How do I troubleshoot issues with Amazon Quick analyses and dashboards?

Resolution

Note: If you receive errors when you run AWS Command Line Interface (AWS CLI) commands, see Troubleshooting errors for the AWS CLI. Also, make sure that you're using the most recent AWS CLI version.

Troubleshoot inactive chart interactions

ML-powered forecasting isn't compatible with small multiples. If your incomplete forecast blocks the interactions on the visual, then you receive the following error message:

"Remove forecast to add small multiples"

To resolve this error, remove the incomplete forecast configurations on the visual. Complete the following steps:

1. Open the Amazon Quick console.
2. In the navigation pane, choose Dashboards.
3. Select the visual.
4. Choose Menu options.
5. Choose Remove forecast.

To check the fields that a custom action uses, complete the following steps:

1. Open the Amazon Quick console.
2. Select the visual.
3. In the navigation bar menu, choose Actions.
4. Open the action, and then note the fields and parameters that it references.
5. To open the Field wells, choose Edit visual.
6. Confirm that each referenced field is present.

Every field and parameter that a custom action references must be active in the parent visual. If a field or parameter is missing, then custom actions silently stops responding.

To resolve this issue, drag the missing field from the Fields list into the correct field well. Confirm that the parameters referenced by the actions exist in the analysis. If a parameter doesn't exist, then recreate the parameter with the same name and data type.

To recreate the parameter, complete the following steps:

1. Open the Amazon Quick console.
2. In the navigation pane, choose Analyses.
3. Open the analysis.
4. Choose Parameters.
5. Choose the add icon.
6. Enter the same Name and Data type as the original parameter.
7. (Optional) Set a default value.
8. Choose Create.
9. Reopen the custom action and re-point it to the recreated parameter.

If you still experience chart interaction unresponsiveness, then duplicate the analysis and reconfigure the custom actions on the new copy.

Complete the following steps:

1. Open the Amazon Quick console.
2. In the navigation pane, choose Analyses.
3. Open the analysis.
4. Choose File.
5. Choose Save as, and then enter a name for the new copy.
6. Choose Save.
7. In the new copy, select the visual.
8. Choose Menu options.
9. Choose Actions.
10. Recreate or re-point each custom action to the correct fields and parameters.

Resolve dataset changes errors

If you modified internal column IDs on a dataset, then you might see missing field errors or get the following error message:

"The dataset changed too much for QuickSight to automatically update your analysis"

To resolve this issue, identify the visuals or filters in the panel that show error or warning icons.

Then, to remove invalid filters that reference columns that don't exist, complete the following steps:

1. Open Amazon Quick console.
2. In the navigation pane, choose Data.
3. Select the dataset.
4. Open the Filters pane.
5. Delete filters that have an error icon.
6. Use the current dataset columns to recreate the filters.

If you re-added a table or modified columns, then you might receive the "Dataset changed too much" error message. It's a best practice to modify columns and use Dataset preview to verify your changes.

To resolve this error, replace your dataset. Complete the following steps:

1. Open the Amazon Quick console.
2. In the navigation pane, choose Analyses.
3. In the analysis, open the Data pane.
4. Choose Menu options, then choose Replace.
5. Select the corrected dataset.
6. Choose Select.

Resolve inconsistent data shown in analysis or published dashboard

If Row-Level Security (RLS) restricts the viewer's data, or the SPICE dataset hasn't been refreshed, then the latest published dashboard might show missing or different data.

To reset the dashboard filter controls, open the published dashboard, and then choose the reset icon on the filter control.

If only specific users are affected, then check the RLS rules. Complete the following steps:

1. Open the Amazon Quick console.
2. In the navigation pane, choose Data.
3. Select the dataset.
4. Choose the Permissions tab.
5. Review the RLS permission dataset for the affected user.
   Note: To test the viewer experience, use a Reader account.

If the RLS permission rule is incorrect, then complete the following steps:

1. Open the Amazon Quick console.
2. In the navigation pane, choose Data.
3. In the RLS rules dataset, correct the row for the affected user or group.
4. Refresh or re-import the RLS rules dataset.
5. Reopen the dataset, and then confirm that the RLS points to the correct rules dataset.
6. Choose Apply.
7. Re-test the viewer experience with a Reader account mapped to that user.

To verify the dataset refresh status, complete the following steps:

1. Open the Amazon Quick console.
2. In the navigation pane, choose Data.
3. Select the dataset.
4. Check the Last refreshed timestamp.
   Note: If the data is stale, then manually refresh or verify that the scheduled refresh is running.

If you recently upgraded a managed dashboard solution, then check whether the upgrade created a new dataset version that the dashboard doesn't reference.

To check for new datasets, run the following describe-dashboard AWS CLI, and then compare the dataset Amazon Resource Names (ARNs) with the current dataset.

aws quicksight describe-dashboard 
--aws-account-id 123456789012 
--dashboard-id dashboard_id

Note: Replace 123456789012 with your account ID and dashboard_id with your dashboard ID.

Resolve validation errors

Validation error or UPDATE_FAILED error on the analysis

If you use the AWS CLI or SDK to create or update an analysis and the definition contains empty filter objects or the analysis is in an UPDATE_FAILED state, then you might receive validation errors or the API operation returns incomplete data.

To resolve validation errors, review the error message path. The API returns the exact location of the not valid element.

Example API output:

definition.filterGroups.20.member.filters.1.member.nestedFilter.innerFilter

Search your definition file for empty objects in Filters, FilterGroups, or ParameterDeclarations. To remove the empty nested filter definitions, complete the following steps:

1. To export the analysis definition to a local file, run the following describe-analysis-definition AWS CLI command:

   aws quicksight describe-analysis-definition
   --aws-account-id 123456789012
   --analysis-id analysis_id

   Note: Replace 123456789012 with your account ID and analysis_id with your analysis ID.

2. Open the file and go to the location from the error path.

3. Delete the empty filter block or populate it with a valid filter.

4. To save and apply the file, run the following update-analysis AWS CLI command:

   aws quicksight  update-analysis
   --aws-account-id 123456789012
   --analysis-id analysis_id
   --name name

   Note: Replace 123456789012 with your account ID, analysis_id with your analysis ID, and name with your analysis name.

To resolve the UPDATE_FAILED state error, complete the following steps:

1. To check the analysis, run the following describe-analysis AWS CLI command:

   aws quicksight describe-analysis 
     --aws-account-id 123456789012 
     --analysis-id your-analysis-id

   Note: Replace 123456789012 with your AWS account ID and your-analysis-id with your analysis ID.
2. In the response, review the Errors array for Typeand Message that identifies the column, dataset or expression that causes the failure.
3. Recreate or remove the missing references.
4. Update the analysis.
5. Open the analysis, and choose Share.
6. Choose Publish dashboard.
7. Choose Replace an existing dashboard.
8. Select the target dashboard.
9. Choose Publish.

Replace an existing dashboard

If the analysis is different from the one that originally created the dashboard, then the target dashboard doesn't appear in the Replace an existing dashboard list.

To resolve this issue, complete the following steps:

1. Run the following describe-dashboard AWS CLI command to identify the name, version, and dataset references:

   aws quicksight describe-dashboard 
     --aws-account-id 123456789012 
     --dashboard-id existing-dashboard-id

   Note: Replace 123456789012 with your AWS account ID, existing-dashboard-id with your dashboard ID, my-new-template with your template ID, new-analysis-id with your analysis ID, and dataset-id with your dataset ID.
2. Run the following create-template AWS CLI command to create a template from the new analysis:

   aws quicksight create-template 
     --aws-account-id 123456789012 
     --template-id my-new-template 
     --source-entity '{"SourceAnalysis":{"Arn":"arn:aws:quicksight:aa-example-1:123456789012:analysis/new-analysis-id","DataSetReferences":[{"DataSetPlaceholder":"dataset1","DataSetArn":"arn:aws:quicksight:aa-example-1:123456789012:dataset/dataset-id"}]}}'

   Note: Replace 123456789012 with your account ID, my-new-template with your template ID, aa-example-1 with your AWS Region, and new-analysis-id with your source analysis ARN. The DataSetReferences must map template placeholders to actual dataset ARNs.
3. Run the following update-dashboard AWS CLI command to update the dashboard to use the new template:

   aws quicksight update-dashboard 
     --aws-account-id 123456789012 
     --dashboard-id existing-dashboard-id 
     --name "My Dashboard" 
     --source-entity '{"SourceTemplate":{"Arn":"arn:aws:quicksight:aa-example-1:123456789012:template/my-new-template","DataSetReferences":[{"DataSetPlaceholder":"dataset1","DataSetArn":"arn:aws:quicksight:aa-example-1:123456789012:dataset/dataset-id"}]}}'

   Note: Replace 123456789012 with your account ID, existing-dashboard-id with your dashboard ID, my-new-template with your template ID, aa-example-1 with your Region, and dataset-id with your dataset ID.
4. Note the version number in the output.
5. Run the update-dashboard-published-version AWS CLI command to publish the new dashboard version:

   aws quicksight update-dashboard-published-version 
     --aws-account-id 123456789012 
     --dashboard-id existing-dashboard-id 
     --version-number version_number

   Note: Replace 123456789012 with your account ID and existing-dashboard-id with your existing dashboard ID, and version_number with the version number.

Related information

My visual can't find the query table