This document provides an introduction to JProfiler and discusses various techniques for profiling Java applications, including bytecode instrumentation, sampling profiling, and Java Management Extensions (JMX). It describes methods like manually adding print statements, using aspects, creating JMX beans, and using the JVM Tool Interface (JVMTI). The document also covers topics like overhead of profiling, hashcodes, equal methods, and examples of using instrumentation and sampling in profiling tools.

1. JProfiler introduction
Tommaso Torti

2. in eXtreme Programming
Make It Work Make It Right Make It Fast

3. Premature optimization is the root of all evil
in eXtreme Programming

4. “A good programmer will not be lulled into
complacency by such reasoning, he will be wise to
look carefully at the critical code; but only after that
code has been identified”
in eXtreme Programming

5. lulled into complacency
• complacency: a feeling of quiet pleasure or security, often while unaware of
some potential danger
• lull: to give or lead to feel a false sense of safety; cause to be less alert, aware, or
watchful.

6. “It is often a mistake to make a priori judgments
about what parts of a program are really critical,
since the universal experience of programmers
who have been using measurement tools has been
that their intuitive guesses fail”
in eXtreme Programming

7. substring
String a =
String b = a.substring(1,3)

8. substring

9. Garbage collector

10. Garbage collector

11. substring
When a is not more referenced, the original char array is not
deallocated, because referenced by another object

12. substring

13. Live Examples

14. Hash Code / Equals
Must implement hash code as a necessary but not sufficient condition for
equality
The default implementation of hashCode() in Object class returns distinct
integers for different objects.

15. Hash Code / Equals

16. How
•Manually add some System.out.println
•Create some kind of javax.management beans to record time. They
can recorded manually and queried with tools later on.
•Use AOP Libraries to build Aspects which record code execution time.
•Build an JVMTI Agent, which uses APIs to add code and record
execution time.

17. Sampling

18. Sampling

19. Sampling

20. Sampling
while (true) sleep …
ThreadMXBean threadMXBean =
java.lang.management.ManagementFactory.getThreadMXBean();
threadMXBean.getThreadCpuTime(monitoredThread.getId());

21. Instrumentation

22. Overhead
• CPU Overhead represents the additional CPU usage caused by
executing monitoring code.
• Memory overhead is caused by the additional data that is stored
within the application-> send data to remote server
• Network traffic. All solutions that follow a distributed approach will
also utilize the network to send data from the application to where it is stored
and processed.

23. Instrumentation
• More accuracy
• More overhead
• May filter own objects
• ‘Recompiling classes’ explained

24. Instrumentation
@Around(" call(void MyApp.method* (..)) ")
public void aroundMethodCall (final ProceedingJoinPoint joinPoint)
throws Throwable {
long cpuStart = threadMXBean.getCurrentThreadCpuTime();
joinPoint.proceed();
long cpuEnd = threadMXBean.getCurrentThreadCpuTime();

25. In Marketplace
• Live instance, continuous listing import running
• looking for classes with filter market*
• memory / cpu use before and after a complete task

26. Cpu

27. Cpu

28. Before…
During…
After…