Break out ConsumeKafkaMessages function.
[R/project-using-kafka-in-R.git] / collectd.R
1 #devtools::install_github("pldimitrov/rrd")
2 library(rrd)
4 rrd_laysan_apache_bytes <- system.file("/home/frederik/apache_bytes.rrd", package = "rrd")
6 apache_bytes <- read_rrd("/home/frederik/apache_bytes.rrd")
7 describe_rrd("/home/frederik/apache_bytes.rrd")
9 end_time <- as.POSIXct("2018-08-15") # timestamp with data in example
10 start_time <- as.POSIXct("2018-04-15")
11 avg_26350 <- read_rra("/home/frederik/apache_bytes.rrd", cf = "AVERAGE",
12                       #step = 86400,
13                       step = 26350, 
14                       #n_steps = 24 * 60,
15                       start = start_time,
16                       end = end_time)
18 avg_10 <- read_rra("/home/frederik/apache_bytes.rrd", cf = "AVERAGE",
19                       #step = 86400,
20                       step =1,
21                       n_steps = 120 ,
22                       end = end_time)
24 names(apache_bytes)
25 library(ggplot2)
26 ggplot(avg_10, aes(x = timestamp, y = value)) + 
27   geom_line() +
28   stat_smooth(method = "loess", span = 0.125, se = FALSE) +
29   ggtitle("apache bytes, data read from RRD file")
31 #devtools::install_github("tidyverts/fable")
32 library(fable)
33 library(tsibble)
34 ts_avg_bytes <- as.tsibble(avg_10, regular = TRUE)
36 ts_avg_bytes %>%
37   fill_na(value = as.integer(median(value))) %>%
38   ETS(value) %>%
39   forecast(h=50) %>%
40   autoplot