2. Image summaries and symbol summaries (opreport)

The opreport utility is the primary utility you will use for getting formatted data out of OProfile. It produces two types of data: image summaries and symbol summaries. An image summary lists the number of samples for individual binary images such as libraries or applications. Symbol summaries provide per-symbol profile data. In the following example, we're getting an image summary for the whole system:

$ opreport --long-filenames
CPU: PIII, speed 863.195 MHz (estimated)
Counted CPU_CLK_UNHALTED events (clocks processor is not halted) with a unit mask of 0x00 (No unit mask) count 23150
   905898 59.7415 /usr/lib/gcc-lib/i386-redhat-linux/3.2/cc1plus
   214320 14.1338 /boot/2.6.0/vmlinux
   103450  6.8222 /lib/i686/libc-2.3.2.so
    60160  3.9674 /usr/local/bin/madplay
    31769  2.0951 /usr/local/oprofile-pp/bin/oprofiled
    26550  1.7509 /usr/lib/libartsflow.so.1.0.0
    23906  1.5765 /usr/bin/as
    18770  1.2378 /oprofile
    15528  1.0240 /usr/lib/qt-3.0.5/lib/libqt-mt.so.3.0.5
    11979  0.7900 /usr/X11R6/bin/XFree86
    11328  0.7471 /bin/bash

If we had specified --symbols in the previous command, we would have gotten a symbol summary of all the images across the entire system. We can restrict this to only part of the system profile; for example, below is a symbol summary of the OProfile daemon. Note that as we used opcontrol --separate=lib,kernel, symbols from images that oprofiled has used are also shown.

$ opreport -l -p /lib/modules/`uname -r` `which oprofiled` 2>/dev/null | more
CPU: Core 2, speed 2.534e+06 MHz (estimated)
Counted CPU_CLK_UNHALTED events (Clock cycles when not halted) with a unit mask of 0x00 (Unhalted core cycles) count 100000
samples  %        image name               symbol name
1353     24.9447  vmlinux                  sidtab_context_to_sid
500       9.2183  vmlinux                  avtab_hash_eval
154       2.8392  vmlinux                  __link_path_walk
152       2.8024  vmlinux                  d_prune_aliases
120       2.2124  vmlinux                  avtab_search_node
104       1.9174  vmlinux                  find_next_bit
85        1.5671  vmlinux                  selinux_file_fcntl
82        1.5118  vmlinux                  avtab_write
81        1.4934  oprofiled                odb_update_node_with_offset
73        1.3459  oprofiled                opd_process_samples
72        1.3274  vmlinux                  avc_has_perm_noaudit
61        1.1246  libc-2.12.so             _IO_vfscanf
59        1.0878  ext4.ko                  ext4_mark_iloc_dirty

These are the two basic ways you are most likely to use regularly, but opreport can do a lot more than that, as described below.

2.1. Merging separate profiles

If you have used one of the --separate[*] options whilst profiling, there can be several separate profiles for a single binary image within a session. Normally the output will keep these images separated. So, for example, if you profiled with separation on a per-cpu basis (opcontrol --separate=cpu or operf --separate-cpu), you would see separate columns in the output of opreport for each CPU where samples were recorded. But it can be useful to merge these results back together to make the report more readable. The --merge option allows you to do that.

2.2. Side-by-side multiple results

If you have used multiple events when profiling, by default you get side-by-side results of each event's sample values from opreport. You can restrict which events to list by appropriate use of the event: profile specifications, etc.

2.3. Callgraph output

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

2.3.1. Callgraph details

When using the --callgraph option, you can see what functions are calling other functions in the output. Consider the following program:

#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);

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

int main()
        while (1)

When running with the call-graph option, OProfile will record the function stack every time it takes a sample. opreport --callgraph outputs an entry for each function, where each entry looks similar to:

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

Here the non-indented line is the function we're focussing upon (strfry()). This line is the same as you'd get from a normal opreport output.

Above the non-indented line we find the functions that called this function (for example, repeat() calls strfry()). The samples and percentage values here refer to the number of times we took a sample where this call was found in the stack; the percentage is relative to all other callers of the function we're focussing on. Note that these values are not call counts; they only reflect the call stack every time a sample is taken; that is, if a call is found in the stack at the time of a sample, it is recorded in this count.

Below the line are functions that are called by strfry() (called callees). It's clear here that strfry() calls random_r(). We also see a special entry with a "[self]" marker. This records the normal samples for the function, but the percentage becomes relative to all callees. This allows you to compare time spent in the function itself compared to functions it calls. Note that if a function calls itself, then it will appear in the list of callees of itself, but without the "[self]" marker; so recursive calls are still clearly separable.

You may have noticed that the output lists main() as calling strfry(), but it's clear from the source that this doesn't actually happen. See Section 3, “Interpreting call-graph profiles” for an explanation.

2.3.2. Callgraph and JIT support

Callgraph output where anonymously mapped code is in the callstack can sometimes be misleading. For all such code, the samples for the anonymously mapped code are stored in a samples subdirectory named {anon:anon}/<tgid>.<begin_addr>.<end_addr>. As stated earlier, if this anonymously mapped code is JITed code from a supported VM like Java, OProfile creates an ELF file to provide a (somewhat) permanent backing file for the code. However, when viewing callgraph output, any anonymously mapped code in the callstack will be attributed to anon (<tgid>: range:<begin_addr>-<end_addr>, even if a .jo ELF file had been created for it. See the example below.

  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]

The output shows that "anon (tgid:10014 range:0x100000-0x103000)" was a callee of j9time_hires_clock, even though the ELF file 10014.jo was created for this profile run. Unfortunately, there is currently no way to correlate that anonymous callgraph entry with its corresponding .jo file.

2.4. Differential profiles with opreport

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> }


We lost our Dragon book down the back of the sofa, so you have to be careful to have spaces around those braces, or things will get hopelessly confused. We can only apologise.

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:

$ ./a
$ oparchive -o orig ./a
$ opcontrol --reset
  # edit and recompile a
$ ./a
  # now compare the current profile of a with the archived profile
$ opreport -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.

2.5. Anonymous executable mappings

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, even when using the legacy mode opcontrol --separate=none command. 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”.

2.6. XML formatted output

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.

2.7. Options for opreport

--accumulated / -a

Accumulate sample and percentage counts in the symbol list.

--callgraph / -c

Show callgraph information.

--debug-info / -g

Show source file and line for each symbol.

--demangle / -D none|normal|smart

none: no demangling. normal: use default demangler (default) smart: use pattern-matching to make C++ symbol demangling more readable.

--details / -d

Show per-instruction details for all selected symbols. Note that, for binaries without symbol information, the VMA values shown are raw file offsets for the image binary.

--exclude-dependent / -x

Do not include application-specific images for libraries, kernel modules and the kernel. This option only makes sense if the profile session used --separate.

--exclude-symbols / -e [symbols]

Exclude all the symbols in the given comma-separated list.

--global-percent / -%

Make all percentages relative to the whole profile.

--help / -? / --usage

Show help message.

--image-path / -p [paths]

Comma-separated list of additional paths to search for binaries. This is needed to find kernel modules.

--root / -R [path]

A path to a filesystem to search for additional binaries.

--include-symbols / -i [symbols]

Only include symbols in the given comma-separated list.

--long-filenames / -f

Output full paths instead of basenames.

--merge / -m [lib,cpu,tid,tgid,unitmask,all]

Merge any profiles separated in a --separate session.


Don't output a header detailing profiling parameters.

--output-file / -o [file]

Output to the given file instead of stdout.

--reverse-sort / -r

Reverse the sort from the default.


Use sample database out of directory dir_path instead of the default location (/var/lib/oprofile).

--show-address / -w

Show the VMA address of each symbol (off by default).

--sort / -s [vma,sample,symbol,debug,image]

Sort the list of symbols by, respectively, symbol address, number of samples, symbol name, debug filename and line number, binary image filename.

--symbols / -l

List per-symbol information instead of a binary image summary.

--threshold / -t [percentage]

Only output data for symbols that have more than the given percentage of total samples.

--verbose / -V [options]

Give verbose debugging output.

--version / -v

Show version.

--xml / -X

Generate XML output.