Dave Gardner - PHP Developer » Dev Environment

Effective load testing with Apache JMeter

Dave — Thu, 23 Sep 2010 13:57:16 +0000

Load testing is surely one of the most important activities that many developers ignore. I would include myself in that bracket; it is far too often something that gets bounced out of a busy schedule. However load testing, and its cousin stress testing, are absolutely essential when attempting to create a reliable application.

This blog post concentrates on load testing, which Wikipedia defines as:

Load testing is the process of putting demand on a system or device and measuring its response.”

This is subtly different to stress testing, which aims to test a system “beyond normal operational capacity, often to a breaking point”. Load testing is useful to ensure that your application meets the business requirements, for example “cope with x million page unique users per day with a response time of less than 1 second”.

This post covers:

Things to consider when load testing
Using Apache JMeter
Verifying the details of a response
Extracting data from a response
Defining load levels using a constant throughput timer

Things to consider when load testing

It’s very easy to carry out useless load testing. I know this from experience. We were testing a system designed to serve 30 API requests per second, each response containing data on a user from a pool of roughly 100,000,000. When we carried out our load testing we designed a test using a pool of 1,000 unique user IDs. Spot the obvious problem! Testing with only 1,000 unique user IDs meant that we quickly reached a point where various layers of caching would be happily dealing with the job of fetching this limited set of data. This includes MySQL’s key cache plus the operating system file system cache.

To avoid making the same mistakes, make sure you consider the following points when load testing.

Use indicative hardware
When load testing to ensure that an application reaches minimum performance standards, you will need to test on hardware that mirrors your “live” setup as closely as possible. Sometimes this is easy, for example if you are running a live system consisting of three servers. If however you are running a 30 server cluster including a 100TB database, getting an accurate staging system can be hard work.
Use indicative data
If you have a production system with 100,000,000 rows of data, it’s a good idea not to carry out load testing on a staging system with only 300 rows. Similarly, if your application stores rows that are roughly 100KB each, the load testing system should be designed to replicate these conditions. The closer you can get to your actual data, the more useful the results.
Think about system state
Layers of caching can make load testing hard work. This includes application caching such as Memcache plus operating system caching and database caching. If your live environment workload can expect warmed caches then it is valid to leave these things warmed! However running a load test over and over again may get your application into an unnatural state of “preparedness”.

Using Apache JMeter

It may be tempting to write your own load test tools. Why not indeed? A few CURLs, a few processes; simple. My advice would be this: before you do this, try out JMeter. You can download JMeter from this page.

This example job reads in a list of user UUIDs from a text file and then makes an HTTP request for each user.

1. Launch JMeter

sh bin/jmeter.sh &

2. Configure job

Right click on Test Plan heading, click Add > Thread Group
Right click on Thread Group, click Add > CSV Data Set Config
Click on the newly added config element and enter a valid Filename – this should contain one user UUID per line
Enter userId under Variable Names (comma-delimited)
Click on the Thread Group, configure the Number of Threads (say 5), the Ramp-Up Period (say 180) and then the test Duration (say 600). This tells JMeter to launch up to 5 threads, ramping these up over 2 minutes, with the test running for a total of 10 minutes.

Right click on Thread Group, click Add > Sampler > HTTP Request
Click on the newly added sampler element and enter a valid Server Name or IP
You should probably add in some Timeouts; depending on your desired performance under load
Enter a Path, including the previously defined variable as follows: /1/user/${userId}/data.json

3. Add a listener

This was a stage that took me a while to figure out! You must have at least one listener, otherwise you cannot view any results from the job. You can add listeners to the Thread Group in the same way you added samplers and config elements. The Summary Report is very useful, as is View Results Tree (especially during debugging).

4. Run the job!

It’s usually a good idea to Clear All (from the Run menu) before you fire off the job.

5. Profit

Verifying the details of a response

By default JMeter will work with HTTP response codes – which is handy. So 404 errors and 500 errors etc… will all be dealt with. It’s often useful to look at the actual content of the response to decide on success. This can help catch things like PHP Fatal Errors (where you may have a 200 OK response, but a completely blank document). This is where the Response Assertion comes in.

Right click on any sampler and then Add > Assertion > Response Assertion. You can then define patterns to test against; these can use regular expressions. One other point to note is that if you wish to have HTTP 500 or 400 errors ignored (treated as success) then you should tick the Ignore Status tick box.

Extracting data from a response

Hitting URLs with known UUIDs is a handy tool, however it’s also useful to call a URL to add a user, extract the newly added user UUID and then use this in any subsequent requests. Fortunately this is also very easy to achieve with JMeter, using the Regular Expression Extractor.

Right click on any sampler and then Add > Post Processors > Regular Expression Extractor. The following settings extract data from a JSONP response which includes a userId definition; this is then assigned to the JMeter variable userId.

Reference Name: userId
Regular Expression: var userId = ‘([a-f0-9-]+)’;
Template: $1$
Match No. (0 for Random): 1
Default Value: null

Defining load levels using a constant throughput timer

When load testing I find it useful to run a number of tests at different levels of load – for a very specifically defined number of requests per second. To achieve this level of control, the Constant Throughput Timer element is very handy. This timer allows you to specific a target throughput in samples per minute. JMeter will then throttle back requests, if needed, to attempt to achieve this rate. The only thing you may need to do is ensure you have enough threads allowed to meet the desired throughput. Remember that the number of threads can be defined within the Thread Group settings.

Enjoy your load testing!

Setting up continuous integration for PHP using Hudson and Phing

Dave — Mon, 09 Nov 2009 13:44:44 +0000

In this, my first post, I’m going to write about the benefits of Unit Testing and how Continuous Integration (CI) can be used to get the best out of Unit Testing. This will include details of how I setup a CI system using Hudson CI server, Phing build tool combined with various other analysis tools (including PHP Unit).

One of the best explanations of Unit Testing I’ve read was posted by benzado on Stack Overflow.

Unit testing is a lot like going to the gym. You know it is good for you, all the arguments make sense, so you start working out. There’s an initial rush, which is great, but after a few days you start to wonder if it is worth the trouble.

The difficulty with Unit Testing is keeping it up. It is very easy to slip into poor habits and before you know it there’s a huge chunk of code with no tests. Possibly a huge, badly designed chunk of code, that didn’t benefit from having tests written before it was coded. Before you know what’s going on, you end up with a project that you really can’t write tests for, because retrofitting the tests is near impossible.

For me, there are two critical reasons for Unit Testing:

Enforcing good design
To be able to write tests, you need to be able to zero in on a “unit” of code, isolating it from all the rest of your 1,000,000 lines of web application. Writing Unit Tests forces you to design systems that have loose coupling because otherwise it is impossible to test.
Allowing changes to be made in confidence
Without Unit Tests, you get to the point where no one really wants to make any changes to the code. This is especially true in a commercial environment, where many people have worked on the code, including some key team member who has since left. Unit Tests allow you to make changes to one part of the code and be pretty convinced you haven’t messed up something else.

Continuous integration

Martin Fowler describes the process of Continuation Integration in detail. He suggests:

Continuous Integration is a software development practice where members of a team integrate their work frequently, usually each person integrates at least daily – leading to multiple integrations per day. Each integration is verified by an automated build (including test) to detect integration errors as quickly as possible. Many teams find that this approach leads to significantly reduced integration problems and allows a team to develop cohesive software more rapidly. This article is a quick overview of Continuous Integration summarizing the technique and its current usage.

The key idea behind CI is to do what is most painful often, namely “building” everyone’s code from source and making sure it all works.

A CI system usually consists of the following key elements:

Continuous integration

Developers commit code
CI server detects changes
CI server checksout code, runs tests, analyses code
CI server feeds back to development team

If you want to find out more about CI, I recommend the excellent book Continuous Integration: Improving Software Quality and Reducing Risk. There is an excerpt published on JavaWorld which covers a lot of the key advantages. In particular, it highlights:

1. Reduce risks
2. Reduce repetitive manual processes
3. Generate deployable software at any time and at any place
4. Enable better project visibility
5. Establish greater confidence in the software product from the development team

CI gets the most out of Unit Tests by forcing them to be run after every change. Not only that, but with a good CI setup, developers instantly know if they haven’t written enough tests. If avoids the situtation where Joe Bloggs has added in a huge chunk of code with zero tests.

Setting up CI for a PHP project

To get my environment setup, I consulted the following blog posts which are worth a read:

I’m assuming you’re using a CentOS 5 server (or I guess RHEL5). If not, you may still find various parts of this useful.

1. Install JDK

EPEL provide a set of CentOS packages, including a package for openJDK. This is the easiest way of installing Java.

Firstly, setup EPEL:

wget -O /etc/yum.repos.d/hudson.repo http://hudson-ci.org/redhat/hudson.repo

Next install OpenJDK:

yum install java-1.6.0-openjdk

2. Install Hudson

Download and install the CentOS RPM for Hudson:

wget -O /etc/yum.repos.d/hudson.repo http://hudson-ci.org/redhat/hudson.repo
rpm --import http://hudson-ci.org/redhat/hudson-ci.org.key
yum install hudson

Now Hudson is installed, we can start using the standard CentOS “service” command.

service hudson start

We can check Hudson is working by pointing the browser at port 8080 (the default Hudson port). Hudson will work “out of the box” and give you a web interface immediately. This is the primary reason I decided to go with Hudson over the other possibilities, eg: CruiseControl and phpUnderControl. Although I didn’t do an exhaustive analysis before I decided on Hudson, it just seemed right to me.

To get the graphing engine working for Hudson, you may need to install x.

yum groupinstall base-x

3. Install phing

Phing is a PHP project build system or build tool based on Apache Ant. A build tool ensures that the process of creating your working web application from source code happens in a structured and repeatable way. This helps reduce the possibility of errors caused by simply uploading files via FTP or some other simple method.

Make sure PEAR is installed for PHP (this is the easiest way of installing phing):

yum install php-pear

Then install the PEAR phing package:

pear channel-discover pear.phing.info
pear install phing/phing

4. Setup SVN

If you haven’t got a Subversion repository, you’re going to need one (or some other SCM tool like CVS, GIT or Mercurial).

yum install mod_dav_svn

The simplest setup involves creating a repo in /var/www/svn/

mkdir -v /var/www/svn/test
svnadmin create --fs-type fsfs /var/www/svn/test
chown –R apache:apache /var/www/svn/test

Setup Apache by pretty much uncommenting the lines in /etc/httpd/conf.d/subversion.conf. Once Apache restarted, you’ll be able to get to it via /repos/test, assuming you’re using the default settings (sets up SVN on /repos). I haven’t gone into the details of getting SVN up and running; there are lots of resources out there that will help you do this.

5. Install PHP tools

PHPDocumentor – to generate documentation automatically from code

pear install PhpDocumentor

PHP CPD – “copy and paste detector” for PHP

This requires PHP 5.2. At time of writing, this wasn’t standard with CentOS 5, but is part of the CentOS “test” repo. This can be setup by creating a yum repo file, eg: /etc/yum.repos.d/centos-test.repo and populating with:

[c5-testing]
name=CentOS-5 Testing
baseurl=http://dev.centos.org/centos/5/testing/$basearch/
enabled=1
gpgcheck=1
gpgkey=http://dev.centos.org/centos/RPM-GPG-KEY-CentOS-testing

Then you can do:

yum update php

You may also need to upgrade pear; if the install of phpcpd fails (below). To do this, try:

pear upgrade pear

or, if this wants to be forced, and you think it’s a good idea (I did):

pear upgrade --force pear

Finally we can install phpcpd!

pear channel-discover pear.phpunit.de
pear install phpunit/phpcpd

PHP Depend – help analyse quality of codebase

Note you may have update PHP to include the DOM module (first line below).

yum install php-dom
pear channel-discover pear.pdepend.org
pear install pdepend/PHP_Depend-beta

PHP Code Sniffer – analyse code for adherence to style/standards

pear install PHP_CodeSniffer-1.2.0

PHP Unit – unit test framework for PHP

pear channel-discover pear.phpunit.de
pear install phpunit/PHPUnit

To make PHP Unit work, we need XDebug installed, the PHP profiler.

yum install php-devel gcc
pecl install xdebug

6. Install Hudson plugins

Use the web interface to install the following plugins (Manage Hudson -> Plugins).

Checkstyle
Clover
DRY
Green Balls (handy because it shows successful builds as green circles rather than blue)
JDepend
xUnit (will handle the output of PHPUnit test results XML)

7. Setup the phing build script

The Phing build script defines what steps will be taken to “build” the application.

Hudson itself works by placing our code into a project workspace. It will checkout the code from subversion and place it into the following location, where “Test” is the name of our project.

/var/lib/hudson/jobs/Test/workspace/

We can then use the Phing build script to carry out a number of processes on this code. When we talk about “building”, what we will actually do is place the code where we need it so it can actually run the website (we’ll keep this within the workspace) plus we run tests etc…

We’ll keep the build script in the subversion repository, so effectively it will be updated from SVN each build. For this approach to work, the following XML needs to be stored in a file named build.xml, stored in the project root folder (within trunk), eg: /trunk/build.xml

8. Setup Hudson

The first step is to create a new job.

From the Hudson homepage, click New Job.
Enter a Job name, for example “Dave’s Product Build” and choose “Build a free-style software project”. Click OK.

Now you need to configure the job; the configuration form should be displayed immidiately after adding.

Under Source Code Management choose Subversion and enter:

Repository URL: http://www.myrepo.com/path/to/repo
Local module directory: source
Check “Use update” which speeds up checkout

Under Build Triggers select Poll SCM and enter the following schedule:

5 * * * *
10 * * * *
15 * * * *
20 * * * *
25 * * * *
30 * * * *
35 * * * *
40 * * * *
45 * * * *
50 * * * *
55 * * * *

Note that this will poll for changes to the repository every 5 minutes and rebuild if any changes are detected.

Under Build click the button to Add build step and choose Execute shell, enter the command:

phing -f $WORKSPACE/source/build.xml prepare app phpdoc phpcs phpunit -Dws=$WORKSPACE

Under Post-build Actions choose:

Check Publish Javadoc and then enter:
Javadoc directory = build/docs/
Check Publish testing tools result report and then click Add and pick PHP Unit, enter:
+ PHPUnit Pattern = build/logs/phpunit.xml
Check Publish Clover Coverage Report and enter:
+ Clover report directory = build/logs/coverage
+ Clover report file name = clover.xml
Check Publish duplicate code analysis results and enter:
+ Duplicate code results = build/logs/phpunit.pmd-cpd.xml
Check Publish Checkstyle analysis results and enter:
+ Checkstyle results = build/logs/checkstyle.xml

Finally, click Build Now to test it all works.