Amazon Redshift will no longer support the creation of new Python UDFs starting Patch 198. Existing Python UDFs will continue to function until June 30, 2026. For more information, see the [ blog post ](https://amazonaws-china.com/blogs/big-data/amazon-redshift-python-user-defined-functions-will-reach-end-of-support-after-june-30-2026/). 

# Viewing the results of a scheduled query with Amazon CloudShell
<a name="query-editor-v2-schedule-query-troubleshooting-cloudshell"></a>

You can use Amazon CloudShell to find out details about a schedule query. You must have the proper permissions to run the Amazon CLI commands shown in the following procedure.

**To view the results of a scheduled query**

1. On the Amazon console, open the Amazon CloudShell command prompt. For more information about Amazon CloudShell, see [What is Amazon CloudShell](https://docs.amazonaws.cn/cloudshell/latest/userguide/welcome.html) in the *Amazon CloudShell User Guide*.

1. Assume the IAM role of the scheduled query. To assume the role, find the IAM role associated with the scheduled query in query editor v2 and use it in the Amazon CLI command in Amazon CloudShell. For example, for the role `scheduler` enter an Amazon STS command to assume the role used by the scheduled query.

   ```
   aws sts assume-role --role-arn "arn:aws:iam::{{123456789012}}:role/scheduler" --role-session-name "scheduler-test" 
   ```

   The credentials returned are similar to the following.

   ```
   "Credentials": {
   "AccessKeyId": "AKIAIOSFODNN7EXAMPLE",
   "SecretAccessKey": "wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY",
   "SessionToken": "je7MtGbClwBF/2Zp9Utk/h3yCo8nvbEXAMPLEKEY...",        
   "Expiration": "2023-08-18T18:19:44+00:00"
   },
   "AssumedRoleUser": {
   "AssumedRoleId": "AROA35B2NH6WBTP7ONL4E:scheduler-test",
   "Arn": "arn:aws:sts::{{123456789012}}:assumed-role/scheduler/scheduler-test"
   }
   }
   ```

1. Create environmental variables in the Amazon CLI using the credentials displayed from assuming the IAM role. You must use these tokens before their expiration time. For example, you enter the following in Amazon CloudShell.

   ```
   export AWS_ACCESS_KEY_ID=AKIAIOSFODNN7EXAMPLE
   export AWS_SECRET_ACCESS_KEY=wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
   export AWS_SESSION_TOKEN=je7MtGbClwBF/2Zp9Utk/h3yCo8nvbEXAMPLEKEY...
   ```

1. To view the error of a failed query, run the Amazon CLI command to describe a statement. The id of the SQL statement is from the **ID** shown in the **Schedule history** section of a scheduled query in the query editor v2.

   ```
   aws redshift-data describe-statement --id {{130d2620-05d2-439c-b7cf-815d9767f513}}
   ```

   In this example, the scheduled SQL `select * from users limit 100` results in a SQL error that the `users` table does not exist.

   ```
   {
   "CreatedAt": "2023-08-18T17:39:15.563000+00:00",
   "Duration": -1,
   "Error": "ERROR: relation \"users\" does not exist",
   "HasResultSet": false,
   "Id": "a1b2c3d4-5678-90ab-cdef-EXAMPLE11111",
   "QueryString": "select * from users limit 100\n—RequestID=a1b2c3d4-5678-90ab-cdef-EXAMPLE22222; TraceID=1-633c5642-4039308d03f3a0ba53dbdf6f",
   "RedshiftPid": 1073766651,
   "RedshiftQueryId": 0,
   "ResultRows": -1,
   "ResultSize": -1,
   "Status": "FAILED",
   "UpdatedAt": "2023-08-18T17:39:16.116000+00:00",
   "WorkgroupName": "default"
   }
   ```