Careful: XDebug can skew your performance numbers
XDebug is a great tool and a really big aid in debugging.
But running it incurs a certain overhead on many common operations - like calling functions. Due to this having XDebug enabled can skew your benchmarking and profiling numbers. (“Enabled” here means just enabled, no debugging going on or such.)
This has an important implication: If you optimize a script while XDebug is enabled it can actually turn out that it gets slower on your production server (as you hopefully don’t have XDebug enabled there).
An example: “Optimizing” a lexer wrapper
For my PHP parser I need a smaller wrapper around PHP’s
token_get_all function. This wrapper (called
PHPParser_Lexer) only does nothing more than a little bit of normalization, filtering and mapping on the tokens.
There are basically two ways how this wrapper can work:
- For every source code to be parsed a new
Lexerinstance is created and passed into the parser, which then does multiple calls to
->lex()to fetch one token at a time.
Lexeris creates once and reused for all source codes. Always only a single call to
->lex()is made, which then returns all the tokens at once.
So, what I did is implement both approaches and see how much time is spent lexing the whole Symfony tree. I got the following results:
Scenario 1 on 5.3.8 with XDebug enabled: 16.939509868622 seconds Scenario 2 on 5.3.8 with XDebug enabled: 6.104107856751 seconds
That’s an impressive saving of 10 seconds (aka 60%) right there! is what I though.
But then I tried the same thing without XDebug:
Scenario 1 on 5.3.8 with XDebug disabled: 3.656718969345 seconds Scenario 2 on 5.3.8 with XDebug disabled: 3.195748090744 seconds
Now that XDebug is disabled the numbers are drastically lower and also much closer. The 17 seconds from above are only 3.7 seconds now. The time for the 6 seconds case halved.
Why is there such a drastic change on the first number, and a less pronounced one on the second? The first scenario needs approximately 70000
->lex() calls, whereas the second one only needs 2000. XDebug adds a quite large overhead to function calls, so the scenario with 70000 calls is impacted much more.
Finally, let’s look at the numbers for PHP 5.4.0 without XDebug:
Scenario 1 on 5.4.0 with XDebug disabled: 2.8629820346832 seconds Scenario 2 on 5.4.0 with XDebug disabled: 3.0883010864258 seconds
And here the numbers are now actually turned around. PHP 5.4 got some optimizations that made the seconds variant slower.
Another example: Micro benchmarking
As pointless as they are, people still love micro benchmarks, I do too. You’ll find lots of blog posts comparing the performance of something vs. something else. The problem is: Most of these are done on development machines, with XDebug enabled.
As an example this recent blog post about the performance of exceptions will serve. Here are the numbers the author measured for exceptions on PHP 5.3/5.4 for a certain script:
PHP 5.3: 1.1479668617249 PHP 5.4: 0.1864490332
Looking at those you might say: Damn, that’s a pretty impressive improvement!
Well, not really: Seeing these numbers I immediately had the suspicion that the author actually measured two different things: 5.3 with XDebug and 5.4 without it.
So I tested both versions without XDebug and got 0.14 seconds for PHP 5.3 and 0.09 seconds for PHP 5.4, i.e. a much smaller difference. You can find more detailed results in edorian’s blog post on the topic.
I think many micro benchmarking posts you’ll find on the net are affected by this. I was also trapped by this multiple times (e.g. see this question I asked about function call performance).
The conclusion from the above is: If you do benchmarking, benchmark on a machine that’s configured like your production machine. Otherwise you might actually be anti-optimizing.
Also: Low level optimizations like function inlining may actually measurably improve performance on your development machine (like in my case), but have little effect in the production environment. So, you can safely go for clean code with small functions and not fear about performance degradation.