1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
|
#!/usr/bin/python
# Copyright 2010 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/>.
# Excercise my btree implementation, for simple benchmarking purposes.
# The benchmark gets a location and an operation count as command line
# arguments.
#
# If the location is the empty string, an in-memory node store is used.
# Otherwise it must be a non-existent directory name.
#
# The benchmark will do the given number of insertions into the tree, and
# measure the speed of that. Then it will look up each of those, and measure
# the lookups.
import cProfile
import os
import random
import shutil
import sys
import time
import btree
def measure(keys, func, final):
start = time.clock()
for key in keys:
func(key)
final()
end = time.clock()
return end - start
def profile(keys, func, final, basename):
def helper():
for key in keys:
func(key)
final()
globaldict = globals().copy()
localdict = locals().copy()
cProfile.runctx('helper()', globaldict, localdict, '%s.prof' % basename)
def main():
if True:
import logging
logging.basicConfig(filename='btree.log', level=logging.DEBUG)
location = sys.argv[1]
n = int(sys.argv[2])
do_profile = True if sys.argv[3] == 'yes' else False
key_size = 19
value_size = 128
node_size = 64*1024
codec = btree.NodeCodec(key_size)
if location == '':
ns = btree.NodeStoreMemory(node_size, codec)
else:
if os.path.exists(location):
raise Exception('%s exists already' % location)
os.mkdir(location)
ns = btree.NodeStoreDisk(location, node_size, codec)
forest = btree.Forest(ns)
tree = forest.new_tree()
# Create list of keys.
keys = ['%0*d' % (key_size, i) for i in xrange(n)]
# Calibrate.
looptime = measure(keys, lambda key: None, lambda: None)
# Measure inserts.
random.shuffle(keys)
value = 'x' * value_size
if do_profile:
profile(keys, lambda key: tree.insert(key, value),
lambda: forest.commit(), 'insert')
else:
insert_time = measure(keys, lambda key: tree.insert(key, value),
lambda: forest.commit())
# Measure lookups.
random.shuffle(keys)
if do_profile:
profile(keys, tree.lookup, lambda: None, 'lookup')
else:
lookup_time = measure(keys, lambda key: tree.lookup(key),
lambda: None) - looptime
# Measure range lookups.
random.shuffle(keys)
max_key = max(keys)
if do_profile:
profile(keys, lambda key: tree.lookup_range(key, max_key),
lambda: None, 'lookup-range')
else:
lookup_range_time = measure(keys,
lambda key: tree.lookup_range(key, max_key),
lambda: None) - looptime
# Measure inserts into existing tree.
random.shuffle(keys)
if do_profile:
profile(keys, lambda key: tree.insert(key, value),
lambda: forest.commit(), 'insert2')
else:
insert2_time = measure(keys, lambda key: tree.insert(key, value),
lambda: forest.commit())
# Measure removes from tree.
random.shuffle(keys)
if do_profile:
profile(keys, lambda key: tree.remove(key),
lambda: forest.commit(), 'remove')
else:
remove_time = measure(keys, lambda key: tree.remove(key),
lambda: forest.commit())
# Measure remove_range. This requires building a new tree.
keys.sort()
ranges = []
range_len = 10
for key in keys:
tree.insert(key, value)
for i in range(0, len(keys), range_len):
ranges.append((keys[i], keys[i+range_len-1]))
random.shuffle(ranges)
if do_profile:
profile(ranges, lambda pair: tree.remove_range(pair[0], pair[1]),
lambda: forest.commit(), 'remove_range')
else:
remove_range_time = measure(ranges,
lambda x: tree.remove_range(x[0], x[1]),
lambda: forest.commit())
# Report
if do_profile:
print 'View *.prof with ./viewprof for profiling results.'
else:
print 'num_operations: %d' % n
print 'insert : %5.3f s (%.1f/s)' % (insert_time, n/insert_time)
print 'lookup : %5.3f s (%.1f/s)' % (lookup_time, n/lookup_time)
print 'lookup_range: %5.3f s (%.1f/s)' % (lookup_range_time,
n/lookup_range_time)
print 'insert2 : %5.3f s (%.1f/s)' % (insert2_time, n/insert2_time)
print 'remove : %5.3f s (%.1f/s)' % (remove_time, n/remove_time)
print 'remove_range: %5.3f s (%.1f/s)' % (remove_range_time,
n/remove_range_time)
# Clean up
if location:
shutil.rmtree(location)
if __name__ == '__main__':
main()
|
