[MINIOR][PYTHON] Specifying udf type in SCHEMA_MISMATCH_FOR_PANDAS_UDF error message

### What changes were proposed in this pull request?

This minor patch adds `udf_type` parameter to `SCHEMA_MISMATCH_FOR_PANDAS_UDF` error message.

### Why are the changes needed?

We actually raise `SCHEMA_MISMATCH_FOR_PANDAS_UDF` message for both Pandas UDF and Arrow batch UDF. But the error message claims `pandas_udf` has error. It might be confused to Arrow batch UDF when seeing it.

### Does this PR introduce _any_ user-facing change?

Yes, the error message to user is changed.

### How was this patch tested?

Unit test

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

No

Closes apache#50312 from viirya/fix_udf_error_message.

Authored-by: Liang-Chi Hsieh <viirya@gmail.com>
Signed-off-by: Liang-Chi Hsieh <viirya@gmail.com>

Author: viirya

python/pyspark/errors/error-conditions.json

@@ -905,7 +905,7 @@
   },
   "SCHEMA_MISMATCH_FOR_PANDAS_UDF": {
     "message": [
-      "Result vector from pandas_udf was not the required length: expected <expected>, got <actual>."
+      "Result vector from <udf_type> was not the required length: expected <expected>, got <actual>."
     ]
   },
   "SESSION_ALREADY_EXIST": {

python/pyspark/worker.py

@@ -141,6 +141,7 @@ def verify_result_length(result, length):
             raise PySparkRuntimeError(
                 errorClass="SCHEMA_MISMATCH_FOR_PANDAS_UDF",
                 messageParameters={
+                    "udf_type": "pandas_udf",
                     "expected": str(length),
                     "actual": str(len(result)),
                 },
@@ -213,6 +214,7 @@ def verify_result_length(result, length):
             raise PySparkRuntimeError(
                 errorClass="SCHEMA_MISMATCH_FOR_PANDAS_UDF",
                 messageParameters={
+                    "udf_type": "arrow_batch_udf",
                     "expected": str(length),
                     "actual": str(len(result)),
                 },