Your Trifacta® deployment must be installed on Azure or AWS and connected to an instance of Databricks Tables.
NOTE: Each user must have a Databricks Personal Access Token installed in their account. For more information, see Databricks Settings Page.
- The Databricks Tables browser appears when you select the Databricks Tables tab to import a dataset. See Import Data Page.
- When specifying a job, you can choose to write a publishing action to Databricks Tables. See Run Job Page.
- For more information on interacting with Databricks Tables, see Using Databricks Tables.
Browse Databricks Tables
Use the links and icons to browse for Databricks databases and tables.
NOTE: Row information is not available for Databricks tables.
NOTE: Databricks does not publish the last modified date for its resources. This information is not available to the Trifacta platform.
NOTE: Avoid using the Back button on your browser, which exits the browser without applying changes to your configuration.
Click these links to open a Databricks database to reveal its tables.
Click the Plus icon to select this Databricks table as your source.
Click the Plus icon to select this view as your source.
Use these links to navigate between pages of databases and tables.
NOTE: In some cases, subsequent pages of tables may be blank, and counts of tables may not match displayed figures. This is a known issue.
Click the links in the breadcrumb trail to navigate.
To filter the list of databases or tables, enter a string in the Search box. The filter is applied as you type and matches anywhere in the name of a currently displayed database or table name.
Preview Table Data
Database tables are displayed by name only. To preview the data in the table, click the Eye icon next to the name of the table.
Tip: Table previews include available metadata information, such as column headers and column and row counts.
NOTE: Previewing complex views may impact performance.
NOTE: Timestamp information is not available from Databricks.
Create Dataset with SQL
As needed, you can pre-filter the selected table inside the database. By entering a custom SQL statement, you can remove unnecessary data from the dataset that is extracted from the database, which enables faster and more meaningful imports of your database data.
NOTE: Multi-statement custom SQL is not supported for Databricks Tables. Custom SQL queries must be a single
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