set.seed(1113)
sample(c("Axel","Mike","Markus"))

1. 'Axel'
2. 'Markus'
3. 'Mike'

set.seed(1214)
sample(c("Axel","Mike","Markus"), size=1)

'Mike'

library("tidyverse")

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.4.4     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

options(repr.plot.width=14, repr.plot.res=300)

cpu <- read_tsv("cpu.tsv") %>% mutate(timestamp = ymd_hms(timestamp))

Rows: 346230 Columns: 10
── Column specification ────────────────────────────────────────────────────────
Delimiter: "\t"
chr (2): hostname, timestamp
dbl (8): interval, CPU, %user, %nice, %system, %iowait, %steal, %idle

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

head(cpu)

A tibble: 6 × 10

hostname	interval	timestamp	CPU	%user	%nice	%system	%iowait	%steal	%idle
<chr>	<dbl>	<dttm>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>	<dbl>
gaia2	60	2024-03-01 09:45:27	-1	1.05	0	2.62	0.09	0	96.23
gaia2	60	2024-03-01 09:46:27	-1	1.33	0	2.92	0.16	0	95.60
gaia2	60	2024-03-01 09:47:27	-1	1.47	0	2.98	0.16	0	95.38
gaia2	60	2024-03-01 09:48:27	-1	1.65	0	3.25	0.09	0	95.01
gaia2	60	2024-03-01 09:49:27	-1	1.05	0	2.42	0.06	0	96.47
gaia2	60	2024-03-01 09:50:27	-1	1.38	0	2.22	0.06	0	96.34

cpu %>%
    ggplot(aes(x=timestamp, y=`%idle`, color=hostname)) + geom_line()

cpu2<-cpu%>%
filter(timestamp<lubridate::ymd("2024-03-31"))

cpu2 %>%
    ggplot(aes(x=timestamp, y=`%idle`, color=hostname)) + geom_line()

summary(cpu2$timestamp)

                      Min.                    1st Qu. 
"2024-03-01 09:45:25.0000" "2024-03-08 16:06:26.0000" 
                    Median                       Mean 
"2024-03-15 22:27:27.0000" "2024-03-15 16:42:06.9877" 
                   3rd Qu.                       Max. 
"2024-03-22 18:14:46.0000" "2024-03-29 10:20:05.0000" 

cpu3 <- cpu2 %>%
    group_by(hostname, lubridate::day(timestamp)) %>%
    summarize(idle=min(`%idle`))

`summarise()` has grouped output by 'hostname'. You can override using the
`.groups` argument.

cpu3%>%
ggplot(aes(x=idle,fill=hostname))+
geom_histogram()

`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

cpu3  %>%
    filter(idle>75 & idle<90)

A grouped_df: 40 × 3

hostname	lubridate::day(timestamp)	idle
<chr>	<int>	<dbl>
gaia2	5	75.80
gaia2	11	89.48
gaia2	25	87.04
gaia3	12	89.67
gaia3	28	87.86
gaia4	2	82.10
gaia4	3	81.42
gaia4	7	88.19
gaia4	8	78.73
gaia4	12	76.43
gaia4	13	75.38
gaia4	14	76.56
gaia4	15	75.30
gaia4	16	75.92
gaia4	25	75.66
gaia5	1	83.84
gaia5	2	82.90
gaia5	3	82.16
gaia5	6	81.99
gaia5	7	80.09
gaia5	9	78.55
gaia5	10	79.08
gaia5	11	78.16
gaia5	13	87.42
gaia5	14	80.74
gaia5	15	82.00
gaia5	16	75.49
gaia5	17	86.24
gaia5	18	83.54
gaia5	19	86.82
gaia5	20	77.34
gaia5	21	89.68
gaia5	22	87.67
gaia5	25	89.70
gaia5	26	89.16
gaia5	27	86.28
gaia5	28	89.08
jupiter4	3	83.03
jupiter4	27	88.34
jupiter5	3	86.39

library(lubridate)

cpu2 %>%
    mutate(d=day(timestamp)) %>%
    filter(hostname=="gaia5", d==5) %>%
    ggplot(aes(x=timestamp, y=`%idle`)) + geom_line()

cpu2 %>%
    mutate(d=day(timestamp)) %>%
    filter(hostname=="gaia5") %>%
    ggplot(aes(x=timestamp, y=`%idle`)) + geom_line() + facet_wrap(d~., scales="free_x")

cpu2 %>%
    mutate(d=day(timestamp)) %>%
    filter(hostname=="jupiter") %>%
    ggplot(aes(x=timestamp, y=`%idle`)) + geom_line() + facet_wrap(d~., scales="free_x")

cpu2 %>%
    mutate(d=day(timestamp)) %>%
    filter(hostname=="jupiter") %>%
    ggplot(aes(x=timestamp, y=`%idle`)) + geom_line() + facet_wrap(d~., scales="free_x")

mem <- read_tsv("mem.tsv") %>% mutate(timestamp = ymd_hms(timestamp))

Rows: 346229 Columns: 14
── Column specification ────────────────────────────────────────────────────────
Delimiter: "\t"
chr  (2): hostname, timestamp
dbl (12): interval, kbmemfree, kbavail, kbmemused, %memused, kbbuffers, kbca...

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

mem2<-mem %>%
   filter(timestamp<lubridate::ymd("2024-03-31"))%>%
filter(hostname=="jupiter") 

mem2%>%
    mutate(d=day(timestamp))%>%
    ggplot(aes(x=timestamp, y=`%memused`)) + geom_line() + facet_wrap(d~., scales="free_x")