Documentation

Submitting a task with MyQueue typically works like this:

$ mq submit <task> -R <resources>

or:

$ mq submit "<task> <arguments>" -R <resources>

And checking the result looks like this:

$ mq list -s <states>  # or just: mq ls

Below, we describe the important concepts Tasks, Arguments, Resources and States.

Tasks

There are five kinds of tasks: Python module, Function in a Python module, Python script, Shell command and Shell-script.

Python module

Examples:

  • module

  • module.submodule (a Python submodule)

These are executed as python3 -m module so Python must be able to import the modules.

Function in a Python module

Examples:

  • module@function

  • module.submodule@function

These are executed as python3 -c "import module; module.function(...) so Python must be able to import the function from the module.

Python script

Examples:

  • script.py (use script.py in folders where tasks are running)

  • ./script.py (use script.py from folder where tasks were submitted)

  • /path/to/script.py (absolute path)

Executed as python3 script.py.

Shell command

Example:

  • shell:command

The command must be in $PATH.

Shell-script

Example:

  • ./script

Executed as . ./script.

Arguments

All tasks can take extra arguments by enclosing task and arguments in quotes like this:

"<task> <arg1> <arg2> ..."

Arguments will simply be added to the command-line that executes the task, except for Function in a Python module tasks where the arguments are converted to Python literals and passed to the function. Some examples:

$ mq submit "script.py ABC 123"

would run python3 script.py ABC 123 and:

$ mq submit "mymod@func ABC 123"

would run python3 -c "import mymod; mymod.func('ABC', 123).

Using a Python virtual environment

If a task is submitted from a virtual environment then that venv will also be activated in the script that runs the task. MyQueue does this by looking for an VIRTUAL_ENV environment variable.

Resources

A resource specification has the form:

cores[:nodename][:processes]:tmax

  • cores: number of cores to reserve

  • nodename: node-name (defaults to best match in the list of node-types)

  • processes: number of MPI processes to start (defaults to number of cores)

  • tmax: maximum time (use s, m, h and d for seconds, minutes, hours and days respectively)

Both the submit and resubmit commands as well as the myqueue.task.task() function, take an optional resources argument (-R or --resources). Default resources are a modest one core and 10 minutes.

Examples:

  • 1:1h 1 core and 1 process for 1 hour

  • 64:xeon:2d 64 cores and 64 processes on “xeon” nodes for 2 days

  • 24:1:30m 24 cores and 1 process for 30 minutes (useful for OpenMP tasks or tasks that do their own mpiexec call)

Resources can also be specified via special comments in scripts:

# MQ: resources=40:1d
from somewhere import run
run('something')

States

These are the 8 possible states a task can be in:

queued

waiting for resources to become available

hold

on hold

running

actually running

done

successfully finished

FAILED

something bad happened

MEMORY

ran out of memory

TIMEOUT

ran out of time

CANCELED

a dependency failed or ran out of memory or time

The the -s or --states options of the list, resubmit, remove and modify use the following abbreviations: q, h, r, d, F, C, M and T. It’s also possible to use a as a shortcut for the all the “good” states qhrd and A for the “bad” ones FCMT.

Examples

  • Sleep for 2 seconds on 1 core using the time.sleep() Python function:

    $ mq submit "time@sleep 2" -R 1:1m
1 ./ time@sleep 2 +1 1:1m
1 task submitted

  • Run the echo hello shell command in two folders (using the defaults of 1 core for 10 minutes):

    $ mkdir f1 f2
$ mq submit "shell:echo hello" f1/ f2/
Submitting tasks: ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 2/2
2 ./f1/ shell:echo hello +1 1:10m
3 ./f2/ shell:echo hello +1 1:10m
2 tasks submitted

  • Run script.py on 8 cores for 10 hours:

    $ echo "x = 1 / 0" > script.py
$ mq submit script.py -R 8:10h
4 ./ script.py 8:10h
1 task submitted

You can see the status of your jobs with:

$ mq list
id folder name       args  info res.   age state  time error
── ────── ────────── ───── ──── ───── ──── ────── ──── ───────────────────────────────────
1  ./     time@sleep 2     +1   1:1m  0:02 done   0:02
2  ./f1/  shell:echo hello +1   1:10m 0:00 done   0:00
3  ./f2/  shell:echo hello +1   1:10m 0:00 done   0:00
4  ./     script.py             8:10h 0:00 FAILED 0:00 ZeroDivisionError: division by zero
── ────── ────────── ───── ──── ───── ──── ────── ──── ───────────────────────────────────
done: 3, FAILED: 1, total: 4

Remove the failed and done jobs from the list with (notice the dot meaning the current folder):

$ mq remove -s Fd -r .
1 ./    time@sleep 2     +1 1:1m  0:02 done   0:02
2 ./f1/ shell:echo hello +1 1:10m 0:00 done   0:00
3 ./f2/ shell:echo hello +1 1:10m 0:00 done   0:00
4 ./    script.py           8:10h 0:00 FAILED 0:00 ZeroDivisionError: division by zero
4 tasks removed

The output files from a task will look like this:

$ ls -l f2
total 4
-rw-rw-r-- 1 jensj jensj 0 Jun 24 22:33 shell:echo.3.err
-rw-rw-r-- 1 jensj jensj 6 Jun 24 22:33 shell:echo.3.out
$ cat f2/shell:echo.3.out
hello

If a job fails or times out, then you can resubmit it with more resources:

$ mq submit "shell:sleep 4" -R 1:2s
5 ./ shell:sleep 4 +1 1:2s
1 task submitted
$ mq list
id folder name        args info res.  age state   time
── ────── ─────────── ──── ──── ──── ──── ─────── ────
5  ./     shell:sleep 4    +1   1:2s 0:02 TIMEOUT 0:02
── ────── ─────────── ──── ──── ──── ──── ─────── ────
TIMEOUT: 1, total: 1
$ mq resubmit -i 5 -R 1:1m
6 ./ shell:sleep 4 +1 1:1m
1 task submitted