![Example (2)
private static void hotMethod(final int i)
{
for (int k = 0; k < N; k++)
{
final int[] array = SafePointBias. array;
final int index = i % SIZE;
for (int j = index; j < SIZE; j++)
{
array[index] += array[j];
}
}
}](https://image.slidesharecdn.com/jvmprofilingunderthehood-150618100908-lva1-app6892/85/Jvm-profiling-under-the-hood-17-320.jpg)
![Compilers: Friend or Fiend?
safe_reset(void*, unsigned long):
lea rdx, [rdi+rsi]
cmp rdi, rdx
jae .L3
sub rdx, rdi
xor esi, esi
jmp memset
.L3:
rep ret](https://image.slidesharecdn.com/jvmprofilingunderthehood-150618100908-lva1-app6892/85/Jvm-profiling-under-the-hood-48-320.jpg)
Jvm profiling under the hood
- 1. JVM Profiling Under da Hood Richard Warburton - @RichardWarburto Nitsan Wakart - @nitsanw
- 2. Why Profile? Lies, Damn Lies and Statistical Profiling Under the Hood Conclusion
- 5. Measure data from your application
- 7. Execution Profiling = Where in code is my application spending time?
- 8. CPU Profiling Limitations ● Finds CPU bound bottlenecks ● Many problems not CPU Bound ○ Networking ○ Database or External Service ○ I/O ○ Garbage Collection ○ Insufficient Parallelism ○ Blocking & Queuing Effects
- 9. Why Profile? Lies, Damn Lies and Statistical Profiling Under the Hood Conclusion
- 11. Different Execution Profilers ● Instrumenting ○ Adds timing code to application ● Sampling ○ Collects thread dumps periodically
- 12. Sampling Profilers WebServerThread.run() Controller.doSomething() Controller.next() Repo.readPerson() new Person() View.printHtml()
- 13. Periodicity Bias ● Bias from sampling at a fixed interval ● Periodic operations with the same frequency as the samples ● Timed operations
- 14. Periodicity Bias a() ??? a() ??? a() ??? a() ???
- 15. Stack Trace Sampling ● JVMTI interface: GetCallTrace ○ Trigger a global safepoint(not on Zing) ○ Collect stack trace ● Large impact on application ● Samples only at safepoints
- 16. Example private static void outer() { for (int i = 0; i < OUTER; i++) { hotMethod(i); } } // https://github.com/RichardWarburton/profiling-samples
- 17. Example (2) private static void hotMethod(final int i) { for (int k = 0; k < N; k++) { final int[] array = SafePointBias. array; final int index = i % SIZE; for (int j = index; j < SIZE; j++) { array[index] += array[j]; } } }
- 19. -XX:+PrintSafepointStatistics ThreadDump 48 Maximum sync time 985 ms
- 20. Whats a safepoint? ● Java threads poll global flag ○ At ‘uncounted’ loops back edge ○ At method exit/enter ● A safepoint poll can be delayed by: ○ Large methods ○ Long running ‘counted’ loops ○ BONUS: Page faults/thread suspension
- 22. Safepoint Bias WebServerThread.run() Controller.doSomething() Controller.next() Repo.readPerson() new Person() View.printHtml() ???
- 24. Let sleeping dogs lie? ● ‘GetCallTrace’ profilers will sample ALL threads ● Even sleeping threads...
- 25. This Application Mostly Sleeps JVisualVM snapshot
- 26. No CPU? No profile! JMC profile
- 27. Why Profile? Lies, Damn Lies and Statistical Profiling Under the Hood Conclusion
- 30. AsyncGetCallTrace ● Used by Oracle Solaris Studio ● Adapted to open source prototype by Google’s Jeremy Manson ● Unsupported, Undocumented … Underestimated
- 31. SIGPROF - Interrupt Handlers ● OS Managed timing based interrupt ● Interrupts the thread and directly calls an event handler ● Used by profilers we’ll be talking about
- 32. Design Log File Processor Thread Graphical UI Console UI Signal Handler Signal Handler Os Timer Thread
- 33. “You are in a maze of twisty little stack frames, all alike”
- 34. AsyncGetCallTrace under the hood ● A Java thread is ‘possessed’ ● You have the PC/FP/SP ● What is the call trace? ○ jmethodId - Java Method Identifier ○ bci - Byte Code Index -> used to find line number
- 35. Where Am I? ● Given a PC what is the current method? ● Is this a Java method? ○ Each method ‘lives’ in a range of addresses ● If not, what do we do?
- 36. Java Method? Which line? ● Given a PC, what is the current line? ○ Not all instructions map directly to a source line ● Given super-scalar CPUs what does PC mean? ● What are the limits of PC accuracy?
- 37. “> I think Andi mentioned this to me last year -- > that instruction profiling was no longer reliable. It never was.” http://permalink.gmane.org/gmane.linux.kernel.perf.user/1948 Exchange between Brenden Gregg and Andi Kleen
- 38. Skid ● PC indicated will be >= to PC at sample time ● Known limitation of instruction profiling ● Leads to harder ‘blame analysis’
- 39. Limits of line number accuracy: Line number (derived from BCI) is the closest attributable BCI to the PC (-XX:+DebugNonSafepoint) The PC itself is within some skid distance from actual sampled instruction
- 40. ● Divided into frames ○ frame { sender*, stack*, pc } ● A single linked list: root(null, s0, pc1) <- call1 (root, s1, pc2) <- call2(call1, s2, pc2) ● Convert to: (jmethodId,lineno) The Stack
- 41. A typical stack ● JVM Thread runner infra: ○ JavaThread::run to JavaCalls::call_helper ● Interleaved Java frames: ○ Interpreted ○ Compiled ○ Java to Native and back ● Top frame may be Java or Native
- 42. Native frames ● Ignored, but need to navigate through ● Use a dedicated FP register to find sender ● But only if compiled to do so… ● Use a last remembered Java frame instead See: http://duartes.org/gustavo/blog/post/journey-to-the-stack/
- 43. Java Compiled Frames ● C1/C2 produce native code ● No FP register: use set frame size ● Challenge: methods can move (GC) ● Challenge: methods can get recompiled
- 44. Java Interpreter frames ● Separately managed by the runtime ● Make an effort to look like normal frames ● Challenge: may be interrupted half-way through construction...
- 45. Virtual Frames ● C1/C2 inline code (intrinsics/other methods) ● No data on stack ● Must use JVM debug info
- 46. AsyncGetCallTrace Limitations ● Only profiles running threads ● Accuracy of line info limited by reality ● Only reports Java frames/threads ● Must lookup debug info during call
- 47. Compilers: Friend or Fiend? void safe_reset(void *start, size_t size) { char *base = reinterpret_cast<char *>(start); char *end = base + size; for (char *p = base; p < end; p++) { *p = 0; } }
- 48. Compilers: Friend or Fiend? safe_reset(void*, unsigned long): lea rdx, [rdi+rsi] cmp rdi, rdx jae .L3 sub rdx, rdi xor esi, esi jmp memset .L3: rep ret
- 49. Concurrency Bug ● Even simple concurrency bugs are hard to spot ● Unspotted race condition in the ring buffer ● Spotted thanks to open source & Rajiv Signal
- 50. Writer Reader
- 51. Writer Reader
- 52. Extra Credit!
- 53. Native Profiling Tools ● Profile native methods ● Profile at the instruction level ● Profile hardware counters
- 54. Perf ● A Linux profiling tool ● Can be made to work with Java ● JMH integration ● Ongoing integration efforts
- 55. Solaris Studio ● Works on Linux! ● Secret Weapon! ● Give it a go!
- 56. ZVision ● Works for Zing ● No HWC support ● Very informative
- 57. Why Profile? Lies, Damn Lies and Statistical Profiling Under the Hood Conclusion
- 58. What did we cover? ● Biases in Profilers ● More accurate sampling ● Alternative Profiling Approaches
- 59. Don’t just blindly trust your tooling.
- 60. Test your measuring instruments
- 61. Open Source enables implementation review
- 63. Slides after here just for reference, don’t delete or show