Forum Discussion
Fully Parse and Extract Nested JSON from AuditData Column in CSV Using Notebook in Fabric
Hi Anonymous ,
Thanks for posting in Microsoft Fabric Community sharing the detailed context.To extract fields or handle cases where certain parts of the JSON may be missing, consider using coalesce while working with the parsed JSON column. This can help avoid issues when some fields are not always present in the data.
A similar thread involved handling nested JSON in Fabric notebooks where using coalesce along with a properly defined schema allowed to extract fields safely, even when certain parts of the JSON were missing or null.
Solved: PySpark Notebook to process complex JSON - Microsoft Fabric Community
You may refer to the discussion and apply the same pattern in your scenario.
Hope this helps. Please reach out for further assistance.
Thank you.
Hi Anonymous ,
Thanks for posting in Microsoft Fabric Community sharing the detailed context.
To extract fields or handle cases where certain parts of the JSON may be missing, consider using coalesce while working with the parsed JSON column. This can help avoid issues when some fields are not always present in the data.
A similar thread involved handling nested JSON in Fabric notebooks where using coalesce along with a properly defined schema allowed to extract fields safely, even when certain parts of the JSON were missing or null.
Solved: PySpark Notebook to process complex JSON - Microsoft Fabric Community
You may refer to the discussion and apply the same pattern in your scenario.
Hope this helps. Please reach out for further assistance.
Thank you.
Hi Anonymous ,
Just wanted to check if the response provided was helpful. If further assistance is needed, please reach out.
Thank you.Yes that thread was perfect. I appreciate your help!