Update a Pipeline¶
While working with your data, you often need to modify an existing pipeline with new transformation code or pipeline parameters. For example, when you develop a machine learning model, you might need to try different versions of your model while your training data stays relatively constant. To make changes to a pipeline, you need to use the
pachctl update pipeline command.
Update Your Pipeline Specification¶
If you need to update your pipeline specification, such as change the parallelism settings, add an input repository, or other, you need to update your JSON file and then run the
pachctl update pipelinecommand. By default, when you update your code, the new pipeline specification does not reprocess the data that has already been processed. Instead, it processes only the new data that you submit to the input repo. If you want to run the changes in your pipeline against the data in the
HEAD commit of your input repo, use the
--reprocess flag. After that, the updated pipeline continues to process new input data. Previous results remain accessible through the corresponding commit IDs.
To update a pipeline specification, complete the following steps:
Make the changes in your pipeline specification JSON file.
Update the pipeline with the new configuration:
pachctl update pipeline -f pipeline.json
update pipeline with the
-f flag can also take a URL if your JSON manifest is hosted on GitHub or other remote location.
Update the Code in a Pipeline¶
pachctl update pipeline updates the code that you use in one or more of your pipelines. To apply your code changes, you need to build a new Docker image and push it to your Docker image registry.
You can either use your registry instructions to build and push your new image or push the new image by using the flags built into the
pachctl update pipeline command. Both procedures achieve the same goal, and it is entirely a matter of a personal preference which one of them to follow. If you do not have a build-push process that you already follow, you might prefer to use Pachyderm's built-in functionality.
To create a new image by using the Pachyderm commands, you need to use the
--build flag with the
pachctl update pipeline command. By default, if you do not specify a registry with the
--registry flag, Pachyderm uses DockerHub. When you build your image with Pachyderm, it assigns a random tag to your new image.
If you use a private registry or any other registry that is different from the default value, use the
--registry flag to specify it. Make sure that you specify the private registry in the pipeline specification.
For example, if you want to push a
pachyderm/opencv image to a registry located at
localhost:5000, you need to add this in your pipeline spec:
Also, to be able to build and push images, you need to make sure that the Docker daemon is running. Depending on your operating system and the Docker distribution that you use, steps for enabling it might vary.
To update the code in your pipeline, complete the following steps:
- Make the code changes.
Verify that the Docker daemon is running:
If you get an error message similar to the following:
Cannot connect to the Docker daemon at unix:///var/run/docker.sock. Is the docker daemon running?
enable the Docker daemon. To enable the Docker daemon, see the Docker documentation for your operating system and platform. For example, if you use
minikubeon macOS, run the following command:
eval $(minikube docker-env)
Build, tag, and push the new image to your image registry:
If you prefer to use Pachyderm commands:
Run the following command:
pachctl update pipeline -f <pipeline name> --build --registry <registry> --username <registry user>
If you use DockerHub, omit the
pachctl update pipeline -f edges.json --build --username testuser
When prompted, type your image registry password:
Password for docker.io/testuser: Building pachyderm/opencv:f1e0239fce5441c483b09de425f06b40, this may take a while.
If you prefer to use instructions for your image registry:
Build, tag, and push a new image as described in the image registry documentation. For example, if you use DockerHub, see Docker Documentation.
Update the pipeline:
pachctl update pipeline -f <pipeline.json>