[SPARK-48938][PYTHON] Improve error messages when registering Python …

…UDTFs

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

This PR improves the error messages when registering Python UDTFs.
Before this PR:
```python
class TestUDTF:
   ...

spark.udtf.register("test_udtf", TestUDTF)
```
This fails with
```
AttributeError: type object "TestUDTF" has no attribute "evalType"
```
After this PR:
```python
spark.udtf.register("test_udtf", TestUDTF)
```
Now we have a nicer error:
```
[CANNOT_REGISTER_UDTF] Cannot register the UDTF 'test_udtf': expected a 'UserDefinedTableFunction'. Please make sure the UDTF is correctly defined as a class, and then either wrap it in the `udtf()` function or annotate it with `udtf(...)`.`
```

### Why are the changes needed?

To improve usability.

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

No

### How was this patch tested?

Existing and new unit tests.

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

No

Closes apache#47408 from allisonwang-db/spark-48938-udtf-register-err-msg.

Authored-by: allisonwang-db <[email protected]>
Signed-off-by: Hyukjin Kwon <[email protected]>

python/pyspark/errors/error-conditions.json

@@ -134,6 +134,11 @@
       "Metadata can only be provided for a single column."
     ]
   },
+  "CANNOT_REGISTER_UDTF": {
+    "message": [
+      "Cannot register the UDTF '<name>': expected a 'UserDefinedTableFunction'. Please make sure the UDTF is correctly defined as a class, and then either wrap it in the `udtf()` function or annotate it with `@udtf(...)`."
+    ]
+  },
   "CANNOT_SET_TOGETHER": {
     "message": [
       "<arg_list> should not be set together."

python/pyspark/sql/connect/udtf.py

@@ -192,6 +192,14 @@ def register(
         name: str,
         f: "UserDefinedTableFunction",
     ) -> "UserDefinedTableFunction":
+        if not isinstance(f, UserDefinedTableFunction):
+            raise PySparkTypeError(
+                error_class="CANNOT_REGISTER_UDTF",
+                message_parameters={
+                    "name": name,
+                },
+            )
+
         if f.evalType not in [PythonEvalType.SQL_TABLE_UDF, PythonEvalType.SQL_ARROW_TABLE_UDF]:
             raise PySparkTypeError(
                 error_class="INVALID_UDTF_EVAL_TYPE",

python/pyspark/sql/tests/test_udtf.py

@@ -935,10 +935,23 @@ def upper(s: str):
 
         self.check_error(
             exception=e.exception,
-            error_class="INVALID_UDTF_EVAL_TYPE",
+            error_class="CANNOT_REGISTER_UDTF",
             message_parameters={
                 "name": "test_udf",
-                "eval_type": "SQL_TABLE_UDF, SQL_ARROW_TABLE_UDF",
+            },
+        )
+
+        class TestUDTF:
+            ...
+
+        with self.assertRaises(PySparkTypeError) as e:
+            self.spark.udtf.register("test_udtf", TestUDTF)
+
+        self.check_error(
+            exception=e.exception,
+            error_class="CANNOT_REGISTER_UDTF",
+            message_parameters={
+                "name": "test_udtf",
             },
         )
 

python/pyspark/sql/udtf.py

@@ -461,6 +461,14 @@ def register(
         >>> spark.sql("SELECT * FROM VALUES (0, 1), (1, 2) t(x, y), LATERAL plus_one(x)").collect()
         [Row(x=0, y=1, c1=0, c2=1), Row(x=1, y=2, c1=1, c2=2)]
         """
+        if not isinstance(f, UserDefinedTableFunction):
+            raise PySparkTypeError(
+                error_class="CANNOT_REGISTER_UDTF",
+                message_parameters={
+                    "name": name,
+                },
+            )
+
         if f.evalType not in [PythonEvalType.SQL_TABLE_UDF, PythonEvalType.SQL_ARROW_TABLE_UDF]:
             raise PySparkTypeError(
                 error_class="INVALID_UDTF_EVAL_TYPE",