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
|
#!/usr/bin/python
# -*- coding: utf-8 -*-
#
# Public Domain 2014-present MongoDB, Inc.
# Public Domain 2008-2014 WiredTiger, Inc.
#
# This is free and unencumbered software released into the public domain.
#
# Anyone is free to copy, modify, publish, use, compile, sell, or
# distribute this software, either in source code form or as a compiled
# binary, for any purpose, commercial or non-commercial, and by any
# means.
#
# In jurisdictions that recognize copyright laws, the author or authors
# of this software dedicate any and all copyright interest in the
# software to the public domain. We make this dedication for the benefit
# of the public at large and to the detriment of our heirs and
# successors. We intend this dedication to be an overt act of
# relinquishment in perpetuity of all present and future rights to this
# software under copyright law.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
# IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR
# OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
# ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
# OTHER DEALINGS IN THE SOFTWARE.
import glob
import json
import re
class PerfStat:
def __init__(self,
short_label: str,
output_label: str,
input_offset: int = 0,
output_precision: int = 0,
pattern: str = None,
stat_file: str = 'test.stat',
conversion_function=int):
self.short_label: str = short_label
self.output_label: str = output_label
self.input_offset: int = input_offset
self.output_precision: int = output_precision
self.pattern: str = pattern
self.stat_file = stat_file
self.conversion_function = conversion_function
self.values = []
def add_values(self, values: list):
for val in values:
converted_value = self.conversion_function(val)
self.values.append(converted_value)
def find_stat(self, test_stat_path: str):
matches = []
for line in open(test_stat_path):
match = re.search(self.pattern, line)
if match:
matches.append(float(line.split()[self.input_offset]))
return matches
def average(self, vals):
return self.conversion_function(sum(vals) / len(vals))
def get_value(self):
"""Return the average of all gathered values"""
if len(self.values) >= 3:
drop_min_and_max = sorted(self.values)[1:-1]
return self.average(drop_min_and_max)
else:
return self.average(self.values)
def get_value_list(self, brief: bool):
as_dict = {
'name': self.output_label,
'value': self.get_value()
}
if not brief:
as_dict['values'] = self.values
return [as_dict]
def are_values_all_zero(self):
result = True
for value in self.values:
if value != 0:
result = False
return result
class PerfStatMin(PerfStat):
def get_value(self):
"""Return the averaged minimum of all gathered values"""
min_3_vals = sorted(self.values)[:3]
return self.average(min_3_vals)
class PerfStatMax(PerfStat):
def get_value(self):
"""Return the averaged maximum of all gathered values"""
max_3_vals = sorted(self.values)[-3:]
return self.average(max_3_vals)
class PerfStatCount(PerfStat):
def find_stat(self, test_stat_path: str):
"""Return the total number of times a pattern matched"""
total = 0
test_stat_path = glob.glob(test_stat_path)[0]
for line in open(test_stat_path):
match = re.search(self.pattern, line)
if match:
total += 1
return [total]
class PerfStatLatency(PerfStat):
def __init__(self, short_label: str, stat_file: str, output_label: str, num_max: int):
super().__init__(short_label=short_label,
stat_file=stat_file,
output_label=output_label)
self.num_max = num_max
def find_stat(self, test_stat_path: str):
values = []
for line in open(test_stat_path):
as_dict = json.loads(line)
values.append(as_dict["wtperf"]["read"]["max latency"])
values.append(as_dict["wtperf"]["update"]["max latency"])
return values
def get_value(self, nth_max: int):
"""Return the nth maximum number from all the gathered values"""
return sorted(self.values)[-nth_max]
def get_value_list(self, brief: bool):
as_list = []
for i in range(1, self.num_max + 1):
as_dict = {
'name': self.output_label + str(i),
'value': self.get_value(i)
}
if not brief:
as_dict['values'] = self.values
as_list.append(as_dict)
return as_list
|
