Use the Redshift browser to read sources stored as Redshift database tables and views, identify new or existing tables to which to write results, or select or create tables to which to publish job results.
- Your Alteryx deployment must be connected to a running instance of Redshift.
- The Redshift browser appears when:
- You select the Redshift connection to create a dataset. See Import Data Page.
- You choose to add a publishing location in Redshift. See Run Job Page.
When exporting results, you can choose to write to a Redshift database. See Export Results Window.
- For more information on interacting with Redshift, see Using Redshift.
Use the links and icons to browse for Redshift databases, schemas, and tables. When you select a Redshift database, you can select one of the available schema objects. Selecting a schema displays the tables and views that use that schema.
NOTE: Avoid using the Back button on your browser, which exits the Redshift browser without applying changes to your configuration.
|Schema||Click a schema link to display the tables and views that use the schema.|
Click the Plus icon to select this Redshift 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.
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.
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.
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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