625f2a378e
Neil Brown pointed out that lock_depth somehow escaped the BKL removal work. Let's get rid of it now. Note that the perf scripting utilities still have a bunch of code for dealing with common_lock_depth in tracepoints; I have left that in place in case anybody wants to use that code with older kernels. Suggested-by: Neil Brown <neilb@suse.de> Signed-off-by: Jonathan Corbet <corbet@lwn.net> Cc: Arnd Bergmann <arnd@arndb.de> Cc: Peter Zijlstra <a.p.zijlstra@chello.nl> Cc: Thomas Gleixner <tglx@linutronix.de> Cc: Linus Torvalds <torvalds@linux-foundation.org> Cc: Andrew Morton <akpm@linux-foundation.org> Link: http://lkml.kernel.org/r/20110422111910.456c0e84@bike.lwn.net Signed-off-by: Ingo Molnar <mingo@elte.hu>
622 lines
23 KiB
Text
622 lines
23 KiB
Text
perf-script-python(1)
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====================
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NAME
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----
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perf-script-python - Process trace data with a Python script
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SYNOPSIS
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--------
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[verse]
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'perf script' [-s [Python]:script[.py] ]
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DESCRIPTION
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-----------
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This perf script option is used to process perf script data using perf's
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built-in Python interpreter. It reads and processes the input file and
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displays the results of the trace analysis implemented in the given
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Python script, if any.
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A QUICK EXAMPLE
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---------------
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This section shows the process, start to finish, of creating a working
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Python script that aggregates and extracts useful information from a
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raw perf script stream. You can avoid reading the rest of this
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document if an example is enough for you; the rest of the document
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provides more details on each step and lists the library functions
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available to script writers.
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This example actually details the steps that were used to create the
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'syscall-counts' script you see when you list the available perf script
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scripts via 'perf script -l'. As such, this script also shows how to
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integrate your script into the list of general-purpose 'perf script'
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scripts listed by that command.
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The syscall-counts script is a simple script, but demonstrates all the
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basic ideas necessary to create a useful script. Here's an example
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of its output (syscall names are not yet supported, they will appear
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as numbers):
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----
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syscall events:
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event count
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---------------------------------------- -----------
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sys_write 455067
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sys_getdents 4072
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sys_close 3037
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sys_swapoff 1769
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sys_read 923
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sys_sched_setparam 826
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sys_open 331
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sys_newfstat 326
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sys_mmap 217
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sys_munmap 216
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sys_futex 141
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sys_select 102
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sys_poll 84
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sys_setitimer 12
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sys_writev 8
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15 8
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sys_lseek 7
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sys_rt_sigprocmask 6
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sys_wait4 3
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sys_ioctl 3
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sys_set_robust_list 1
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sys_exit 1
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56 1
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sys_access 1
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----
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Basically our task is to keep a per-syscall tally that gets updated
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every time a system call occurs in the system. Our script will do
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that, but first we need to record the data that will be processed by
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that script. Theoretically, there are a couple of ways we could do
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that:
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- we could enable every event under the tracing/events/syscalls
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directory, but this is over 600 syscalls, well beyond the number
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allowable by perf. These individual syscall events will however be
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useful if we want to later use the guidance we get from the
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general-purpose scripts to drill down and get more detail about
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individual syscalls of interest.
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- we can enable the sys_enter and/or sys_exit syscalls found under
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tracing/events/raw_syscalls. These are called for all syscalls; the
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'id' field can be used to distinguish between individual syscall
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numbers.
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For this script, we only need to know that a syscall was entered; we
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don't care how it exited, so we'll use 'perf record' to record only
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the sys_enter events:
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----
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# perf record -a -e raw_syscalls:sys_enter
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^C[ perf record: Woken up 1 times to write data ]
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[ perf record: Captured and wrote 56.545 MB perf.data (~2470503 samples) ]
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----
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The options basically say to collect data for every syscall event
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system-wide and multiplex the per-cpu output into a single stream.
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That single stream will be recorded in a file in the current directory
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called perf.data.
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Once we have a perf.data file containing our data, we can use the -g
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'perf script' option to generate a Python script that will contain a
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callback handler for each event type found in the perf.data trace
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stream (for more details, see the STARTER SCRIPTS section).
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----
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# perf script -g python
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generated Python script: perf-script.py
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The output file created also in the current directory is named
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perf-script.py. Here's the file in its entirety:
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# perf script event handlers, generated by perf script -g python
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# Licensed under the terms of the GNU GPL License version 2
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# The common_* event handler fields are the most useful fields common to
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# all events. They don't necessarily correspond to the 'common_*' fields
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# in the format files. Those fields not available as handler params can
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# be retrieved using Python functions of the form common_*(context).
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# See the perf-script-python Documentation for the list of available functions.
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import os
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import sys
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sys.path.append(os.environ['PERF_EXEC_PATH'] + \
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'/scripts/python/perf-script-Util/lib/Perf/Trace')
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from perf_trace_context import *
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from Core import *
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def trace_begin():
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print "in trace_begin"
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def trace_end():
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print "in trace_end"
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def raw_syscalls__sys_enter(event_name, context, common_cpu,
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common_secs, common_nsecs, common_pid, common_comm,
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id, args):
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print_header(event_name, common_cpu, common_secs, common_nsecs,
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common_pid, common_comm)
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print "id=%d, args=%s\n" % \
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(id, args),
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def trace_unhandled(event_name, context, common_cpu, common_secs, common_nsecs,
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common_pid, common_comm):
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print_header(event_name, common_cpu, common_secs, common_nsecs,
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common_pid, common_comm)
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def print_header(event_name, cpu, secs, nsecs, pid, comm):
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print "%-20s %5u %05u.%09u %8u %-20s " % \
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(event_name, cpu, secs, nsecs, pid, comm),
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----
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At the top is a comment block followed by some import statements and a
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path append which every perf script script should include.
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Following that are a couple generated functions, trace_begin() and
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trace_end(), which are called at the beginning and the end of the
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script respectively (for more details, see the SCRIPT_LAYOUT section
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below).
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Following those are the 'event handler' functions generated one for
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every event in the 'perf record' output. The handler functions take
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the form subsystem__event_name, and contain named parameters, one for
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each field in the event; in this case, there's only one event,
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raw_syscalls__sys_enter(). (see the EVENT HANDLERS section below for
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more info on event handlers).
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The final couple of functions are, like the begin and end functions,
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generated for every script. The first, trace_unhandled(), is called
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every time the script finds an event in the perf.data file that
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doesn't correspond to any event handler in the script. This could
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mean either that the record step recorded event types that it wasn't
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really interested in, or the script was run against a trace file that
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doesn't correspond to the script.
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The script generated by -g option simply prints a line for each
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event found in the trace stream i.e. it basically just dumps the event
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and its parameter values to stdout. The print_header() function is
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simply a utility function used for that purpose. Let's rename the
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script and run it to see the default output:
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----
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# mv perf-script.py syscall-counts.py
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# perf script -s syscall-counts.py
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raw_syscalls__sys_enter 1 00840.847582083 7506 perf id=1, args=
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raw_syscalls__sys_enter 1 00840.847595764 7506 perf id=1, args=
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raw_syscalls__sys_enter 1 00840.847620860 7506 perf id=1, args=
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raw_syscalls__sys_enter 1 00840.847710478 6533 npviewer.bin id=78, args=
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raw_syscalls__sys_enter 1 00840.847719204 6533 npviewer.bin id=142, args=
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raw_syscalls__sys_enter 1 00840.847755445 6533 npviewer.bin id=3, args=
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raw_syscalls__sys_enter 1 00840.847775601 6533 npviewer.bin id=3, args=
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raw_syscalls__sys_enter 1 00840.847781820 6533 npviewer.bin id=3, args=
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.
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.
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.
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----
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Of course, for this script, we're not interested in printing every
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trace event, but rather aggregating it in a useful way. So we'll get
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rid of everything to do with printing as well as the trace_begin() and
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trace_unhandled() functions, which we won't be using. That leaves us
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with this minimalistic skeleton:
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----
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import os
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import sys
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sys.path.append(os.environ['PERF_EXEC_PATH'] + \
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'/scripts/python/perf-script-Util/lib/Perf/Trace')
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from perf_trace_context import *
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from Core import *
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def trace_end():
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print "in trace_end"
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def raw_syscalls__sys_enter(event_name, context, common_cpu,
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common_secs, common_nsecs, common_pid, common_comm,
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id, args):
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----
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In trace_end(), we'll simply print the results, but first we need to
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generate some results to print. To do that we need to have our
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sys_enter() handler do the necessary tallying until all events have
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been counted. A hash table indexed by syscall id is a good way to
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store that information; every time the sys_enter() handler is called,
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we simply increment a count associated with that hash entry indexed by
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that syscall id:
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----
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syscalls = autodict()
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try:
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syscalls[id] += 1
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except TypeError:
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syscalls[id] = 1
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----
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The syscalls 'autodict' object is a special kind of Python dictionary
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(implemented in Core.py) that implements Perl's 'autovivifying' hashes
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in Python i.e. with autovivifying hashes, you can assign nested hash
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values without having to go to the trouble of creating intermediate
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levels if they don't exist e.g syscalls[comm][pid][id] = 1 will create
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the intermediate hash levels and finally assign the value 1 to the
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hash entry for 'id' (because the value being assigned isn't a hash
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object itself, the initial value is assigned in the TypeError
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exception. Well, there may be a better way to do this in Python but
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that's what works for now).
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Putting that code into the raw_syscalls__sys_enter() handler, we
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effectively end up with a single-level dictionary keyed on syscall id
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and having the counts we've tallied as values.
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The print_syscall_totals() function iterates over the entries in the
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dictionary and displays a line for each entry containing the syscall
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name (the dictonary keys contain the syscall ids, which are passed to
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the Util function syscall_name(), which translates the raw syscall
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numbers to the corresponding syscall name strings). The output is
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displayed after all the events in the trace have been processed, by
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calling the print_syscall_totals() function from the trace_end()
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handler called at the end of script processing.
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The final script producing the output shown above is shown in its
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entirety below (syscall_name() helper is not yet available, you can
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only deal with id's for now):
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----
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import os
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import sys
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sys.path.append(os.environ['PERF_EXEC_PATH'] + \
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'/scripts/python/perf-script-Util/lib/Perf/Trace')
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from perf_trace_context import *
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from Core import *
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from Util import *
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syscalls = autodict()
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def trace_end():
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print_syscall_totals()
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def raw_syscalls__sys_enter(event_name, context, common_cpu,
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common_secs, common_nsecs, common_pid, common_comm,
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id, args):
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try:
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syscalls[id] += 1
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except TypeError:
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syscalls[id] = 1
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def print_syscall_totals():
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if for_comm is not None:
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print "\nsyscall events for %s:\n\n" % (for_comm),
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else:
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print "\nsyscall events:\n\n",
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print "%-40s %10s\n" % ("event", "count"),
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print "%-40s %10s\n" % ("----------------------------------------", \
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"-----------"),
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for id, val in sorted(syscalls.iteritems(), key = lambda(k, v): (v, k), \
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reverse = True):
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print "%-40s %10d\n" % (syscall_name(id), val),
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----
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The script can be run just as before:
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# perf script -s syscall-counts.py
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So those are the essential steps in writing and running a script. The
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process can be generalized to any tracepoint or set of tracepoints
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you're interested in - basically find the tracepoint(s) you're
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interested in by looking at the list of available events shown by
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'perf list' and/or look in /sys/kernel/debug/tracing events for
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detailed event and field info, record the corresponding trace data
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using 'perf record', passing it the list of interesting events,
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generate a skeleton script using 'perf script -g python' and modify the
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code to aggregate and display it for your particular needs.
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After you've done that you may end up with a general-purpose script
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that you want to keep around and have available for future use. By
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writing a couple of very simple shell scripts and putting them in the
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right place, you can have your script listed alongside the other
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scripts listed by the 'perf script -l' command e.g.:
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----
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root@tropicana:~# perf script -l
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List of available trace scripts:
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workqueue-stats workqueue stats (ins/exe/create/destroy)
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wakeup-latency system-wide min/max/avg wakeup latency
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rw-by-file <comm> r/w activity for a program, by file
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rw-by-pid system-wide r/w activity
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----
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A nice side effect of doing this is that you also then capture the
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probably lengthy 'perf record' command needed to record the events for
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the script.
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To have the script appear as a 'built-in' script, you write two simple
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scripts, one for recording and one for 'reporting'.
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The 'record' script is a shell script with the same base name as your
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script, but with -record appended. The shell script should be put
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into the perf/scripts/python/bin directory in the kernel source tree.
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In that script, you write the 'perf record' command-line needed for
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your script:
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----
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# cat kernel-source/tools/perf/scripts/python/bin/syscall-counts-record
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#!/bin/bash
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perf record -a -e raw_syscalls:sys_enter
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----
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The 'report' script is also a shell script with the same base name as
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your script, but with -report appended. It should also be located in
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the perf/scripts/python/bin directory. In that script, you write the
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'perf script -s' command-line needed for running your script:
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----
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# cat kernel-source/tools/perf/scripts/python/bin/syscall-counts-report
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#!/bin/bash
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# description: system-wide syscall counts
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perf script -s ~/libexec/perf-core/scripts/python/syscall-counts.py
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----
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Note that the location of the Python script given in the shell script
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is in the libexec/perf-core/scripts/python directory - this is where
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the script will be copied by 'make install' when you install perf.
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For the installation to install your script there, your script needs
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to be located in the perf/scripts/python directory in the kernel
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source tree:
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----
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# ls -al kernel-source/tools/perf/scripts/python
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root@tropicana:/home/trz/src/tip# ls -al tools/perf/scripts/python
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total 32
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drwxr-xr-x 4 trz trz 4096 2010-01-26 22:30 .
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drwxr-xr-x 4 trz trz 4096 2010-01-26 22:29 ..
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drwxr-xr-x 2 trz trz 4096 2010-01-26 22:29 bin
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-rw-r--r-- 1 trz trz 2548 2010-01-26 22:29 check-perf-script.py
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drwxr-xr-x 3 trz trz 4096 2010-01-26 22:49 perf-script-Util
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-rw-r--r-- 1 trz trz 1462 2010-01-26 22:30 syscall-counts.py
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----
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Once you've done that (don't forget to do a new 'make install',
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otherwise your script won't show up at run-time), 'perf script -l'
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should show a new entry for your script:
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----
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root@tropicana:~# perf script -l
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List of available trace scripts:
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workqueue-stats workqueue stats (ins/exe/create/destroy)
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wakeup-latency system-wide min/max/avg wakeup latency
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rw-by-file <comm> r/w activity for a program, by file
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rw-by-pid system-wide r/w activity
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syscall-counts system-wide syscall counts
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----
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You can now perform the record step via 'perf script record':
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# perf script record syscall-counts
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and display the output using 'perf script report':
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# perf script report syscall-counts
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STARTER SCRIPTS
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---------------
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You can quickly get started writing a script for a particular set of
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trace data by generating a skeleton script using 'perf script -g
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python' in the same directory as an existing perf.data trace file.
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That will generate a starter script containing a handler for each of
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the event types in the trace file; it simply prints every available
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field for each event in the trace file.
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You can also look at the existing scripts in
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~/libexec/perf-core/scripts/python for typical examples showing how to
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do basic things like aggregate event data, print results, etc. Also,
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the check-perf-script.py script, while not interesting for its results,
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attempts to exercise all of the main scripting features.
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EVENT HANDLERS
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--------------
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When perf script is invoked using a trace script, a user-defined
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'handler function' is called for each event in the trace. If there's
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no handler function defined for a given event type, the event is
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ignored (or passed to a 'trace_handled' function, see below) and the
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next event is processed.
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Most of the event's field values are passed as arguments to the
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handler function; some of the less common ones aren't - those are
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available as calls back into the perf executable (see below).
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As an example, the following perf record command can be used to record
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all sched_wakeup events in the system:
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# perf record -a -e sched:sched_wakeup
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Traces meant to be processed using a script should be recorded with
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the above option: -a to enable system-wide collection.
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The format file for the sched_wakep event defines the following fields
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(see /sys/kernel/debug/tracing/events/sched/sched_wakeup/format):
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----
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format:
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field:unsigned short common_type;
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field:unsigned char common_flags;
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field:unsigned char common_preempt_count;
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field:int common_pid;
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field:char comm[TASK_COMM_LEN];
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field:pid_t pid;
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field:int prio;
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field:int success;
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field:int target_cpu;
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----
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The handler function for this event would be defined as:
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----
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def sched__sched_wakeup(event_name, context, common_cpu, common_secs,
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common_nsecs, common_pid, common_comm,
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comm, pid, prio, success, target_cpu):
|
|
pass
|
|
----
|
|
|
|
The handler function takes the form subsystem__event_name.
|
|
|
|
The common_* arguments in the handler's argument list are the set of
|
|
arguments passed to all event handlers; some of the fields correspond
|
|
to the common_* fields in the format file, but some are synthesized,
|
|
and some of the common_* fields aren't common enough to to be passed
|
|
to every event as arguments but are available as library functions.
|
|
|
|
Here's a brief description of each of the invariant event args:
|
|
|
|
event_name the name of the event as text
|
|
context an opaque 'cookie' used in calls back into perf
|
|
common_cpu the cpu the event occurred on
|
|
common_secs the secs portion of the event timestamp
|
|
common_nsecs the nsecs portion of the event timestamp
|
|
common_pid the pid of the current task
|
|
common_comm the name of the current process
|
|
|
|
All of the remaining fields in the event's format file have
|
|
counterparts as handler function arguments of the same name, as can be
|
|
seen in the example above.
|
|
|
|
The above provides the basics needed to directly access every field of
|
|
every event in a trace, which covers 90% of what you need to know to
|
|
write a useful trace script. The sections below cover the rest.
|
|
|
|
SCRIPT LAYOUT
|
|
-------------
|
|
|
|
Every perf script Python script should start by setting up a Python
|
|
module search path and 'import'ing a few support modules (see module
|
|
descriptions below):
|
|
|
|
----
|
|
import os
|
|
import sys
|
|
|
|
sys.path.append(os.environ['PERF_EXEC_PATH'] + \
|
|
'/scripts/python/perf-script-Util/lib/Perf/Trace')
|
|
|
|
from perf_trace_context import *
|
|
from Core import *
|
|
----
|
|
|
|
The rest of the script can contain handler functions and support
|
|
functions in any order.
|
|
|
|
Aside from the event handler functions discussed above, every script
|
|
can implement a set of optional functions:
|
|
|
|
*trace_begin*, if defined, is called before any event is processed and
|
|
gives scripts a chance to do setup tasks:
|
|
|
|
----
|
|
def trace_begin:
|
|
pass
|
|
----
|
|
|
|
*trace_end*, if defined, is called after all events have been
|
|
processed and gives scripts a chance to do end-of-script tasks, such
|
|
as display results:
|
|
|
|
----
|
|
def trace_end:
|
|
pass
|
|
----
|
|
|
|
*trace_unhandled*, if defined, is called after for any event that
|
|
doesn't have a handler explicitly defined for it. The standard set
|
|
of common arguments are passed into it:
|
|
|
|
----
|
|
def trace_unhandled(event_name, context, common_cpu, common_secs,
|
|
common_nsecs, common_pid, common_comm):
|
|
pass
|
|
----
|
|
|
|
The remaining sections provide descriptions of each of the available
|
|
built-in perf script Python modules and their associated functions.
|
|
|
|
AVAILABLE MODULES AND FUNCTIONS
|
|
-------------------------------
|
|
|
|
The following sections describe the functions and variables available
|
|
via the various perf script Python modules. To use the functions and
|
|
variables from the given module, add the corresponding 'from XXXX
|
|
import' line to your perf script script.
|
|
|
|
Core.py Module
|
|
~~~~~~~~~~~~~~
|
|
|
|
These functions provide some essential functions to user scripts.
|
|
|
|
The *flag_str* and *symbol_str* functions provide human-readable
|
|
strings for flag and symbolic fields. These correspond to the strings
|
|
and values parsed from the 'print fmt' fields of the event format
|
|
files:
|
|
|
|
flag_str(event_name, field_name, field_value) - returns the string represention corresponding to field_value for the flag field field_name of event event_name
|
|
symbol_str(event_name, field_name, field_value) - returns the string represention corresponding to field_value for the symbolic field field_name of event event_name
|
|
|
|
The *autodict* function returns a special kind of Python
|
|
dictionary that implements Perl's 'autovivifying' hashes in Python
|
|
i.e. with autovivifying hashes, you can assign nested hash values
|
|
without having to go to the trouble of creating intermediate levels if
|
|
they don't exist.
|
|
|
|
autodict() - returns an autovivifying dictionary instance
|
|
|
|
|
|
perf_trace_context Module
|
|
~~~~~~~~~~~~~~~~~~~~~~~~~
|
|
|
|
Some of the 'common' fields in the event format file aren't all that
|
|
common, but need to be made accessible to user scripts nonetheless.
|
|
|
|
perf_trace_context defines a set of functions that can be used to
|
|
access this data in the context of the current event. Each of these
|
|
functions expects a context variable, which is the same as the
|
|
context variable passed into every event handler as the second
|
|
argument.
|
|
|
|
common_pc(context) - returns common_preempt count for the current event
|
|
common_flags(context) - returns common_flags for the current event
|
|
common_lock_depth(context) - returns common_lock_depth for the current event
|
|
|
|
Util.py Module
|
|
~~~~~~~~~~~~~~
|
|
|
|
Various utility functions for use with perf script:
|
|
|
|
nsecs(secs, nsecs) - returns total nsecs given secs/nsecs pair
|
|
nsecs_secs(nsecs) - returns whole secs portion given nsecs
|
|
nsecs_nsecs(nsecs) - returns nsecs remainder given nsecs
|
|
nsecs_str(nsecs) - returns printable string in the form secs.nsecs
|
|
avg(total, n) - returns average given a sum and a total number of values
|
|
|
|
SEE ALSO
|
|
--------
|
|
linkperf:perf-script[1]
|