mirror of https://github.com/databricks/cli.git
072fa812e2
## Changes This updates the templates to include a `permissions` section. Having a permissions section is a best practice, is helpful to understand the notion of permissions, and helps diagnose permission errors (https://github.com/databricks/cli/pull/1386). This is a cherry-pick from https://github.com/databricks/cli/pull/1387. This change was verified to work both in dev and prod. Existing unit tests validate the validity of the templates in these modes. |
||
---|---|---|
.. | ||
.vscode | ||
resources | ||
scratch | ||
src | ||
README.md.tmpl | ||
databricks.yml.tmpl |
README.md.tmpl
# {{.project_name}} The '{{.project_name}}' project was generated by using the default-sql template. ## Getting started 1. Install the Databricks CLI from https://docs.databricks.com/dev-tools/cli/install.html 2. Authenticate to your Databricks workspace (if you have not done so already): ``` $ databricks configure ``` 3. To deploy a development copy of this project, type: ``` $ databricks bundle deploy --target dev ``` (Note that "dev" is the default target, so the `--target` parameter is optional here.) This deploys everything that's defined for this project. For example, the default template would deploy a job called `[dev yourname] {{.project_name}}_job` to your workspace. You can find that job by opening your workpace and clicking on **Workflows**. 4. Similarly, to deploy a production copy, type: ``` $ databricks bundle deploy --target prod ``` 5. To run a job, use the "run" command: ``` $ databricks bundle run ``` 6. Optionally, install developer tools such as the Databricks extension for Visual Studio Code from https://docs.databricks.com/dev-tools/vscode-ext.html. 7. For documentation on the Databricks Asset Bundles format used for this project, and for CI/CD configuration, see https://docs.databricks.com/dev-tools/bundles/index.html.