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# 4 fprof - The File Trace Profiler

fprof is a profiling tool that can be used to get a picture of how much processing time different functions consumes and in which processes.

fprof uses tracing with timestamps to collect profiling data. Therfore there is no need for special compilation of any module to be profiled.

fprof presents wall clock times from the host machine OS, with the assumption that OS scheduling will randomly load the profiled functions in a fair way. Both own time i.e the time used by a function for its own execution, and accumulated time i.e execution time including called functions.

Profiling is essentially done in 3 steps:

1
  Tracing; to file, as mentioned in the previous paragraph.
2
  Profiling; the trace file is read and raw profile data is collected into an internal RAM storage on the node. During this step the trace data may be dumped in text format to file or console.
3
  Analysing; the raw profile data is sorted and dumped in text format either to file or console.

Since fprof uses trace to file, the runtime performance degradation is minimized, but still far from negligible, especially not for programs that use the filesystem heavily by themselves. Where you place the trace file is also important, e.g on Solaris /tmp is usually a good choice, while any NFS mounted disk is a lousy choice.

Fprof can also skip the file step and trace to a tracer process of its own that does the profiling in runtime.

The following sections show some examples of how to profile with Fprof. See also the reference manual fprof(3).

### 4.1 Profiling from the source code

If you can edit and recompile the source code, it is convenient to insert fprof:trace(start) and fprof:trace(stop) before and after the code to be profiled. All spawned processes are also traced. If you want some other filename than the default try fprof:trace(start, "my_fprof.trace").

Then read the trace file and create the raw profile data with fprof:profile(), or perhaps fprof:profile(file, "my_fprof.trace") for non-default filename.

Finally create an informative table dumped on the console with fprof:analyse(), or on file with fprof:analyse(dest, []), or perhaps even fprof:analyse([{dest, "my_fprof.analysis"}, {cols, 120}]) for a wider listing on non-default filename.

See the fprof(3) manual page for more options and arguments to the functions trace, profile and analyse.

### 4.2 Profiling a function

If you have one function that does the task that you want to profile, and the function returns when the profiling should stop, it is convenient to use fprof:apply(Module, Function, Args) and related for the tracing step.

If the tracing should continue after the function returns, for example if it is a start function that spawns processes to be profiled, you can use fprof:apply(M, F, Args, [continue | OtherOpts]). The tracing has to be stopped at a suitable later time using fprof:trace(stop).

### 4.3 Immediate profiling

It is also possible to trace immediately into the profiling process that creates the raw profile data, that is to short circuit the tracing and profiling steps so that the filesystem is not used.

Do something like this:

    {ok, Tracer} = fprof:profile(start),
    fprof:trace([start, {tracer, Tracer}]),
    %% Code to profile
    fprof:trace(stop);

This puts less load on the filesystem, but much more on the Erlang runtime system.