.txt | 95 -- .../digging_deeper.txt | 105 -- .../edge_rails_features.txt | 185 --- .../benchmarking_and_profiling/gameplan.txt | 27 - .../benchmarking_and_profiling/rubyprof.txt | 179 --- .../benchmarking_and_profiling/statistics.txt | 57 - railties/doc/guides/source/index.txt | 2 +- .../index.txt => performance_testing.txt} | 185 ++- 11 files changed, 721 insertions(+), 1696 deletions(-) delete mode 100644 railties/doc/guides/html/benchmarking_and_profiling.html create mode 100644 railties/doc/guides/html/performance_testing.html delete mode 100644 railties/doc/guides/source/benchmarking_and_profiling/appendix.txt delete mode 100644 railties/doc/guides/source/benchmarking_and_profiling/digging_deeper.txt delete mode 100644 railties/doc/guides/source/benchmarking_and_profiling/edge_rails_features.txt delete mode 100644 railties/doc/guides/source/benchmarking_and_profiling/gameplan.txt delete mode 100644 railties/doc/guides/source/benchmarking_and_profiling/rubyprof.txt delete mode 100644 railties/doc/guides/source/benchmarking_and_profiling/statistics.txt rename railties/doc/guides/source/{benchmarking_and_profiling/index.txt => performance_testing.txt} (50%) diff --git a/railties/doc/guides/html/benchmarking_and_profiling.html b/railties/doc/guides/html/benchmarking_and_profiling.html deleted file mode 100644 index 7a50e5a68c..0000000000 --- a/railties/doc/guides/html/benchmarking_and_profiling.html +++ /dev/null @@ -1,1003 +0,0 @@ - - - - - Benchmarking and Profiling Rails - - - - - - - - - -
- - - -
-

Benchmarking and Profiling Rails

-
-
-

This guide covers the benchmarking and profiling tactics/tools of Rails and Ruby in general. By referring to this guide, you will be able to:

-
    -
  • -

    -Understand the various types of benchmarking and profiling metrics -

    -
    • -
  • -

    -Generate performance/benchmarking tests -

    -
    • -
  • -

    -Use GC patched Ruby binary to measure memory usage and object allocation -

    -
    • -
  • -

    -Understand the information provided by Rails inside the log files -

    -
    • -
  • -

    -Learn about various tools facilitating benchmarking and profiling -

    -
    • -
-
-
-

1. Why Benchmark and Profile ?

-
-

Benchmarking and Profiling 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 plesant browsing experience to the end users and cutting cost of unnecessary hardwares is important for any web application.

-

1.1. What is the difference between benchmarking and profiling ?

-

Benchmarking is the process of finding out if a piece of code is slow or not. Whereas profiling is the process of finding out what exactly is slowing down that piece of code.

-
-

2. Using and understanding the log files

-
-

Rails logs files containt basic but very useful information about the time taken to serve every request. A typical log entry looks something like :

-
-
-
Processing ItemsController#index (for 127.0.0.1 at 2008-10-17 00:08:18) [GET]
-  Session ID: BAh7BiIKZmxhc2hJQzonQWN0aHsABjoKQHVzZWR7AA==--83cff4fe0a897074a65335
-  Parameters: {"action"=>"index", "controller"=>"items"}
-Rendering template within layouts/items
-Rendering items/index
-Completed in 5ms (View: 2, DB: 0) | 200 OK [http://localhost/items]
-

For this section, we’re only interested in the last line from that log entry:

-
-
-
Completed in 5ms (View: 2, DB: 0) | 200 OK [http://localhost/items]
-

This data is fairly straight forward to understand. Rails uses millisecond(ms) as the metric to measures 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.

-
-

3. Helper methods

-
-

Rails provides various helper methods inside Active Record, Action Controller and Action View to measure the time taken by a specific code. The method is called benchmark() in all three components.

-
-
-
Project.benchmark("Creating project") do
-  project = Project.create("name" => "stuff")
-  project.create_manager("name" => "David")
-  project.milestones << Milestone.find(:all)
-end
-

The above code benchmarks the multiple statments enclosed inside Project.benchmark("Creating project") do..end block and prints the results inside log files. The statement inside log files will look like:

-
-
-
Creating projectem (185.3ms)
-

Please refer to API docs for optional options to benchmark()

-

Similarly, you could use this helper method inside controllers ( Note that it’s a class method here ):

-
-
-
def process_projects
-  self.class.benchmark("Processing projects") do
-    Project.process(params[:project_ids])
-    Project.update_cached_projects
-  end
-end
-

and views:

-
-
-
<% benchmark("Showing projects partial") do %>
-  <%= render :partial => @projects %>
-<% end %>
-
-

4. Performance Test Cases

-
-

Rails provides a very easy to write performance test cases, which look just like the regular integration tests.

-

If you have a look at test/performance/browsing_test.rb in a newly created Rails application:

-
-
-
require 'test_helper'
-require 'performance_test_help'
-
-# Profiling results for each test method are written to tmp/performance.
-class BrowsingTest < ActionController::PerformanceTest
-  def test_homepage
-    get '/'
-  end
-end
-

This is an automatically generated example performance test file, for testing performance of homepage(/) of the application.

-

4.1. Modes

-

4.1.1. Benchmarking

-

4.1.2. Profiling

-

4.2. Metrics

-

4.2.1. Process Time

-

CPU Cycles.

-

4.2.2. Memory

-

Memory taken.

-

4.2.3. Objects

-

Objects allocated.

-

4.2.4. GC Runs

-

Number of times the Ruby GC was run.

-

4.2.5. GC Time

-

Time spent running the Ruby GC.

-

4.3. Preparing Ruby and Ruby-prof

-

Before we go ahead, Rails performance testing requires you to build a special Ruby binary with some super powers - GC patch for measuring GC Runs/Time. This process is very straight forward. If you’ve never compiled a Ruby binary before, you can follow the following steps to build a ruby binary inside your home directory:

-

4.3.1. Compile

-
-
-
[lifo@null ~]$ mkdir rubygc
-[lifo@null ~]$ wget ftp://ftp.ruby-lang.org/pub/ruby/1.8/ruby-1.8.6-p111.tar.gz
-[lifo@null ~]$ tar -xzvf ruby-1.8.6-p111.tar.gz
-[lifo@null ~]$ cd ruby-1.8.6-p111
-[lifo@null ruby-1.8.6-p111]$ curl http://rubyforge.org/tracker/download.php/1814/7062/17676/3291/ruby186gc.patch | patch -p0
-[lifo@null ruby-1.8.6-p111]$ ./configure --prefix=/Users/lifo/rubygc
-[lifo@null ruby-1.8.6-p111]$ make && make install
-

4.3.2. Prepare aliases

-

Add the following lines in your ~/.profile for convenience:

-
-
-
alias gcruby='/Users/lifo/rubygc/bin/ruby'
-alias gcrake='/Users/lifo/rubygc/bin/rake'
-alias gcgem='/Users/lifo/rubygc/bin/gem'
-alias gcirb='/Users/lifo/rubygc/bin/irb'
-alias gcrails='/Users/lifo/rubygc/bin/rails'
-
-

4.3.3. Install rubygems and some basic gems

-
-
-
[lifo@null ~]$ wget http://rubyforge.org/frs/download.php/38646/rubygems-1.2.0.tgz
-[lifo@null ~]$ tar -xzvf rubygems-1.2.0.tgz
-[lifo@null ~]$ cd rubygems-1.2.0
-[lifo@null rubygems-1.2.0]$ gcruby setup.rb
-[lifo@null rubygems-1.2.0]$ cd ~
-[lifo@null ~]$ gcgem install rake
-[lifo@null ~]$ gcgem install rails
-
-

4.3.4. Install MySQL gem

-
-
-
[lifo@null ~]$ gcgem install mysql
-
-

If this fails, you can try to install it manually:

-
-
-
[lifo@null ~]$ cd /Users/lifo/rubygc/lib/ruby/gems/1.8/gems/mysql-2.7/
-[lifo@null mysql-2.7]$ gcruby extconf.rb --with-mysql-config
-[lifo@null mysql-2.7]$ make && make install
-
-

4.4. Installing Jeremy Kemper’s ruby-prof

-

We also need to install Jeremy’s ruby-prof gem using our newly built ruby:

-
-
-
[lifo@null ~]$ git clone git://github.com/jeremy/ruby-prof.git
-[lifo@null ~]$ cd ruby-prof/
-[lifo@null ruby-prof (master)]$ gcrake gem
-[lifo@null ruby-prof (master)]$ gcgem install pkg/ruby-prof-0.6.1.gem
-

4.5. Generating performance test

-

Rails provides a simple generator for creating new performance tests:

-
-
-
[lifo@null application (master)]$ script/generate performance_test homepage
-

This will generate test/performance/homepage_test.rb:

-
-
-
require 'test_helper'
-require 'performance_test_help'
-
-class HomepageTest < ActionController::PerformanceTest
-  # Replace this with your real tests.
-  def test_homepage
-    get '/'
-  end
-end
-

Which you can modify to suit your needs.

-

4.6. Running tests

-
-

5. Understanding Performance Tests Outputs

-
-

5.1. Our First Performance Test

-

So how do we profile a request.

-

One of the things that is important to us is how long it takes to render the home page - so let’s make a request to the home page. Once the request is complete, the results will be outputted in the terminal.

-

In the terminal run

-
-
-
[User profiling_tester]$ gcruby tests/performance/homepage.rb
-

After the tests runs for a few seconds you should see something like this.

-
-
-
HomepageTest#test_homepage (19 ms warmup)
-        process_time: 26 ms
-              memory: 298.79 KB
-             objects: 1917
-
-Finished in 2.207428 seconds.
-
-

Simple but efficient.

-
    -
  • -

    -Process Time refers to amount of time necessary to complete the action. -

    -
    • -
  • -

    -memory is the amount of information loaded into memory -

    -
    • -
  • -

    -object ??? #TODO find a good definition. Is it the amount of objects put into a ruby heap for this process? -

    -
    • -
-

In addition we also gain three types of itemized log files for each of these outputs. They can be found in your tmp directory of your application.

-

The Three types are

-
    -
  • -

    -Flat File - A simple text file with the data laid out in a grid -

    -
    • -
  • -

    -Graphical File - A html colored coded version of the simple text file with hyperlinks between the various methods. Most useful is the bolding of the main processes for each portion of the action. -

    -
    • -
  • -

    -Tree File - A file output that can be use in conjunction with KCachegrind to visualize the process -

    -
    • -
-
- - - -
-Note -KCachegrind is Linux only. For Mac this means you have to do a full KDE install to have it working in your OS. Which is over 3 gigs in size. For windows there is clone called wincachegrind but it is no longer actively being developed.
-
-

Below are examples for Flat Files and Graphical Files

-

5.2. Flat Files

-
-
Flat File Output Processing Time
-
-

Thread ID: 2279160 -Total: 0.026097

-
-
-
%self     total     self     wait    child    calls  name
- 6.41      0.06     0.04     0.00     0.02      571  Kernel#===
- 3.17      0.00     0.00     0.00     0.00      172  Hash#[]
- 2.42      0.00     0.00     0.00     0.00       13  MonitorMixin#mon_exit
- 2.05      0.00     0.00     0.00     0.00       15  Array#each
- 1.56      0.00     0.00     0.00     0.00        6  Logger#add
- 1.55      0.00     0.00     0.00     0.00       13  MonitorMixin#mon_enter
- 1.36      0.03     0.00     0.00     0.03        1  ActionController::Integration::Session#process
- 1.31      0.00     0.00     0.00     0.00       13  MonitorMixin#mon_release
- 1.15      0.00     0.00     0.00     0.00        8  MonitorMixin#synchronize-1
- 1.09      0.00     0.00     0.00     0.00       23  Class#new
- 1.03      0.01     0.00     0.00     0.01        5  MonitorMixin#synchronize
- 0.89      0.00     0.00     0.00     0.00       74  Hash#default
- 0.89      0.00     0.00     0.00     0.00        6  Hodel3000CompliantLogger#format_message
- 0.80      0.00     0.00     0.00     0.00        9  c
- 0.80      0.00     0.00     0.00     0.00       11  ActiveRecord::ConnectionAdapters::ConnectionHandler#retrieve_connection_pool
- 0.79      0.01     0.00     0.00     0.01        1  ActionController::Benchmarking#perform_action_without_rescue
- 0.18      0.00     0.00     0.00     0.00       17  <Class::Object>#allocate
-
-
-

So what do these columns tell us:

-
    -
  • -

    -%self - The percentage of time spent processing the method. This is derived from self_time/total_time -

    -
    • -
  • -

    -total - The time spent in this method and its children. -

    -
    • -
  • -

    -self - The time spent in this method. -

    -
    • -
  • -

    -wait - Time processed was queued -

    -
    • -
  • -

    -child - The time spent in this method’s children. -

    -
    • -
  • -

    -calls - The number of times this method was called. -

    -
    • -
  • -

    -name - The name of the method. -

    -
    • -
-

Name can be displayed three seperate ways: - * #toplevel - The root method that calls all other methods - * MyObject#method - Example Hash#each, The class Hash is calling the method each - * <Object:MyObject>#test - The <> characters indicate a singleton method on a singleton class. Example <Class::Object>#allocate

-

Methods are sorted based on %self. Hence the ones taking the most time and resources will be at the top.

-

So for Array#each which is calling each on the class array. We find that it processing time is 2% of the total and was called 15 times. The rest of the information is 0.00 because the process is so fast it isn’t recording times less then 100 ms.

-
-
Flat File Memory Output
-
-

Thread ID: 2279160 -Total: 509.724609

-
-
-
%self     total     self     wait    child    calls  name
- 4.62     23.57    23.57     0.00     0.00       34  String#split
- 3.95     57.66    20.13     0.00    37.53        3  <Module::YAML>#quick_emit
- 2.82     23.70    14.35     0.00     9.34        2  <Module::YAML>#quick_emit-1
- 1.37     35.87     6.96     0.00    28.91        1  ActionView::Helpers::FormTagHelper#form_tag
- 1.35      7.69     6.88     0.00     0.81        1  ActionController::HttpAuthentication::Basic::ControllerMethods#authenticate_with_http_basic
- 1.06      6.09     5.42     0.00     0.67       90  String#gsub
- 1.01      5.13     5.13     0.00     0.00       27  Array#-
-
-
-

Very similar to the processing time format. The main difference here is that instead of calculating time we are now concerned with the amount of KB put into memory (or is it strictly into the heap) can I get clarification on this minor point?

-

So for <Module::YAML>#quick_emit which is singleton method on the class YAML it uses 57.66 KB in total, 23.57 through its own actions, 6.69 from actions it calls itself and that it was called twice.

-
-
Flat File Objects
-
-

Thread ID: 2279160 -Total: 6537.000000

-
-
-
%self     total     self     wait    child    calls  name
-15.16   1096.00   991.00     0.00   105.00       66  Hash#each
- 5.25    343.00   343.00     0.00     0.00        4  Mysql::Result#each_hash
- 4.74   2203.00   310.00     0.00  1893.00       42  Array#each
- 3.75   4529.00   245.00     0.00  4284.00        1  ActionView::Base::CompiledTemplates#_run_erb_47app47views47layouts47application46html46erb
- 2.00    136.00   131.00     0.00     5.00       90  String#gsub
- 1.73    113.00   113.00     0.00     0.00       34  String#split
- 1.44    111.00    94.00     0.00    17.00       31  Array#each-1
-
-
-
-
-
#TODO Find correct terminology for how to describe what this is exactly profiling as in are there really 2203 array objects or 2203 pointers to array objects?.
-
-

5.3. Graph Files

-

While the information gleamed from flat files is very useful we still don’t know which processes each method is calling. We only know how many. This is not true for a graph file. Below is a text representation of a graph file. The actual graph file is an html entity and an example of which can be found Here

-

#TODO (Handily the graph file has links both between it many processes and to the files that actually contain them for debugging. - )

-
-
Graph File
-
-

Thread ID: 21277412

-
-
-
  %total   %self     total      self    children               calls   Name
-/____________________________________________________________________________/
-100.00%   0.00%      8.77      0.00      8.77                   1     #toplevel*
-                     8.77      0.00      8.77                 1/1     Object#run_primes
-/____________________________________________________________________________/
-                     8.77      0.00      8.77                 1/1     #toplevel
-100.00%   0.00%      8.77      0.00      8.77                   1     Object#run_primes*
-                     0.02      0.00      0.02                 1/1     Object#make_random_array
-                     2.09      0.00      2.09                 1/1     Object#find_largest
-                     6.66      0.00      6.66                 1/1     Object#find_primes
-/____________________________________________________________________________/
-                     0.02      0.02      0.00                 1/1     Object#make_random_array
-0.18%     0.18%      0.02      0.02      0.00                   1     Array#each_index
-                     0.00      0.00      0.00             500/500     Kernel.rand
-                     0.00      0.00      0.00             500/501     Array#[]=
-/____________________________________________________________________________/
-
-
-

As you can see the calls have been separated into slices, no longer is the order determined by process time but instead from hierarchy. Each slice profiles a primary entry, with the primary entry’s parents being shown above itself and it’s children found below. A primary entry can be ascertained by it having values in the %total and %self columns. Here the main entry here have been bolded for connivence.

-

So if we look at the last slice. The primary entry would be Array#each_index. It takes 0.18% of the total process time and it is only called once. It is called from Object#make_random_array which is only called once. It’s children are Kernal.rand which is called by it all 500 its times that it was call in this action and Arry#[]= which was called 500 times by Array#each_index and once by some other entry.

-

5.4. Tree Files

-

It’s pointless trying to represent a tree file textually so here’s a few pretty pictures of it’s usefulness

-
KCachegrind Graph

-Graph created by KCachegrind -

-
KCachegrind List

-List created by KCachegrind -

-

#TODO Add a bit more information to this.

-
-

6. Getting to the Point of all of this

-
-

Now I know all of this is a bit dry and academic. But it’s a very powerful tool when you know how to leverage it properly. Which we are going to take a look at in our next section

-
-

7. Real Life Example

-
-

7.1. The setup

-

So I have been building this application for the last month and feel pretty good about the ruby code. I’m readying it for beta testers when I discover to my shock that with less then twenty people it starts to crash. It’s a pretty simple Ecommerce site so I’m very confused by what I’m seeing. On running looking through my log files I find to my shock that the lowest time for a page run is running around 240 ms. My database finds aren’t the problems so I’m lost as to what is happening to cause all this. Lets run a benchmark.

-
-
-
class HomepageTest < ActionController::PerformanceTest
-  # Replace this with your real tests.
-  def test_homepage
-    get '/'
-  end
-end
-
-
Output
-
-
HomepageTest#test_homepage (115 ms warmup)
-        process_time: 591 ms
-        memory: 3052.90 KB
-        objects: 59471
-
-

Obviously something is very very wrong here. 3052.90 Kb to load my minimal homepage. For Comparison for another site running well I get this for my homepage test.

-
-
Default
-
-
HomepageTest#test_homepage (19 ms warmup)
-        process_time: 26 ms
-              memory: 298.79 KB
-             objects: 1917
-
-

that over a factor of ten difference. Lets look at our flat process time file to see if anything pops out at us.

-
-
Process time
-
-
20.73      0.39     0.12     0.00     0.27      420  Pathname#cleanpath_aggressive
-17.07      0.14     0.10     0.00     0.04     3186  Pathname#chop_basename
- 6.47      0.06     0.04     0.00     0.02     6571  Kernel#===
- 5.04      0.06     0.03     0.00     0.03      840  Pathname#initialize
- 5.03      0.05     0.03     0.00     0.02        4  ERB::Compiler::ExplicitScanner#scan
- 4.51      0.03     0.03     0.00     0.00     9504  String#==
- 2.94      0.46     0.02     0.00     0.44     1393  String#gsub
- 2.66      0.09     0.02     0.00     0.07      480  Array#each
- 2.46      0.01     0.01     0.00     0.00     3606  Regexp#to_s
-
-

Yes indeed we seem to have found the problem. Pathname#cleanpath_aggressive is taking nearly a quarter our process time and Pathname#chop_basename another 17%. From here I do a few more benchmarks to make sure that these processes are slowing down the other pages. They are so now I know what I must do. If we can get rid of or shorten these processes we can make our pages run much quicker.

-

Now both of these are main ruby processes so are goal right now is to find out what other process is calling them. Glancing at our Graph file I see that #cleanpath is calling #cleanpath_aggressive. #cleanpath is being called by String#gsub and from there some html template errors. But my page seems to be rendering fine. why would it be calling template errors. I’m decide to check my object flat file to see if I can find any more information.

-
-
Objects Created
-
-
20.74  34800.00 12324.00     0.00 22476.00      420  Pathname#cleanpath_aggressive
-16.79  18696.00  9978.00     0.00  8718.00     3186  Pathname#chop_basename
-11.47  13197.00  6813.00     0.00  6384.00      480  Array#each
- 8.51  41964.00  5059.00     0.00 36905.00     1386  String#gsub
- 6.07   3606.00  3606.00     0.00     0.00     3606  Regexp#to_s
-
-

nope nothing new here. Lets look at memory usage

-
-
Memory Consuption
-
-
 40.17   1706.80  1223.70     0.00   483.10     3186  Pathname#chop_basename
- 14.92    454.47   454.47     0.00     0.00     3606  Regexp#to_s
-  7.09   2381.36   215.99     0.00  2165.37     1386  String#gsub
-  5.08    231.19   154.73     0.00    76.46      420  Pathname#prepend_prefix
-  2.34     71.35    71.35     0.00     0.00     1265  String#initialize_copy
-
-

Ok so it seems Regexp#to_s is the second costliest process. At this point I try to figure out what could be calling a regular expression cause I very rarely use them. Going over my standard layout I discover at the top.

-
-
-
<%if request.env["HTTP_USER_AGENT"].match(/Opera/)%>
-<%= stylesheet_link_tag "opera" %>
-<% end %>
-

That’s wrong. I mistakenly am using a search function for a simple compare function. Lets fix that.

-
-
-
<%if request.env["HTTP_USER_AGENT"] =~ /Opera/%>
-<%= stylesheet_link_tag "opera" %>
-<% end %>
-

I’ll now try my test again.

-
-
-
process_time: 75 ms
-              memory: 519.95 KB
-             objects: 6537
-
-

Much better. The problem has been solved. Now I should have realized earlier due to the String#gsub that my problem had to be with reqexp serch function but such knowledge comes with time. Looking through the mass output data is a skill.

-
-

8. Get Yourself a Game Plan

-
-

You end up dealing with a large amount of data whenever you profile an application. It’s crucial to use a rigorous approach to analyzing your application’s performance else fail miserably in a vortex of numbers. This leads us to -

-

8.1. The Analysis Process

-

I’m going to give an example methodology for conducting your benchmarking and profiling on an application. It is based on your typical scientific method.

-

For something as complex as Benchmarking you need to take any methodology with a grain of salt but there are some basic strictures that you can depend on.

-

Formulate a question you need to answer which is simple, tests the smallest measurable thing possible, and is exact. This is typically the hardest part of the experiment. From there some steps that you should follow are.

-
    -
  • -

    -Develop a set of variables and processes to measure in order to answer this question! -

    -
    • -
  • -

    -Profile based on the question and variables. Key problems to avoid when designing this experiment are: -

    -
      -
    • -

      -Confounding: Test one thing at a time, keep everything the same so you don’t poison the data with uncontrolled processes. -

      -
      • -
    • -

      -Cross Contamination: Make sure that runs from one test do not harm the other tests. -

      -
      • -
    • -

      -Steady States: If you’re testing long running process. You must take the ramp up time and performance hit into your initial measurements. -

      -
      • -
    • -

      -Sampling Error: Data should perform have a steady variance or range. If you get wild swings or sudden spikes, etc. then you must either account for the reason why or you have a sampling error. -

      -
      • -
    • -

      -Measurement Error: Aka Human error, always go through your calculations at least twice to make sure there are no mathematical errors. . -

      -
      • -
    -
    • -
  • -

    -Do a small run of the experiment to verify the design. -

    -
    • -
  • -

    -Use the small run to determine a proper sample size. -

    -
    • -
  • -

    -Run the test. -

    -
    • -
  • -

    -Perform the analysis on the results and determine where to go from there. -

    -
    • -
-

Note: Even though we are using the typical scientific method; developing a hypothesis is not always useful in terms of profiling.

-
-

9. Other Profiling Tools

-
-

There are a lot of great profiling tools out there. Some free, some not so free. This is a sort list detailing some of them.

-

9.1. httperf

-

http://www.hpl.hp.com/research/linux/httperf/

-

A necessary tool in your arsenal. Very useful for load testing your website.

-

#TODO write and link to a short article on how to use httperf. Anybody have a good tutorial availble.

-

9.2. Rails Analyzer

-

The Rails Analyzer project contains a collection of tools for Rails. It’s open source and pretty speedy. It’s not being actively worked on but is still contains some very useful tools.

-
    -
  • -

    -The Production Log Analyzer examines Rails log files and gives back a report. It also includes action_grep which will give you all log results for a particular action. -

    -
    • -
  • -

    -The Action Profiler similar to Ruby-Prof profiler. -

    -
    • -
  • -

    -rails_stat which gives a live counter of requests per second of a running Rails app. -

    -
    • -
  • -

    -The SQL Dependency Grapher allows you to visualize the frequency of table dependencies in a Rails application. -

    -
    • -
-

Their project homepage can be found at http://rails-analyzer.rubyforge.org/

-

The one major caveat is that it needs your log to be in a different format from how rails sets it up specifically SyslogLogger.

-

9.2.1. SyslogLogger

-

SyslogLogger is a Logger work-alike that logs via syslog instead of to a file. You can add SyslogLogger to your Rails production environment to aggregate logs between multiple machines.

-

More information can be found out at http://rails-analyzer.rubyforge.org/hacks/classes/SyslogLogger.html

-

If you don’t have access to your machines root system or just want something a bit easier to implement there is also a module developed by Geoffrey Grosenbach

-

9.2.2. A Hodel 3000 Compliant Logger for the Rest of Us

-

Directions taken from -link to module file

-

Just put the module in your lib directory and add this to your environment.rb in it’s config portion.

-
-
-
require 'hodel_3000_compliant_logger'
-config.logger = Hodel3000CompliantLogger.new(config.log_path)
-
-

It’s that simple. Your log output on restart should look like this.

-
-
Hodel 3000 Example
-
-
Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:
-Parameters: {"action"=>"shipping", "controller"=>"checkout"}
-Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: 
-[4;36;1mBook Columns (0.003155)   SHOW FIELDS FROM `books`
-Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: 
-[4;35;1mBook Load (0.000881)   SELECT * FROM `books` WHERE (`books`.`id` = 1 AND (`books`.`sold` = 1)) 
-Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: 
-[4;36;1mShippingAddress Columns (0.002683)   SHOW FIELDS FROM `shipping_addresses`
-Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: 
-[4;35;1mBook Load (0.000362)   SELECT ounces FROM `books` WHERE (`books`.`id` = 1) 
-Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:
-Rendering template within layouts/application
-Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:
-Rendering checkout/shipping
-Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: 
-[4;36;1mBook Load (0.000548)   SELECT * FROM `books`
-WHERE (sold = 0) LIMIT 3
-Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: 
-[4;35;1mAuthor Columns (0.002571)   SHOW FIELDS FROM `authors`
-Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:
-Author Load (0.000811)   SELECT * FROM `authors` WHERE (`authors`.`id` = 1) 
-Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:
-Rendered store/_new_books (0.01358)
-Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:
-Completed in 0.37297 (2 reqs/sec) | Rendering: 0.02971 (7%) | DB: 0.01697 (4%) | 200 OK [https://secure.jeffbooks/checkout/shipping]
-
-

9.3. Palmist

-

An open source mysql query analyzer. Full featured and easy to work with. Also requires Hodel 3000 -http://www.flyingmachinestudios.com/projects/

-

9.4. New Relic

-

http://www.newrelic.com/

-

Pretty nifty performance tools, pricey though. They do have a basic free -service both for when in development and when you put your application into production. Very simple installation and signup.

-

#TODO more in-depth without being like an advertisement.

-

9.4.1. Manage

-

Like new relic a production monitoring tool.

-
-

10. Changelog

-
-

Lighthouse ticket

-
    -
  • -

    -October 17, 2008: First revision by Pratik -

    -
    • -
  • -

    -September 6, 2008: Initial version by Matthew Bergman <MzbPhoto@gmail.com> -

    -
    • -
-
- -
-
- - diff --git a/railties/doc/guides/html/index.html b/railties/doc/guides/html/index.html index 38e1b310d7..b2dce5cd67 100644 --- a/railties/doc/guides/html/index.html +++ b/railties/doc/guides/html/index.html @@ -348,7 +348,7 @@ of your code.

-
Benchmarking and Profiling Rails Applications
+
Performance testing Rails Applications
diff --git a/railties/doc/guides/html/performance_testing.html b/railties/doc/guides/html/performance_testing.html new file mode 100644 index 0000000000..c03447289f --- /dev/null +++ b/railties/doc/guides/html/performance_testing.html @@ -0,0 +1,577 @@ + + + + + Performance testing Rails Applications + + + + + + + + + +
+ + + +
+

Performance testing Rails Applications

+
+
+

This guide covers the benchmarking and profiling tactics/tools of Rails and Ruby in general. By referring to this guide, you will be able to:

+
    +
  • +

    +Understand the various types of benchmarking and profiling metrics +

    +
    • +
  • +

    +Generate performance/benchmarking tests +

    +
    • +
  • +

    +Use GC patched Ruby binary to measure memory usage and object allocation +

    +
    • +
  • +

    +Understand the information provided by Rails inside the log files +

    +
    • +
  • +

    +Learn about 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 plesant browsing experience to the end users and cutting cost of unnecessary hardwares is important for any web application.

+
+
+

1. Using and understanding the log files

+
+

Rails logs files containt basic but very useful information about the time taken to serve every request. A typical log entry looks something like :

+
+
+
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 from that log entry:

+
+
+
Completed in 5ms (View: 2, DB: 0) | 200 OK [http://0.0.0.0/items]
+

This data is fairly straight forward to understand. Rails uses millisecond(ms) as the metric to measures 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.

+
+

2. Helper methods

+
+

Rails provides various helper methods inside Active Record, Action Controller and Action View to measure the time taken by a specific code. The method is called benchmark() in all three components.

+
+
+
Project.benchmark("Creating project") do
+  project = Project.create("name" => "stuff")
+  project.create_manager("name" => "David")
+  project.milestones << Milestone.find(:all)
+end
+

The above code benchmarks the multiple statments enclosed inside Project.benchmark("Creating project") do..end block and prints the results inside log files. The statement inside log files will look like:

+
+
+
Creating projectem (185.3ms)
+

Please refer to API docs for optional options to benchmark()

+

Similarly, you could use this helper method inside controllers ( Note that it’s a class method here ):

+
+
+
def process_projects
+  self.class.benchmark("Processing projects") do
+    Project.process(params[:project_ids])
+    Project.update_cached_projects
+  end
+end
+

and views:

+
+
+
<% benchmark("Showing projects partial") do %>
+  <%= render :partial => @projects %>
+<% end %>
+
+

3. Performance Test Cases

+
+

Rails provides a very easy way to write performance test cases, which look just like the regular integration tests. Performance tests run a code profiler on your test methods. Profiling output for combinations of each test method, measurement, and output format are written to your tmp/performance directory. By default, process_time is measured and both flat and graph_html output formats are written, so you’ll have two output files per test method.

+

If you have a look at test/performance/browsing_test.rb in a newly created Rails application:

+
+
+
require 'test_helper'
+require 'performance_test_help'
+
+# Profiling results for each test method are written to tmp/performance.
+class BrowsingTest < ActionController::PerformanceTest
+  def test_homepage
+    get '/'
+  end
+end
+

This is an automatically generated example performance test file, for testing performance of homepage(/) of the application.

+

3.1. Modes

+

Performance test cases can be run in two modes : Benchmarking and Profling.

+

3.1.1. Benchmarking

+

Benchmarking helps you find out how fast are your test cases. To run performance tests in benchmarking mode:

+
+
+
[lifo@null application (master)]$ rake test:benchmark
+

3.1.2. Profiling

+

Profiling helps introspect into your test cases and figure out which are the slow parts. To run performance tests in profiling mode:

+
+
+
[lifo@null application (master)]$ rake test:profile
+

3.2. Metrics

+

Benchmarking and profiling run performance test cases in various modes to help precisely figure out the where the problem lies.

+

3.2.1. 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.

+

Mode : Benchmarking, Profiling

+

3.2.2. Memory

+

Measures the amount of memory used for the performance test case.

+

Mode : Benchmarking, Profiling

+

3.2.3. Objects

+

Measures the number of objects allocated for the performance test case.

+

Mode : Benchmarking, Profiling

+

3.2.4. GC Runs

+

Measures the number of times GC was invoked for the performance test case.

+

Mode : Benchmarking

+

3.2.5. GC Time

+

Measures the amount of time spent in GC for the performance test case.

+

Mode : Benchmarking

+

3.3. Understanding the output

+

3.3.1. Benchmarking

+

3.3.2. Profiling

+

3.4. Preparing Ruby and Ruby-prof

+

Before we go ahead, Rails performance testing requires you to build a special Ruby binary with some super powers - GC patch for measuring GC Runs/Time. This process is very straight forward. If you’ve never compiled a Ruby binary before, you can follow the following steps to build a ruby binary inside your home directory:

+

3.4.1. Compile

+
+
+
[lifo@null ~]$ mkdir rubygc
+[lifo@null ~]$ wget ftp://ftp.ruby-lang.org/pub/ruby/1.8/ruby-1.8.6-p111.tar.gz
+[lifo@null ~]$ tar -xzvf ruby-1.8.6-p111.tar.gz
+[lifo@null ~]$ cd ruby-1.8.6-p111
+[lifo@null ruby-1.8.6-p111]$ curl http://rubyforge.org/tracker/download.php/1814/7062/17676/3291/ruby186gc.patch | patch -p0
+[lifo@null ruby-1.8.6-p111]$ ./configure --prefix=/Users/lifo/rubygc
+[lifo@null ruby-1.8.6-p111]$ make && make install
+

3.4.2. Prepare aliases

+

Add the following lines in your ~/.profile for convenience:

+
+
+
alias gcruby='/Users/lifo/rubygc/bin/ruby'
+alias gcrake='/Users/lifo/rubygc/bin/rake'
+alias gcgem='/Users/lifo/rubygc/bin/gem'
+alias gcirb='/Users/lifo/rubygc/bin/irb'
+alias gcrails='/Users/lifo/rubygc/bin/rails'
+
+

3.4.3. Install rubygems and some basic gems

+

Download Rubygems and install it from source. Afterwards, install rake. rails, ruby-prof and rack gems:

+
+
+
[lifo@null ~]$ gcgem install rake
+[lifo@null ~]$ gcgem install rails
+[lifo@null ~]$ gcgem install ruby-prof
+[lifo@null ~]$ gcgem install rack
+
+

3.4.4. Install MySQL gem

+
+
+
[lifo@null ~]$ gcgem install mysql
+
+

If this fails, you can try to install it manually:

+
+
+
[lifo@null ~]$ cd /Users/lifo/rubygc/lib/ruby/gems/1.8/gems/mysql-2.7/
+[lifo@null mysql-2.7]$ gcruby extconf.rb --with-mysql-config
+[lifo@null mysql-2.7]$ make && make install
+
+

3.5. Generating performance test

+

Rails provides a generator for creating new performance tests:

+
+
+
[lifo@null application (master)]$ script/generate performance_test homepage
+

This will generate test/performance/homepage_test.rb:

+
+
+
require 'test_helper'
+require 'performance_test_help'
+
+class HomepageTest < ActionController::PerformanceTest
+  # Replace this with your real tests.
+  def test_homepage
+    get '/'
+  end
+end
+

Which you can modify to suit your needs.

+
+

4. Other Profiling Tools

+
+

There are a lot of great profiling tools out there. Some free, some not so free. This is a sort list detailing some of them.

+

4.1. httperf

+

http://www.hpl.hp.com/research/linux/httperf/

+

A necessary tool in your arsenal. Very useful for load testing your website.

+

#TODO write and link to a short article on how to use httperf. Anybody have a good tutorial availble.

+

4.2. Rails Analyzer

+

The Rails Analyzer project contains a collection of tools for Rails. It’s open source and pretty speedy. It’s not being actively worked on but is still contains some very useful tools.

+
    +
  • +

    +The Production Log Analyzer examines Rails log files and gives back a report. It also includes action_grep which will give you all log results for a particular action. +

    +
    • +
  • +

    +The Action Profiler similar to Ruby-Prof profiler. +

    +
    • +
  • +

    +rails_stat which gives a live counter of requests per second of a running Rails app. +

    +
    • +
  • +

    +The SQL Dependency Grapher allows you to visualize the frequency of table dependencies in a Rails application. +

    +
    • +
+

Their project homepage can be found at http://rails-analyzer.rubyforge.org/

+

The one major caveat is that it needs your log to be in a different format from how rails sets it up specifically SyslogLogger.

+

4.2.1. SyslogLogger

+

SyslogLogger is a Logger work-alike that logs via syslog instead of to a file. You can add SyslogLogger to your Rails production environment to aggregate logs between multiple machines.

+

More information can be found out at http://rails-analyzer.rubyforge.org/hacks/classes/SyslogLogger.html

+

If you don’t have access to your machines root system or just want something a bit easier to implement there is also a module developed by Geoffrey Grosenbach

+

4.2.2. A Hodel 3000 Compliant Logger for the Rest of Us

+

Directions taken from +link to module file

+

Just put the module in your lib directory and add this to your environment.rb in it’s config portion.

+
+
+
require 'hodel_3000_compliant_logger'
+config.logger = Hodel3000CompliantLogger.new(config.log_path)
+
+

It’s that simple. Your log output on restart should look like this.

+
+
Hodel 3000 Example
+
+
Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:
+Parameters: {"action"=>"shipping", "controller"=>"checkout"}
+Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: 
+[4;36;1mBook Columns (0.003155)   SHOW FIELDS FROM `books`
+Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: 
+[4;35;1mBook Load (0.000881)   SELECT * FROM `books` WHERE (`books`.`id` = 1 AND (`books`.`sold` = 1)) 
+Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: 
+[4;36;1mShippingAddress Columns (0.002683)   SHOW FIELDS FROM `shipping_addresses`
+Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: 
+[4;35;1mBook Load (0.000362)   SELECT ounces FROM `books` WHERE (`books`.`id` = 1) 
+Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:
+Rendering template within layouts/application
+Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:
+Rendering checkout/shipping
+Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: 
+[4;36;1mBook Load (0.000548)   SELECT * FROM `books`
+WHERE (sold = 0) LIMIT 3
+Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: 
+[4;35;1mAuthor Columns (0.002571)   SHOW FIELDS FROM `authors`
+Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:
+Author Load (0.000811)   SELECT * FROM `authors` WHERE (`authors`.`id` = 1) 
+Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:
+Rendered store/_new_books (0.01358)
+Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:
+Completed in 0.37297 (2 reqs/sec) | Rendering: 0.02971 (7%) | DB: 0.01697 (4%) | 200 OK [https://secure.jeffbooks/checkout/shipping]
+
+

4.3. Palmist

+

An open source mysql query analyzer. Full featured and easy to work with. Also requires Hodel 3000 +http://www.flyingmachinestudios.com/projects/

+

4.4. New Relic

+

http://www.newrelic.com/

+

Pretty nifty performance tools, pricey though. They do have a basic free +service both for when in development and when you put your application into production. Very simple installation and signup.

+

#TODO more in-depth without being like an advertisement.

+

4.4.1. Manage

+

Like new relic a production monitoring tool.

+
+

5. Changelog

+
+

Lighthouse ticket

+
    +
  • +

    +October 17, 2008: First revision by Pratik +

    +
    • +
  • +

    +September 6, 2008: Initial version by Matthew Bergman <MzbPhoto@gmail.com> +

    +
    • +
+
+ +
+
+ + diff --git a/railties/doc/guides/source/benchmarking_and_profiling/appendix.txt b/railties/doc/guides/source/benchmarking_and_profiling/appendix.txt deleted file mode 100644 index 8e2e383ff3..0000000000 --- a/railties/doc/guides/source/benchmarking_and_profiling/appendix.txt +++ /dev/null @@ -1,95 +0,0 @@ -== Other Profiling Tools == - -There are a lot of great profiling tools out there. Some free, some not so free. This is a sort list detailing some of them. - -=== httperf === -http://www.hpl.hp.com/research/linux/httperf/[http://www.hpl.hp.com/research/linux/httperf/] - -A necessary tool in your arsenal. Very useful for load testing your website. - -#TODO write and link to a short article on how to use httperf. Anybody have a good tutorial availble. - - -=== Rails Analyzer === - -The Rails Analyzer project contains a collection of tools for Rails. It's open source and pretty speedy. It's not being actively worked on but is still contains some very useful tools. - -* The Production Log Analyzer examines Rails log files and gives back a report. It also includes action_grep which will give you all log results for a particular action. - -* The Action Profiler similar to Ruby-Prof profiler. - -* rails_stat which gives a live counter of requests per second of a running Rails app. - -* The SQL Dependency Grapher allows you to visualize the frequency of table dependencies in a Rails application. - -Their project homepage can be found at http://rails-analyzer.rubyforge.org/[http://rails-analyzer.rubyforge.org/] - -The one major caveat is that it needs your log to be in a different format from how rails sets it up specifically SyslogLogger. - - -==== SyslogLogger ==== - -SyslogLogger is a Logger work-alike that logs via syslog instead of to a file. You can add SyslogLogger to your Rails production environment to aggregate logs between multiple machines. - -More information can be found out at http://rails-analyzer.rubyforge.org/hacks/classes/SyslogLogger.html[http://rails-analyzer.rubyforge.org/hacks/classes/SyslogLogger.html] - -If you don't have access to your machines root system or just want something a bit easier to implement there is also a module developed by Geoffrey Grosenbach - -==== A Hodel 3000 Compliant Logger for the Rest of Us ==== - -Directions taken from -http://topfunky.net/svn/plugins/hodel_3000_compliant_logger/lib/hodel_3000_compliant_logger.rb[link to module file] - -Just put the module in your lib directory and add this to your environment.rb in it's config portion. - ------------------------------------------------------------- -require 'hodel_3000_compliant_logger' -config.logger = Hodel3000CompliantLogger.new(config.log_path) -------------------------------------------------------------- - -It's that simple. Your log output on restart should look like this. - -.Hodel 3000 Example ----------------------------------------------------------------------------- -Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: -Parameters: {"action"=>"shipping", "controller"=>"checkout"} -Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:  -[4;36;1mBook Columns (0.003155) SHOW FIELDS FROM `books` -Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:  -[4;35;1mBook Load (0.000881) SELECT * FROM `books` WHERE (`books`.`id` = 1 AND (`books`.`sold` = 1))  -Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:  -[4;36;1mShippingAddress Columns (0.002683) SHOW FIELDS FROM `shipping_addresses` -Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:  -[4;35;1mBook Load (0.000362) SELECT ounces FROM `books` WHERE (`books`.`id` = 1)  -Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: -Rendering template within layouts/application -Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: -Rendering checkout/shipping -Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:  -[4;36;1mBook Load (0.000548) SELECT * FROM `books` -WHERE (sold = 0) LIMIT 3 -Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:  -[4;35;1mAuthor Columns (0.002571) SHOW FIELDS FROM `authors` -Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: -Author Load (0.000811) SELECT * FROM `authors` WHERE (`authors`.`id` = 1)  -Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: -Rendered store/_new_books (0.01358) -Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: -Completed in 0.37297 (2 reqs/sec) | Rendering: 0.02971 (7%) | DB: 0.01697 (4%) | 200 OK [https://secure.jeffbooks/checkout/shipping] ----------------------------------------------------------------------------- - -=== Palmist === -An open source mysql query analyzer. Full featured and easy to work with. Also requires Hodel 3000 -http://www.flyingmachinestudios.com/projects/[http://www.flyingmachinestudios.com/projects/] - -=== New Relic === -http://www.newrelic.com/[http://www.newrelic.com/] - -Pretty nifty performance tools, pricey though. They do have a basic free -service both for when in development and when you put your application into production. Very simple installation and signup. - -#TODO more in-depth without being like an advertisement. - -==== Manage ==== - -Like new relic a production monitoring tool. diff --git a/railties/doc/guides/source/benchmarking_and_profiling/digging_deeper.txt b/railties/doc/guides/source/benchmarking_and_profiling/digging_deeper.txt deleted file mode 100644 index fe22fba078..0000000000 --- a/railties/doc/guides/source/benchmarking_and_profiling/digging_deeper.txt +++ /dev/null @@ -1,105 +0,0 @@ -== Real Life Example == -=== The setup === - -So I have been building this application for the last month and feel pretty good about the ruby code. I'm readying it for beta testers when I discover to my shock that with less then twenty people it starts to crash. It's a pretty simple Ecommerce site so I'm very confused by what I'm seeing. On running looking through my log files I find to my shock that the lowest time for a page run is running around 240 ms. My database finds aren't the problems so I'm lost as to what is happening to cause all this. Lets run a benchmark. - - -[source, ruby] ----------------------------------------------------------------------------- -class HomepageTest < ActionController::PerformanceTest - # Replace this with your real tests. - def test_homepage - get '/' - end -end ----------------------------------------------------------------------------- - -.Output ----------------------------------------------------------------------------- -HomepageTest#test_homepage (115 ms warmup) - process_time: 591 ms - memory: 3052.90 KB - objects: 59471 ----------------------------------------------------------------------------- - - - -Obviously something is very very wrong here. 3052.90 Kb to load my minimal homepage. For Comparison for another site running well I get this for my homepage test. - -.Default ----------------------------------------------------------------------------- -HomepageTest#test_homepage (19 ms warmup) - process_time: 26 ms - memory: 298.79 KB - objects: 1917 ----------------------------------------------------------------------------- - -that over a factor of ten difference. Lets look at our flat process time file to see if anything pops out at us. - -.Process time ----------------------------------------------------------------------------- -20.73 0.39 0.12 0.00 0.27 420 Pathname#cleanpath_aggressive -17.07 0.14 0.10 0.00 0.04 3186 Pathname#chop_basename - 6.47 0.06 0.04 0.00 0.02 6571 Kernel#=== - 5.04 0.06 0.03 0.00 0.03 840 Pathname#initialize - 5.03 0.05 0.03 0.00 0.02 4 ERB::Compiler::ExplicitScanner#scan - 4.51 0.03 0.03 0.00 0.00 9504 String#== - 2.94 0.46 0.02 0.00 0.44 1393 String#gsub - 2.66 0.09 0.02 0.00 0.07 480 Array#each - 2.46 0.01 0.01 0.00 0.00 3606 Regexp#to_s ----------------------------------------------------------------------------- - -Yes indeed we seem to have found the problem. Pathname#cleanpath_aggressive is taking nearly a quarter our process time and Pathname#chop_basename another 17%. From here I do a few more benchmarks to make sure that these processes are slowing down the other pages. They are so now I know what I must do. *If we can get rid of or shorten these processes we can make our pages run much quicker*. - -Now both of these are main ruby processes so are goal right now is to find out what other process is calling them. Glancing at our Graph file I see that #cleanpath is calling #cleanpath_aggressive. #cleanpath is being called by String#gsub and from there some html template errors. But my page seems to be rendering fine. why would it be calling template errors. I'm decide to check my object flat file to see if I can find any more information. - -.Objects Created ----------------------------------------------------------------------------- -20.74 34800.00 12324.00 0.00 22476.00 420 Pathname#cleanpath_aggressive -16.79 18696.00 9978.00 0.00 8718.00 3186 Pathname#chop_basename -11.47 13197.00 6813.00 0.00 6384.00 480 Array#each - 8.51 41964.00 5059.00 0.00 36905.00 1386 String#gsub - 6.07 3606.00 3606.00 0.00 0.00 3606 Regexp#to_s ----------------------------------------------------------------------------- - -nope nothing new here. Lets look at memory usage - -.Memory Consuption ----------------------------------------------------------------------------- - 40.17 1706.80 1223.70 0.00 483.10 3186 Pathname#chop_basename - 14.92 454.47 454.47 0.00 0.00 3606 Regexp#to_s - 7.09 2381.36 215.99 0.00 2165.37 1386 String#gsub - 5.08 231.19 154.73 0.00 76.46 420 Pathname#prepend_prefix - 2.34 71.35 71.35 0.00 0.00 1265 String#initialize_copy ----------------------------------------------------------------------------- - -Ok so it seems Regexp#to_s is the second costliest process. At this point I try to figure out what could be calling a regular expression cause I very rarely use them. Going over my standard layout I discover at the top. - - -[source, html] ----------------------------------------------------------------------------- -<%if request.env["HTTP_USER_AGENT"].match(/Opera/)%> -<%= stylesheet_link_tag "opera" %> -<% end %> ----------------------------------------------------------------------------- - -That's wrong. I mistakenly am using a search function for a simple compare function. Lets fix that. - - -[source, html] ----------------------------------------------------------------------------- -<%if request.env["HTTP_USER_AGENT"] =~ /Opera/%> -<%= stylesheet_link_tag "opera" %> -<% end %> ----------------------------------------------------------------------------- - -I'll now try my test again. - ----------------------------------------------------------------------------- -process_time: 75 ms - memory: 519.95 KB - objects: 6537 ----------------------------------------------------------------------------- - -Much better. The problem has been solved. Now I should have realized earlier due to the String#gsub that my problem had to be with reqexp serch function but such knowledge comes with time. Looking through the mass output data is a skill. - diff --git a/railties/doc/guides/source/benchmarking_and_profiling/edge_rails_features.txt b/railties/doc/guides/source/benchmarking_and_profiling/edge_rails_features.txt deleted file mode 100644 index 765a1e2120..0000000000 --- a/railties/doc/guides/source/benchmarking_and_profiling/edge_rails_features.txt +++ /dev/null @@ -1,185 +0,0 @@ -== Performance Testing Built into Rails == - -As of June 20, 2008 edge rails has had a new type of Unit test geared towards profiling. Of course like most great things, getting it working takes bit of work. The test relies on statistics gathered from the Garbage Collection that isn't readily available from standard compiled ruby. There is a patch located at http://rubyforge.org/tracker/download.php/1814/7062/17676/3291/ruby186gc.patch[http://rubyforge.org/tracker/download.php/1814/7062/17676/3291/ruby186gc.patch] - -Also the test requires a new version of Ruby-Prof version of 0.6.1. It is not readily available at the moment and can most easily be found as a tarball on github. It's repository is located at git://github.com/jeremy/ruby-prof.git. - -What follows is a description of how to set up an alternative ruby install to use these features - -=== Compiling the Interpreter === - - -[source, shell] ----------------------------------------------------------------------------- -[User ~]$ mkdir rubygc -[User ~]$ wget ftp://ftp.ruby-lang.org/pub/ruby/1.8/ruby-1.8.6-p111.tar.gz -[User ~]$ tar -xzvf ruby-1.8.6-p111.tar.gz -[User ~]$ cd ruby-1.8.6-p111 -[User ruby-1.8.6-p111]$ curl http://rubyforge.org/tracker/download.php/1814/7062/17676/3291/ruby186gc.patch | patch -p0 - -#I like putting my alternative ruby builds in an opt directory, set the prefix to where ever you feel is most comfortable. - -[User ruby-1.8.6-p111]$ ./configure --prefix=/opt/rubygc -[User ruby-1.8.6-p111]$ sudo make && make install ----------------------------------------------------------------------------- - -Add the following lines in your \~/.profile or \~/.bash\_login for convenience. - ----------------------------------------------------------------------------- -alias gcruby='/opt/rubygc/rubygc/bin/ruby' -alias gcrake='/opt/rubygc/rubygc/bin/rake' -alias gcgem='/opt/rubygc/rubygc/bin/gem' -alias gcirb=/opt/rubygc/rubygc/bin/irb' -alias gcrails='/opt/rubygc/rubygc/bin/rails' ----------------------------------------------------------------------------- - -=== Installing RubyGems === - -Next we need to install rubygems and rails so that we can use the interpreter properly. - - -[source, shell] ----------------------------------------------------------------------------- -[User ~]$ wget http://rubyforge.org/frs/download.php/38646/rubygems-1.2.0.tgz -[User ~]$ tar -xzvf rubygems-1.2.0.tgz -[User ~]$ cd rubygems-1.2.0 -[User rubygems-1.2.0]$ gcruby setup.rb -[User rubygems-1.2.0]$ cd ~ -[User ~]$ gcgem install rake -[User ~]$ gcgem install mysql -[User ~]$ gcgem install rails ----------------------------------------------------------------------------- - -If installing mysql gem fails ( like it did for me ), you will have to manually install it : - -[source, shell] ----------------------------------------------------------------------------- -[User ~]$ cd /Users/lifo/rubygc/lib/ruby/gems/1.8/gems/mysql-2.7/ -[User mysql-2.7]$ gcruby extconf.rb --with-mysql-config -[User mysql-2.7]$ make && make install ----------------------------------------------------------------------------- - -=== Installing Jeremy Kemper's ruby-prof === - -We are in the home stretch. All we need now is ruby-proff 0.6.1 - - -[source, shell] ----------------------------------------------------------------------------- -[User ~]$ git clone git://github.com/jeremy/ruby-prof.git -[User ~]$ cd ruby-prof/ -[User ruby-prof (master)]$ gcrake gem -[User ruby-prof (master)]$ gcgem install pkg/ruby-prof-0.6.1.gem ----------------------------------------------------------------------------- - -Finished, go get yourself a power drink! - -=== Ok so I lied, a few more things we need to do === - -You have everything we need to start profiling through rails Unit Testing. Unfortunately we are still missing a few files. I'm going to do the next step on a fresh Rails app, but it will work just as well on developmental 2.1 rails application. - -==== The Rails App ==== - -First I need to generate a rail app - -[source, shell] ----------------------------------------------------------------------------- -[User ~]$ gcrails profiling_tester -d mysql -[User ~]$ cd profiling_tester -[User profiling_tester]$ script/generate scaffold item name:string -[User profiling_tester]$ gcrake db:create:all -[User profiling_tester]$ gcrake db:migrate -[User profiling_tester (master)]$ rm public/index.html ----------------------------------------------------------------------------- - -Now I'm going to init it as a git repository and add edge rails as a submodule to it. - -[source, shell] ----------------------------------------------------------------------------- -[User profiling_tester]$ git init -[User profiling_tester (master)]$ git submodule add git://github.com/rails/rails.git vendor/rails ----------------------------------------------------------------------------- - -Finally we want to change config.cache_classes to true in our environment.rb - ----------------------------------------------------------------------------- -config.cache_classes = true ----------------------------------------------------------------------------- - -If we don't cache classes, then the time Rails spends reloading and compiling our models and controllers will confound our results. Obviously we will try to make our test setup as similar as possible to our production environment. - -=== Generating and Fixing the tests === - -Ok next we need to generate the test script. - -[source, shell] ----------------------------------------------------------------------------- -[User profiling_tester (master)]$ script/generate performance_test homepage ----------------------------------------------------------------------------- - -This will generate _test/performance/homepage_test.rb_ for you. However, as I have generated the project using Rails 2.1 gem, we'll need to manually generate one more file before we can go ahead. - -We need to put the following inside _test/performance/test_helper.rb - - -[source, ruby] ----------------------------------------------------------------------------- -require 'test_helper' -require 'performance_test_help' ----------------------------------------------------------------------------- - -Though this depends where you run your tests from and your system config. I myself run my tests from the Application root directory - -so instead of - -[source, ruby] ----------------------------------------------------------------------------- -require 'test_helper' - -#I have - -require 'test/test_helper' ----------------------------------------------------------------------------- - -Also I needed to change homepage_test.rb to reflect this also - -[source, ruby] ----------------------------------------------------------------------------- -require 'test/performance/test_helper.rb' ----------------------------------------------------------------------------- - -=== Testing === - -#TODO is there some way to compare multiple request at once like ruby_analyze - -Now, if we look at the generated performance test ( one we generated using _script/generate performance_test_ ), it'll look something like : - -[source, ruby] ----------------------------------------------------------------------------- -.require 'performance/test_helper' - -class HomepageTest < ActionController::PerformanceTest - # Replace this with your real tests. - def test_homepage - get '/' - end -end ----------------------------------------------------------------------------- - - -The format looks very similar to that of an integration test. And guess what, that's what it is. But that doesn't stop you from testing your Model methods. You could very well write something like : - -[source, ruby] ----------------------------------------------------------------------------- -require 'performance/test_helper' - -class UserModelTest < ActionController::PerformanceTest - # Replace this with your real tests. - def test_slow_find - User.this_takes_shlong_to_run - end -end ----------------------------------------------------------------------------- - - -Which is very useful way to profile individual processes. diff --git a/railties/doc/guides/source/benchmarking_and_profiling/gameplan.txt b/railties/doc/guides/source/benchmarking_and_profiling/gameplan.txt deleted file mode 100644 index 1f1d365eff..0000000000 --- a/railties/doc/guides/source/benchmarking_and_profiling/gameplan.txt +++ /dev/null @@ -1,27 +0,0 @@ -== Get Yourself a Game Plan == - -You end up dealing with a large amount of data whenever you profile an application. It's crucial to use a rigorous approach to analyzing your application's performance else fail miserably in a vortex of numbers. This leads us to - - -=== The Analysis Process === - -I’m going to give an example methodology for conducting your benchmarking and profiling on an application. It is based on your typical scientific method. - -For something as complex as Benchmarking you need to take any methodology with a grain of salt but there are some basic strictures that you can depend on. - -Formulate a question you need to answer which is simple, tests the smallest measurable thing possible, and is exact. This is typically the hardest part of the experiment. From there some steps that you should follow are. - -* Develop a set of variables and processes to measure in order to answer this question! -* Profile based on the question and variables. Key problems to avoid when designing this experiment are: - - Confounding: Test one thing at a time, keep everything the same so you don't poison the data with uncontrolled processes. - - Cross Contamination: Make sure that runs from one test do not harm the other tests. - - Steady States: If you’re testing long running process. You must take the ramp up time and performance hit into your initial measurements. - - Sampling Error: Data should perform have a steady variance or range. If you get wild swings or sudden spikes, etc. then you must either account for the reason why or you have a sampling error. - - Measurement Error: Aka Human error, always go through your calculations at least twice to make sure there are no mathematical errors. . -* Do a small run of the experiment to verify the design. -* Use the small run to determine a proper sample size. -* Run the test. -* Perform the analysis on the results and determine where to go from there. - -Note: Even though we are using the typical scientific method; developing a hypothesis is not always useful in terms of profiling. - - diff --git a/railties/doc/guides/source/benchmarking_and_profiling/rubyprof.txt b/railties/doc/guides/source/benchmarking_and_profiling/rubyprof.txt deleted file mode 100644 index fa01d413a1..0000000000 --- a/railties/doc/guides/source/benchmarking_and_profiling/rubyprof.txt +++ /dev/null @@ -1,179 +0,0 @@ -== Understanding Performance Tests Outputs == - -=== Our First Performance Test === - -So how do we profile a request. - -One of the things that is important to us is how long it takes to render the home page - so let's make a request to the home page. Once the request is complete, the results will be outputted in the terminal. - -In the terminal run - -[source, ruby] ----------------------------------------------------------------------------- -[User profiling_tester]$ gcruby tests/performance/homepage.rb ----------------------------------------------------------------------------- - -After the tests runs for a few seconds you should see something like this. - ----------------------------------------------------------------------------- -HomepageTest#test_homepage (19 ms warmup) - process_time: 26 ms - memory: 298.79 KB - objects: 1917 - -Finished in 2.207428 seconds. ----------------------------------------------------------------------------- - -Simple but efficient. - -* Process Time refers to amount of time necessary to complete the action. -* memory is the amount of information loaded into memory -* object ??? #TODO find a good definition. Is it the amount of objects put into a ruby heap for this process? - -In addition we also gain three types of itemized log files for each of these outputs. They can be found in your tmp directory of your application. - -*The Three types are* - -* Flat File - A simple text file with the data laid out in a grid -* Graphical File - A html colored coded version of the simple text file with hyperlinks between the various methods. Most useful is the bolding of the main processes for each portion of the action. -* Tree File - A file output that can be use in conjunction with KCachegrind to visualize the process - -NOTE: KCachegrind is Linux only. For Mac this means you have to do a full KDE install to have it working in your OS. Which is over 3 gigs in size. For windows there is clone called wincachegrind but it is no longer actively being developed. - -Below are examples for Flat Files and Graphical Files - -=== Flat Files === - -.Flat File Output Processing Time -============================================================================ -Thread ID: 2279160 -Total: 0.026097 - - %self total self wait child calls name - 6.41 0.06 0.04 0.00 0.02 571 Kernel#=== - 3.17 0.00 0.00 0.00 0.00 172 Hash#[] - 2.42 0.00 0.00 0.00 0.00 13 MonitorMixin#mon_exit - 2.05 0.00 0.00 0.00 0.00 15 Array#each - 1.56 0.00 0.00 0.00 0.00 6 Logger#add - 1.55 0.00 0.00 0.00 0.00 13 MonitorMixin#mon_enter - 1.36 0.03 0.00 0.00 0.03 1 ActionController::Integration::Session#process - 1.31 0.00 0.00 0.00 0.00 13 MonitorMixin#mon_release - 1.15 0.00 0.00 0.00 0.00 8 MonitorMixin#synchronize-1 - 1.09 0.00 0.00 0.00 0.00 23 Class#new - 1.03 0.01 0.00 0.00 0.01 5 MonitorMixin#synchronize - 0.89 0.00 0.00 0.00 0.00 74 Hash#default - 0.89 0.00 0.00 0.00 0.00 6 Hodel3000CompliantLogger#format_message - 0.80 0.00 0.00 0.00 0.00 9 c - 0.80 0.00 0.00 0.00 0.00 11 ActiveRecord::ConnectionAdapters::ConnectionHandler#retrieve_connection_pool - 0.79 0.01 0.00 0.00 0.01 1 ActionController::Benchmarking#perform_action_without_rescue - 0.18 0.00 0.00 0.00 0.00 17 #allocate -============================================================================ - -So what do these columns tell us: - - * %self - The percentage of time spent processing the method. This is derived from self_time/total_time - * total - The time spent in this method and its children. - * self - The time spent in this method. - * wait - Time processed was queued - * child - The time spent in this method's children. - * calls - The number of times this method was called. - * name - The name of the method. - -Name can be displayed three seperate ways: - * #toplevel - The root method that calls all other methods - * MyObject#method - Example Hash#each, The class Hash is calling the method each - * #test - The <> characters indicate a singleton method on a singleton class. Example #allocate - -Methods are sorted based on %self. Hence the ones taking the most time and resources will be at the top. - -So for Array#each which is calling each on the class array. We find that it processing time is 2% of the total and was called 15 times. The rest of the information is 0.00 because the process is so fast it isn't recording times less then 100 ms. - - -.Flat File Memory Output -============================================================================ -Thread ID: 2279160 -Total: 509.724609 - - %self total self wait child calls name - 4.62 23.57 23.57 0.00 0.00 34 String#split - 3.95 57.66 20.13 0.00 37.53 3 #quick_emit - 2.82 23.70 14.35 0.00 9.34 2 #quick_emit-1 - 1.37 35.87 6.96 0.00 28.91 1 ActionView::Helpers::FormTagHelper#form_tag - 1.35 7.69 6.88 0.00 0.81 1 ActionController::HttpAuthentication::Basic::ControllerMethods#authenticate_with_http_basic - 1.06 6.09 5.42 0.00 0.67 90 String#gsub - 1.01 5.13 5.13 0.00 0.00 27 Array#- -============================================================================ - -Very similar to the processing time format. The main difference here is that instead of calculating time we are now concerned with the amount of KB put into memory *(or is it strictly into the heap) can I get clarification on this minor point?* - -So for #quick_emit which is singleton method on the class YAML it uses 57.66 KB in total, 23.57 through its own actions, 6.69 from actions it calls itself and that it was called twice. - -.Flat File Objects -============================================================================ -Thread ID: 2279160 -Total: 6537.000000 - - %self total self wait child calls name - 15.16 1096.00 991.00 0.00 105.00 66 Hash#each - 5.25 343.00 343.00 0.00 0.00 4 Mysql::Result#each_hash - 4.74 2203.00 310.00 0.00 1893.00 42 Array#each - 3.75 4529.00 245.00 0.00 4284.00 1 ActionView::Base::CompiledTemplates#_run_erb_47app47views47layouts47application46html46erb - 2.00 136.00 131.00 0.00 5.00 90 String#gsub - 1.73 113.00 113.00 0.00 0.00 34 String#split - 1.44 111.00 94.00 0.00 17.00 31 Array#each-1 -============================================================================ - - - #TODO Find correct terminology for how to describe what this is exactly profiling as in are there really 2203 array objects or 2203 pointers to array objects?. - -=== Graph Files === - -While the information gleamed from flat files is very useful we still don't know which processes each method is calling. We only know how many. This is not true for a graph file. Below is a text representation of a graph file. The actual graph file is an html entity and an example of which can be found link:examples/graph.html[Here] - -#TODO (Handily the graph file has links both between it many processes and to the files that actually contain them for debugging. - ) - -.Graph File -============================================================================ -Thread ID: 21277412 - - %total %self total self children calls Name -/____________________________________________________________________________/ -100.00% 0.00% 8.77 0.00 8.77 1 #toplevel* - 8.77 0.00 8.77 1/1 Object#run_primes -/____________________________________________________________________________/ - 8.77 0.00 8.77 1/1 #toplevel -100.00% 0.00% 8.77 0.00 8.77 1 Object#run_primes* - 0.02 0.00 0.02 1/1 Object#make_random_array - 2.09 0.00 2.09 1/1 Object#find_largest - 6.66 0.00 6.66 1/1 Object#find_primes -/____________________________________________________________________________/ - 0.02 0.02 0.00 1/1 Object#make_random_array -0.18% 0.18% 0.02 0.02 0.00 1 Array#each_index - 0.00 0.00 0.00 500/500 Kernel.rand - 0.00 0.00 0.00 500/501 Array#[]= -/____________________________________________________________________________/ -============================================================================ - -As you can see the calls have been separated into slices, no longer is the order determined by process time but instead from hierarchy. Each slice profiles a primary entry, with the primary entry's parents being shown above itself and it's children found below. A primary entry can be ascertained by it having values in the %total and %self columns. Here the main entry here have been bolded for connivence. - -So if we look at the last slice. The primary entry would be Array#each_index. It takes 0.18% of the total process time and it is only called once. It is called from Object#make_random_array which is only called once. It's children are Kernal.rand which is called by it all 500 its times that it was call in this action and Arry#[]= which was called 500 times by Array#each_index and once by some other entry. - -=== Tree Files === - -It's pointless trying to represent a tree file textually so here's a few pretty pictures of it's usefulness - -.KCachegrind Graph -[caption="KCachegrind graph"] -image:images/kgraph.png[Graph created by KCachegrind] - -.KCachegrind List -[caption="KCachegrind List"] -image:images/klist.png[List created by KCachegrind] - -#TODO Add a bit more information to this. - -== Getting to the Point of all of this == - -Now I know all of this is a bit dry and academic. But it's a very powerful tool when you know how to leverage it properly. Which we are going to take a look at in our next section - diff --git a/railties/doc/guides/source/benchmarking_and_profiling/statistics.txt b/railties/doc/guides/source/benchmarking_and_profiling/statistics.txt deleted file mode 100644 index 9fca979dec..0000000000 --- a/railties/doc/guides/source/benchmarking_and_profiling/statistics.txt +++ /dev/null @@ -1,57 +0,0 @@ -== A Lession In Statistics == - -#TODO COMPRESS DOWN INTO A PARAGRAPH AND A HALF -maybe I'll just combine with the methodology portion as an appendix. - -Adapted from a blog Article by Zed Shaw. His rant is funnier but will take longer to read.
http://www.zedshaw.com/rants/programmer_stats.html[Programmers Need To Learn Statistics Or I Will Kill Them All] - -=== Why Learn Statistics === - -Statistics is a hard discipline. One can study it for years without fully grasping all the complexities. But its a necessary evil for coders of every level to at least know the basics. You can't optimize without it, and if you use it wrong, you'll just waste your time and the rest of your team's. - -=== Power-of-Ten Syndrome === - -If you done any benchmarking you have probably heard -“All you need to do is run that test [insert power-of-ten] times and then do an average.” - -For new developers this whole power of ten comes about because we need enough data to minimize the results being contaminated by outliers. If you loaded a page five times with three of those times being around 75ms and twice 250ms you have no way of knowing the real average processing time for you page. But if we take a 1000 times and 950 are 75ms and 50 are 250ms we have a much clearer picture of the situation. - -But this still begs the question of how you determine that 1000 is the correct number of iterations to improve the power of the experiment? (Power in this context basically means the chance that your experiment is right.) - -The first thing that needs to be determined is how you are performing the samplings? 1000 iterations run in a massive sequential row? A set of 10 runs with 100 each? The statistics are different depending on which you do, but the 10 runs of 100 each would be a better approach. This lets you compare sample means and figure out if your repeated runs have any bias. More simply put, this allows you to see if you have a many or few outliers that might be poisoning your averages. - -Another consideration is if a 1000 transactions is enough to get the process into a steady state after the ramp-up period? If you are benchmarking a long running process that stabilizes only after a warm-up time you must take that into consideration. - -Also remember getting an average is not an end goal in itself. In fact in some cases they tell you almost nothing. - -=== Don't Just Use Averages! === - -One cannot simply say my website “[insert power-of-ten] requests per second”. This is due to it being an Average. Without some form of range or variance error analysis it's a useless number. Two averages can be the same, but hide massive differences in behavior. Without a standard deviation it’s not possible to figure out if the two might even be close. - -Two averages can be the same say 30 requests a second and yet have a completely different standard deviation. Say the first sample has +-3 and the second is +-30 - -Stability is vastly different for these two samples If this were a web server performance run I’d say the second server has a major reliability problem. No, it’s not going to crash, but it’s performance response is so erratic that you’d never know how long a request would take. Even though the two servers perform the same on average, users will think the second one is slower because of how it seems to randomly perform. - -Another big thing to take into consideration when benchmarking and profiling is Confounding - -=== Confounding === - -The idea of confounding is pretty simple: If you want to measure something, then don’t measure anything else. - -#TODO add more information in how to avoid confounding. - -* Your testing system and your production system must be separate. You can't profile on the same system because you are using resources to run the test that your server should be using to serve the requests. - -And one more thing. - -=== Define what you are Measuring === - -Before you can measure something you really need to lay down a very concrete definition of what you’re measuring. You should also try to measure the simplest thing you can and try to avoid confounding. - -The most important thing to determine though is how much data you can actually send to your application through it's pipe. - -=== Back to Business === - -Now I know this was all a bit boring, but these fundamentals a necessary for understanding what we are actually doing here. Now onto the actual code and rails processes. - - diff --git a/railties/doc/guides/source/index.txt b/railties/doc/guides/source/index.txt index cd536873e7..130beedf08 100644 --- a/railties/doc/guides/source/index.txt +++ b/railties/doc/guides/source/index.txt @@ -113,7 +113,7 @@ ways of achieving this and how to understand what is happening "behind the scene of your code. *********************************************************** -.link:benchmarking_and_profiling.html[Benchmarking and Profiling Rails Applications] +.link:performance_testing.html[Performance testing Rails Applications] *********************************************************** CAUTION: link:http://rails.lighthouseapp.com/projects/16213/tickets/4[Lighthouse Ticket] diff --git a/railties/doc/guides/source/benchmarking_and_profiling/index.txt b/railties/doc/guides/source/performance_testing.txt similarity index 50% rename from railties/doc/guides/source/benchmarking_and_profiling/index.txt rename to railties/doc/guides/source/performance_testing.txt index ef45ff62c6..25a8791344 100644 --- a/railties/doc/guides/source/benchmarking_and_profiling/index.txt +++ b/railties/doc/guides/source/performance_testing.txt @@ -1,5 +1,5 @@ -Benchmarking and Profiling Rails -================================ +Performance testing Rails Applications +====================================== This guide covers the benchmarking and profiling tactics/tools of Rails and Ruby in general. By referring to this guide, you will be able to: @@ -9,13 +9,7 @@ This guide covers the benchmarking and profiling tactics/tools of Rails and Ruby * Understand the information provided by Rails inside the log files * Learn about various tools facilitating benchmarking and profiling -== Why Benchmark and Profile ? - -Benchmarking and Profiling 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 plesant browsing experience to the end users and cutting cost of unnecessary hardwares is important for any web application. - -=== What is the difference between benchmarking and profiling ? === - -Benchmarking is the process of finding out if a piece of code is slow or not. Whereas profiling is the process of finding out what exactly is slowing down that piece of code. +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 plesant browsing experience to the end users and cutting cost of unnecessary hardwares is important for any web application. == Using and understanding the log files == @@ -23,19 +17,17 @@ Rails logs files containt basic but very useful information about the time taken [source, ruby] ---------------------------------------------------------------------------- -Processing ItemsController#index (for 127.0.0.1 at 2008-10-17 00:08:18) [GET] - Session ID: BAh7BiIKZmxhc2hJQzonQWN0aHsABjoKQHVzZWR7AA==--83cff4fe0a897074a65335 - Parameters: {"action"=>"index", "controller"=>"items"} +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://localhost/items] +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 from that log entry: [source, ruby] ---------------------------------------------------------------------------- -Completed in 5ms (View: 2, DB: 0) | 200 OK [http://localhost/items] +Completed in 5ms (View: 2, DB: 0) | 200 OK [http://0.0.0.0/items] ---------------------------------------------------------------------------- This data is fairly straight forward to understand. Rails uses millisecond(ms) as the metric to measures 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. @@ -85,7 +77,7 @@ and http://api.rubyonrails.com/classes/ActionController/Benchmarking/ClassMethod == Performance Test Cases == -Rails provides a very easy to write performance test cases, which look just like the regular integration tests. +Rails provides a very easy way to write performance test cases, which look just like the regular integration tests. Performance tests run a code profiler on your test methods. Profiling output for combinations of each test method, measurement, and output format are written to your +tmp/performance+ directory. By default, process_time is measured and both flat and graph_html output formats are written, so you'll have two output files per test method. If you have a look at +test/performance/browsing_test.rb+ in a newly created Rails application: @@ -106,30 +98,65 @@ This is an automatically generated example performance test file, for testing pe === Modes === +Performance test cases can be run in two modes : Benchmarking and Profling. + ==== Benchmarking ==== + +Benchmarking helps you find out how fast are your test cases. To run performance tests in benchmarking mode: + +[source, shell] +---------------------------------------------------------------------------- +[lifo@null application (master)]$ rake test:benchmark +---------------------------------------------------------------------------- + ==== Profiling ==== +Profiling helps introspect into your test cases and figure out which are the slow parts. To run performance tests in profiling mode: + +[source, shell] +---------------------------------------------------------------------------- +[lifo@null application (master)]$ rake test:profile +---------------------------------------------------------------------------- + === Metrics === +Benchmarking and profiling run performance test cases in various modes to help precisely figure out the where the problem lies. + ==== Process Time ==== -CPU Cycles. +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. + +Mode : Benchmarking, Profiling ==== Memory ==== -Memory taken. +Measures the amount of memory used for the performance test case. + +Mode : Benchmarking, Profiling ==== Objects ==== -Objects allocated. +Measures the number of objects allocated for the performance test case. + +Mode : Benchmarking, Profiling ==== GC Runs ==== -Number of times the Ruby GC was run. +Measures the number of times GC was invoked for the performance test case. + +Mode : Benchmarking ==== GC Time ==== -Time spent running the Ruby GC. +Measures the amount of time spent in GC for the performance test case. + +Mode : Benchmarking + +=== Understanding the output === + +==== Benchmarking ==== + +==== Profiling ==== === Preparing Ruby and Ruby-prof === @@ -162,14 +189,13 @@ alias gcrails='/Users/lifo/rubygc/bin/rails' ==== Install rubygems and some basic gems ==== +Download http://rubyforge.org/projects/rubygems[Rubygems] and install it from source. Afterwards, install rake. rails, ruby-prof and rack gems: + ---------------------------------------------------------------------------- -[lifo@null ~]$ wget http://rubyforge.org/frs/download.php/38646/rubygems-1.2.0.tgz -[lifo@null ~]$ tar -xzvf rubygems-1.2.0.tgz -[lifo@null ~]$ cd rubygems-1.2.0 -[lifo@null rubygems-1.2.0]$ gcruby setup.rb -[lifo@null rubygems-1.2.0]$ cd ~ [lifo@null ~]$ gcgem install rake [lifo@null ~]$ gcgem install rails +[lifo@null ~]$ gcgem install ruby-prof +[lifo@null ~]$ gcgem install rack ---------------------------------------------------------------------------- ==== Install MySQL gem ==== @@ -186,21 +212,9 @@ If this fails, you can try to install it manually: [lifo@null mysql-2.7]$ make && make install ---------------------------------------------------------------------------- -=== Installing Jeremy Kemper's ruby-prof === - -We also need to install Jeremy's ruby-prof gem using our newly built ruby: - -[source, shell] ----------------------------------------------------------------------------- -[lifo@null ~]$ git clone git://github.com/jeremy/ruby-prof.git -[lifo@null ~]$ cd ruby-prof/ -[lifo@null ruby-prof (master)]$ gcrake gem -[lifo@null ruby-prof (master)]$ gcgem install pkg/ruby-prof-0.6.1.gem ----------------------------------------------------------------------------- - === Generating performance test === -Rails provides a simple generator for creating new performance tests: +Rails provides a generator for creating new performance tests: [source, shell] ---------------------------------------------------------------------------- @@ -224,15 +238,100 @@ end Which you can modify to suit your needs. -=== Running tests === +== Other Profiling Tools == -include::rubyprof.txt[] +There are a lot of great profiling tools out there. Some free, some not so free. This is a sort list detailing some of them. -include::digging_deeper.txt[] +=== httperf === +http://www.hpl.hp.com/research/linux/httperf/[http://www.hpl.hp.com/research/linux/httperf/] -include::gameplan.txt[] +A necessary tool in your arsenal. Very useful for load testing your website. -include::appendix.txt[] +#TODO write and link to a short article on how to use httperf. Anybody have a good tutorial availble. + + +=== Rails Analyzer === + +The Rails Analyzer project contains a collection of tools for Rails. It's open source and pretty speedy. It's not being actively worked on but is still contains some very useful tools. + +* The Production Log Analyzer examines Rails log files and gives back a report. It also includes action_grep which will give you all log results for a particular action. + +* The Action Profiler similar to Ruby-Prof profiler. + +* rails_stat which gives a live counter of requests per second of a running Rails app. + +* The SQL Dependency Grapher allows you to visualize the frequency of table dependencies in a Rails application. + +Their project homepage can be found at http://rails-analyzer.rubyforge.org/[http://rails-analyzer.rubyforge.org/] + +The one major caveat is that it needs your log to be in a different format from how rails sets it up specifically SyslogLogger. + +==== SyslogLogger ==== + +SyslogLogger is a Logger work-alike that logs via syslog instead of to a file. You can add SyslogLogger to your Rails production environment to aggregate logs between multiple machines. + +More information can be found out at http://rails-analyzer.rubyforge.org/hacks/classes/SyslogLogger.html[http://rails-analyzer.rubyforge.org/hacks/classes/SyslogLogger.html] + +If you don't have access to your machines root system or just want something a bit easier to implement there is also a module developed by Geoffrey Grosenbach + +==== A Hodel 3000 Compliant Logger for the Rest of Us ==== + +Directions taken from +http://topfunky.net/svn/plugins/hodel_3000_compliant_logger/lib/hodel_3000_compliant_logger.rb[link to module file] + +Just put the module in your lib directory and add this to your environment.rb in it's config portion. + +------------------------------------------------------------ +require 'hodel_3000_compliant_logger' +config.logger = Hodel3000CompliantLogger.new(config.log_path) +------------------------------------------------------------- + +It's that simple. Your log output on restart should look like this. + +.Hodel 3000 Example +---------------------------------------------------------------------------- +Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: +Parameters: {"action"=>"shipping", "controller"=>"checkout"} +Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:  +[4;36;1mBook Columns (0.003155) SHOW FIELDS FROM `books` +Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:  +[4;35;1mBook Load (0.000881) SELECT * FROM `books` WHERE (`books`.`id` = 1 AND (`books`.`sold` = 1))  +Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:  +[4;36;1mShippingAddress Columns (0.002683) SHOW FIELDS FROM `shipping_addresses` +Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:  +[4;35;1mBook Load (0.000362) SELECT ounces FROM `books` WHERE (`books`.`id` = 1)  +Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: +Rendering template within layouts/application +Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: +Rendering checkout/shipping +Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:  +[4;36;1mBook Load (0.000548) SELECT * FROM `books` +WHERE (sold = 0) LIMIT 3 +Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]:  +[4;35;1mAuthor Columns (0.002571) SHOW FIELDS FROM `authors` +Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: +Author Load (0.000811) SELECT * FROM `authors` WHERE (`authors`.`id` = 1)  +Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: +Rendered store/_new_books (0.01358) +Jul 15 11:45:43 matthew-bergmans-macbook-pro-15 rails[16207]: +Completed in 0.37297 (2 reqs/sec) | Rendering: 0.02971 (7%) | DB: 0.01697 (4%) | 200 OK [https://secure.jeffbooks/checkout/shipping] +---------------------------------------------------------------------------- + +=== Palmist === +An open source mysql query analyzer. Full featured and easy to work with. Also requires Hodel 3000 +http://www.flyingmachinestudios.com/projects/[http://www.flyingmachinestudios.com/projects/] + +=== New Relic === +http://www.newrelic.com/[http://www.newrelic.com/] + +Pretty nifty performance tools, pricey though. They do have a basic free +service both for when in development and when you put your application into production. Very simple installation and signup. + +#TODO more in-depth without being like an advertisement. + +==== Manage ==== + +Like new relic a production monitoring tool. == Changelog ==