X-Git-Url: https://git.arvados.org/arvados.git/blobdiff_plain/d6d7788c4e6b1d3da88833329b326fd7a3891503..759878e0a72644c5e537c51da9806672cf92e458:/doc/user/topics/tutorial-parallel.html.textile.liquid diff --git a/doc/user/topics/tutorial-parallel.html.textile.liquid b/doc/user/topics/tutorial-parallel.html.textile.liquid index 0cbceda619..9be610358b 100644 --- a/doc/user/topics/tutorial-parallel.html.textile.liquid +++ b/doc/user/topics/tutorial-parallel.html.textile.liquid @@ -1,10 +1,10 @@ --- layout: default navsection: userguide -title: "Parallel Crunch tasks" +title: "Concurrent 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. +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: @@ -13,33 +13,33 @@ Start by entering the @crunch_scripts@ directory of your Git repository: -Next, using @nano@ or your favorite Unix text editor, create a new file called @parallel-hash.py@ in the @crunch_scripts@ directory. +Next, using @nano@ or your favorite Unix text editor, create a new file called @concurrent-hash.py@ in the @crunch_scripts@ directory. -notextile. 
~/$USER/crunch_scripts$ nano parallel-hash.py
+notextile. 
~/$USER/crunch_scripts$ nano concurrent-hash.py
Add the following code to compute the MD5 hash of each file in a collection: - {% code 'parallel_hash_script_py' as python %} + {% code 'concurrent_hash_script_py' as python %} Make the file executable: -notextile. 
~/$USER/crunch_scripts$ chmod +x parallel-hash.py
+notextile. 
~/$USER/crunch_scripts$ chmod +x concurrent-hash.py
Add the file to the Git staging area, commit, and push: -
~/$USER/crunch_scripts$ git add parallel-hash.py
-~/$USER/crunch_scripts$ git commit -m"parallel hash"
+
~/$USER/crunch_scripts$ git add concurrent-hash.py
+~/$USER/crunch_scripts$ git commit -m"concurrent hash"
 ~/$USER/crunch_scripts$ 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 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).
 
 
 
~/$USER/crunch_scripts$ cat >~/the_job <<EOF
 {
- "script": "parallel-hash.py",
+ "script": "concurrent-hash.py",
  "repository": "$USER",
  "script_version": "master",
  "script_parameters":
@@ -65,7 +65,7 @@ EOF
 
 (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:
+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:
 
 
 
~/$USER/crunch_scripts$ arv keep ls e2ccd204bca37c77c0ba59fc470cd0f7+162