Use the AWS Glue browser to read sources stored as Glue database tables.
- Your Alteryx® deployment must be connected to a running instance of Glue. For more information, see Enable AWS Glue Access.
- The Glue browser appears when you select the Glue tab to create a dataset. See Import Data Page.
- For more information on interacting with Glue, see Using AWS Glue.
Figure: Glue Browser
Browse AWS Glue
NOTE: Last update timestamp information is not available through AWS Glue. That column always contains blank values.
Use the links and icons to browse for Glue databases and tables.
NOTE: Avoid using the Back button on your browser, which exits the Glue browser without applying changes to your configuration.
| Identifier | Type | Description |
|---|---|---|
| Database | Click these links to open a Glue database to reveal its tables. |
| Table | Click the Plus icon to select this Glue table as your source. To preview its data, hover over the name of the table, and then click the Eye icon. Tip: Sizes and update timestamps are calculated and displayed next to tables. They are not displayed next to databases. |
| View | Click the Plus icon to select this view as your source. To preview its data, hover over the view name and then click the Eye icon. NOTE: Previewing complex views may impact performance. |
| Page navigation | 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. |
| Breadcrumb | Click the links in the breadcrumb trail to navigate. |
Search List
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.
Create Dataset with SQL
As needed, you can pre-filter the selected table or view 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. See Create Dataset with SQL.
For more information, see Enable Custom SQL Query.
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