You can confirm that the notebook is shared by choosing Shared to my team and checking that the notebook is listed.Right-click on the notebook you want to share and choose Share with my team.Choose Notebooks in the left pane and navigate to My notebooks.If you haven’t used the query editor v2 before, please configure your account to use query editor v2. After you configure these permissions, navigate to the Amazon Redshift console and choose Query editor v2 in the navigation pane.Set the value of this tag to the principal (user, group, or role) you’re granting access to.Add a principal tag to the role with the tag name sqlworkbench-team.Create an IAM role with the managed policy AmazonRedshiftQueryEditorV2FullAccess attached to the role.To share the notebooks, complete the following steps: The output of the ML function is captured in the field predicted_qty_sold, which is the predicted ticket sold quantity. The following is the output received by applying the ML function predict_ticket_sold on the original dataset. Enter and run the following command to see the available datashares for the cluster:Įventname, saletime, day, week, month, qtr, year, holiday ) AS predicted_qty_sold,.Enter Show available data share in the cell.Choose the plus sign and choose Notebook.For the remaining part of this tutorial, we run queries in the notebook and create comments in the markdown cell for each step. Connect to your Amazon Redshift cluster in the navigation pane.Īmazon Redshift provides a feature to create notebooks and run your queries the notebook feature is currently in preview and available in all Regions.In the navigation pane, choose Query editor v2.On the Subscriptions tab, confirm that the AWS Data Exchange datashare is available.On the Amazon Redshift console, choose Datashares in the navigation pane.To set up prediction using Redshift ML, complete the following steps: Confirm the catalog is subscribed by checking that it’s listed on the Subscriptions page.Choose Worldwide Event Attendance (Test Product).
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