---
layout: default
navsection: userguide
title: "Parallel Crunch tasks"
...
In the previous tutorials, we used @arvados.job_setup.one_task_per_input_file()@ to automatically parallelize our jobs by creating a separate task per file. For some types of jobs, you may need to split the work up differently, for example creating tasks to process different segments of a single large file. In this this tutorial will demonstrate how to create Crunch tasks directly.
Start by entering the @crunch_scripts@ directory of your git repository:
~$ cd you/crunch_scripts
Next, using @nano@ or your favorite Unix text editor, create a new file called @parallel-hash.py@ in the @crunch_scripts@ directory.
notextile. ~/you/crunch_scripts$ nano parallel-hash.py
Add the following code to compute the md5 hash of each file in a collection:
{% code 'parallel_hash_script_py' as python %}
Make the file executable:
notextile. ~/you/crunch_scripts$ chmod +x parallel-hash.py
Next, add the file to @git@ staging, commit and push:
~/you/crunch_scripts$ git add parallel-hash.py
~/you/crunch_scripts$ git commit -m"parallel hash"
~/you/crunch_scripts$ git push origin master
You should now be able to run your new script using Crunch, with "script" referring to our new "parallel-hash.py" script. We will use a different input from our previous examples. We will use @887cd41e9c613463eab2f0d885c6dd96+83@ which consists of three files, "alice.txt", "bob.txt" and "carol.txt" (the example collection used previously in "fetching data from Arvados using Keep":{{site.baseurl}}/user/tutorials/tutorial-keep.html#dir).
~/you/crunch_scripts$ cat >~/the_job <<EOF
{
"script": "parallel-hash.py",
"repository": "$USER",
"script_version": "master",
"script_parameters":
{
"input": "887cd41e9c613463eab2f0d885c6dd96+83"
}
}
EOF
~/you/crunch_scripts$ arv job create --job "$(cat ~/the_job)"
{
...
"uuid":"qr1hi-xxxxx-xxxxxxxxxxxxxxx"
...
}
~/you/crunch_scripts$ arv job get --uuid qr1hi-xxxxx-xxxxxxxxxxxxxxx
{
...
"output":"e2ccd204bca37c77c0ba59fc470cd0f7+162",
...
}
(Your shell should automatically fill in @$USER@ with your login name. The job JSON that gets saved should have @"repository"@ pointed at your personal git repository.)
Because the job ran in parallel, each instance of parallel-hash creates a separate @md5sum.txt@ as output. Arvados automatically collates theses files into a single collection, which is the output of the job:
~/you/crunch_scripts$ arv keep ls e2ccd204bca37c77c0ba59fc470cd0f7+162
./md5sum.txt
~/you/crunch_scripts$ arv keep get e2ccd204bca37c77c0ba59fc470cd0f7+162/md5sum.txt
0f1d6bcf55c34bed7f92a805d2d89bbf alice.txt
504938460ef369cd275e4ef58994cffe bob.txt
8f3b36aff310e06f3c5b9e95678ff77a carol.txt