Get started with the query editor in Amazon SageMaker Unified Studio

1. Navigate to Amazon SageMaker Unified Studio using the URL from your admin and log in using your SSO or AWS credentials.

   For more information, see Access Amazon SageMaker Unified Studio.

2. Create a project with a SQL analytics project profile. This project profile sets up your project with access to Amazon Redshift Serverless and Amazon Athena resources. For more information, see Create a new project.

After you create a project, you can use the query editor to write and run queries.

1. Navigate to the project you created in the top center menu of the Amazon SageMaker Unified Studio home page.

2. Expand the Build menu in the top navigation bar, then choose Query editor.

3. Create a new querybook tab. A querybook is a kind of SQL notebook where you can draw from multiple engines to design and visualize data analytics solutions.

4. Select a data source for your queries by using the menu in the upper-right corner of the querybook.

   1. Under Connections, choose Athena (Lakehouse) to connect to your Lakehouse resources.

   2. Under Catalogs, choose AwsDataCatalog.

   3. Under Databases, choose the name of the AWS Glue database. This database was created for use when the project was created.

5. Choose Choose to connect to the database and query engine.

6. Copy the following SQL query into the querybook cell to create a table in the database.

   
   CREATE TABLE mkt_sls_table AS
   SELECT 146776932 AS ord_num, 23 AS sales_qty_sld, 23.4 AS wholesale_cost, 45.0 as lst_pr, 43.0 as sell_pr, 2.0 as disnt, 12 as ship_mode,13 as warehouse_id, 23 as item_id, 34 as ctlg_page, 232 as ship_cust_id, 4556 as bill_cust_id
   UNION ALL SELECT 46776931, 24, 24.4, 46, 44, 1, 14, 15, 24, 35, 222, 4551
   UNION ALL SELECT 46777394, 42, 43.4, 60, 50, 10, 30, 20, 27, 43, 241, 4565
   UNION ALL SELECT 46777831, 33, 40.4, 51, 46, 15, 16, 26, 33, 40, 234, 4563
   UNION ALL SELECT 46779160, 29, 26.4, 50, 61, 8, 31, 15, 36, 40, 242, 4562
   UNION ALL SELECT 46778595, 43, 28.4, 49, 47, 7, 28, 22, 27, 43, 224, 4555
   UNION ALL SELECT 46779482, 34, 33.4, 64, 44, 10, 17, 27, 43, 52, 222, 4556
   UNION ALL SELECT 46779650, 39, 37.4, 51, 62, 13, 31, 25, 31, 52, 224, 4551
   UNION ALL SELECT 46780524, 33, 40.4, 60, 53, 18, 32, 31, 31, 39, 232, 4563
   UNION ALL SELECT 46780634, 39, 35.4, 46, 44, 16, 33, 19, 31, 52, 242, 4557
   UNION ALL SELECT 46781887, 24, 30.4, 54, 62, 13, 18, 29, 24, 52, 223, 4561
       

7. Choose the Run cell icon.

   When the query finishes running, a Result tab appears below the cell to display the outcome.

8. Refresh the Data explorer navigation pane, and view the table you created in the Lakehouse section.

9. Choose Add SQL to add another cell to the querybook. Then enter the following script:

   
   select * from mkt_sls_table limit 10
       

10. Choose the Run cell icon.

    In the Results tab, the first ten rows of the table you created are displayed.

11. Choose Add SQL to add another cell to the querybook. Then enter the following script:

    
    select item_id, sales_qty_sld 
    from mkt_sls_table 
    where sales_qty_sld > 30
        

12. Choose the Run cell icon.

    In the Results tab, only data that fulfills the specified requirements is displayed.

13. In the Results tab, choose the Chart view icon.

    This opens up a chart view with a line graph as a default.

14. Set up the chart to display a pie chart.

    1. For Type, choose Pie.

    2. For Values, choose sales_qty_sold.

    3. For Labels, choose item_id.

    This displays a pie chart so you can visualize results.