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perf script: Introduce task analyzer python script

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Introduce a new 'perf script' to analyze task scheduling behavior.

During the task analysis, some data is always needed - which goes beyond
the simple time of switching on and off a task (process/thread). This
concerns for example the runtime of a process or the frequency with
which the process was called. This script serves to simplify this
recurring analyze process. It immediately provides the user with helpful
task characteristic information about the tasks runtimes.

Usage:

Recorded can be in two ways:

  $ perf script record tasks-analyzer -- sleep 10
  $ perf record -e sched:sched_switch -a -- sleep 10

The script can parse all perf.data files, most important: sched:sched_switch
events are mandatory, other events will be ignored.

Most simple report use case is to just call the script without arguments:

  $ perf script report tasks-analyzer
      Switched-In      Switched-Out CPU      PID      TID             Comm    Runtime     Time Out-In
  15576.658891407   15576.659156086   4     2412     2428            gdbus        265            1949
  15576.659111320   15576.659455410   0     2412     2412      gnome-shell        344            2267
  15576.659491326   15576.659506173   2       74       74      kworker/2:1         15           13145
  15576.659506173   15576.659825748   2     2858     2858  gnome-terminal-        320           63263
  15576.659871270   15576.659902872   6    20932    20932    kworker/u16:0         32         2314582
  15576.659909951   15576.659945501   3    27264    27264               sh         36              -1
  15576.659853285   15576.659971052   7    27265    27265             perf        118         5050741
  [...]

What is not shown here are the ASCII color sequences. For example, if
the task consists of only one thread, the TID is grayed out.

Runtime is the time the task was running on the CPU, Time Out-In is the
time between the process being scheduled *out* and scheduled back *in*.
So the last time span between two executions. If -1 is printed, then the
task simply ran the first time in the measurements - a Out-In delta
could not be calculated.

In addition to the chronological representation, there is a summary on
task level. This output can be additionally switched on via the
--summary option and provides information such as max, min & average
runtime per process. The maximum runtime is often important for
debugging. The call looks like this:

  $ perf script report tasks-analyzer --summary
  Summary
       Task Information                       Runtime Information
    PID   TID            Comm Runs Accumulated    Mean  Median  Min   Max          Max At
     14    14     ksoftirqd/0   13         334      26      15    9   127 15571.621211956
     15    15     rcu_preempt  133        1778      13      13    2    33 15572.581176024
     16    16     migration/0    3          49      16      13   12    24 15571.608915425
     20    20     migration/1    3          34      11      13    8    13 15571.639101555
     25    25     migration/2    3          32      11      12    9    12 15575.639239896
  [...]

Besides these two options, there are a number of other options that change the
output and behavior. This can be queried via --help. Options worth mentioning include:

- filter-tasks         - filter out unneeded tasks, --filter-task 1337,/sbin/init
- highlight-tasks      - more pleasant focusing, --highlight-tasks 1:red,mutt:yellow
- extended-times       - show combinations of elapsed times between schedule in/schedule out
- summary-extended     - summary with additional information, like maximum delta time statistics
- rename-comms-by-tids - handy for inexpressive processnames like python, --rename 1337:my-python-app
- ms                   - show timestamps in milliseconds, nanoseconds is also possible (--ns)
- time-limit           - limit the analyzer to a time range, --time-limit 15576.0:15576.1

Script is tested and prime time ready for python2 & python3:

- make PYTHON=python3 prefix=/usr/local install
- make PYTHON=python2 prefix=/usr/local install

Signed-off-by: Hagen Paul Pfeifer <hagen@jauu.net>
Cc: Andi Kleen <ak@linux.intel.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/20221206154406.41941-2-petar.gligor@gmail.com
Signed-off-by: Petar Gligoric <petar.gligoric@rohde-schwarz.com>
Signed-off-by: Arnaldo Carvalho de Melo <acme@redhat.com>
This commit is contained in:
Hagen Paul Pfeifer 2022-12-06 10:44:04 -05:00 committed by Arnaldo Carvalho de Melo
parent 55c1de9973
commit e76aff0523
3 changed files with 843 additions and 0 deletions
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2
tools/perf/scripts/python/bin/task-analyzer-record Executable file
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#!/bin/bash
perf record -e sched:sched_switch -e sched:sched_migrate_task "$@"

3
tools/perf/scripts/python/bin/task-analyzer-report Executable file
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#!/bin/bash
# description: analyze timings of tasks
perf script -s "$PERF_EXEC_PATH"/scripts/python/task-analyzer.py -- "$@"

838
tools/perf/scripts/python/task-analyzer.py Executable file
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# task-analyzer.py - comprehensive perf tasks analysis
# SPDX-License-Identifier: GPL-2.0
# Copyright (c) 2022, Hagen Paul Pfeifer <hagen@jauu.net>
# Licensed under the terms of the GNU GPL License version 2
#
# Usage:
#
# perf record -e sched:sched_switch -a -- sleep 10
# perf script report task-analyzer
#
from __future__ import print_function
import sys
import os
import string
import argparse
import decimal
sys.path.append(
os.environ["PERF_EXEC_PATH"] + "/scripts/python/Perf-Trace-Util/lib/Perf/Trace"
)
from perf_trace_context import *
from Core import *
# Definition of possible ASCII color codes
_COLORS = {
"grey": "\033[90m",
"red": "\033[91m",
"green": "\033[92m",
"yellow": "\033[93m",
"blue": "\033[94m",
"violet": "\033[95m",
"reset": "\033[0m",
}
# Columns will have a static size to align everything properly
# Support of 116 days of active update with nano precision
LEN_SWITCHED_IN = len("9999999.999999999") # 17
LEN_SWITCHED_OUT = len("9999999.999999999") # 17
LEN_CPU = len("000")
LEN_PID = len("maxvalue") # 8
LEN_TID = len("maxvalue") # 8
LEN_COMM = len("max-comms-length") # 16
LEN_RUNTIME = len("999999.999") # 10
# Support of 3.45 hours of timespans
LEN_OUT_IN = len("99999999999.999") # 15
LEN_OUT_OUT = len("99999999999.999") # 15
LEN_IN_IN = len("99999999999.999") # 15
LEN_IN_OUT = len("99999999999.999") # 15
# py2/py3 compatibility layer, see PEP469
try:
dict.iteritems
except AttributeError:
# py3
def itervalues(d):
return iter(d.values())
def iteritems(d):
return iter(d.items())
else:
# py2
def itervalues(d):
return d.itervalues()
def iteritems(d):
return d.iteritems()
def _check_color():
global _COLORS
"""user enforced no-color or if stdout is no tty we disable colors"""
if sys.stdout.isatty() and args.stdio_color != "never":
return
_COLORS = {
"grey": "",
"red": "",
"green": "",
"yellow": "",
"blue": "",
"violet": "",
"reset": "",
}
def _parse_args():
global args
parser = argparse.ArgumentParser(description="Analyze tasks behavior")
parser.add_argument(
"--time-limit",
default=[],
help=
"print tasks only in time[s] window e.g"
" --time-limit 123.111:789.222(print all between 123.111 and 789.222)"
" --time-limit 123: (print all from 123)"
" --time-limit :456 (print all until incl. 456)",
)
parser.add_argument(
"--summary", action="store_true", help="print addtional runtime information"
)
parser.add_argument(
"--summary-only", action="store_true", help="print only summary without traces"
)
parser.add_argument(
"--summary-extended",
action="store_true",
help="print the summary with additional information of max inter task times"
" relative to the prev task",
)
parser.add_argument(
"--ns", action="store_true", help="show timestamps in nanoseconds"
)
parser.add_argument(
"--ms", action="store_true", help="show timestamps in miliseconds"
)
parser.add_argument(
"--extended-times",
action="store_true",
help="Show the elapsed times between schedule in/schedule out"
" of this task and the schedule in/schedule out of previous occurrence"
" of the same task",
)
parser.add_argument(
"--filter-tasks",
default=[],
help="filter out unneeded tasks by tid, pid or processname."
" E.g --filter-task 1337,/sbin/init ",
)
parser.add_argument(
"--limit-to-tasks",
default=[],
help="limit output to selected task by tid, pid, processname."
" E.g --limit-to-tasks 1337,/sbin/init",
)
parser.add_argument(
"--highlight-tasks",
default="",
help="colorize special tasks by their pid/tid/comm."
" E.g. --highlight-tasks 1:red,mutt:yellow"
" Colors available: red,grey,yellow,blue,violet,green",
)
parser.add_argument(
"--rename-comms-by-tids",
default="",
help="rename task names by using tid (<tid>:<newname>,<tid>:<newname>)"
" This option is handy for inexpressive processnames like python interpreted"
" process. E.g --rename 1337:my-python-app",
)
parser.add_argument(
"--stdio-color",
default="auto",
choices=["always", "never", "auto"],
help="always, never or auto, allowing configuring color output"
" via the command line",
)
args = parser.parse_args()
args.tid_renames = dict()
_argument_filter_sanity_check()
_argument_prepare_check()
def time_uniter(unit):
picker = {
"s": 1,
"ms": 1e3,
"us": 1e6,
"ns": 1e9,
}
return picker[unit]
def _init_db():
global db
db = dict()
db["running"] = dict()
db["cpu"] = dict()
db["tid"] = dict()
db["global"] = []
if args.summary or args.summary_extended or args.summary_only:
db["task_info"] = dict()
db["runtime_info"] = dict()
# min values for summary depending on the header
db["task_info"]["pid"] = len("PID")
db["task_info"]["tid"] = len("TID")
db["task_info"]["comm"] = len("Comm")
db["runtime_info"]["runs"] = len("Runs")
db["runtime_info"]["acc"] = len("Accumulated")
db["runtime_info"]["max"] = len("Max")
db["runtime_info"]["max_at"] = len("Max At")
db["runtime_info"]["min"] = len("Min")
db["runtime_info"]["mean"] = len("Mean")
db["runtime_info"]["median"] = len("Median")
if args.summary_extended:
db["inter_times"] = dict()
db["inter_times"]["out_in"] = len("Out-In")
db["inter_times"]["inter_at"] = len("At")
db["inter_times"]["out_out"] = len("Out-Out")
db["inter_times"]["in_in"] = len("In-In")
db["inter_times"]["in_out"] = len("In-Out")
def _median(numbers):
"""phython3 hat statistics module - we have nothing"""
n = len(numbers)
index = n // 2
if n % 2:
return sorted(numbers)[index]
return sum(sorted(numbers)[index - 1 : index + 1]) / 2
def _mean(numbers):
return sum(numbers) / len(numbers)
class Timespans(object):
"""
The elapsed time between two occurrences of the same task is being tracked with the
help of this class. There are 4 of those Timespans Out-Out, In-Out, Out-In and
In-In.
The first half of the name signals the first time point of the
first task. The second half of the name represents the second
timepoint of the second task.
"""
def __init__(self):
self._last_start = None
self._last_finish = None
self.out_out = -1
self.in_out = -1
self.out_in = -1
self.in_in = -1
if args.summary_extended:
self._time_in = -1
self.max_out_in = -1
self.max_at = -1
self.max_in_out = -1
self.max_in_in = -1
self.max_out_out = -1
def feed(self, task):
"""
Called for every recorded trace event to find process pair and calculate the
task timespans. Chronological ordering, feed does not do reordering
"""
if not self._last_finish:
self._last_start = task.time_in(time_unit)
self._last_finish = task.time_out(time_unit)
return
self._time_in = task.time_in()
time_in = task.time_in(time_unit)
time_out = task.time_out(time_unit)
self.in_in = time_in - self._last_start
self.out_in = time_in - self._last_finish
self.in_out = time_out - self._last_start
self.out_out = time_out - self._last_finish
if args.summary_extended:
self._update_max_entries()
self._last_finish = task.time_out(time_unit)
self._last_start = task.time_in(time_unit)
def _update_max_entries(self):
if self.in_in > self.max_in_in:
self.max_in_in = self.in_in
if self.out_out > self.max_out_out:
self.max_out_out = self.out_out
if self.in_out > self.max_in_out:
self.max_in_out = self.in_out
if self.out_in > self.max_out_in:
self.max_out_in = self.out_in
self.max_at = self._time_in
class Summary(object):
"""
Primary instance for calculating the summary output. Processes the whole trace to
find and memorize relevant data such as mean, max et cetera. This instance handles
dynamic alignment aspects for summary output.
"""
def __init__(self):
self._body = []
class AlignmentHelper:
"""
Used to calculated the alignment for the output of the summary.
"""
def __init__(self, pid, tid, comm, runs, acc, mean,
median, min, max, max_at):
self.pid = pid
self.tid = tid
self.comm = comm
self.runs = runs
self.acc = acc
self.mean = mean
self.median = median
self.min = min
self.max = max
self.max_at = max_at
if args.summary_extended:
self.out_in = None
self.inter_at = None
self.out_out = None
self.in_in = None
self.in_out = None
def _print_header(self):
'''
Output is trimmed in _format_stats thus additional adjustment in the header
is needed, depending on the choice of timeunit. The adjustment corresponds
to the amount of column titles being adjusted in _column_titles.
'''
decimal_precision = 6 if not args.ns else 9
fmt = " {{:^{}}}".format(sum(db["task_info"].values()))
fmt += " {{:^{}}}".format(
sum(db["runtime_info"].values()) - 2 * decimal_precision
)
_header = ("Task Information", "Runtime Information")
if args.summary_extended:
fmt += " {{:^{}}}".format(
sum(db["inter_times"].values()) - 4 * decimal_precision
)
_header += ("Max Inter Task Times",)
print(fmt.format(*_header))
def _column_titles(self):
"""
Cells are being processed and displayed in different way so an alignment adjust
is implemented depeding on the choice of the timeunit. The positions of the max
values are being displayed in grey. Thus in their format two additional {},
are placed for color set and reset.
"""
decimal_precision, time_precision = _prepare_fmt_precision()
fmt = " {{:>{}}}".format(db["task_info"]["pid"])
fmt += " {{:>{}}}".format(db["task_info"]["tid"])
fmt += " {{:>{}}}".format(db["task_info"]["comm"])
fmt += " {{:>{}}}".format(db["runtime_info"]["runs"])
fmt += " {{:>{}}}".format(db["runtime_info"]["acc"])
fmt += " {{:>{}}}".format(db["runtime_info"]["mean"])
fmt += " {{:>{}}}".format(db["runtime_info"]["median"])
fmt += " {{:>{}}}".format(db["runtime_info"]["min"] - decimal_precision)
fmt += " {{:>{}}}".format(db["runtime_info"]["max"] - decimal_precision)
fmt += " {{}}{{:>{}}}{{}}".format(db["runtime_info"]["max_at"] - time_precision)
column_titles = ("PID", "TID", "Comm")
column_titles += ("Runs", "Accumulated", "Mean", "Median", "Min", "Max")
column_titles += (_COLORS["grey"], "At", _COLORS["reset"])
if args.summary_extended:
fmt += " {{:>{}}}".format(db["inter_times"]["out_in"] - decimal_precision)
fmt += " {{}}{{:>{}}}{{}}".format(
db["inter_times"]["inter_at"] - time_precision
)
fmt += " {{:>{}}}".format(db["inter_times"]["out_out"] - decimal_precision)
fmt += " {{:>{}}}".format(db["inter_times"]["in_in"] - decimal_precision)
fmt += " {{:>{}}}".format(db["inter_times"]["in_out"] - decimal_precision)
column_titles += ("Out-In", _COLORS["grey"], "Max At", _COLORS["reset"],
"Out-Out", "In-In", "In-Out")
print(fmt.format(*column_titles))
def _task_stats(self):
"""calculates the stats of every task and constructs the printable summary"""
for tid in sorted(db["tid"]):
color_one_sample = _COLORS["grey"]
color_reset = _COLORS["reset"]
no_executed = 0
runtimes = []
time_in = []
timespans = Timespans()
for task in db["tid"][tid]:
pid = task.pid
comm = task.comm
no_executed += 1
runtimes.append(task.runtime(time_unit))
time_in.append(task.time_in())
timespans.feed(task)
if len(runtimes) > 1:
color_one_sample = ""
color_reset = ""
time_max = max(runtimes)
time_min = min(runtimes)
max_at = time_in[runtimes.index(max(runtimes))]
# The size of the decimal after sum,mean and median varies, thus we cut
# the decimal number, by rounding it. It has no impact on the output,
# because we have a precision of the decimal points at the output.
time_sum = round(sum(runtimes), 3)
time_mean = round(_mean(runtimes), 3)
time_median = round(_median(runtimes), 3)
align_helper = self.AlignmentHelper(pid, tid, comm, no_executed, time_sum,
time_mean, time_median, time_min, time_max, max_at)
self._body.append([pid, tid, comm, no_executed, time_sum, color_one_sample,
time_mean, time_median, time_min, time_max,
_COLORS["grey"], max_at, _COLORS["reset"], color_reset])
if args.summary_extended:
self._body[-1].extend([timespans.max_out_in,
_COLORS["grey"], timespans.max_at,
_COLORS["reset"], timespans.max_out_out,
timespans.max_in_in,
timespans.max_in_out])
align_helper.out_in = timespans.max_out_in
align_helper.inter_at = timespans.max_at
align_helper.out_out = timespans.max_out_out
align_helper.in_in = timespans.max_in_in
align_helper.in_out = timespans.max_in_out
self._calc_alignments_summary(align_helper)
def _format_stats(self):
decimal_precision, time_precision = _prepare_fmt_precision()
fmt = " {{:>{}d}}".format(db["task_info"]["pid"])
fmt += " {{:>{}d}}".format(db["task_info"]["tid"])
fmt += " {{:>{}}}".format(db["task_info"]["comm"])
fmt += " {{:>{}d}}".format(db["runtime_info"]["runs"])
fmt += " {{:>{}.{}f}}".format(db["runtime_info"]["acc"], time_precision)
fmt += " {{}}{{:>{}.{}f}}".format(db["runtime_info"]["mean"], time_precision)
fmt += " {{:>{}.{}f}}".format(db["runtime_info"]["median"], time_precision)
fmt += " {{:>{}.{}f}}".format(
db["runtime_info"]["min"] - decimal_precision, time_precision
)
fmt += " {{:>{}.{}f}}".format(
db["runtime_info"]["max"] - decimal_precision, time_precision
)
fmt += " {{}}{{:>{}.{}f}}{{}}{{}}".format(
db["runtime_info"]["max_at"] - time_precision, decimal_precision
)
if args.summary_extended:
fmt += " {{:>{}.{}f}}".format(
db["inter_times"]["out_in"] - decimal_precision, time_precision
)
fmt += " {{}}{{:>{}.{}f}}{{}}".format(
db["inter_times"]["inter_at"] - time_precision, decimal_precision
)
fmt += " {{:>{}.{}f}}".format(
db["inter_times"]["out_out"] - decimal_precision, time_precision
)
fmt += " {{:>{}.{}f}}".format(
db["inter_times"]["in_in"] - decimal_precision, time_precision
)
fmt += " {{:>{}.{}f}}".format(
db["inter_times"]["in_out"] - decimal_precision, time_precision
)
return fmt
def _calc_alignments_summary(self, align_helper):
# Length is being cut in 3 groups so that further addition is easier to handle.
# The length of every argument from the alignment helper is being checked if it
# is longer than the longest until now. In that case the length is being saved.
for key in db["task_info"]:
if len(str(getattr(align_helper, key))) > db["task_info"][key]:
db["task_info"][key] = len(str(getattr(align_helper, key)))
for key in db["runtime_info"]:
if len(str(getattr(align_helper, key))) > db["runtime_info"][key]:
db["runtime_info"][key] = len(str(getattr(align_helper, key)))
if args.summary_extended:
for key in db["inter_times"]:
if len(str(getattr(align_helper, key))) > db["inter_times"][key]:
db["inter_times"][key] = len(str(getattr(align_helper, key)))
def print(self):
print("\nSummary")
self._task_stats()
self._print_header()
self._column_titles()
fmt = self._format_stats()
for i in range(len(self._body)):
print(fmt.format(*tuple(self._body[i])))
class Task(object):
""" The class is used to handle the information of a given task."""
def __init__(self, id, tid, cpu, comm):
self.id = id
self.tid = tid
self.cpu = cpu
self.comm = comm
self.pid = None
self._time_in = None
self._time_out = None
def schedule_in_at(self, time):
"""set the time where the task was scheduled in"""
self._time_in = time
def schedule_out_at(self, time):
"""set the time where the task was scheduled out"""
self._time_out = time
def time_out(self, unit="s"):
"""return time where a given task was scheduled out"""
factor = time_uniter(unit)
return self._time_out * decimal.Decimal(factor)
def time_in(self, unit="s"):
"""return time where a given task was scheduled in"""
factor = time_uniter(unit)
return self._time_in * decimal.Decimal(factor)
def runtime(self, unit="us"):
factor = time_uniter(unit)
return (self._time_out - self._time_in) * decimal.Decimal(factor)
def update_pid(self, pid):
self.pid = pid
def _task_id(pid, cpu):
"""returns a "unique-enough" identifier, please do not change"""
return "{}-{}".format(pid, cpu)
def _filter_non_printable(unfiltered):
"""comm names may contain loony chars like '\x00000'"""
filtered = ""
for char in unfiltered:
if char not in string.printable:
continue
filtered += char
return filtered
def _fmt_header():
fmt = "{{:>{}}}".format(LEN_SWITCHED_IN)
fmt += " {{:>{}}}".format(LEN_SWITCHED_OUT)
fmt += " {{:>{}}}".format(LEN_CPU)
fmt += " {{:>{}}}".format(LEN_PID)
fmt += " {{:>{}}}".format(LEN_TID)
fmt += " {{:>{}}}".format(LEN_COMM)
fmt += " {{:>{}}}".format(LEN_RUNTIME)
fmt += " {{:>{}}}".format(LEN_OUT_IN)
if args.extended_times:
fmt += " {{:>{}}}".format(LEN_OUT_OUT)
fmt += " {{:>{}}}".format(LEN_IN_IN)
fmt += " {{:>{}}}".format(LEN_IN_OUT)
return fmt
def _fmt_body():
decimal_precision, time_precision = _prepare_fmt_precision()
fmt = "{{}}{{:{}.{}f}}".format(LEN_SWITCHED_IN, decimal_precision)
fmt += " {{:{}.{}f}}".format(LEN_SWITCHED_OUT, decimal_precision)
fmt += " {{:{}d}}".format(LEN_CPU)
fmt += " {{:{}d}}".format(LEN_PID)
fmt += " {{}}{{:{}d}}{{}}".format(LEN_TID)
fmt += " {{}}{{:>{}}}".format(LEN_COMM)
fmt += " {{:{}.{}f}}".format(LEN_RUNTIME, time_precision)
if args.extended_times:
fmt += " {{:{}.{}f}}".format(LEN_OUT_IN, time_precision)
fmt += " {{:{}.{}f}}".format(LEN_OUT_OUT, time_precision)
fmt += " {{:{}.{}f}}".format(LEN_IN_IN, time_precision)
fmt += " {{:{}.{}f}}{{}}".format(LEN_IN_OUT, time_precision)
else:
fmt += " {{:{}.{}f}}{{}}".format(LEN_OUT_IN, time_precision)
return fmt
def _print_header():
fmt = _fmt_header()
header = ("Switched-In", "Switched-Out", "CPU", "PID", "TID", "Comm", "Runtime",
"Time Out-In")
if args.extended_times:
header += ("Time Out-Out", "Time In-In", "Time In-Out")
print(fmt.format(*header))
def _print_task_finish(task):
"""calculating every entry of a row and printing it immediately"""
c_row_set = ""
c_row_reset = ""
out_in = -1
out_out = -1
in_in = -1
in_out = -1
fmt = _fmt_body()
# depending on user provided highlight option we change the color
# for particular tasks
if str(task.tid) in args.highlight_tasks_map:
c_row_set = _COLORS[args.highlight_tasks_map[str(task.tid)]]
c_row_reset = _COLORS["reset"]
if task.comm in args.highlight_tasks_map:
c_row_set = _COLORS[args.highlight_tasks_map[task.comm]]
c_row_reset = _COLORS["reset"]
# grey-out entries if PID == TID, they
# are identical, no threaded model so the
# thread id (tid) do not matter
c_tid_set = ""
c_tid_reset = ""
if task.pid == task.tid:
c_tid_set = _COLORS["grey"]
c_tid_reset = _COLORS["reset"]
if task.tid in db["tid"]:
# get last task of tid
last_tid_task = db["tid"][task.tid][-1]
# feed the timespan calculate, last in tid db
# and second the current one
timespan_gap_tid = Timespans()
timespan_gap_tid.feed(last_tid_task)
timespan_gap_tid.feed(task)
out_in = timespan_gap_tid.out_in
out_out = timespan_gap_tid.out_out
in_in = timespan_gap_tid.in_in
in_out = timespan_gap_tid.in_out
if args.extended_times:
print(fmt.format(c_row_set, task.time_in(), task.time_out(), task.cpu, task.pid,
c_tid_set, task.tid, c_tid_reset, c_row_set, task.comm,
task.runtime(time_unit), out_in, out_out, in_in, in_out,
c_row_reset))
else:
print(fmt.format(c_row_set, task.time_in(), task.time_out(), task.cpu, task.pid,
c_tid_set, task.tid, c_tid_reset, c_row_set, task.comm,
task.runtime(time_unit), out_in, c_row_reset))
def _record_cleanup(_list):
"""
no need to store more then one element if --summarize
is not enabled
"""
if not args.summary and len(_list) > 1:
_list = _list[len(_list) - 1 :]
def _record_by_tid(task):
tid = task.tid
if tid not in db["tid"]:
db["tid"][tid] = []
db["tid"][tid].append(task)
_record_cleanup(db["tid"][tid])
def _record_by_cpu(task):
cpu = task.cpu
if cpu not in db["cpu"]:
db["cpu"][cpu] = []
db["cpu"][cpu].append(task)
_record_cleanup(db["cpu"][cpu])
def _record_global(task):
"""record all executed task, ordered by finish chronological"""
db["global"].append(task)
_record_cleanup(db["global"])
def _handle_task_finish(tid, cpu, time, perf_sample_dict):
if tid == 0:
return
_id = _task_id(tid, cpu)
if _id not in db["running"]:
# may happen, if we missed the switch to
# event. Seen in combination with --exclude-perf
# where the start is filtered out, but not the
# switched in. Probably a bug in exclude-perf
# option.
return
task = db["running"][_id]
task.schedule_out_at(time)
# record tid, during schedule in the tid
# is not available, update now
pid = int(perf_sample_dict["sample"]["pid"])
task.update_pid(pid)
del db["running"][_id]
# print only tasks which are not being filtered and no print of trace
# for summary only, but record every task.
if not _limit_filtered(tid, pid, task.comm) and not args.summary_only:
_print_task_finish(task)
_record_by_tid(task)
_record_by_cpu(task)
_record_global(task)
def _handle_task_start(tid, cpu, comm, time):
if tid == 0:
return
if tid in args.tid_renames:
comm = args.tid_renames[tid]
_id = _task_id(tid, cpu)
if _id in db["running"]:
# handle corner cases where already running tasks
# are switched-to again - saw this via --exclude-perf
# recorded traces. We simple ignore this "second start"
# event.
return
assert _id not in db["running"]
task = Task(_id, tid, cpu, comm)
task.schedule_in_at(time)
db["running"][_id] = task
def _time_to_internal(time_ns):
"""
To prevent float rounding errors we use Decimal internally
"""
return decimal.Decimal(time_ns) / decimal.Decimal(1e9)
def _limit_filtered(tid, pid, comm):
if args.filter_tasks:
if str(tid) in args.filter_tasks or comm in args.filter_tasks:
return True
else:
return False
if args.limit_to_tasks:
if str(tid) in args.limit_to_tasks or comm in args.limit_to_tasks:
return False
else:
return True
def _argument_filter_sanity_check():
if args.limit_to_tasks and args.filter_tasks:
sys.exit("Error: Filter and Limit at the same time active.")
if args.extended_times and args.summary_only:
sys.exit("Error: Summary only and extended times active.")
if args.time_limit and ":" not in args.time_limit:
sys.exit(
"Error: No bound set for time limit. Please set bound by ':' e.g :123."
)
if args.time_limit and (args.summary or args.summary_only or args.summary_extended):
sys.exit("Error: Cannot set time limit and print summary")
def _argument_prepare_check():
global time_unit
if args.filter_tasks:
args.filter_tasks = args.filter_tasks.split(",")
if args.limit_to_tasks:
args.limit_to_tasks = args.limit_to_tasks.split(",")
if args.time_limit:
args.time_limit = args.time_limit.split(":")
for rename_tuple in args.rename_comms_by_tids.split(","):
tid_name = rename_tuple.split(":")
if len(tid_name) != 2:
continue
args.tid_renames[int(tid_name[0])] = tid_name[1]
args.highlight_tasks_map = dict()
for highlight_tasks_tuple in args.highlight_tasks.split(","):
tasks_color_map = highlight_tasks_tuple.split(":")
# default highlight color to red if no color set by user
if len(tasks_color_map) == 1:
tasks_color_map.append("red")
if args.highlight_tasks and tasks_color_map[1].lower() not in _COLORS:
sys.exit(
"Error: Color not defined, please choose from grey,red,green,yellow,blue,"
"violet"
)
if len(tasks_color_map) != 2:
continue
args.highlight_tasks_map[tasks_color_map[0]] = tasks_color_map[1]
time_unit = "us"
if args.ns:
time_unit = "ns"
elif args.ms:
time_unit = "ms"
def _is_within_timelimit(time):
"""
Check if a time limit was given by parameter, if so ignore the rest. If not,
process the recorded trace in its entirety.
"""
if not args.time_limit:
return True
lower_time_limit = args.time_limit[0]
upper_time_limit = args.time_limit[1]
# check for upper limit
if upper_time_limit == "":
if time >= decimal.Decimal(lower_time_limit):
return True
# check for lower limit
if lower_time_limit == "":
if time <= decimal.Decimal(upper_time_limit):
return True
# quit if time exceeds upper limit. Good for big datasets
else:
quit()
if lower_time_limit != "" and upper_time_limit != "":
if (time >= decimal.Decimal(lower_time_limit) and
time <= decimal.Decimal(upper_time_limit)):
return True
# quit if time exceeds upper limit. Good for big datasets
elif time > decimal.Decimal(upper_time_limit):
quit()
def _prepare_fmt_precision():
decimal_precision = 6
time_precision = 3
if args.ns:
decimal_precision = 9
time_precision = 0
return decimal_precision, time_precision
def trace_unhandled(event_name, context, event_fields_dict, perf_sample_dict):
pass
def trace_begin():
_parse_args()
_check_color()
_init_db()
if not args.summary_only:
_print_header()
def trace_end():
if args.summary or args.summary_extended or args.summary_only:
Summary().print()
def sched__sched_switch(event_name, context, common_cpu, common_secs, common_nsecs,
common_pid, common_comm, common_callchain, prev_comm,
prev_pid, prev_prio, prev_state, next_comm, next_pid,
next_prio, perf_sample_dict):
# ignore common_secs & common_nsecs cause we need
# high res timestamp anyway, using the raw value is
# faster
time = _time_to_internal(perf_sample_dict["sample"]["time"])
if not _is_within_timelimit(time):
# user specific --time-limit a:b set
return
next_comm = _filter_non_printable(next_comm)
_handle_task_finish(prev_pid, common_cpu, time, perf_sample_dict)
_handle_task_start(next_pid, common_cpu, next_comm, time)