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Databricks Autoloader simply does not return results if the schema provided has something wrong. Whereas it should provide some error. It Simply does not returns any rows making it difficult to debug.

tech2cloud
New Contributor II
1 ACCEPTED SOLUTION

Accepted Solutions

Anonymous
Not applicable

@Ravi Vishwakarma​ :

You are correct that if there is an issue with the schema provided to Databricks Autoloader, it may not return any rows and make it difficult to debug. However, there are a few steps you can take to troubleshoot this issue:

  1. Check the job logs: When a Databricks Autoloader job is run, it generates job logs that can provide insight into any issues that may have occurred. You can access the job logs by clicking on the "Logs" tab for the Autoloader job. Look for any error messages or warnings that may indicate an issue with the schema.
  2. Validate the schema: Double-check the schema you are using to make sure it is correct and matches the structure of the data you are trying to load. You can use the StructType method in PySpark or the StructType() constructor in SQL to define the schema.
  3. Test the schema with a smaller dataset: If you are having trouble identifying the issue with the schema, you can try testing it with a smaller dataset to see if it loads correctly. This can help you isolate the issue and narrow down the possible causes.
  4. Use the "failfast" option: Databricks Autoloader has an option called "failfast" that can be used to terminate the job immediately if any data is found that does not match the schema. This can be useful for catching schema issues early on and preventing the job from running on bad data.

By taking these steps, you should be able to identify any issues with the schema and debug your Databricks Autoloader job more effectively.

View solution in original post

3 REPLIES 3

Anonymous
Not applicable

@Ravi Vishwakarma​ :

You are correct that if there is an issue with the schema provided to Databricks Autoloader, it may not return any rows and make it difficult to debug. However, there are a few steps you can take to troubleshoot this issue:

  1. Check the job logs: When a Databricks Autoloader job is run, it generates job logs that can provide insight into any issues that may have occurred. You can access the job logs by clicking on the "Logs" tab for the Autoloader job. Look for any error messages or warnings that may indicate an issue with the schema.
  2. Validate the schema: Double-check the schema you are using to make sure it is correct and matches the structure of the data you are trying to load. You can use the StructType method in PySpark or the StructType() constructor in SQL to define the schema.
  3. Test the schema with a smaller dataset: If you are having trouble identifying the issue with the schema, you can try testing it with a smaller dataset to see if it loads correctly. This can help you isolate the issue and narrow down the possible causes.
  4. Use the "failfast" option: Databricks Autoloader has an option called "failfast" that can be used to terminate the job immediately if any data is found that does not match the schema. This can be useful for catching schema issues early on and preventing the job from running on bad data.

By taking these steps, you should be able to identify any issues with the schema and debug your Databricks Autoloader job more effectively.

I managed to get the problematic column by redirecting the error records.

Anonymous
Not applicable

Hi @Ravi Vishwakarma​ 

Thank you for posting your question in our community! We are happy to assist you.

To help us provide you with the most accurate information, could you please take a moment to review the responses and select the one that best answers your question?

This will also help other community members who may have similar questions in the future. Thank you for your participation and let us know if you need any further assistance! 

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