Performance Analysis of J2EE Applications Using AOP Techniques

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Tutorial: Performance Analysis of J2EE Applications Using AOP Techniques

Performance Analysis of J2EE Applications Using AOP Techniques In this article we demonstrate the use of AOP techniques through which J2EE applications can be easily instrumented without any modifications to application code. We have developed a very sim

Tutorial Details:

In a complex distributed computing environment like J2EE, it is very difficult to pinpoint the component that is causing a performance bottleneck. Applications can be profiled by including instrumentation code manually, but this could be cumbersome and time-consuming, and might impact the stability of the application itself. Aspect-Oriented Programming (AOP) technology can be elegantly and effectively applied for performance analysis, as illustrated by Davies et al.

AOP Infrastructure
We considered both AspectJ and Aspectwerkz for providing the AOP infrastructure and chose Aspectwerkz, since it does not require the J2EE application to be re-compiled. Due to this capability, we can profile an existing J2EE application without any additional development activity. But we also noticed that Aspectwerkz introduces a tiny overhead as compared to AspectJ; this is due to reflection (java.lang.reflect.Method.invoke()) used by Aspectwerkz to incorporate the advices into the application code. By defining the point-cuts in a simple XML file, Aspectwerkz makes it much easier in our situation to decide which methods need to be profiled.

Capturing CPU Time
While it is easy to capture the elapsed time using System.currentTimeMillis(), this measure is not accurate in all situations, especially if there are contentions. The CPU time is a more accurate measure of the execution time of a method. We capture the CPU time using the JVM Profiler Interface (JVMPI). Please refer to "Using JVM Profiler Interface for Accurate Timing," by Jesper Gortz, for more information.

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