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#!/usr/bin/python
# Copyright 2010-2011 Lars Wirzenius
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import cliapp
import cProfile
import csv
import os
import subprocess
import sys
import time
import larch
class CodecBenchmark(cliapp.Application):
def add_settings(self):
self.settings.string(['csv'],
'append a CSV row to FILE',
metavar='FILE')
self.settings.boolean(['profile'],
'run benchmark under profiling?')
self.settings.integer(['keys', 'n'],
'run benchmark with N keys (default: %default)',
metavar='N',
default=10000)
def process_args(self, args):
n = self.settings['keys']
do_profile = self.settings['profile']
# Prepare data for tests.
key_size = 19
value_size = 128
node_size = 64*1024
codec = larch.NodeCodec(key_size)
key_fmt = '%%0%dd' % key_size
keys = [key_fmt % i for i in range(n)]
value_fmt = '%%0%dd' % value_size
leaf_values = [value_fmt % i for i in range(n)]
index_values = range(n)
leaf = larch.LeafNode(42, keys, leaf_values)
encoded_leaf = codec.encode_leaf(leaf)
index = larch.IndexNode(42, keys, index_values)
encoded_index = codec.encode_index(index)
# Measure and report.
print 'num_operations: %d' % n
leaf_size = self.measure(n, len(encoded_leaf),
lambda: codec.leaf_size(keys, leaf_values),
do_profile, 'leaf_size')
encode_leaf = self.measure(n, len(encoded_leaf),
lambda: codec.encode_leaf(leaf),
do_profile, 'encode_leaf')
decode_leaf = self.measure(n, len(encoded_leaf),
lambda: codec.decode(encoded_leaf),
do_profile, 'decode_leaf')
encode_index = self.measure(n, len(encoded_index),
lambda: codec.encode_index(index),
do_profile, 'encode_index')
decode_index = self.measure(n, len(encoded_index),
lambda: codec.decode_index(encoded_index),
do_profile, 'decode_index')
if do_profile:
print 'View *.prof with ./viewprof for profiling results.'
if self.settings['csv']:
self.append_csv(n, leaf_size, encode_leaf, decode_leaf,
encode_index, decode_index)
def measure(self, n, unit_size, func, do_profile, profname):
def helper():
for i in range(n):
func()
start_time = time.time()
start = time.clock()
if do_profile:
globaldict = globals().copy()
localdict = locals().copy()
cProfile.runctx('helper()', globaldict, localdict,
'%s.prof' % profname)
else:
helper()
end = time.clock()
end_time = time.time()
def speed(secs):
MiB = 1024**2
return float(n * unit_size) / float(secs) / MiB
cpu_speed = speed(end - start)
wall_speed = speed(end_time - start_time)
fmt = '%12s %6.0f MiB/s (CPU) %6.0f MiBs (wall)'
print fmt % (profname, cpu_speed, wall_speed)
return cpu_speed
def append_csv(self, keys, leaf_size, encode_leaf, decode_leaf,
encode_index, decode_index):
write_title = not os.path.exists(self.settings['csv'])
f = open(self.settings['csv'], 'a')
self.writer = csv.writer(f, lineterminator='\n')
if write_title:
self.writer.writerow(('revno',
'keys',
'leaf_size (MiB/s)',
'encode_leaf (MiB/s)',
'decode_leaf (MiB/s)',
'encode_index (MiB/s)',
'decode_index (MiB/s)'))
if os.path.exists('.bzr'):
p = subprocess.Popen(['bzr', 'revno'], stdout=subprocess.PIPE)
out, err = p.communicate()
if p.returncode != 0:
raise cliapp.AppException('bzr failed')
revno = out.strip()
else:
revno = '?'
self.writer.writerow((revno,
keys,
self.format(leaf_size),
self.format(encode_leaf),
self.format(decode_leaf),
self.format(encode_index),
self.format(decode_index)))
f.close()
def format(self, value):
return '%.1f' % value
if __name__ == '__main__':
CodecBenchmark().run()
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