-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.
+In the previous tutorials, we used @arvados.job_setup.one_task_per_input_file()@ to automatically create concurrent 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:
+Start by entering the @crunch_scripts@ directory of your Git repository:
-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 should now be able to run your new script using Crunch, with "script" referring to our new "concurrent-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).
-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:
+(Your shell should automatically fill in @$USER@ with your login name. The job JSON that gets saved should have @"repository"@ pointed at your personal Git repository.)
+
+Because the job ran in concurrent, each instance of concurrent-hash creates a separate @md5sum.txt@ as output. Arvados automatically collates theses files into a single collection, which is the output of the job:
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-<pre><code>~/<b>you</b>/crunch_scripts$ <span class="userinput">arv keep ls e2ccd204bca37c77c0ba59fc470cd0f7+162</span>
-md5sum.txt
-md5sum.txt
-md5sum.txt
-~/<b>you</b>/crunch_scripts$ <span class="userinput">arv keep get e2ccd204bca37c77c0ba59fc470cd0f7+162/md5sum.txt</span>
+<pre><code>~/$USER/crunch_scripts$ <span class="userinput">arv keep ls e2ccd204bca37c77c0ba59fc470cd0f7+162</span>
+./md5sum.txt
+~/$USER/crunch_scripts$ <span class="userinput">arv keep get e2ccd204bca37c77c0ba59fc470cd0f7+162/md5sum.txt</span>