Exceptional Performance Improvement

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This post is part of our series on the Top Application Performance Challenges.

Over the past couple of weeks we helped a few DevOps groups troubleshoot performance problems in their production Java-based applications. While the applications themselves bore little resemblance to one another, they all shared one common problem. They were full of runtime exceptions.

When I brought the exceptions to the attention of some of the teams I got a variety of different answers.

  • “Oh yeah, we know all about that one, just some old debug info … I think”
  • “Can you just tell the APM tool to just ignore that exception because it happens way too much”
  • “I have no idea where that exception comes from, I think it’s the vendor/contractor/off shore team’s/someone else’s code”
  • “Sometimes that exception indicates an error, sometimes we use it for flow control”

The response was the same – because the exception did not affect the functionality of (read: did not break) the application it was deemed unimportant. But what about performance?

In one high-volume production application (100’s of calls/second) we observed an NPE (Null Pointer Exception) rate of more than 1000 exceptions per minute (17,800/15 min). This particular NPE occurred in the exact same line of code and propagated some 20 calls up in the stack before a catch clause handled it. The pseudo code for the line read if the string equaled null and the length of the trimmed string was zero then do x otherwise just exit. When we read the line out loud the problem was immediately obvious – you cannot trim a null string. While the team agreed that they needed to fix the code, they remained skeptical that simply changing ‘=’ to ‘!’ would really improve performance.

Using basic simulations we estimate this error rate imposes a 3-4% slow down on basic response time at a minimum. You heard me, 3-4% slow down at a minimum.

And these response issues get compounded in multi-threaded application server environments. When multiple pooled threads slow down to cope with error handling then the application has fewer resources available to process new requests. At the JVM level the errors cause more IO, more objects created in the heap, more garbage collection. In a multi-threaded environment the error threatens more than response times, it threatens load capacity.

And if the application is distributed across multiple JVM’s … well you get the picture.

The web contains many articles and discussions on the performance impact of Java’s exception handling. The examples in these posts provide sufficient data to show that a real performance penalty exists for throwing and catching exceptions. Doing the fix really does improve the performance!

Runtime Exceptions happen. When they occur frequently, they do appreciably slow down your application. The slowness becomes contagious to all transactions being served by the application. Don’t mute them. Don’t ignore them. Don’t dismiss them. Don’t convince yourself they are harmless. If you want a simple way to improve your applications performance, start by fixing up these regular occurring exceptions. Who knows, you just might help everyone’s code run a little faster.

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