This section provides details on how to use the OProfile callgraph feature.

#include <string.h>
#include <stdlib.h>
#include <stdio.h>

#define SIZE 500000

static int compare(const void *s1, const void *s2)
{
        return strcmp(s1, s2);
}

static void repeat(void)
{
        int i;
        char *strings[SIZE];
        char str[] = "abcdefghijklmnopqrstuvwxyz";

        for (i = 0; i < SIZE; ++i) {
                strings[i] = strdup(str);
                strfry(strings[i]);
        }

        qsort(strings, SIZE, sizeof(char *), compare);
}

int main()
{
        while (1)
                repeat();
}

samples  %        image name               symbol name
  197       0.1548  cg                       main
  127036   99.8452  cg                       repeat
84590    42.5084  libc-2.3.2.so            strfry
  84590    66.4838  libc-2.3.2.so            strfry [self]
  39169    30.7850  libc-2.3.2.so            random_r
  3475      2.7312  libc-2.3.2.so            __i686.get_pc_thunk.bx
-------------------------------------------------------------------------------

-------------------------------------------------------------------------------
  1         2.2727  libj9ute23.so            java.bin                 traceV
  2         4.5455  libj9ute23.so            java.bin                 utsTraceV
  4         9.0909  libj9trc23.so            java.bin                 fillInUTInterfaces
  37       84.0909  libj9trc23.so            java.bin                 twGetSequenceCounter
8         0.0154  libj9prt23.so            java.bin                 j9time_hires_clock
  27       61.3636  anon (tgid:10014 range:0x100000-0x103000) java.bin                 (no symbols)
  9        20.4545  libc-2.4.so              java.bin                 gettimeofday
  8        18.1818  libj9prt23.so            java.bin                 j9time_hires_clock [self]
-------------------------------------------------------------------------------

Often, we'd like to be able to compare two profiles. For example, when analysing the performance of an application, we'd like to make code changes and examine the effect of the change. This is supported in opreport by giving a profile specification that identifies two different profiles. The general form is of:

$ opreport <shared-spec> { <first-profile> } { <second-profile> }

For each of the profiles, the shared section is prefixed, and then the specification is analysed. The usual parameters work both within the shared section, and in the sub-specification within the curly braces.

A typical way to use this feature is with archives created with oparchive. Let's look at an example:

$ operf ./a
$ oparchive -o orig ./a
  # edit and recompile a
$ operf ./a
  # now compare the current profile of a with the archived profile
$ opreport  --session-dir=`pwd`/oprofile_data/ -xl ./a { archive:./orig } { }
CPU: PIII, speed 863.233 MHz (estimated)
Counted CPU_CLK_UNHALTED events (clocks processor is not halted) with a
unit mask of 0x00 (No unit mask) count 100000
samples  %        diff %    symbol name
92435    48.5366  +0.4999   a
54226    ---      ---       c
49222    25.8459  +++       d
48787    25.6175  -2.2e-01  b

Note that we specified an empty second profile in the curly braces, as we wanted to use the current session; alternatively, we could have specified another archive, or a tgid etc. We specified the binary a in the shared section, so we matched that in both the profiles we're diffing.

As in the normal output, the results are sorted by the number of samples, and the percentage field represents the relative percentage of the symbol's samples in the second profile.

Notice the new column in the output. This value represents the percentage change of the relative percent between the first and the second profile: roughly, "how much more important this symbol is". Looking at the symbol a(), we can see that it took roughly the same amount of the total profile in both the first and the second profile. The function c() was not in the new profile, so has been marked with ---. Note that the sample value is the number of samples in the first profile; since we're displaying results for the second profile, we don't list a percentage value for it, as it would be meaningless. d() is new in the second profile, and consequently marked with +++.

When comparing profiles between different binaries, it should be clear that functions can change in terms of VMA and size. To avoid this problem, opreport considers a symbol to be the same if the symbol name, image name, and owning application name all match; any other factors are ignored. Note that the check for application name means that trying to compare library profiles between two different applications will not work as you might expect: each symbol will be considered different.

Many applications, typically ones involving dynamic compilation into machine code (just-in-time, or "JIT", compilation), have executable mappings that are not backed by an ELF file. opreport has basic support for showing the samples taken in these regions; for example:

$ opreport /usr/bin/mono -l
CPU: ppc64 POWER5, speed 1654.34 MHz (estimated)
Counted CYCLES events (Processor Cycles using continuous sampling) with a unit mask of 0x00 (No unit mask) count 100000
samples  %        image name    		                symbol name
47       58.7500  mono                     			(no symbols)
14       17.5000  anon (tgid:3189 range:0xf72aa000-0xf72fa000)  (no symbols)
9        11.2500  anon (tgid:3189 range:0xf6cca000-0xf6dd9000)  (no symbols)
.	 .	  .						.

Note that, since such mappings are dependent upon individual invocations of a binary, these mappings are always listed as a dependent image. Equally, the results are not affected by the --merge option.

As shown in the opreport output above, OProfile is unable to attribute the samples to any symbol(s) because there is no ELF file for this code. Enhanced support for JITed code is now available for some virtual machines; e.g., the Java Virtual Machine. For details about OProfile output for JITed code, see Section 4, “OProfile results with JIT samples”.

For more information about JIT support in OProfile, see Section 4.1, “Support for dynamically compiled (JIT) code”.

The --xml option can be used to generate XML instead of the usual text format. This allows opreport to eliminate some of the constraints dictated by the two dimensional text format. For example, it is possible to separate the sample data across multiple events, cpus and threads. The XML schema implemented by opreport is found in doc/opreport.xsd. It contains more detailed comments about the structure of the XML generated by opreport.

Since XML is consumed by a client program rather than a user, its structure is fairly static. In particular, the --sort option is incompatible with the --xml option. Percentages are not dislayed in the XML so the options related to percentages will have no effect. Full pathnames are always displayed in the XML so --long-filenames is not necessary. The --details option will cause all of the individual sample data to be included in the XML as well as the instruction byte stream for each symbol (for doing disassembly) and can result in very large XML files.