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
|
import pandas as pd
import time
import csv
import os
from time import gmtime, strftime
import numpy as np
import matplotlib.pyplot as plt
PATH = "/src/experiment1/output/gmail/greenifier-demo-scaling/raw-output/0/seed=0/"
CONSTANT = 3_6000_000 / 24
def create_dataframes() -> tuple[pd.DataFrame, pd.DataFrame]:
cwd = os.getcwd()
cwd = cwd + PATH
print(cwd)
hosts: str = "%shost.parquet" % cwd
tasks: str = "%stask.parquet" % cwd
try:
df_hosts = pd.read_parquet(hosts)
df_tasks = pd.read_parquet(tasks)
return (df_hosts, df_tasks)
except Exception:
print("Exception: error opening files.")
exit(1)
def get_name() -> str:
curr = time.time()
s = strftime("%d_%b_%Y_%H%M%S", gmtime(curr))
return s
def iterate(frame):
dictionary = {}
for i in range(len(frame)):
if frame["downtime"].iloc[i] > 0.0:
ts = frame["timestamp"].iloc[i]
dictionary[(ts)] = dictionary.get((ts), 0) + 1
return dictionary
# This is a running function frequently changed
def plot_hosts(frame: pd.DataFrame):
dictionary = {
216000000: 277,
219600000: 277,
280800000: 139,
727200000: 139,
730800000: 139,
802800000: 162,
1407600000: 139,
1850400000: 139,
1857600000: 277,
1861200000: 277,
1872000000: 139,
1926000000: 62,
2023200000: 162,
2037600000: 277,
2041200000: 208,
2070000000: 139,
}
dictionary2 = {
3600000: 11,
180000000: 11,
212400000: 103,
216000000: 103,
219600000: 103,
223200000: 103,
374400000: 57,
712800000: 103,
795600000: 57,
838800000: 11,
882000000: 103,
975600000: 57,
979200000: 11,
982800000: 11,
1087200000: 11,
1234800000: 11,
1404000000: 11,
1854000000: 103,
1857600000: 103,
1861200000: 103,
1926000000: 36,
2034000000: 103,
2037600000: 103,
2041200000: 34,
2080800000: 11,
2102400000: 11,
2163600000: 11,
2185200000: 57,
2383200000: 57,
}
for key in dictionary2.keys():
dictionary2[key] += 150
df = pd.DataFrame(list(dictionary2.items()), columns=["timestamp", "count"])
df3 = iterate(frame)
df2 = pd.DataFrame(list(df3.items()), columns=["timestamp", "count"])
plt.plot(
df2["timestamp"] / CONSTANT,
df2["count"],
label="Actual failures",
linewidth=1,
zorder=2,
)
plt.plot(
df["timestamp"] / CONSTANT,
df["count"],
label="Detected failures",
linewidth=3,
zorder=1,
)
plt.xlabel("Time [days]")
plt.ylabel("Failures per timestamp")
plt.title("Failure detection results")
plt.legend()
path = os.getcwd() + "/src/experiment1/"
location: str = path + "figures/%s.pdf" % get_name()
plt.savefig(location, dpi=300)
total = sum(dictionary.values())
total2 = sum(df3.values())
print(f"Percentage detected: {total/total2}")
def export_results(path: str):
assert path
# 0 is hosts, 1 is tasks
frames: tuple = create_dataframes()
plot_hosts(frames[0])
def main():
export_results(PATH)
if __name__ == "__main__":
main()
|
