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The Databricks extension for VSCode allows you to develop for the Databricks Lakehouse platform from VSCode.
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The extension is available from the [Visual Studio Marketplace](https://marketplace.visualstudio.com/itemdetails?itemName=databricks.databricks-vscode).
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This is an open source project because we want you to be involved. We love issues, feature requests, code reviews, pull
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requests or any positive contribution. See [CONTRIBUTING.md](CONTRIBUTING.md).
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This is an open source project because we want you to be involved. We love issues, feature requests, code reviews, pull requests or any positive contribution. See [CONTRIBUTING.md](CONTRIBUTING.md).
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## Features
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<mark>TODO</mark>
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- Synchronize code to a Databricks workspace
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- Run Python files on a Databricks cluster
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- Run notebooks and Python files as Workflows
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Describe specific features of your extension including screenshots of your extension in action. Image paths are relative to this README file.
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For example if there is an image subfolder under your extension project workspace:
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\!\[feature X\]\(images/feature-x.png\)
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> Tip: Many popular extensions utilize animations. This is an excellent way to show off your extension! We recommend short, focused animations that are easy to follow.
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## Requirements
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<mark>TODO</mark>
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If you have any requirements or dependencies, add a section describing those and how to install and configure them.
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## Extension Settings
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<mark>TODO</mark>
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Include if your extension adds any VS Code settings through the `contributes.configuration` extension point.
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In order to use this extension you need acceess to a Databricks workspace:
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For example:
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1. Databricks workspace with:
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1.`Repos` enabled
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2.`Files in Repos` enabled
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2. Permission to access the workspace using a personal access token (PAT)
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3. Access to an interactive cluster or permissions to create a cluster
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4. Permissions to create Databricks repos
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This extension contributes the following settings:
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## Documentation
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-`myExtension.enable`: enable/disable this extension
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-`myExtension.thing`: set to `blah` to do something
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## Known Issues
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<mark>TODO</mark>
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Calling out known issues can help limit users opening duplicate issues against your extension.
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- The [Quick Start Guide](README.quickstart.md) provides an overview
1. Open the Databricks panel by clicking on the Databricks icon on the left
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2. Click the "Configure Databricks" button
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## Running Code
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## <aid="running-code"></a>Running Code
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Once you have your project configured you can sync your local code to the repo and run it on a cluster. You can use the https://github.com/databricks/ide-best-practices repository as an example.
3. Click the "Run" icon in the tab bar and select "Run File on Databricks"
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This will start the code synchronization and run the active python file on the configured cluster. The result is printed in the "debug" output panel.
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### Running PySpark and notebooks as a Workflow
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### <aid="running-code-as-workflows"></a>Running PySpark and notebooks as a Workflow
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1. Create a python file or a python based notebook
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1. You can create a python based notebook by exporting a notebook from the Databricks web application or use a notebook that is already tracked in git, such as https://github.com/databricks/notebook-best-practices
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2. Click the "Run" icon in the tab bar and select "Run File as Workflow on Databricks"
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This will run the file using the Jobs API on the configured cluster and render the result in a WebView.
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### Advanced: Running using custom run configurations
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### <aid="run-configurations"></a>Advanced: Running using custom run configurations
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Both ways of running code on a cluster are also available in custom run configurations. In the "Run and Debug" panel you can click "Add configuration..." and select either "Databricks: Launch" or "Databricks: Launch as Workflow". Using run configuration you can also pass in command line arguments and run your code by simply pressing `F5`.
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## <aid="settings"></a>Extension Settings
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This extension contributes the following settings:
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-`databricks.logs.maxFieldLength`: The maximum length of each field displayed in logs outputs panel
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-`databricks.logs.truncationDepth`: The max depth of logs to show without truncation
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-`databricks.logs.maxArrayLength`: The maximum number of items to show for array fields
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-`databricks.logs.enabled`: Enable/disable logging. Reload window for changes to take effect
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## <aid="commands"></a>`Databricks:` Commands
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The Databricks extension provides commands (prefixed with `Databricks:`) to the VS Code _command
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palette_, available by selecting _View > Command Palette_ or by typing
|`Databricks: Configure sync destination`| Configure target directory for synchronizing code to the configured Databricks workspace |
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|`Databricks: Detach sync destination`| Detach the configured sync destination |
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|`Databricks: Start synchronization`| Start synchronizing local code to the Databricks workspace. This command performs an incremental sync. |
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|`Databricks: Start synchronization (full sync)`| Start synchronizing local code to the Databricks workspace. This command performs full sync even if an incremental sync is possible. |
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