statsgod pidstat

library("ggplot2")
library("dplyr")
library("tidyr")

cleanup_pidstat_h_file <- function(filename) {
  lines <- readLines(filename)
  # Extract the first instance of the column headers and remove the # prefix.
  header_line <- substring(lines[3], 8)
  # Remove blank lines.
  lines <- lines[! lines %in% ""]
  # Remove all instances of the repeated header line (regex could be better).
  lines <- lines[-grep("^#", lines)]
  # Put the column headers back in place of the first mpstat output line.
  lines[1] <- header_line
  lines
}

filename <- "statsgod_pidstat_1422995277.txt"

lines <- cleanup_pidstat_h_file(filename)

df <- read.table(text=lines, header=TRUE)
df$Time <- as.POSIXct(df$Time, origin="1970-01-01")

df_long <- df %>%
  gather(metric, value, -Time, -PID, -Command)

df_long %>%
  filter(metric %in% c("X.CPU", "X.usr", "X.system")) %>% 
  ggplot(aes(Time, value, colour=metric, alpha=0.4)) +
  geom_line() +
  ylab("% CPU") +
  ggtitle("CPU usage") +
  facet_wrap(~metric, ncol=1)

df %>%
  ggplot(aes(Time, RSS/1024)) +
  geom_line() +
  ylab("RSS in mb") +
  ggtitle("Memory usage")