parallel

Parallel

The parallel command is a powerful tool that allows you to run multiple commands or jobs concurrently, utilizing available system resources such as CPU cores and memory. It’s designed to speed up tasks that can be executed independently, making it ideal for tasks like data processing, file compression, and image processing.

Use Cases

  • Running multiple shell scripts simultaneously
  • Executing a series of commands on a large dataset
  • Compressing or archiving files in parallel
  • Performing CPU-intensive tasks like video encoding or scientific simulations

Example Usage

To give you an idea of how parallel works, consider this example:
bash
find . -type f | parallel gzip {}

In this scenario, the find command searches for all files ( -type f ) within the current directory and its subdirectories. The output is then piped into parallel, which takes each file as input and executes the gzip command on it in parallel.

Special Hacks

  • Using -j <n>: This option controls the number of jobs to run concurrently. For example, find . -type f | parallel -j 4 gzip {} will execute up to four gzip commands at a time.
  • Using --bar: This flag adds a progress bar that displays the number of completed tasks and the total count.
  • Using --halt-on-error: If any job fails or encounters an error, parallel will stop execution altogether.

Experience Level

The parallel command is most suitable for users with some experience in Linux scripting and automation. It’s a powerful tool that can save time and improve efficiency, but it requires a basic understanding of how to work with pipes, shell scripts, and job control.

To use parallel effectively, you should be familiar with:

  • Shell scripting basics (e.g., writing simple scripts)
  • Pipelining commands
  • Understanding CPU cores and resource utilization

If you’re new to Linux or still learning the ropes, it’s recommended to start with simpler tools like find, xargs, or GNU make before diving into parallel.

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