title: "Running a pipeline on the command line"
...
-In "Writing a pipeline":{{ site.baseurl }}/user/tutorials/tutorial-firstscript.html, we learned how to create a pipeline template on the command-line. Let's create one that doesn't require any user input to start:
+This tutorial demonstrates how to use the command line to run the same pipeline as described in "running a pipeline using Workbench.":{{site.baseurl}}/user/tutorials/tutorial-pipeline-workbench.html
-<notextile>
-<pre><code>~$ <span class="userinput">cat >the_pipeline <<EOF
-{
- "name":"Filter md5 hash values",
- "components":{
- "do_hash":{
- "script":"hash.py",
- "script_parameters":{
- "input": "887cd41e9c613463eab2f0d885c6dd96+83"
- },
- "repository":"$USER",
- "script_version":"master"
- },
- "filter":{
- "script":"0-filter.py",
- "script_parameters":{
- "input":{
- "output_of":"do_hash"
- }
- },
- "repository":"$USER",
- "script_version":"master"
- }
- }
-}
-EOF</span>
-~$ <span class="userinput">arv pipeline_template create --pipeline-template "$(cat the_pipeline)"</span></code></pre>
-</notextile>
-
-(Your shell should automatically fill in @$USER@ with your login name. The JSON that gets saved should have @"repository"@ pointed at your personal git repository.)
-
-You can run this pipeline from the command line using @arv pipeline run@, filling in the UUID that you received from @arv pipeline_template create@:
-
-<notextile>
-<pre><code>~$ <span class="userinput">arv pipeline run --run-here --template qr1hi-p5p6p-xxxxxxxxxxxxxxx</span>
-2013-12-16 14:08:40 +0000 -- pipeline_instance qr1hi-d1hrv-vxzkp38nlde9yyr
-do_hash qr1hi-8i9sb-hoyc2u964ecv1s6 queued 2013-12-16T14:08:40Z
-filter - -
+{% include 'tutorial_expectations' %}
-2013-12-16 14:08:51 +0000 -- pipeline_instance qr1hi-d1hrv-vxzkp38nlde9yyr
-do_hash qr1hi-8i9sb-hoyc2u964ecv1s6 1ed9ed18ef31ad21bcabcfeff7777bae+162
-filter qr1hi-8i9sb-w5k40fztqgg9i2x queued 2013-12-16T14:08:50Z
+When you use the command line, you must use Arvados unique identifiers to refer to objects. The identifiers in this example correspond to the following Arvados objects:
-2013-12-16 14:09:01 +0000 -- pipeline_instance qr1hi-d1hrv-vxzkp38nlde9yyr
-do_hash qr1hi-8i9sb-hoyc2u964ecv1s6 1ed9ed18ef31ad21bcabcfeff7777bae+162
-filter qr1hi-8i9sb-w5k40fztqgg9i2x d3bcc2ee0f0ea31049000c721c0f3a2a+56
-</code></pre>
-</notextile>
-
-This instantiates your pipeline and displays a live feed of its status. The new pipeline instance will also show up on Workbench *Activity* %(rarr)→% *Recent pipeline instances* page.
+* <i class="fa fa-fw fa-gear"></i> "Tutorial align using bwa mem (qr1hi-p5p6p-itzkwxblfermlwv)":https://{{ site.arvados_workbench_host }}/pipeline_templates/qr1hi-p5p6p-itzkwxblfermlwv
+* <i class="fa fa-fw fa-archive"></i> "Tutorial chromosome 19 reference (2463fa9efeb75e099685528b3b9071e0+438)":https://{{ site.arvados_workbench_host }}/collections/2463fa9efeb75e099685528b3b9071e0+438
+* <i class="fa fa-fw fa-archive"></i> "Tutorial sample exome (3229739b505d2b878b62aed09895a55a+142)":https://{{ site.arvados_workbench_host }}/collections/3229739b505d2b878b62aed09895a55a+142
-Arvados adds each pipeline component to the job queue as its dependencies are satisfied (or immediately if it has no dependencies) and finishes when all components are completed or failed and there is no more work left to do.
-
-The Keep locators of the output of each of @"do_hash"@ and @"filter"@ component are available from the output log shown above. The output is also available on the Workbench by navigating to *Activity* %(rarr)→% *Recent pipeline instances* %(rarr)→% pipeline UUID under the *Instance* column %(rarr)→% *output* column.
+Use @arv pipeline run@ to run the pipeline, supplying the inputs to the bwa-mem component on the command line:
<notextile>
-<pre><code>~$ <span class="userinput">arv keep get 1ed9ed18ef31ad21bcabcfeff7777bae+162/md5sum.txt</span>
-0f1d6bcf55c34bed7f92a805d2d89bbf 887cd41e9c613463eab2f0d885c6dd96+83/./alice.txt
-504938460ef369cd275e4ef58994cffe 887cd41e9c613463eab2f0d885c6dd96+83/./bob.txt
-8f3b36aff310e06f3c5b9e95678ff77a 887cd41e9c613463eab2f0d885c6dd96+83/./carol.txt
-~$ <span class="userinput">arv keep get d3bcc2ee0f0ea31049000c721c0f3a2a+56/0-filter.txt</span>
-0f1d6bcf55c34bed7f92a805d2d89bbf 887cd41e9c613463eab2f0d885c6dd96+83/./alice.txt
-</code></pre>
-</notextile>
-
-Indeed, the filter has picked out just the "alice" file as having a hash that starts with 0.
+<pre><code>~$ <span class="userinput">arv pipeline run --run-here --template qr1hi-p5p6p-itzkwxblfermlwv bwa-mem::reference_collection=2463fa9efeb75e099685528b3b9071e0+438 bwa-mem::sample=3229739b505d2b878b62aed09895a55a+142</span>
-h3. Running a pipeline with different parameters
+2014-07-25 18:05:26 +0000 -- pipeline_instance qr1hi-d1hrv-d14trje19pna7f2
+bwa-mem qr1hi-8i9sb-67n1qvsronmd2z6 queued 2014-07-25T18:05:25Z
-Notice that the pipeline template explicitly specifies the Keep locator for the input:
+2014-07-25 18:05:36 +0000 -- pipeline_instance qr1hi-d1hrv-d14trje19pna7f2
+bwa-mem qr1hi-8i9sb-67n1qvsronmd2z6 {:done=>0, :running=>1, :failed=>0, :todo=>0}
-<notextile>
-<pre><code>...
- "do_hash":{
- "script_parameters":{
- "input": "887cd41e9c613463eab2f0d885c6dd96+83"
- },
- }
-...
+2014-07-25 18:05:46 +0000 -- pipeline_instance qr1hi-d1hrv-d14trje19pna7f2
+bwa-mem qr1hi-8i9sb-67n1qvsronmd2z6 49bae1066f4ebce72e2587a3efa61c7d+88
</code></pre>
</notextile>
-You can specify values for pipeline component script_parameters like this:
-
-<notextile>
-<pre><code>~$ <span class="userinput">arv pipeline run --run-here --template qr1hi-p5p6p-xxxxxxxxxxxxxxx do_hash::input=c1bad4b39ca5a924e481008009d94e32+210</span>
-2013-12-17 20:31:24 +0000 -- pipeline_instance qr1hi-d1hrv-tlkq20687akys8e
-do_hash qr1hi-8i9sb-rffhuay4jryl2n2 queued 2013-12-17T20:31:24Z
-filter - -
-
-2013-12-17 20:31:34 +0000 -- pipeline_instance qr1hi-d1hrv-tlkq20687akys8e
-do_hash qr1hi-8i9sb-rffhuay4jryl2n2 {:done=>1, :running=>1, :failed=>0, :todo=>0}
-filter - -
-
-2013-12-17 20:31:55 +0000 -- pipeline_instance qr1hi-d1hrv-tlkq20687akys8e
-do_hash qr1hi-8i9sb-rffhuay4jryl2n2 50cafdb29cc21dd6eaec85ba9e0c6134+56
-filter qr1hi-8i9sb-j347g1sqovdh0op queued 2013-12-17T20:31:55Z
+This instantiates your pipeline and displays a live feed of its status. The new pipeline instance will also show up on Workbench dashboard.
-2013-12-17 20:32:05 +0000 -- pipeline_instance qr1hi-d1hrv-tlkq20687akys8e
-do_hash qr1hi-8i9sb-rffhuay4jryl2n2 50cafdb29cc21dd6eaec85ba9e0c6134+56
-filter qr1hi-8i9sb-j347g1sqovdh0op 490cd451c8108824b8a17e3723e1f236+19
-</code></pre>
-</notextile>
+Arvados adds each pipeline component to the job queue as its dependencies are satisfied (or immediately if it has no dependencies) and finishes when all components are completed or failed and there is no more work left to do.
-Now check the output:
+The Keep locators of the output of of the @bwa-mem@ components are available from the status feed shown above:
<notextile>
-<pre><code>~$ <span class="userinput">arv keep get 50cafdb29cc21dd6eaec85ba9e0c6134+56/md5sum.txt</span>
-44b8ae3fde7a8a88d2f7ebd237625b4f c1bad4b39ca5a924e481008009d94e32+210/./var-GS000016015-ASM.tsv.bz2
-~$ <span class="userinput">arv keep get 490cd451c8108824b8a17e3723e1f236+19/0-filter.txt</span>
+<pre><code>~$ <span class="userinput">arv keep ls -s 49bae1066f4ebce72e2587a3efa61c7d+88</span>
+ 29226 ./HWI-ST1027_129_D0THKACXX.1_1.sam
</code></pre>
</notextile>
-
-Since none of the files in the collection have hash code that start with 0, the output of the filter component is empty.
projects / arvados.git / blobdiff