AWS sagemaker-unified-studio documentation change
Summary
Removed 'Configuring Spark compute' section and reorganized content
Security assessment
Content reorganization without any security-related changes or mentions.
Diff
diff --git a/sagemaker-unified-studio/latest/userguide/managing-configurations.md b/sagemaker-unified-studio/latest/userguide/managing-configurations.md index 0b63b5565..86fe26ea3 100644 --- a//sagemaker-unified-studio/latest/userguide/managing-configurations.md +++ b//sagemaker-unified-studio/latest/userguide/managing-configurations.md @@ -5,2 +4,0 @@ -Configuring Spark compute - @@ -24,8 +21,0 @@ You can edit your JupyterLab configurations on the JupyterLab page by choosing C -## Configuring Spark compute - -Amazon SageMaker Unified Studio provides a set of Jupyter magic commands. Magic commands, or magics, enhance the functionality of the IPython environment. For more information about the magics that Amazon SageMaker Unified Studio provides, run `%help` in a notebook. - -Compute-specific configurations can be set by using the `%%configure` Jupyter magic. The `%%configure` magic takes a JSON-formatted dictionary. To use %%configure magic, specify the compute name in the argument `-n`. Including `-f` will restart the session to forcefully apply the new configuration. Otherwise, this configuration will apply when the next session starts. - -For example: `%%configure -n `compute_name` -f`. - @@ -40 +30 @@ JupyterLab -Accessing metadata +Configuring Spark compute