steve/databricks-cli
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databricks-cli
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databricks-cli/acceptance/bundle/templates/default-sql/output/my_default_sql
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Denis Bilenko 2175dd24a4
Do not gitignore .databricks and terraform (#2318) 
For acceptance/bundle/templates I'd like to run "bundle deploy". This
would create .databricks directory inside materialized output. It might
makes sense to commit some of this as part of golden files output. Even
if we did not commit anything, the test runner will see those files and
show the difference. Thus git should also see them.

Also rename .gitignore to out.gitignore in those tests, since that
includes .databricks as well.
 		2025-02-10 11:42:39 +01:00
..
.vscode Include a materialized copy of built-in templates (#2146) 2025-01-17 15:03:59 +00:00
resources acc: Use [VARNAME] instead of $VARNAME (#2282) 2025-02-03 14:10:19 +00:00
scratch Switch to using `[` from `<` in text replacements (#2224) 2025-01-28 10:54:23 +00:00
src Include a materialized copy of built-in templates (#2146) 2025-01-17 15:03:59 +00:00
README.md Include a materialized copy of built-in templates (#2146) 2025-01-17 15:03:59 +00:00
databricks.yml acc: Use [VARNAME] instead of $VARNAME (#2282) 2025-02-03 14:10:19 +00:00
out.gitignore Do not gitignore .databricks and terraform (#2318) 2025-02-10 11:42:39 +01:00

README.md

my_default_sql

The 'my_default_sql' 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] my_default_sql_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.