+++ title = "Supercharge Your Bash Scripts with Multiprocessing" date = "2021-05-05T17:08:12+03:00" author = "Yigit Colakoglu" authorTwitter = "theFr1nge" cover = "images/supercharge-your-bash-scripts-with-multiprocessing.png" tags = ["bash", "scripting", "programming"] keywords = ["bash", "scripting"] description = "Bash is a great tool for automating tasks and improving your workflow. However, it is SLOW. Adding multiprocessing to the scripts you write can improve the performance greatly." showFullContent = false draft=false +++
Bash is a great tool for automating tasks and improving your workflow. However, it is SLOW. Adding multiprocessing to the scripts you write can improve the performance greatly.
In the simplest terms, multiprocessing is the principle of splitting the computations or jobs that a script has to do and running them on different processes. In even simpler terms however, multiprocessing is the computer science equivalent of hiring more than one worker when you are constructing a building.
While implementing multiprocessing the sign &
is going to be our greatest
friend. It is an essential sign if you are writing bash scripts and a very
useful tool in general when you are in the terminal. What &
does is that it
makes the command you added it to the end of run in the background and allows
the rest of the script to continue running as the command runs in the
background. One thing to keep in mind is that since it creates a fork of the
process you ran the command on, if you change a variable that the command in the
background uses while it runs, it will not be affected. Here is a simple
example:
{{< code language="bash" id="1" expand="Show" collapse="Hide" isCollapsed="false" >}} foo="yeet"
function run_in_background(){ sleep 0.5 echo "The value of foo in the function run_in_background is $foo" }
run_in_background & # Spawn the function run_in_background in the background foo="YEET" echo "The value of foo changed to $foo." wait # wait for the background process to finish {{< /code >}}
This should output:
The value of foo changed to YEET.
The value of foo in here is yeet
As you can see, the value of foo
did not change in the background process even though
we changed it in the main function.
Just like anything related to computer science, there is more than one way of achieving our goal. We are going to take the easier, less intimidating but less efficient route first before moving on to the big boy implementation. Let's open up vim and get to scripting! First of all, let's write a very simple function that allows us to easily test our implementation:
{{< code language="bash" id="1" expand="Show" collapse="Hide" isCollapsed="false" >}} function tester(){
echo "$1" sleep "$1" echo "ENDED $1" } {{< /code >}}
Now that we have something to run in our processes, we now need to spawn several
of them in controlled manner. Controlled being the keyword here. That's because
each system has a maximum number of processes that can be spawned (You can find
that out with the command ulimit -u
). In our case, we want to limit the
processes being ran to the variable num_processes
. Here is the implementation:
{{< code language="bash" id="1" expand="Show" collapse="Hide" isCollapsed="false" >}} num_processes=$1 pcount=0 for i in {1..10}; do ((pcount=pcount%num_processes)); ((pcount++==0)) && wait tester $i & done {{< /code >}}
What this loop does is that it takes the number of processes you would like to
spawn as an argument and runs tester
in that many processes. Go ahead and test it out!
You might notice however that the processes are run int batches. And the size of
batches is the num_processes
variable. The reason this happens is because
every time we spawn num_processes
processes, we wait
for all the processes
to end. This implementation is not a problem in itself, there are many cases
where you can use this implementation and it works perfectly fine. However, if
you don't want this to happen, we have to dump this naive approach all together
and improve our tool belt.
The solution to the bottleneck that was introduced in our previous approach lies in using job pools. Job pools are where jobs created by a main process get sent and wait to get executed. This approach solves our problems because instead of spawning a new process for every copy and waiting for all the processes to finish we instead only create a set number of processes(workers) which continuously pick up jobs from the job pool not waiting for any other process to finish. Here is the implementation that uses job pools. Brace yourselves, because it is kind of complicated.
{{< code language="bash" id="1" expand="Show" collapse="Hide" isCollapsed="false" >}} job_pool_end_of_jobs="NO_JOB_LEFT" job_pool_job_queue=/tmp/job_pool_job_queue_$$ job_pool_progress=/tmp/job_pool_progress_$$ job_pool_pool_size=-1 job_pool_nerrors=0
function job_pool_cleanup() { rm -f ${job_pool_job_queue} rm -f ${job_pool_progress} }
function job_pool_exit_handler() { job_pool_stop_workers job_pool_cleanup }
function job_pool_worker() { local id=$1 local job_queue=$2 local cmd= local args=
exec 7<> ${job_queue}
while [[ "${cmd}" != "${job_pool_end_of_jobs}" && -e "${job_queue}" ]]; do
flock --exclusive 7
IFS=$'\v'
read cmd args <${job_queue}
set -- ${args}
unset IFS
flock --unlock 7
if [[ "${cmd}" == "${job_pool_end_of_jobs}" ]]; then
echo "${cmd}" >&7
else
{ ${cmd} "$@" ; }
fi
done
exec 7>&-
}
function job_pool_stop_workers() { echo ${job_pool_end_of_jobs} >> ${job_pool_job_queue} wait }
function job_pool_start_workers() { local job_queue=$1 for ((i=0; i<${job_pool_pool_size}; i++)); do job_pool_worker ${i} ${job_queue} & done }
function job_pool_init() { local pool_size=$1 job_pool_pool_size=${pool_size:=1} rm -rf ${job_pool_job_queue} rm -rf ${job_pool_progress} touch ${job_pool_progress} mkfifo ${job_pool_job_queue} echo 0 >${job_pool_progress} & job_pool_start_workers ${job_pool_job_queue} }
function job_pool_shutdown() { job_pool_stop_workers job_pool_cleanup }
function job_pool_run() { if ; then job_pool_init fi printf "%s\v" "$@" >> ${job_pool_job_queue} echo >> ${job_pool_job_queue} }
function job_pool_wait() { job_pool_stop_workers job_pool_start_workers ${job_pool_job_queue} } {{< /code >}}
Ok... But that the actual fuck is going in here???
In order to understand what this code is doing, you first need to understand two
key commands that we are using, fifo
and flock
. Despite their complicated
names, they are actually quite simple. Let's check their man pages to figure out
their purposes, shall we?
fifo's man page tells us that:
NAME
fifo - first-in first-out special file, named pipe
DESCRIPTION
A FIFO special file (a named pipe) is similar to a pipe, except that
it is accessed as part of the filesystem. It can be opened by multiple
processes for reading or writing. When processes are exchanging data
via the FIFO, the kernel passes all data internally without writing it
to the filesystem. Thus, the FIFO special file has no contents on the
filesystem; the filesystem entry merely serves as a reference point so
that processes can access the pipe using a name in the filesystem.
So put in very simple terms, a fifo is a named pipe that allows
communication between processes. Using a fifo allows us to loop through the jobs
in the pool without having to delete them manually, because once we read them
with read cmd args < ${job_queue}
, the job is out of the pipe and the next
read outputs the next job in the pool. However the fact that we have multiple
processes introduces one caveat, what if two processes access the pipe at the
same time? They would run the same command and we don't want that. So we resort
to using flock
.
flock's man page defines it as:
SYNOPSIS
flock [options] file|directory command [arguments]
flock [options] file|directory -c command
flock [options] number
DESCRIPTION
This utility manages flock(2) locks from within shell scripts or from
the command line.
The first and second of the above forms wrap the lock around the
execution of a command, in a manner similar to su(1) or newgrp(1).
They lock a specified file or directory, which is created (assuming
appropriate permissions) if it does not already exist. By default, if
the lock cannot be immediately acquired, flock waits until the lock is
available.
The third form uses an open file by its file descriptor number. See
the examples below for how that can be used.
Cool, translated to modern English that us regular folks use, flock
is a thin
wrapper around the C standard function flock
(see man 2 flock
if you are
interested). It is used to manage locks and has several forms. The one we are
interested in is the third one. According to the man page, it uses and open file
by its file descriptor number. Aha! so that was the purpose of the exec 7<> ${job_queue}
calls in the job_pool_worker
function. It would essentially
assign the file descriptor 7 to the fifo job_queue
and afterwards lock it with
flock --exclusive 7
. Cool. This way only one process at a time can read from
the fifo job_queue
It depends on your preference, you can either save this in a file(e.g. job_pool.sh) and source it in your bash script. Or you can simply paste it inside an existing bash script. Whatever tickles your fancy. I have also provided an example that replicates our first implementation. Just paste the below code under our "chad" job pool script.
{{< code language="bash" id="1" expand="Show" collapse="Hide" isCollapsed="false" >}} function tester(){
echo "$1" sleep "$1" echo "ENDED $1" }
num_workers=$1 job_pool_init $num_workers pcount=0 for i in {1..10}; do job_pool_run tester "$i" done
job_pool_wait job_pool_shutdown {{< /code >}}
Hopefully this article was(or will be) helpful to you. From now on, you don't ever have to write single threaded bash scripts like normies :)