Frequently asked questions - Amazon SageMaker
Snowflake FAQs
Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China (PDF).

Frequently asked questions

The following FAQs answer common general questions.

A: The SQL extension writes its log in the general log file of your JupyterLab application in Studio. You can find those logs at /var/log/apps/app_container.log.

A: Create a new cell and load the extension again using %load_ext amazon_sagemaker_sql_magic.

A: Use %%sm_sql? to get the help content of the command.

A: Ensure that your space uses a SageMaker distribution image version 1.6 or higher. These SageMaker images come pre-installed with the extension.

If you updated the image of your JupyterLab application space in Studio, refresh your browser.

A: Try refreshing the right panel using the Refresh button in the bottom right corner of the SQL extension UI in your notebook.

A: Try clearing the cached connections by running the following magic command %sm_sql_manage --clear-cached-connections.

A: The SQL extension only supports running one SQL query at a time.

Snowflake FAQs

The following FAQs answer common general questions for users of the SQL extension using Snowflake as their data source.

A: This can happen if the default warehouse for a user is not selected. Run the command USE WAREHOUSE warehouse_name for each session.

A: Ensure that your Snowflake user has access to the given object.