---
layout: default
navsection: userguide
-title: Best Practices for writing CWL
+title: Guidelines for Writing High-Performance Portable Workflows
...
{% comment %}
Copyright (C) The Arvados Authors. All rights reserved.
SPDX-License-Identifier: CC-BY-SA-3.0
{% endcomment %}
-* To run on Arvados, a workflow should provide a @DockerRequirement@ in the @hints@ section.
+h2(#performance). Performance
-* Build a reusable library of components. Share tool wrappers and subworkflows between projects. Make use of and contribute to "community maintained workflows and tools":https://github.com/common-workflow-language/workflows and tool registries such as "Dockstore":http://dockstore.org .
+To get the best perfomance from your workflows, be aware of the following Arvados features, behaviors, and best practices.
-* When combining a parameter value with a string, such as adding a filename extension, write @$(inputs.file.basename).ext@ instead of @$(inputs.file.basename + 'ext')@. The first form is evaluated as a simple text substitution, the second form (using the @+@ operator) is evaluated as an arbitrary Javascript expression and requires that you declare @InlineJavascriptRequirement@.
+Does your application support NVIDIA GPU acceleration? Use "cwltool:CUDARequirement":cwl-extensions.html#CUDARequirement to request nodes with GPUs.
-* Avoid declaring @InlineJavascriptRequirement@ or @ShellCommandRequirement@ unless you specifically need them. Don't include them "just in case" because they change the default behavior and may imply extra overhead.
+If you have a sequence of short-running steps (less than 1-2 minutes each), use the Arvados extension "arv:RunInSingleContainer":cwl-extensions.html#RunInSingleContainer to avoid scheduling and data transfer overhead by running all the steps together in the same container on the same node. To use this feature, @cwltool@ must be installed in the container image. Example:
-* Don't write CWL scripts that access the Arvados SDK. This is non-portable; a script that access Arvados directly won't work with @cwltool@ or crunch v2.
-
-* CommandLineTools wrapping custom scripts should represent the script as an input parameter with the script file as a default value. Use @secondaryFiles@ for scripts that consist of multiple files. For example:
-
-<pre>
+{% codeblock as yaml %}
+class: Workflow
cwlVersion: v1.0
-class: CommandLineTool
-baseCommand: python
+$namespaces:
+ arv: "http://arvados.org/cwl#"
inputs:
- script:
- type: File
- inputBinding: {position: 1}
- default:
- class: File
- location: bclfastq.py
- secondaryFiles:
- - class: File
- location: helper1.py
- - class: File
- location: helper2.py
- inputfile:
- type: File
- inputBinding: {position: 2}
-outputs:
- out:
- type: File
- outputBinding:
- glob: "*.fastq"
-</pre>
+ file: File
+outputs: []
+requirements:
+ SubworkflowFeatureRequirement: {}
+steps:
+ subworkflow-with-short-steps:
+ in:
+ file: file
+ out: [out]
+ # This hint indicates that the subworkflow should be bundled and
+ # run in a single container, instead of the normal behavior, which
+ # is to run each step in a separate container. This greatly
+ # reduces overhead if you have a series of short jobs, without
+ # requiring any changes the CWL definition of the sub workflow.
+ hints:
+ - class: arv:RunInSingleContainer
+ run: subworkflow-with-short-steps.cwl
+{% endcodeblock %}
-* You can get the designated temporary directory using @$(runtime.tmpdir)@ in your CWL file, or from the @$TMPDIR@ environment variable in your script.
+Avoid declaring @InlineJavascriptRequirement@ or @ShellCommandRequirement@ unless you specifically need them. Don't include them "just in case" because they change the default behavior and may add extra overhead.
-* Similarly, you can get the designated output directory using $(runtime.outdir), or from the @HOME@ environment variable in your script.
+When combining a parameter value with a string, such as adding a filename extension, write @$(inputs.file.basename).ext@ instead of @$(inputs.file.basename + 'ext')@. The first form is evaluated as a simple text substitution, the second form (using the @+@ operator) is evaluated as an arbitrary Javascript expression and requires that you declare @InlineJavascriptRequirement@.
-* Use @ExpressionTool@ to efficiently rearrange input files between steps of a Workflow. For example, the following expression accepts a directory containing files paired by @_R1_@ and @_R2_@ and produces an array of Directories containing each pair.
+Use @ExpressionTool@ to efficiently rearrange input files between steps of a Workflow. For example, the following expression accepts a directory containing files paired by @_R1_@ and @_R2_@ and produces an array of Directories containing each pair.
-<pre>
+{% codeblock as yaml %}
class: ExpressionTool
cwlVersion: v1.0
inputs:
}
return {"out": dirs};
}
-</pre>
+{% endcodeblock %}
-* Avoid specifying resource requirements in CommandLineTool. Prefer to specify them in the workflow. You can provide a default resource requirement in the top level @hints@ section, and individual steps can override it with their own resource requirement.
+Available compute nodes types vary over time and across different cloud providers, so try to limit the RAM requirement to what the program actually needs. However, if you need to target a specific compute node type, see this discussion on "calculating RAM request and choosing instance type for containers.":{{site.baseurl}}/api/execution.html#RAM
-<pre>
-cwlVersion: v1.0
-class: Workflow
-inputs:
- inp: File
-hints:
- ResourceRequirement:
- ramMin: 1000
- coresMin: 1
- tmpdirMin: 45000
-steps:
- step1:
- in: {inp: inp}
- out: [out]
- run: tool1.cwl
- step2:
- in: {inp: step1/inp}
- out: [out]
- run: tool2.cwl
- hints:
- ResourceRequirement:
- ramMin: 2000
- coresMin: 2
- tmpdirMin: 90000
-</pre>
-
-* Available compute nodes types vary over time and across different cloud providers, so try to limit the RAM requirement to what the program actually needs. However, if you need to target a specific compute node type, see this discussion on "calculating RAM request and choosing instance type for containers.":{{site.baseurl}}/api/execution.html#RAM
-
-* Instead of scattering separate steps, prefer to scatter over a subworkflow.
+Instead of scattering separate steps, prefer to scatter over a subworkflow.
With the following pattern, @step1@ has to wait for all samples to complete before @step2@ can start computing on any samples. This means a single long-running sample can prevent the rest of the workflow from moving on:
-<pre>
+{% codeblock as yaml %}
cwlVersion: v1.0
class: Workflow
inputs:
scatter: inp
out: [out]
run: tool3.cwl
-</pre>
+{% endcodeblock %}
Instead, scatter over a subworkflow. In this pattern, a sample can proceed to @step2@ as soon as @step1@ is done, independently of any other samples.
Example: (note, the subworkflow can also be put in a separate file)
-<pre>
+{% codeblock as yaml %}
cwlVersion: v1.0
class: Workflow
steps:
in: {inp: step2/inp}
out: [out]
run: tool3.cwl
-</pre>
+{% endcodeblock %}
+
-h2(#migrate). Migrating running CWL on jobs API to containers API
+h2. Portability
-* When migrating from jobs API (--api=jobs) (sometimes referred to as "crunch v1") to the containers API (--api=containers) ("crunch v2") there are a few differences in behavior:
-** The tool is limited to accessing only collections which are explicitly listed in the input, and further limited to only the subdirectories of collections listed in input. For example, given an explicit file input @/dir/subdir/file1.txt@, a tool will not be able to implicitly access the file @/dir/file2.txt@. Use @secondaryFiles@ or a @Directory@ input to describe trees of files.
-** Files listed in @InitialWorkDirRequirement@ appear in the output directory as normal files (not symlinks) but cannot be moved, renamed or deleted. These files will be added to the output collection but without any additional copies of the underlying data.
-** Tools are disallowed network access by default. Tools which require network access must include @arv:APIRequirement: {}@ in their @requirements@ section.
+To write workflows that are easy to modify and portable across CWL runners (in the event you need to share your workflow with others), there are several best practices to follow:
+
+Workflows should always provide @DockerRequirement@ in the @hints@ or @requirements@ section.
+
+Build a reusable library of components. Share tool wrappers and subworkflows between projects. Make use of and contribute to "community maintained workflows and tools":https://github.com/common-workflow-library and tool registries such as "Dockstore":http://dockstore.org .
+
+CommandLineTools wrapping custom scripts should represent the script as an input parameter with the script file as a default value. Use @secondaryFiles@ for scripts that consist of multiple files. For example:
+
+{% codeblock as yaml %}
+cwlVersion: v1.0
+class: CommandLineTool
+baseCommand: python
+inputs:
+ script:
+ type: File
+ inputBinding: {position: 1}
+ default:
+ class: File
+ location: bclfastq.py
+ secondaryFiles:
+ - class: File
+ location: helper1.py
+ - class: File
+ location: helper2.py
+ inputfile:
+ type: File
+ inputBinding: {position: 2}
+outputs:
+ out:
+ type: File
+ outputBinding:
+ glob: "*.fastq"
+{% endcodeblock %}
+
+You can get the designated temporary directory using @$(runtime.tmpdir)@ in your CWL file, or from the @$TMPDIR@ environment variable in your script.
+
+Similarly, you can get the designated output directory using $(runtime.outdir), or from the @HOME@ environment variable in your script.
+
+Avoid specifying resource requirements in CommandLineTool. Prefer to specify them in the workflow. You can provide a default resource requirement in the top level @hints@ section, and individual steps can override it with their own resource requirement.
+
+{% codeblock as yaml %}
+cwlVersion: v1.0
+class: Workflow
+inputs:
+ inp: File
+hints:
+ ResourceRequirement:
+ ramMin: 1000
+ coresMin: 1
+ tmpdirMin: 45000
+steps:
+ step1:
+ in: {inp: inp}
+ out: [out]
+ run: tool1.cwl
+ step2:
+ in: {inp: step1/inp}
+ out: [out]
+ run: tool2.cwl
+ hints:
+ ResourceRequirement:
+ ramMin: 2000
+ coresMin: 2
+ tmpdirMin: 90000
+{% endcodeblock %}
projects / arvados.git / blobdiff