[SPARK-55723][PYTHON] Generalize enforce_schema error to PySparkTypeError

[Yicong-Huang]

What changes were proposed in this pull request?

Replace PySparkRuntimeError with RESULT_COLUMNS_MISMATCH_FOR_ARROW_UDTF error class in enforce_schema and ArrowStreamArrowUDTFSerializer with a general PySparkTypeError that reports column name, expected type, and actual type without being specific to any UDF type.

Why are the changes needed?

The RESULT_COLUMNS_MISMATCH_FOR_ARROW_UDTF error class was UDTF-specific, but enforce_schema is a general utility used across UDF types. The error message ("Column names ... do not match specified schema") was also misleading -- the actual failure is a type cast error, not a column name mismatch.

Does this PR introduce any user-facing change?

Yes. The error type changes from PySparkRuntimeError to PySparkTypeError, and the message now accurately describes the type mismatch:

Before:

PySparkRuntimeError: [RESULT_COLUMNS_MISMATCH_FOR_ARROW_UDTF] Column names of the returned pyarrow.Table or pyarrow.RecordBatch do not match specified schema. Expected: int32 Actual: string

After:

PySparkTypeError: Result type of column 'id' does not match the expected type. Expected: int32, got: string.

How was this patch tested?

Updated existing test in test_arrow_udtf.py.

Was this patch authored or co-authored using generative AI tooling?

No

[Yicong-Huang]

cc @gaogaotiantian