Fabric having issues importing or ingesting json files and responses

[smeetsh]

Good morning All,

We ingest a lot of data using the API endpoint of our third parties, and I have build a lot of pipelines doing just that

I am working with a new API since friday and I am having issues doing an import of the mapping (using a json file or a json response). It sits there for ages spinning and either times out with a error like "Failed to import source schema. undefined.
Activity ID: undefined." , or keeps on spinning.

One of the jsons is very big, it has about 225000 lines for one response, which is multiple (nested) objects, which may or may not contain arrays. The actual size is just 3 mb though.

I figured the sheer number of lines, objects and nesting was potentially the issue, but when i tried the second endpoint I had the same issue. This file is only 50kb and has only 3600 lines, albeit with multiple objects with nested arrays as well.

This has never been an issue in the past. since we have ingested many json responses, with nesting this way

Has something been broken or radically changed since the last update?

Cheers

Hans

PS: I know a notebook would be an option, but it seems somewhat silly to have to write a bunch of code for something that Fabric used to be able to do by itself. Especially with the big response there is many object to flatten, parse and potentially explode.

[v-hashadapu]

Hi @smeetsh , Hope you're doing okay! May we know if it worked for you, or are you still experiencing difficulties? Let us know — your feedback can really help others in the same situation.

[smeetsh]

 All,

It appears indeed that the complexity of the json is the issue. I am trying to unravel it using a notebook and multiple table in our lakehouse. Powerquery is not a solution, but a notebook to ingest into lakehouse and using ETL to a warehouse may be.

[v-hashadapu · Accepted solution]

Hi @smeetsh , Yeah, I think the issue is with the JSON complexity rather than the payload size too. Fabric generally handles large JSON files fine, but deeply nested and irregular schemas with optional arrays/objects can make the automatic schema import struggle or hang. The fact that even the smaller endpoint failed during schema import points more toward a schema inference limitation than a pure performance problem.

Your notebook -> Lakehouse -> ETL/Warehouse approach is probably the better fit here anyway. Spark gives you much more control over flattening arrays, handling nullable branches and managing evolving schemas compared to relying on automatic inference in the import UI.

[v-hashadapu]

Hi @smeetsh , Hope you're doing fine. Can you confirm if the problem is solved or still persists? Sharing your details will help others in the community.

[v-hashadapu]

Hi @smeetsh , Hope you are doing well. Kindly let us know if the issue has been resolved or if further assistance is needed. Your input could be helpful to others in the community.

[v-hashadapu]

Hi @smeetsh , Thank you for reaching out to the Microsoft Community Forum.

This sounds more like a Fabric/Dataflow schema inference issue than a problem with the actual file size. A 3 MB JSON is not especially large and the fact that even the smaller 50 KB response hangs points more toward the parser struggling with the nested structure and arrays during automatic schema detection.

I do not think Microsoft intentionally changed support for nested JSON, but I did hear about of flaky behaviour around complex JSON imports and schema detection in Fabric. The generic “Failed to import source schema. undefined” error is usually thrown before the actual transformations even start, so the failure is likely happening during the import/inference step itself.

As a workaround, you can ingest the raw JSON first and then expand it manually step by step in Power Query, instead of relying on automatic schema import. If possible, testing with a simplified or partially flattened response can also help confirm whether a specific nested branch is causing the parser to choke.