Tymon Tobolski

Measuring and visualizing GenStage/Flow with Gnuplot

After my recent post about Elixir GenStage/Flow some people asked about follow-up on measurements and plotting, so here it is.

White lies

Before we start, I need to admit to one thing. In the last post, I’ve written that I’ve used Repo.stream from Ecto. The truth is, I’ve used my own version of Repo.stream that has been in Recruitee codebase long before Ecto got one. This difference will be very important when we will talk about measuring progress.

Measuring progress

First, we need to somehow gather progress data for every stage.

Every metrics system is composed from at least these three components:

  • collector
  • storage (not necessarily persistent)
  • events/metrics emitter (reporter)

And the one I’m going to describe, although being extremely simple is no different.

In Elixir/Erlang world it comes quite naturally that the collector could be a separate process and to emit metrics events we can send messages to that process. And for the storage part we can just use the file system.

Below is the annotated, complete source code of the progress collector, based on GenServer:

defmodule Progress do
  use GenServer

  @timeres :millisecond


  # Progress.start_link [:a, :b, :c]
  def start_link(scopes \\ []) do
    GenServer.start_link(__MODULE__, scopes, name: __MODULE__)

  def stop do

  # increment counter for given scope by `n`
  #     Progress.incr(:my_scope)
  #     Progress.incr(:my_scope, 10)
  def incr(scope, n \\ 1) do
    GenServer.cast __MODULE__, {:incr, scope, n}


  def init(scopes) do
    # open "progress-{scope}.log" file for every scope
    files = Enum.map(scopes, fn scope ->
      {scope, File.open!("progress-#{scope}.log", [:write])}

    # keep current counter for every scope
    counts = Enum.map(scopes, fn scope -> {scope, 0} end)

    # save current time
    time = :os.system_time(@timeres)

    # write first data point for every scope with current time and value 0
    # this helps to keep the graph starting nicely at (0,0) point
    Enum.each(files, fn {_, io} -> write(io, time, 0) end)

    {:ok, {time, files, counts}}

  def handle_cast({:incr, scope, n}, {time, files, counts}) do
    # update counter
    {value, counts} = Keyword.get_and_update!(counts, scope, &({&1+n, &1+n}))

    # write new data point
    write(files[scope], time, value)

    {:noreply, {time, files, counts}}

  defp write(file, time, value) do
    time = :os.system_time(@timeres) - time
    IO.write(file, "#{time}\t#{value}\n")

In short, the progress process opens a separate log file for every scope given, saves the time of own start and for every :incr message writes a new line into a related file. We keep the files open to avoid opening it for every event (which would be much slower). Since it is a separate process, that is stopped after processing is finished, we don’t really have to care about closing open files - every file handle is actually another separate process, linked to the process that originally opened it, and will be closed when parent process terminates.

In order to emit metrics events I had to modify stages functions with calls to Progress.incr. It was mostly straightforward, except it required a small addition to Repo.stream code.

def select do
  |> Repo.stream(chunk_size: 500, on_chunk: fn list ->
    # use `on_chunk` hook to report progress
    Progress.incr(:select, length(list))

def download(record) do
  file = do_the_download(...)
  # increment counter by 1 after downloading

def extract(file) do
  text = do_the_extract(...)
  # increment counter by 1 after extracting

def index(texts) do
  # increment counter by list length
  Progress.incr(:index, length(texts))

And the perform function looks like this:

def perform do
  # start progress process ...
  Progress.start_link([:select, :download, :extract, :index])

  |> Flow.from_enumerable(max_demand: 100)
  |> ...
  |> Flow.run

  # ... and stop it after processing is done

Plotting the results

I’ve spent quite some time with various plotting options. The first version of collector simply sent all time/count data into stdout that I would select & copy. First, I’ve tried Apple Numbers, which can’t really handle more that 15 rows. Then I switched to Google Docs Spreadsheets which was surprisingly much better than Numbers, but I got tired of that copying & pasting, so I went to look for some automated solution. After digging through thousands of JavaScript graphing libraries I’ve decided to give gnuplot one more chance.

The biggest issue I have with gnuplot is that it’s a bit ugly by default, and all the examples one can find use some shorthand mnemonics that must be deciphered with trial & error.

After some time of playing with gnuplot I’ve managed to write a script that will produce exactly what I wanted:

# plot.gp
# output to png with decend font and image size
set terminal png font "Arial,10" size 700,500
set output "progress.png"

set title "Elixir Flow processing progress over time"
set xlabel "Time (ms)"
set ylabel "Items processed"
set key top left # put labels in top-left corner

# limit x range to 15.000 ms instead of dynamic one, must-have
# when generating few graphs that will be later compared visually
set xrange [0:15000]

# plot series (see below for explanation)
# plot [file] with [line type] ls [line style id] [title ...  | notitle]

plot  "progress-select.log"    with steps   ls 1 title "Select",\
      "progress-select.log"    with points  ls 1 notitle,\
      "progress-download.log"  with lines   ls 2 title "Download",\
      "progress-extract.log"   with lines   ls 3 title "Extract",\
      "progress-index.log"     with steps   ls 4 title "Index",\
      "progress-index.log"     with points  ls 4 notitle
  • SELECT and INDEX are plotted once with steps and then again with [http://stackoverflow.com/questions/16736861/pointtype-command-for-gnuplot]
  • DOWNLOAD and EXTRACT are plotted with lines
  • lines colors are matched using ls (line style) setting

Then running it with

$ gnuplot plot.gp


That’s it

I think the biggest advantage of using tools like gnuplot instead of Excel/Google Docs is the mentioned automation. Most modern image browsers can automatically reload a file when it’s changed, so you can see the data plotted almost instantly. And as a bonus, you get .png files ready for Twitter/Blog post ;)

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