Importing JSON files when format is subject to evolution

[etum]

Hi there,

I'm reaching out for some assistance with importing JSON files into Databricks. Still a beginner even if I've gained experience working with various data import batches (CSV/JSON) for application monitoring:  I'm currently facing a challenge with a specific JSON data set.

The structure of this JSON file has evolved over the past year, with new fields being added. As a result, our current Python code using inferSchema to automatically detect the format is encountering errors during import.

I've explored several approaches to handle schema evolution, including concepts like schema merging, but haven't yet found a solution that works consistently. I believe I'm close to a solution, but I'm running into some roadblocks.

Any insights or suggestions you might have on handling evolving JSON schemas during import would be greatly appreciated.

Thanks in advance for your help!

[Kaniz_Fatma]

Hi @etum, 

• In JSON Schema, you can use the allOf keyword. It allows you to specify that the data must be valid against both the parent schema (the original schema) and the child schema (the new fields). This way, you ensure compatibility with both old and new data.
• When evolving an open schema, consider backward compatibility (old schemas can read new data) and fo...².
•  Instead of relying solely on inferSchema, explicitly define your schema using the StructType in Databricks. This way, you have better control over the schema and can handle changes more effectively.

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