The error message you are encountering,

Warning from normalization: Normalization failed during the dbt run. This may indicate a problem with the data itself.

, is a common issue that can arise during the normalization step in Airbyte. This error can be caused by various factors, including issues with the data itself, database connection problems, or specific limitations of the dbt tool. Here are some potential causes and solutions based on the provided knowledge sources: 1. Database Connection Issues: - Ensure that your database credentials are correct and that the database is accessible. For example, in one case, the error was due to an unexpected packet from the server (Source: [Forum Post: Normalization fails from MySQL, MS SQL Server to Clickhouse during sync](https://discuss.airbyte.io/t/3350)). - Another instance involved a login failure for a specific user (Source: [Github Issue: Destination MSSQL: dbt normalization not escaping passwords correctly](https://github.com/airbytehq/airbyte/issues/34498)). 2. Data Size and Schema Limitations: - If you are working with a large number of schemas or objects, dbt might encounter limitations. For example, dbt can only handle schemas with fewer than 10,000 objects (Source: [Forum Post: Dbt failure with tabular normalization PostgreSQL -> Snowflake](https://discuss.airbyte.io/t/2552)). 3. Data Type Issues: - Certain data types might cause issues during normalization. For instance, the SUPER datatype in Redshift can cause errors if the value exceeds the export size (Source: [Forum Post: Destination Redshift - Workaround for failed DBT normalization of SUPER datatype](https://discuss.airbyte.io/t/3754)). 4. JSON Schema Validation: - Ensure that your JSON schema is correctly defined. Errors in the JSON schema can cause normalization to fail (Source: [Forum Post: Destination BigQuery - Normalization Error with CDC](https://discuss.airbyte.io/t/2839)). ### Steps to Troubleshoot and Resolve 1. Check Database Credentials and Connection: - Verify that your database credentials are correct. - Ensure that the database is accessible and there are no network issues. 2. Review Data and Schema: - Check if the data being processed is within the limits of what dbt can handle. - Simplify the schema if possible, especially if you have a large number of objects. 3. Validate JSON Schema: - Ensure that your JSON schema is correctly defined and adheres to the expected standards. 4. Review Logs for Specific Errors: - Examine the logs for specific error messages that can provide more insight into what might be causing the issue. For example, look for errors related to data types, schema validation, or database connectivity. If the issue persists, you might want to consider using orchestration tools like Airflow or Dagster to handle dbt operations more robustly, as suggested in the [Github Issue: If Normalization fails retry only this operation](https://github.com/airbytehq/airbyte/issues/11933). For more detailed troubleshooting, you can refer to the specific logs and error messages provided in the knowledge sources linked above.

Normalization can be triggered during the data clearing stage due to the way Airbyte handles the ELT (Extract, Load, Transform) process. Here are some key points to understand why normalization might be running during data clearing: 1. Normalization as Part of ELT: - Airbyte's ELT process involves extracting data from the source, loading it into the destination, and then transforming it (normalization). Normalization is the step where the raw JSON data is converted into a structured format suitable for the destination (Source: [Basic Normalization - High-Level Overview](https://docs.airbyte.com/using-airbyte/core-concepts/basic-normalization#high-level-overview)). 2. Normalization After Data Sync: - When data is synced, Airbyte performs normalization to structure the data appropriately. This step is crucial for making the data usable in the destination database (Source: [Basic Normalization - Why does Airbyte have Basic Normalization?](https://docs.airbyte.com/using-airbyte/core-concepts/basic-normalization#why-does-airbyte-have-basic-normalization)). 3. Clearing Data and Normalization: - When you clear data, Airbyte deletes all records from your destination tables but does not remove the tables themselves. This process can trigger normalization to ensure that the tables are correctly structured and any necessary cleanup is performed (Source: [Clearing your data - Clear behavior](https://docs.airbyte.com/operator-guides/reset#clear-behavior)). 4. Normalization and Data Integrity: - Normalization might be necessary after clearing data to maintain data integrity and ensure that the destination schema is consistent. This is especially important if there are any changes in the schema or if the data needs to be restructured after clearing (Source: [Re-evaluate skip normalization if no new data feature](https://github.com/airbytehq/airbyte/issues/17578)). ### Example Scenario If you have a connection where normalization is enabled, and you perform a data clearing operation, Airbyte might run normalization to ensure that the destination tables are correctly structured and any necessary cleanup is performed. This can help avoid issues with orphaned tables or inconsistent schemas. ### Troubleshooting Steps 1. Review Logs: - Check the logs to see if there are any specific errors related to normalization during the data clearing stage. 2. Validate Schema: - Ensure that the schema definitions are correct and that there are no issues with the data types or structure. 3. Check Normalization Settings: - Verify that the normalization settings are correctly configured for your connection. If you continue to experience issues, you might want to refer to the detailed documentation on [Basic Normalization](https://docs.airbyte.com/using-airbyte/core-concepts/basic-normalization#high-level-overview) and [Clearing your data](https://docs.airbyte.com/operator-guides/reset#clear-behavior) for further guidance.