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There could be various reasons for the code not functioning properly such as:

1. Incorrect file path: The fileName might be incorrect or pointing to a non-existent file.

2. Incorrect file type: The file format might not be csv, which could cause issues during reading.

3. Invalid schema: The schema provided might not match the columns in the csv file.

4. Insufficient file permissions: The user might not have sufficient permissions to access or read the file.

5. Resource limitations: The cluster resources might be insufficient to read the file, causing the job to fail.

6. Encoding issues: The file might be encoded in a format that is not supported by the spark.read function.

7. Network connectivity issues: If the file is located on a remote server, there might be network connectivity issues that could cause the job to fail.