grpc/tools/profiling/microbenchmarks/bm_diff/bm_diff.py

#!/usr/bin/env python3
#
# Copyright 2017 gRPC authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
""" Computes the diff between two bm runs and outputs significant results """

import argparse
import collections
import json
import os
import subprocess
import sys

sys.path.append(os.path.join(os.path.dirname(sys.argv[0]), '..'))

import bm_constants
import bm_json
import bm_speedup
import tabulate

verbose = False


def _median(ary):
    assert (len(ary))
    ary = sorted(ary)
    n = len(ary)
    if n % 2 == 0:
        return (ary[(n - 1) // 2] + ary[(n - 1) // 2 + 1]) / 2.0
    else:
        return ary[n // 2]


def _args():
    argp = argparse.ArgumentParser(
        description='Perform diff on microbenchmarks')
    argp.add_argument('-t',
                      '--track',
                      choices=sorted(bm_constants._INTERESTING),
                      nargs='+',
                      default=sorted(bm_constants._INTERESTING),
                      help='Which metrics to track')
    argp.add_argument('-b',
                      '--benchmarks',
                      nargs='+',
                      choices=bm_constants._AVAILABLE_BENCHMARK_TESTS,
                      default=bm_constants._AVAILABLE_BENCHMARK_TESTS,
                      help='Which benchmarks to run')
    argp.add_argument(
        '-l',
        '--loops',
        type=int,
        default=20,
        help=
        'Number of times to loops the benchmarks. Must match what was passed to bm_run.py'
    )
    argp.add_argument('-r',
                      '--regex',
                      type=str,
                      default="",
                      help='Regex to filter benchmarks run')
    argp.add_argument('--counters', dest='counters', action='store_true')
    argp.add_argument('--no-counters', dest='counters', action='store_false')
    argp.set_defaults(counters=True)
    argp.add_argument('-n', '--new', type=str, help='New benchmark name')
    argp.add_argument('-o', '--old', type=str, help='Old benchmark name')
    argp.add_argument('-v',
                      '--verbose',
                      type=bool,
                      help='Print details of before/after')
    args = argp.parse_args()
    global verbose
    if args.verbose:
        verbose = True
    assert args.new
    assert args.old
    return args


def _maybe_print(str):
    if verbose:
        print(str)


class Benchmark:

    def __init__(self):
        self.samples = {
            True: collections.defaultdict(list),
            False: collections.defaultdict(list)
        }
        self.final = {}
        self.speedup = {}

    def add_sample(self, track, data, new):
        for f in track:
            if f in data:
                self.samples[new][f].append(float(data[f]))

    def process(self, track, new_name, old_name):
        for f in sorted(track):
            new = self.samples[True][f]
            old = self.samples[False][f]
            if not new or not old:
                continue
            mdn_diff = abs(_median(new) - _median(old))
            _maybe_print('%s: %s=%r %s=%r mdn_diff=%r' %
                         (f, new_name, new, old_name, old, mdn_diff))
            s = bm_speedup.speedup(new, old, 1e-5)
            self.speedup[f] = s
            if abs(s) > 3:
                if mdn_diff > 0.5:
                    self.final[f] = '%+d%%' % s
        return self.final.keys()

    def skip(self):
        return not self.final

    def row(self, flds):
        return [self.final[f] if f in self.final else '' for f in flds]

    def speedup(self, name):
        if name in self.speedup:
            return self.speedup[name]
        return None


def _read_json(filename, badjson_files, nonexistant_files):
    stripped = ".".join(filename.split(".")[:-2])
    try:
        with open(filename) as f:
            r = f.read()
            return json.loads(r)
    except IOError as e:
        if stripped in nonexistant_files:
            nonexistant_files[stripped] += 1
        else:
            nonexistant_files[stripped] = 1
        return None
    except ValueError as e:
        print(r)
        if stripped in badjson_files:
            badjson_files[stripped] += 1
        else:
            badjson_files[stripped] = 1
        return None


def fmt_dict(d):
    return ''.join(["    " + k + ": " + str(d[k]) + "\n" for k in d])


def diff(bms, loops, regex, track, old, new, counters):
    benchmarks = collections.defaultdict(Benchmark)

    badjson_files = {}
    nonexistant_files = {}
    for bm in bms:
        for loop in range(0, loops):
            for line in subprocess.check_output([
                    'bm_diff_%s/opt/%s' % (old, bm), '--benchmark_list_tests',
                    '--benchmark_filter=%s' % regex
            ]).splitlines():
                line = line.decode('UTF-8')
                stripped_line = line.strip().replace("/", "_").replace(
                    "<", "_").replace(">", "_").replace(", ", "_")
                js_new_opt = _read_json(
                    '%s.%s.opt.%s.%d.json' % (bm, stripped_line, new, loop),
                    badjson_files, nonexistant_files)
                js_old_opt = _read_json(
                    '%s.%s.opt.%s.%d.json' % (bm, stripped_line, old, loop),
                    badjson_files, nonexistant_files)
                if counters:
                    js_new_ctr = _read_json(
                        '%s.%s.counters.%s.%d.json' %
                        (bm, stripped_line, new, loop), badjson_files,
                        nonexistant_files)
                    js_old_ctr = _read_json(
                        '%s.%s.counters.%s.%d.json' %
                        (bm, stripped_line, old, loop), badjson_files,
                        nonexistant_files)
                else:
                    js_new_ctr = None
                    js_old_ctr = None

                for row in bm_json.expand_json(js_new_ctr, js_new_opt):
                    name = row['cpp_name']
                    if name.endswith('_mean') or name.endswith('_stddev'):
                        continue
                    benchmarks[name].add_sample(track, row, True)
                for row in bm_json.expand_json(js_old_ctr, js_old_opt):
                    name = row['cpp_name']
                    if name.endswith('_mean') or name.endswith('_stddev'):
                        continue
                    benchmarks[name].add_sample(track, row, False)

    really_interesting = set()
    for name, bm in benchmarks.items():
        _maybe_print(name)
        really_interesting.update(bm.process(track, new, old))
    fields = [f for f in track if f in really_interesting]

    # figure out the significance of the changes... right now we take the 95%-ile
    # benchmark delta %-age, and then apply some hand chosen thresholds
    histogram = []
    _NOISY = ["BM_WellFlushed"]
    for name, bm in benchmarks.items():
        if name in _NOISY:
            print("skipping noisy benchmark '%s' for labelling evaluation" %
                  name)
        if bm.skip():
            continue
        d = bm.speedup['cpu_time']
        if d is None:
            continue
        histogram.append(d)
    histogram.sort()
    print("histogram of speedups: ", histogram)
    if len(histogram) == 0:
        significance = 0
    else:
        delta = histogram[int(len(histogram) * 0.95)]
        mul = 1
        if delta < 0:
            delta = -delta
            mul = -1
        if delta < 2:
            significance = 0
        elif delta < 5:
            significance = 1
        elif delta < 10:
            significance = 2
        else:
            significance = 3
        significance *= mul

    headers = ['Benchmark'] + fields
    rows = []
    for name in sorted(benchmarks.keys()):
        if benchmarks[name].skip():
            continue
        rows.append([name] + benchmarks[name].row(fields))
    note = None
    if len(badjson_files):
        note = 'Corrupt JSON data (indicates timeout or crash): \n%s' % fmt_dict(
            badjson_files)
    if len(nonexistant_files):
        if note:
            note += '\n\nMissing files (indicates new benchmark): \n%s' % fmt_dict(
                nonexistant_files)
        else:
            note = '\n\nMissing files (indicates new benchmark): \n%s' % fmt_dict(
                nonexistant_files)
    if rows:
        return tabulate.tabulate(rows, headers=headers,
                                 floatfmt='+.2f'), note, significance
    else:
        return None, note, 0


if __name__ == '__main__':
    args = _args()
    diff, note = diff(args.benchmarks, args.loops, args.regex, args.track,
                      args.old, args.new, args.counters)
    print('%s\n%s' % (note, diff if diff else "No performance differences"))