Skimming the process poolAugust 3, 2020
Say you have a lot of independent computing tasks to complete. You don't have to finish one before starting the next, and you'd like to parallelize them to speed up collective execution. This means running the tasks simultaneously in separate processes. How many processes do you spin up?
If you have a hundred tasks, you could run each task in its own OS process. If you have millions of tasks though, you won't be able to create this many processes (you'll hit the PID limit well before). Even if the number of tasks is within the PID limit, and supposing you don't hit other limits (e.g. file descriptors), spinning up hundreds of processes could consume a lot of CPU or make a lot of network requests and eat up your bandwidth.
A better option would be to create a "pool" with a fixed number of processes. Each process would run a task and, when it's finished, begin the next task that hasn't been claimed by another process. This way, you get the benefits of parallelization without exhausting resources on your machine or the network.
Fortunately, this is trivial to achieve with the UNIX command,
xargs. Suppose you have a
file with a thousand lines where each line is a task input. The command,
do-stuff, runs the task in question. The following snippet divides the tasks among 10 processess, passing each line in the file as the input to
xargs -a "$file" -n 1 -P 10 do-stuff
do-stuff doesn't exist and you'd like to write your own shell code that performs arbitary processing on each line in the file? The following snippet achieves this:
xargs -a "$file" -n 1 -P 10 bash -c $' # your shell code that does arbitrary processing # # example - prepends each line with "foo" and prints result: echo "foo$0"'
Next time you'd like to parallelize the execution of many tasks, try implementing a process pool with
Addendum: When I originally wrote this post, I neglected to mention
parallel, an obvious choice for running tasks in parallel! This tool is, on the surface, quite similar to
xargs. However, it allows for running tasks in parallel with a counting semaphore, distributing jobs across disparate machines with SSH login, and much more!