Answer: All of the fields had at least one null value

## Explanation Auto Loader's schema inference works by sampling a subset of files to determine column types. When Auto Loader encounters **null values** in the sampled data for certain columns, it defaults to the **string type** for those columns as a safe fallback. This is because: 1. **Null values don't provide type information** - When Auto Loader samples files and finds null values in a column, it cannot determine the intended data type (boolean, integer, float, etc.) from null alone. 2. **String is the most flexible type** - String can accommodate any data format, so Auto Loader chooses string as the default to avoid data loss or parsing errors. 3. **This is a known behavior** - In Databricks Auto Loader, if the initial sample contains null values for certain fields, those columns will be inferred as string type rather than their actual intended types. **Why other options are incorrect:** - **A**: Auto Loader *can* infer schema - it has schema inference capabilities - **B**: While JSON is text-based, Auto Loader can still infer numeric and boolean types from JSON data - **C**: Auto Loader works with various data types, not just strings **Solution**: To fix this issue, the data engineer should: 1. Provide explicit schema hints using `cloudFiles.schemaHints` option 2. Increase the sample size for schema inference 3. Use `cloudFiles.schemaEvolutionMode` to control how schema changes are handled 4. Manually specify the schema using `schema` option if the data structure is known

Author: Keng Suppaseth