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
|
# Copyright 2009-2012 10gen, Inc.
#
# 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.
"""MongoDB benchmarking suite."""
import time
import sys
sys.path[0:0] = [""]
import datetime
import cProfile
from pymongo import connection
from pymongo import ASCENDING
trials = 2
per_trial = 5000
batch_size = 100
small = {}
medium = {"integer": 5,
"number": 5.05,
"boolean": False,
"array": ["test", "benchmark"]
}
# this is similar to the benchmark data posted to the user list
large = {"base_url": "http://www.example.com/test-me",
"total_word_count": 6743,
"access_time": datetime.datetime.utcnow(),
"meta_tags": {"description": "i am a long description string",
"author": "Holly Man",
"dynamically_created_meta_tag": "who know\n what"
},
"page_structure": {"counted_tags": 3450,
"no_of_js_attached": 10,
"no_of_images": 6
},
"harvested_words": ["10gen", "web", "open", "source", "application",
"paas", "platform-as-a-service", "technology",
"helps", "developers", "focus", "building",
"mongodb", "mongo"] * 20
}
def setup_insert(db, collection, object):
db.drop_collection(collection)
def insert(db, collection, object):
for i in range(per_trial):
to_insert = object.copy()
to_insert["x"] = i
db[collection].insert(to_insert)
def insert_batch(db, collection, object):
for i in range(per_trial / batch_size):
db[collection].insert([object] * batch_size)
def find_one(db, collection, x):
for _ in range(per_trial):
db[collection].find_one({"x": x})
def find(db, collection, x):
for _ in range(per_trial):
for _ in db[collection].find({"x": x}):
pass
def timed(name, function, args=[], setup=None):
times = []
for _ in range(trials):
if setup:
setup(*args)
start = time.time()
function(*args)
times.append(time.time() - start)
best_time = min(times)
print "%s%d" % (name + (60 - len(name)) * ".", per_trial / best_time)
return best_time
def main():
connection._TIMEOUT = 60 # jack up the timeout
c = connection.Connection()
c.drop_database("benchmark")
db = c.benchmark
timed("insert (small, no index)", insert,
[db, 'small_none', small], setup_insert)
timed("insert (medium, no index)", insert,
[db, 'medium_none', medium], setup_insert)
timed("insert (large, no index)", insert,
[db, 'large_none', large], setup_insert)
db.small_index.create_index("x", ASCENDING)
timed("insert (small, indexed)", insert, [db, 'small_index', small])
db.medium_index.create_index("x", ASCENDING)
timed("insert (medium, indexed)", insert, [db, 'medium_index', medium])
db.large_index.create_index("x", ASCENDING)
timed("insert (large, indexed)", insert, [db, 'large_index', large])
timed("batch insert (small, no index)", insert_batch,
[db, 'small_bulk', small], setup_insert)
timed("batch insert (medium, no index)", insert_batch,
[db, 'medium_bulk', medium], setup_insert)
timed("batch insert (large, no index)", insert_batch,
[db, 'large_bulk', large], setup_insert)
timed("find_one (small, no index)", find_one,
[db, 'small_none', per_trial / 2])
timed("find_one (medium, no index)", find_one,
[db, 'medium_none', per_trial / 2])
timed("find_one (large, no index)", find_one,
[db, 'large_none', per_trial / 2])
timed("find_one (small, indexed)", find_one,
[db, 'small_index', per_trial / 2])
timed("find_one (medium, indexed)", find_one,
[db, 'medium_index', per_trial / 2])
timed("find_one (large, indexed)", find_one,
[db, 'large_index', per_trial / 2])
timed("find (small, no index)", find, [db, 'small_none', per_trial / 2])
timed("find (medium, no index)", find, [db, 'medium_none', per_trial / 2])
timed("find (large, no index)", find, [db, 'large_none', per_trial / 2])
timed("find (small, indexed)", find, [db, 'small_index', per_trial / 2])
timed("find (medium, indexed)", find, [db, 'medium_index', per_trial / 2])
timed("find (large, indexed)", find, [db, 'large_index', per_trial / 2])
# timed("find range (small, no index)", find,
# [db, 'small_none',
# {"$gt": per_trial / 4, "$lt": 3 * per_trial / 4}])
# timed("find range (medium, no index)", find,
# [db, 'medium_none',
# {"$gt": per_trial / 4, "$lt": 3 * per_trial / 4}])
# timed("find range (large, no index)", find,
# [db, 'large_none',
# {"$gt": per_trial / 4, "$lt": 3 * per_trial / 4}])
timed("find range (small, indexed)", find,
[db, 'small_index',
{"$gt": per_trial / 2, "$lt": per_trial / 2 + batch_size}])
timed("find range (medium, indexed)", find,
[db, 'medium_index',
{"$gt": per_trial / 2, "$lt": per_trial / 2 + batch_size}])
timed("find range (large, indexed)", find,
[db, 'large_index',
{"$gt": per_trial / 2, "$lt": per_trial / 2 + batch_size}])
if __name__ == "__main__":
# cProfile.run("main()")
main()
|
