-
Notifications
You must be signed in to change notification settings - Fork 2
/
Copy pathexporting.R
127 lines (91 loc) · 4.35 KB
/
exporting.R
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
# Exporting of Queues
rollingQueueGraphs<- function(selected,startMonth = "01/2024",endMonth = "08/2024"){
db<-daily_utilization(queues = c(selected), start = startMonth, end = endMonth)
rolling<- rollapply(db$DailyUtilization, width = 3, by =1, FUN = mean, align = "center", fill = NA, partial = TRUE)
gg<- ggplot(db, aes(x = as.Date(Date) , y = DailyUtilization, color = queue)) +
geom_line(
aes(y = rolling),
color = "blue",
linewidth = 1,
na.rm = TRUE
) +
ylim(0,1) +
scale_x_date(date_labels = "%b %Y", date_breaks = "1 month") +
labs(title = "Daily Queue Utilization", x = "Date", y = "Daily Utilization") + theme_light()
return(gg)
}
#-------------------------------------------------------------------------------
# MPI queues: 4, a/a128, u, z
util4<-rollingQueueGraphs(selected = c("4")) + ggtitle("Daily Utilization for 4 Queue")
utila<-rollingQueueGraphs(selected=c("a","a128")) + ggtitle("Daily Utilization for a Queue")
utilu<- rollingQueueGraphs(selected=c("u")) + ggtitle("Daily Utilization for u Queue")
utilz<-rollingQueueGraphs(selected=c('z')) + ggtitle("Daily Utilization for z Queue")
#--------------------------------------------------------------------------------
# “old” 1p queues: b, b-long, p
ggplotly(utila)
old1p <- daily_utilization(queues = c("b","b-long","p"), start = "01/2024", end = "08/2024")
ggplot(old1p, aes(x=as.Date(Date) , y = DailyUtilization , color = queue)) +
geom_line(
linewidth = 1,
na.rm = TRUE
) +
ylim(0,1) +
scale_x_date(date_labels = "%b %Y", date_breaks = "1 month") +
labs(title = "Daily Queue Utilization of Old 1p Queues", x = "Date", y = "Daily Utilization") + theme_light()
# “new” 1p queues: f, w, w-long, y
new1p <- daily_utilization(queues = c("f","w","w-long", "y"), start = "01/2024", end = "08/2024")
ggplot(new1p, aes(x=as.Date(Date) , y = DailyUtilization , color = queue)) +
geom_line(
linewidth = 1,
na.rm = TRUE
) +
ylim(0,1) +
scale_x_date(date_labels = "%b %Y", date_breaks = "1 month") +
labs(title = "Daily Queue Utilization of New 1p Queues", x = "Date", y = "Daily Utilization") + theme_light()
# “1TB node”: mem1024
tb1 <- daily_utilization(queues = c("mem1024"), start = "01/2024", end = "08/2024")
ggplot(tb1, aes(x=as.Date(Date) , y = DailyUtilization , color = queue)) +
geom_line(
linewidth = 1,
na.rm = TRUE
) +
ylim(0,1) +
scale_x_date(date_labels = "%b %Y", date_breaks = "1 month") +
labs(title = "Daily Queue Utilization of 1TB Queues", x = "Date", y = "Daily Utilization") + theme_light()
# “old interactive queue” p-int
oldint<- daily_utilization(queues = c("p-int"), start = "01/2024", end = "08/2024")
ggplot(oldint, aes(x=as.Date(Date) , y = DailyUtilization , color = queue)) +
geom_line(
linewidth = 1,
na.rm = TRUE
) +
ylim(0,1) +
scale_x_date(date_labels = "%b %Y", date_breaks = "1 month") +
labs(title = "Daily Queue Utilization of Old Interactive Queue", x = "Date", y = "Daily Utilization") + theme_light()
# “28 core queues” queues: mem384, mem512, w28,
twentyeightcore<- daily_utilization(queues = c("mem384", "mem512","w28"), start = "01/2024", end = "08/2024")
ggplot(twentyeightcore, aes(x=as.Date(Date), y=DailyUtilization, color = queue)) +
geom_line(
linewidth = 1,
na.rm = TRUE
) +
ylim(0,1) +
scale_x_date(date_labels = "%b %Y", date_breaks = "1 month") +
labs(title = "Daily Queue Utilization of 28 Core Queues", x = "Date", y = "Daily Utilization") + theme_light()
# “8 and 16 core queues” queues: c, p8, p16, e8
eightsixteen<- daily_utilization(queues = c("c","p8", "p16", "e8"), start = "01/2024", end = "08/2024")
ggplot(eightsixteen, aes(x=as.Date(Date), y= DailyUtilization, color = queue)) +
geom_line(
linewidth = 1,
na.rm = TRUE
) +
ylim(0,1) +
scale_x_date(date_labels = "%b %Y", date_breaks = "1 month") +
labs(title = "Daily Queue Utilization of 8 and 16 Core Queues", x = "Date", y = "Daily Utilization") + theme_light()
#-------------------------------------------------------------------------------
# Data Exportation
df <- get_acct(2023, 2024, datatype="feather")
df<- df %>% mutate(Year = year(end_date))
aqueue <- df %>% filter (qname %in% c("a", "a128"))
aqueue<- aqueue %>% group_by(qname, Year, project,owner) %>% summarise(N=n(), .groups = "keep")
write.csv(aqueue, "aqueueutil.csv")