Commit e0c48bf9 authored by Adrian Hunter's avatar Adrian Hunter Committed by Arnaldo Carvalho de Melo

perf scripts python: Add a script to run instances of 'perf script' in parallel

Add a Python script to run a perf script command multiple times in
parallel, using perf script options --cpu and --time so that each job
processes a different chunk of the data.

Extend perf script tests to test also the new script.

The script supports the use of normal 'perf script' options like
--dlfilter and --script, so that the benefit of running parallel jobs
naturally extends to them also. In addition, a command can be provided
(refer --pipe-to option) to pipe standard output to a custom command.

Refer to the script's own help text at the end of the patch for more
details.

The script is useful for Intel PT traces, that can be efficiently
decoded by 'perf script' when split by CPU and/or time ranges. Running
jobs in parallel can decrease the overall decoding time.

Committer testing:

  Ian reported that shellcheck found some issues, I installed it as there
  are no warnings about it not being available, but when available it
  fails the build with:

    TEST    /tmp/build/perf-tools-next/tests/shell/script.sh.shellcheck_log
    CC      /tmp/build/perf-tools-next/util/header.o

  In tests/shell/script.sh line 20:
                  rm -rf "${temp_dir}/"*
                         ^-------------^ SC2115 (warning): Use "${var:?}" to ensure this never expands to /* .

  In tests/shell/script.sh line 83:
          output1_dir="${temp_dir}/output1"
          ^---------^ SC2034 (warning): output1_dir appears unused. Verify use (or export if used externally).

  In tests/shell/script.sh line 84:
          output2_dir="${temp_dir}/output2"
          ^---------^ SC2034 (warning): output2_dir appears unused. Verify use (or export if used externally).

  In tests/shell/script.sh line 86:
          python3 "${pp}" -o "${output_dir}" --jobs 4 --verbose -- perf script -i "${perf_data}"
                              ^-----------^ SC2154 (warning): output_dir is referenced but not assigned (did you mean 'output1_dir'?).

  For more information:
    https://www.shellcheck.net/wiki/SC2034 -- output1_dir appears unused. Verif...
    https://www.shellcheck.net/wiki/SC2115 -- Use "${var:?}" to ensure this nev...
    https://www.shellcheck.net/wiki/SC2154 -- output_dir is referenced but not ...

Did these fixes:

  -               rm -rf "${temp_dir}/"*
  +               rm -rf "${temp_dir:?}/"*

And:

   @@ -83,8 +83,8 @@ test_parallel_perf()
          output1_dir="${temp_dir}/output1"
          output2_dir="${temp_dir}/output2"
          perf record -o "${perf_data}" --sample-cpu uname
  -       python3 "${pp}" -o "${output_dir}" --jobs 4 --verbose -- perf script -i "${perf_data}"
  -       python3 "${pp}" -o "${output_dir}" --jobs 4 --verbose --per-cpu -- perf script -i "${perf_data}"
  +       python3 "${pp}" -o "${output1_dir}" --jobs 4 --verbose -- perf script -i "${perf_data}"
  +       python3 "${pp}" -o "${output2_dir}" --jobs 4 --verbose --per-cpu -- perf script -i "${perf_data}"

After that:

  root@number:~# perf test -vv "perf script tests"
   97: perf script tests:
  --- start ---
  test child forked, pid 4084139
  DB test
  [ perf record: Woken up 1 times to write data ]
  [ perf record: Captured and wrote 0.032 MB /tmp/perf-test-script.T4MJDr0L6J/perf.data (7 samples) ]
  <SNIP>
  DB test [Success]
  parallel-perf test
  Linux
  [ perf record: Woken up 1 times to write data ]
  [ perf record: Captured and wrote 0.034 MB /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data (7 samples) ]
  Starting: perf script --time=,91898.301878499 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --time=91898.301878500,91898.301905999 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --time=91898.301906000,91898.301933499 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --time=91898.301933500, -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --time=91898.301878500,91898.301905999 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --time=91898.301906000,91898.301933499 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  There are 4 jobs: 2 completed, 2 running
  Finished: perf script --time=,91898.301878499 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --time=91898.301933500, -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  There are 4 jobs: 4 completed, 0 running
  All jobs finished successfully
  parallel-perf.py done
  Starting: perf script --cpu=0 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=1 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=2 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=3 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=0 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=1 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=2 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=3 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  There are 28 jobs: 4 completed, 0 running
  Starting: perf script --cpu=4 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=5 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=6 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=7 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=4 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=5 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=6 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=7 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  There are 28 jobs: 8 completed, 0 running
  Starting: perf script --cpu=8 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=9 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=10 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=11 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=8 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=9 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=10 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=11 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  There are 28 jobs: 12 completed, 0 running
  Starting: perf script --cpu=12 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=13 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=14 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=15 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=12 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=13 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=14 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=15 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  There are 28 jobs: 16 completed, 0 running
  Starting: perf script --cpu=16 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=17 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=18 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=19 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=16 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=17 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=18 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=19 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  There are 28 jobs: 20 completed, 0 running
  Starting: perf script --cpu=20 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=21 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=22 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=23 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=20 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=21 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=22 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=23 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  There are 28 jobs: 24 completed, 0 running
  Starting: perf script --cpu=24 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=25 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=26 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Starting: perf script --cpu=27 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=25 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=26 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  Finished: perf script --cpu=27 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  There are 28 jobs: 27 completed, 1 running
  Finished: perf script --cpu=24 -i /tmp/perf-test-script.T4MJDr0L6J/pp-perf.data
  There are 28 jobs: 28 completed, 0 running
  All jobs finished successfully
  parallel-perf.py done
  parallel-perf test [Success]
  --- Cleaning up ---
  ---- end(0) ----
   97: perf script tests                                               : Ok
  root@number:~#
Reviewed-by: default avatarAndi Kleen <ak@linux.intel.com>
Signed-off-by: default avatarAdrian Hunter <adrian.hunter@intel.com>
Tested-by: default avatarArnaldo Carvalho de Melo <acme@redhat.com>
Cc: Ian Rogers <irogers@google.com>
Cc: Jiri Olsa <jolsa@kernel.org>
Cc: Namhyung Kim <namhyung@kernel.org>
Link: https://lore.kernel.org/r/20240423133248.10206-1-adrian.hunter@intel.comSigned-off-by: default avatarArnaldo Carvalho de Melo <acme@redhat.com>
parent cd88c11c
#!/usr/bin/env python3
# SPDX-License-Identifier: GPL-2.0
#
# Run a perf script command multiple times in parallel, using perf script
# options --cpu and --time so that each job processes a different chunk
# of the data.
#
# Copyright (c) 2024, Intel Corporation.
import subprocess
import argparse
import pathlib
import shlex
import time
import copy
import sys
import os
import re
glb_prog_name = "parallel-perf.py"
glb_min_interval = 10.0
glb_min_samples = 64
class Verbosity():
def __init__(self, quiet=False, verbose=False, debug=False):
self.normal = True
self.verbose = verbose
self.debug = debug
self.self_test = True
if self.debug:
self.verbose = True
if self.verbose:
quiet = False
if quiet:
self.normal = False
# Manage work (Start/Wait/Kill), as represented by a subprocess.Popen command
class Work():
def __init__(self, cmd, pipe_to, output_dir="."):
self.popen = None
self.consumer = None
self.cmd = cmd
self.pipe_to = pipe_to
self.output_dir = output_dir
self.cmdout_name = f"{output_dir}/cmd.txt"
self.stdout_name = f"{output_dir}/out.txt"
self.stderr_name = f"{output_dir}/err.txt"
def Command(self):
sh_cmd = [ shlex.quote(x) for x in self.cmd ]
return " ".join(self.cmd)
def Stdout(self):
return open(self.stdout_name, "w")
def Stderr(self):
return open(self.stderr_name, "w")
def CreateOutputDir(self):
pathlib.Path(self.output_dir).mkdir(parents=True, exist_ok=True)
def Start(self):
if self.popen:
return
self.CreateOutputDir()
with open(self.cmdout_name, "w") as f:
f.write(self.Command())
f.write("\n")
stdout = self.Stdout()
stderr = self.Stderr()
if self.pipe_to:
self.popen = subprocess.Popen(self.cmd, stdout=subprocess.PIPE, stderr=stderr)
args = shlex.split(self.pipe_to)
self.consumer = subprocess.Popen(args, stdin=self.popen.stdout, stdout=stdout, stderr=stderr)
else:
self.popen = subprocess.Popen(self.cmd, stdout=stdout, stderr=stderr)
def RemoveEmptyErrFile(self):
if os.path.exists(self.stderr_name):
if os.path.getsize(self.stderr_name) == 0:
os.unlink(self.stderr_name)
def Errors(self):
if os.path.exists(self.stderr_name):
if os.path.getsize(self.stderr_name) != 0:
return [ f"Non-empty error file {self.stderr_name}" ]
return []
def TidyUp(self):
self.RemoveEmptyErrFile()
def RawPollWait(self, p, wait):
if wait:
return p.wait()
return p.poll()
def Poll(self, wait=False):
if not self.popen:
return None
result = self.RawPollWait(self.popen, wait)
if self.consumer:
res = result
result = self.RawPollWait(self.consumer, wait)
if result != None and res == None:
self.popen.kill()
result = None
elif result == 0 and res != None and res != 0:
result = res
if result != None:
self.TidyUp()
return result
def Wait(self):
return self.Poll(wait=True)
def Kill(self):
if not self.popen:
return
self.popen.kill()
if self.consumer:
self.consumer.kill()
def KillWork(worklist, verbosity):
for w in worklist:
w.Kill()
for w in worklist:
w.Wait()
def NumberOfCPUs():
return os.sysconf("SC_NPROCESSORS_ONLN")
def NanoSecsToSecsStr(x):
if x == None:
return ""
x = str(x)
if len(x) < 10:
x = "0" * (10 - len(x)) + x
return x[:len(x) - 9] + "." + x[-9:]
def InsertOptionAfter(cmd, option, after):
try:
pos = cmd.index(after)
cmd.insert(pos + 1, option)
except:
cmd.append(option)
def CreateWorkList(cmd, pipe_to, output_dir, cpus, time_ranges_by_cpu):
max_len = len(str(cpus[-1]))
cpu_dir_fmt = f"cpu-%.{max_len}u"
worklist = []
pos = 0
for cpu in cpus:
if cpu >= 0:
cpu_dir = os.path.join(output_dir, cpu_dir_fmt % cpu)
cpu_option = f"--cpu={cpu}"
else:
cpu_dir = output_dir
cpu_option = None
tr_dir_fmt = "time-range"
if len(time_ranges_by_cpu) > 1:
time_ranges = time_ranges_by_cpu[pos]
tr_dir_fmt += f"-{pos}"
pos += 1
else:
time_ranges = time_ranges_by_cpu[0]
max_len = len(str(len(time_ranges)))
tr_dir_fmt += f"-%.{max_len}u"
i = 0
for r in time_ranges:
if r == [None, None]:
time_option = None
work_output_dir = cpu_dir
else:
time_option = "--time=" + NanoSecsToSecsStr(r[0]) + "," + NanoSecsToSecsStr(r[1])
work_output_dir = os.path.join(cpu_dir, tr_dir_fmt % i)
i += 1
work_cmd = list(cmd)
if time_option != None:
InsertOptionAfter(work_cmd, time_option, "script")
if cpu_option != None:
InsertOptionAfter(work_cmd, cpu_option, "script")
w = Work(work_cmd, pipe_to, work_output_dir)
worklist.append(w)
return worklist
def DoRunWork(worklist, nr_jobs, verbosity):
nr_to_do = len(worklist)
not_started = list(worklist)
running = []
done = []
chg = False
while True:
nr_done = len(done)
if chg and verbosity.normal:
nr_run = len(running)
print(f"\rThere are {nr_to_do} jobs: {nr_done} completed, {nr_run} running", flush=True, end=" ")
if verbosity.verbose:
print()
chg = False
if nr_done == nr_to_do:
break
while len(running) < nr_jobs and len(not_started):
w = not_started.pop(0)
running.append(w)
if verbosity.verbose:
print("Starting:", w.Command())
w.Start()
chg = True
if len(running):
time.sleep(0.1)
finished = []
not_finished = []
while len(running):
w = running.pop(0)
r = w.Poll()
if r == None:
not_finished.append(w)
continue
if r == 0:
if verbosity.verbose:
print("Finished:", w.Command())
finished.append(w)
chg = True
continue
if verbosity.normal and not verbosity.verbose:
print()
print("Job failed!\n return code:", r, "\n command: ", w.Command())
if w.pipe_to:
print(" piped to: ", w.pipe_to)
print("Killing outstanding jobs")
KillWork(not_finished, verbosity)
KillWork(running, verbosity)
return False
running = not_finished
done += finished
errorlist = []
for w in worklist:
errorlist += w.Errors()
if len(errorlist):
print("Errors:")
for e in errorlist:
print(e)
elif verbosity.normal:
print("\r"," "*50, "\rAll jobs finished successfully", flush=True)
return True
def RunWork(worklist, nr_jobs=NumberOfCPUs(), verbosity=Verbosity()):
try:
return DoRunWork(worklist, nr_jobs, verbosity)
except:
for w in worklist:
w.Kill()
raise
return True
def ReadHeader(perf, file_name):
return subprocess.Popen([perf, "script", "--header-only", "--input", file_name], stdout=subprocess.PIPE).stdout.read().decode("utf-8")
def ParseHeader(hdr):
result = {}
lines = hdr.split("\n")
for line in lines:
if ":" in line and line[0] == "#":
pos = line.index(":")
name = line[1:pos-1].strip()
value = line[pos+1:].strip()
if name in result:
orig_name = name
nr = 2
while True:
name = f"{orig_name} {nr}"
if name not in result:
break
nr += 1
result[name] = value
return result
def HeaderField(hdr_dict, hdr_fld):
if hdr_fld not in hdr_dict:
raise Exception(f"'{hdr_fld}' missing from header information")
return hdr_dict[hdr_fld]
# Represent the position of an option within a command string
# and provide the option value and/or remove the option
class OptPos():
def Init(self, opt_element=-1, value_element=-1, opt_pos=-1, value_pos=-1, error=None):
self.opt_element = opt_element # list element that contains option
self.value_element = value_element # list element that contains option value
self.opt_pos = opt_pos # string position of option
self.value_pos = value_pos # string position of value
self.error = error # error message string
def __init__(self, args, short_name, long_name, default=None):
self.args = list(args)
self.default = default
n = 2 + len(long_name)
m = len(short_name)
pos = -1
for opt in args:
pos += 1
if m and opt[:2] == f"-{short_name}":
if len(opt) == 2:
if pos + 1 < len(args):
self.Init(pos, pos + 1, 0, 0)
else:
self.Init(error = f"-{short_name} option missing value")
else:
self.Init(pos, pos, 0, 2)
return
if opt[:n] == f"--{long_name}":
if len(opt) == n:
if pos + 1 < len(args):
self.Init(pos, pos + 1, 0, 0)
else:
self.Init(error = f"--{long_name} option missing value")
elif opt[n] == "=":
self.Init(pos, pos, 0, n + 1)
else:
self.Init(error = f"--{long_name} option expected '='")
return
if m and opt[:1] == "-" and opt[:2] != "--" and short_name in opt:
ipos = opt.index(short_name)
if "-" in opt[1:]:
hpos = opt[1:].index("-")
if hpos < ipos:
continue
if ipos + 1 == len(opt):
if pos + 1 < len(args):
self.Init(pos, pos + 1, ipos, 0)
else:
self.Init(error = f"-{short_name} option missing value")
else:
self.Init(pos, pos, ipos, ipos + 1)
return
self.Init()
def Value(self):
if self.opt_element >= 0:
if self.opt_element != self.value_element:
return self.args[self.value_element]
else:
return self.args[self.value_element][self.value_pos:]
return self.default
def Remove(self, args):
if self.opt_element == -1:
return
if self.opt_element != self.value_element:
del args[self.value_element]
if self.opt_pos:
args[self.opt_element] = args[self.opt_element][:self.opt_pos]
else:
del args[self.opt_element]
def DetermineInputFileName(cmd):
p = OptPos(cmd, "i", "input", "perf.data")
if p.error:
raise Exception(f"perf command {p.error}")
file_name = p.Value()
if not os.path.exists(file_name):
raise Exception(f"perf command input file '{file_name}' not found")
return file_name
def ReadOption(args, short_name, long_name, err_prefix, remove=False):
p = OptPos(args, short_name, long_name)
if p.error:
raise Exception(f"{err_prefix}{p.error}")
value = p.Value()
if remove:
p.Remove(args)
return value
def ExtractOption(args, short_name, long_name, err_prefix):
return ReadOption(args, short_name, long_name, err_prefix, True)
def ReadPerfOption(args, short_name, long_name):
return ReadOption(args, short_name, long_name, "perf command ")
def ExtractPerfOption(args, short_name, long_name):
return ExtractOption(args, short_name, long_name, "perf command ")
def PerfDoubleQuickCommands(cmd, file_name):
cpu_str = ReadPerfOption(cmd, "C", "cpu")
time_str = ReadPerfOption(cmd, "", "time")
# Use double-quick sampling to determine trace data density
times_cmd = ["perf", "script", "--ns", "--input", file_name, "--itrace=qqi"]
if cpu_str != None and cpu_str != "":
times_cmd.append(f"--cpu={cpu_str}")
if time_str != None and time_str != "":
times_cmd.append(f"--time={time_str}")
cnts_cmd = list(times_cmd)
cnts_cmd.append("-Fcpu")
times_cmd.append("-Fcpu,time")
return cnts_cmd, times_cmd
class CPUTimeRange():
def __init__(self, cpu):
self.cpu = cpu
self.sample_cnt = 0
self.time_ranges = None
self.interval = 0
self.interval_remaining = 0
self.remaining = 0
self.tr_pos = 0
def CalcTimeRangesByCPU(line, cpu, cpu_time_ranges, max_time):
cpu_time_range = cpu_time_ranges[cpu]
cpu_time_range.remaining -= 1
cpu_time_range.interval_remaining -= 1
if cpu_time_range.remaining == 0:
cpu_time_range.time_ranges[cpu_time_range.tr_pos][1] = max_time
return
if cpu_time_range.interval_remaining == 0:
time = TimeVal(line[1][:-1], 0)
time_ranges = cpu_time_range.time_ranges
time_ranges[cpu_time_range.tr_pos][1] = time - 1
time_ranges.append([time, max_time])
cpu_time_range.tr_pos += 1
cpu_time_range.interval_remaining = cpu_time_range.interval
def CountSamplesByCPU(line, cpu, cpu_time_ranges):
try:
cpu_time_ranges[cpu].sample_cnt += 1
except:
print("exception")
print("cpu", cpu)
print("len(cpu_time_ranges)", len(cpu_time_ranges))
raise
def ProcessCommandOutputLines(cmd, per_cpu, fn, *x):
# Assume CPU number is at beginning of line and enclosed by []
pat = re.compile(r"\s*\[[0-9]+\]")
p = subprocess.Popen(cmd, stdout=subprocess.PIPE)
while True:
if line := p.stdout.readline():
line = line.decode("utf-8")
if pat.match(line):
line = line.split()
if per_cpu:
# Assumes CPU number is enclosed by []
cpu = int(line[0][1:-1])
else:
cpu = 0
fn(line, cpu, *x)
else:
break
p.wait()
def IntersectTimeRanges(new_time_ranges, time_ranges):
pos = 0
new_pos = 0
# Can assume len(time_ranges) != 0 and len(new_time_ranges) != 0
# Note also, there *must* be at least one intersection.
while pos < len(time_ranges) and new_pos < len(new_time_ranges):
# new end < old start => no intersection, remove new
if new_time_ranges[new_pos][1] < time_ranges[pos][0]:
del new_time_ranges[new_pos]
continue
# new start > old end => no intersection, check next
if new_time_ranges[new_pos][0] > time_ranges[pos][1]:
pos += 1
if pos < len(time_ranges):
continue
# no next, so remove remaining
while new_pos < len(new_time_ranges):
del new_time_ranges[new_pos]
return
# Found an intersection
# new start < old start => adjust new start = old start
if new_time_ranges[new_pos][0] < time_ranges[pos][0]:
new_time_ranges[new_pos][0] = time_ranges[pos][0]
# new end > old end => keep the overlap, insert the remainder
if new_time_ranges[new_pos][1] > time_ranges[pos][1]:
r = [ time_ranges[pos][1] + 1, new_time_ranges[new_pos][1] ]
new_time_ranges[new_pos][1] = time_ranges[pos][1]
new_pos += 1
new_time_ranges.insert(new_pos, r)
continue
# new [start, end] is within old [start, end]
new_pos += 1
def SplitTimeRangesByTraceDataDensity(time_ranges, cpus, nr, cmd, file_name, per_cpu, min_size, min_interval, verbosity):
if verbosity.normal:
print("\rAnalyzing...", flush=True, end=" ")
if verbosity.verbose:
print()
cnts_cmd, times_cmd = PerfDoubleQuickCommands(cmd, file_name)
nr_cpus = cpus[-1] + 1 if per_cpu else 1
if per_cpu:
nr_cpus = cpus[-1] + 1
cpu_time_ranges = [ CPUTimeRange(cpu) for cpu in range(nr_cpus) ]
else:
nr_cpus = 1
cpu_time_ranges = [ CPUTimeRange(-1) ]
if verbosity.debug:
print("nr_cpus", nr_cpus)
print("cnts_cmd", cnts_cmd)
print("times_cmd", times_cmd)
# Count the number of "double quick" samples per CPU
ProcessCommandOutputLines(cnts_cmd, per_cpu, CountSamplesByCPU, cpu_time_ranges)
tot = 0
mx = 0
for cpu_time_range in cpu_time_ranges:
cnt = cpu_time_range.sample_cnt
tot += cnt
if cnt > mx:
mx = cnt
if verbosity.debug:
print("cpu:", cpu_time_range.cpu, "sample_cnt", cnt)
if min_size < 1:
min_size = 1
if mx < min_size:
# Too little data to be worth splitting
if verbosity.debug:
print("Too little data to split by time")
if nr == 0:
nr = 1
return [ SplitTimeRangesIntoN(time_ranges, nr, min_interval) ]
if nr:
divisor = nr
min_size = 1
else:
divisor = NumberOfCPUs()
interval = int(round(tot / divisor, 0))
if interval < min_size:
interval = min_size
if verbosity.debug:
print("divisor", divisor)
print("min_size", min_size)
print("interval", interval)
min_time = time_ranges[0][0]
max_time = time_ranges[-1][1]
for cpu_time_range in cpu_time_ranges:
cnt = cpu_time_range.sample_cnt
if cnt == 0:
cpu_time_range.time_ranges = copy.deepcopy(time_ranges)
continue
# Adjust target interval for CPU to give approximately equal interval sizes
# Determine number of intervals, rounding to nearest integer
n = int(round(cnt / interval, 0))
if n < 1:
n = 1
# Determine interval size, rounding up
d, m = divmod(cnt, n)
if m:
d += 1
cpu_time_range.interval = d
cpu_time_range.interval_remaining = d
cpu_time_range.remaining = cnt
# Init. time ranges for each CPU with the start time
cpu_time_range.time_ranges = [ [min_time, max_time] ]
# Set time ranges so that the same number of "double quick" samples
# will fall into each time range.
ProcessCommandOutputLines(times_cmd, per_cpu, CalcTimeRangesByCPU, cpu_time_ranges, max_time)
for cpu_time_range in cpu_time_ranges:
if cpu_time_range.sample_cnt:
IntersectTimeRanges(cpu_time_range.time_ranges, time_ranges)
return [cpu_time_ranges[cpu].time_ranges for cpu in cpus]
def SplitSingleTimeRangeIntoN(time_range, n):
if n <= 1:
return [time_range]
start = time_range[0]
end = time_range[1]
duration = int((end - start + 1) / n)
if duration < 1:
return [time_range]
time_ranges = []
for i in range(n):
time_ranges.append([start, start + duration - 1])
start += duration
time_ranges[-1][1] = end
return time_ranges
def TimeRangeDuration(r):
return r[1] - r[0] + 1
def TotalDuration(time_ranges):
duration = 0
for r in time_ranges:
duration += TimeRangeDuration(r)
return duration
def SplitTimeRangesByInterval(time_ranges, interval):
new_ranges = []
for r in time_ranges:
duration = TimeRangeDuration(r)
n = duration / interval
n = int(round(n, 0))
new_ranges += SplitSingleTimeRangeIntoN(r, n)
return new_ranges
def SplitTimeRangesIntoN(time_ranges, n, min_interval):
if n <= len(time_ranges):
return time_ranges
duration = TotalDuration(time_ranges)
interval = duration / n
if interval < min_interval:
interval = min_interval
return SplitTimeRangesByInterval(time_ranges, interval)
def RecombineTimeRanges(tr):
new_tr = copy.deepcopy(tr)
n = len(new_tr)
i = 1
while i < len(new_tr):
# if prev end + 1 == cur start, combine them
if new_tr[i - 1][1] + 1 == new_tr[i][0]:
new_tr[i][0] = new_tr[i - 1][0]
del new_tr[i - 1]
else:
i += 1
return new_tr
def OpenTimeRangeEnds(time_ranges, min_time, max_time):
if time_ranges[0][0] <= min_time:
time_ranges[0][0] = None
if time_ranges[-1][1] >= max_time:
time_ranges[-1][1] = None
def BadTimeStr(time_str):
raise Exception(f"perf command bad time option: '{time_str}'\nCheck also 'time of first sample' and 'time of last sample' in perf script --header-only")
def ValidateTimeRanges(time_ranges, time_str):
n = len(time_ranges)
for i in range(n):
start = time_ranges[i][0]
end = time_ranges[i][1]
if i != 0 and start <= time_ranges[i - 1][1]:
BadTimeStr(time_str)
if start > end:
BadTimeStr(time_str)
def TimeVal(s, dflt):
s = s.strip()
if s == "":
return dflt
a = s.split(".")
if len(a) > 2:
raise Exception(f"Bad time value'{s}'")
x = int(a[0])
if x < 0:
raise Exception("Negative time not allowed")
x *= 1000000000
if len(a) > 1:
x += int((a[1] + "000000000")[:9])
return x
def BadCPUStr(cpu_str):
raise Exception(f"perf command bad cpu option: '{cpu_str}'\nCheck also 'nrcpus avail' in perf script --header-only")
def ParseTimeStr(time_str, min_time, max_time):
if time_str == None or time_str == "":
return [[min_time, max_time]]
time_ranges = []
for r in time_str.split():
a = r.split(",")
if len(a) != 2:
BadTimeStr(time_str)
try:
start = TimeVal(a[0], min_time)
end = TimeVal(a[1], max_time)
except:
BadTimeStr(time_str)
time_ranges.append([start, end])
ValidateTimeRanges(time_ranges, time_str)
return time_ranges
def ParseCPUStr(cpu_str, nr_cpus):
if cpu_str == None or cpu_str == "":
return [-1]
cpus = []
for r in cpu_str.split(","):
a = r.split("-")
if len(a) < 1 or len(a) > 2:
BadCPUStr(cpu_str)
try:
start = int(a[0].strip())
if len(a) > 1:
end = int(a[1].strip())
else:
end = start
except:
BadCPUStr(cpu_str)
if start < 0 or end < 0 or end < start or end >= nr_cpus:
BadCPUStr(cpu_str)
cpus.extend(range(start, end + 1))
cpus = list(set(cpus)) # Remove duplicates
cpus.sort()
return cpus
class ParallelPerf():
def __init__(self, a):
for arg_name in vars(a):
setattr(self, arg_name, getattr(a, arg_name))
self.orig_nr = self.nr
self.orig_cmd = list(self.cmd)
self.perf = self.cmd[0]
if os.path.exists(self.output_dir):
raise Exception(f"Output '{self.output_dir}' already exists")
if self.jobs < 0 or self.nr < 0 or self.interval < 0:
raise Exception("Bad options (negative values): try -h option for help")
if self.nr != 0 and self.interval != 0:
raise Exception("Cannot specify number of time subdivisions and time interval")
if self.jobs == 0:
self.jobs = NumberOfCPUs()
if self.nr == 0 and self.interval == 0:
if self.per_cpu:
self.nr = 1
else:
self.nr = self.jobs
def Init(self):
if self.verbosity.debug:
print("cmd", self.cmd)
self.file_name = DetermineInputFileName(self.cmd)
self.hdr = ReadHeader(self.perf, self.file_name)
self.hdr_dict = ParseHeader(self.hdr)
self.cmd_line = HeaderField(self.hdr_dict, "cmdline")
def ExtractTimeInfo(self):
self.min_time = TimeVal(HeaderField(self.hdr_dict, "time of first sample"), 0)
self.max_time = TimeVal(HeaderField(self.hdr_dict, "time of last sample"), 0)
self.time_str = ExtractPerfOption(self.cmd, "", "time")
self.time_ranges = ParseTimeStr(self.time_str, self.min_time, self.max_time)
if self.verbosity.debug:
print("time_ranges", self.time_ranges)
def ExtractCPUInfo(self):
if self.per_cpu:
nr_cpus = int(HeaderField(self.hdr_dict, "nrcpus avail"))
self.cpu_str = ExtractPerfOption(self.cmd, "C", "cpu")
if self.cpu_str == None or self.cpu_str == "":
self.cpus = [ x for x in range(nr_cpus) ]
else:
self.cpus = ParseCPUStr(self.cpu_str, nr_cpus)
else:
self.cpu_str = None
self.cpus = [-1]
if self.verbosity.debug:
print("cpus", self.cpus)
def IsIntelPT(self):
return self.cmd_line.find("intel_pt") >= 0
def SplitTimeRanges(self):
if self.IsIntelPT() and self.interval == 0:
self.split_time_ranges_for_each_cpu = \
SplitTimeRangesByTraceDataDensity(self.time_ranges, self.cpus, self.orig_nr,
self.orig_cmd, self.file_name, self.per_cpu,
self.min_size, self.min_interval, self.verbosity)
elif self.nr:
self.split_time_ranges_for_each_cpu = [ SplitTimeRangesIntoN(self.time_ranges, self.nr, self.min_interval) ]
else:
self.split_time_ranges_for_each_cpu = [ SplitTimeRangesByInterval(self.time_ranges, self.interval) ]
def CheckTimeRanges(self):
for tr in self.split_time_ranges_for_each_cpu:
# Re-combined time ranges should be the same
new_tr = RecombineTimeRanges(tr)
if new_tr != self.time_ranges:
if self.verbosity.debug:
print("tr", tr)
print("new_tr", new_tr)
raise Exception("Self test failed!")
def OpenTimeRangeEnds(self):
for time_ranges in self.split_time_ranges_for_each_cpu:
OpenTimeRangeEnds(time_ranges, self.min_time, self.max_time)
def CreateWorkList(self):
self.worklist = CreateWorkList(self.cmd, self.pipe_to, self.output_dir, self.cpus, self.split_time_ranges_for_each_cpu)
def PerfDataRecordedPerCPU(self):
if "--per-thread" in self.cmd_line.split():
return False
return True
def DefaultToPerCPU(self):
# --no-per-cpu option takes precedence
if self.no_per_cpu:
return False
if not self.PerfDataRecordedPerCPU():
return False
# Default to per-cpu for Intel PT data that was recorded per-cpu,
# because decoding can be done for each CPU separately.
if self.IsIntelPT():
return True
return False
def Config(self):
self.Init()
self.ExtractTimeInfo()
if not self.per_cpu:
self.per_cpu = self.DefaultToPerCPU()
if self.verbosity.debug:
print("per_cpu", self.per_cpu)
self.ExtractCPUInfo()
self.SplitTimeRanges()
if self.verbosity.self_test:
self.CheckTimeRanges()
# Prefer open-ended time range to starting / ending with min_time / max_time resp.
self.OpenTimeRangeEnds()
self.CreateWorkList()
def Run(self):
if self.dry_run:
print(len(self.worklist),"jobs:")
for w in self.worklist:
print(w.Command())
return True
result = RunWork(self.worklist, self.jobs, verbosity=self.verbosity)
if self.verbosity.verbose:
print(glb_prog_name, "done")
return result
def RunParallelPerf(a):
pp = ParallelPerf(a)
pp.Config()
return pp.Run()
def Main(args):
ap = argparse.ArgumentParser(
prog=glb_prog_name, formatter_class = argparse.RawDescriptionHelpFormatter,
description =
"""
Run a perf script command multiple times in parallel, using perf script options
--cpu and --time so that each job processes a different chunk of the data.
""",
epilog =
"""
Follow the options by '--' and then the perf script command e.g.
$ perf record -a -- sleep 10
$ parallel-perf.py --nr=4 -- perf script --ns
All jobs finished successfully
$ tree parallel-perf-output/
parallel-perf-output/
├── time-range-0
│   ├── cmd.txt
│   └── out.txt
├── time-range-1
│   ├── cmd.txt
│   └── out.txt
├── time-range-2
│   ├── cmd.txt
│   └── out.txt
└── time-range-3
├── cmd.txt
└── out.txt
$ find parallel-perf-output -name cmd.txt | sort | xargs grep -H .
parallel-perf-output/time-range-0/cmd.txt:perf script --time=,9466.504461499 --ns
parallel-perf-output/time-range-1/cmd.txt:perf script --time=9466.504461500,9469.005396999 --ns
parallel-perf-output/time-range-2/cmd.txt:perf script --time=9469.005397000,9471.506332499 --ns
parallel-perf-output/time-range-3/cmd.txt:perf script --time=9471.506332500, --ns
Any perf script command can be used, including the use of perf script options
--dlfilter and --script, so that the benefit of running parallel jobs
naturally extends to them also.
If option --pipe-to is used, standard output is first piped through that
command. Beware, if the command fails (e.g. grep with no matches), it will be
considered a fatal error.
Final standard output is redirected to files named out.txt in separate
subdirectories under the output directory. Similarly, standard error is
written to files named err.txt. In addition, files named cmd.txt contain the
corresponding perf script command. After processing, err.txt files are removed
if they are empty.
If any job exits with a non-zero exit code, then all jobs are killed and no
more are started. A message is printed if any job results in a non-empty
err.txt file.
There is a separate output subdirectory for each time range. If the --per-cpu
option is used, these are further grouped under cpu-n subdirectories, e.g.
$ parallel-perf.py --per-cpu --nr=2 -- perf script --ns --cpu=0,1
All jobs finished successfully
$ tree parallel-perf-output
parallel-perf-output/
├── cpu-0
│   ├── time-range-0
│   │   ├── cmd.txt
│   │   └── out.txt
│   └── time-range-1
│   ├── cmd.txt
│   └── out.txt
└── cpu-1
├── time-range-0
│   ├── cmd.txt
│   └── out.txt
└── time-range-1
├── cmd.txt
└── out.txt
$ find parallel-perf-output -name cmd.txt | sort | xargs grep -H .
parallel-perf-output/cpu-0/time-range-0/cmd.txt:perf script --cpu=0 --time=,9469.005396999 --ns
parallel-perf-output/cpu-0/time-range-1/cmd.txt:perf script --cpu=0 --time=9469.005397000, --ns
parallel-perf-output/cpu-1/time-range-0/cmd.txt:perf script --cpu=1 --time=,9469.005396999 --ns
parallel-perf-output/cpu-1/time-range-1/cmd.txt:perf script --cpu=1 --time=9469.005397000, --ns
Subdivisions of time range, and cpus if the --per-cpu option is used, are
expressed by the --time and --cpu perf script options respectively. If the
supplied perf script command has a --time option, then that time range is
subdivided, otherwise the time range given by 'time of first sample' to
'time of last sample' is used (refer perf script --header-only). Similarly, the
supplied perf script command may provide a --cpu option, and only those CPUs
will be processed.
To prevent time intervals becoming too small, the --min-interval option can
be used.
Note there is special handling for processing Intel PT traces. If an interval is
not specified and the perf record command contained the intel_pt event, then the
time range will be subdivided in order to produce subdivisions that contain
approximately the same amount of trace data. That is accomplished by counting
double-quick (--itrace=qqi) samples, and choosing time ranges that encompass
approximately the same number of samples. In that case, time ranges may not be
the same for each CPU processed. For Intel PT, --per-cpu is the default, but
that can be overridden by --no-per-cpu. Note, for Intel PT, double-quick
decoding produces 1 sample for each PSB synchronization packet, which in turn
come after a certain number of bytes output, determined by psb_period (refer
perf Intel PT documentation). The minimum number of double-quick samples that
will define a time range can be set by the --min_size option, which defaults to
64.
""")
ap.add_argument("-o", "--output-dir", default="parallel-perf-output", help="output directory (default 'parallel-perf-output')")
ap.add_argument("-j", "--jobs", type=int, default=0, help="maximum number of jobs to run in parallel at one time (default is the number of CPUs)")
ap.add_argument("-n", "--nr", type=int, default=0, help="number of time subdivisions (default is the number of jobs)")
ap.add_argument("-i", "--interval", type=float, default=0, help="subdivide the time range using this time interval (in seconds e.g. 0.1 for a tenth of a second)")
ap.add_argument("-c", "--per-cpu", action="store_true", help="process data for each CPU in parallel")
ap.add_argument("-m", "--min-interval", type=float, default=glb_min_interval, help=f"minimum interval (default {glb_min_interval} seconds)")
ap.add_argument("-p", "--pipe-to", help="command to pipe output to (optional)")
ap.add_argument("-N", "--no-per-cpu", action="store_true", help="do not process data for each CPU in parallel")
ap.add_argument("-b", "--min_size", type=int, default=glb_min_samples, help="minimum data size (for Intel PT in PSBs)")
ap.add_argument("-D", "--dry-run", action="store_true", help="do not run any jobs, just show the perf script commands")
ap.add_argument("-q", "--quiet", action="store_true", help="do not print any messages except errors")
ap.add_argument("-v", "--verbose", action="store_true", help="print more messages")
ap.add_argument("-d", "--debug", action="store_true", help="print debugging messages")
cmd_line = list(args)
try:
split_pos = cmd_line.index("--")
cmd = cmd_line[split_pos + 1:]
args = cmd_line[:split_pos]
except:
cmd = None
args = cmd_line
a = ap.parse_args(args=args[1:])
a.cmd = cmd
a.verbosity = Verbosity(a.quiet, a.verbose, a.debug)
try:
if a.cmd == None:
if len(args) <= 1:
ap.print_help()
return True
raise Exception("Command line must contain '--' before perf command")
return RunParallelPerf(a)
except Exception as e:
print("Fatal error: ", str(e))
if a.debug:
raise
return False
if __name__ == "__main__":
if not Main(sys.argv):
sys.exit(1)
...@@ -17,7 +17,7 @@ cleanup() ...@@ -17,7 +17,7 @@ cleanup()
sane=$(echo "${temp_dir}" | cut -b 1-21) sane=$(echo "${temp_dir}" | cut -b 1-21)
if [ "${sane}" = "/tmp/perf-test-script" ] ; then if [ "${sane}" = "/tmp/perf-test-script" ] ; then
echo "--- Cleaning up ---" echo "--- Cleaning up ---"
rm -f "${temp_dir}/"* rm -rf "${temp_dir:?}/"*
rmdir "${temp_dir}" rmdir "${temp_dir}"
fi fi
} }
...@@ -65,7 +65,31 @@ _end_of_file_ ...@@ -65,7 +65,31 @@ _end_of_file_
echo "DB test [Success]" echo "DB test [Success]"
} }
test_parallel_perf()
{
echo "parallel-perf test"
if ! python3 --version >/dev/null 2>&1 ; then
echo "SKIP: no python3"
err=2
return
fi
pp=$(dirname "$0")/../../scripts/python/parallel-perf.py
if [ ! -f "${pp}" ] ; then
echo "SKIP: parallel-perf.py script not found "
err=2
return
fi
perf_data="${temp_dir}/pp-perf.data"
output1_dir="${temp_dir}/output1"
output2_dir="${temp_dir}/output2"
perf record -o "${perf_data}" --sample-cpu uname
python3 "${pp}" -o "${output1_dir}" --jobs 4 --verbose -- perf script -i "${perf_data}"
python3 "${pp}" -o "${output2_dir}" --jobs 4 --verbose --per-cpu -- perf script -i "${perf_data}"
echo "parallel-perf test [Success]"
}
test_db test_db
test_parallel_perf
cleanup cleanup
......
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