[GitHub] [spark] itholic commented on a diff in pull request #41606: [WIP] [SPARK-44061] Add assertDFEquality util function

["itholic (via GitHub)" <gi...@apache.org>]

itholic commented on code in PR #41606:
URL: https://github.com/apache/spark/pull/41606#discussion_r1250546812


##########
python/pyspark/testing/utils.py:
##########
@@ -209,3 +220,45 @@ def check_error(
         self.assertEqual(
             expected, actual, f"Expected message parameters was '{expected}', got '{actual}'"
         )
+
+
+def assertSparkSchemaEquality(
+    s1: Optional[Union[AtomicType, StructType, str, List[str], Tuple[str, ...]]],
+    s2: Optional[Union[AtomicType, StructType, str, List[str], Tuple[str, ...]]],
+):
+    if s1 != s2:
+        msg = "Schemas are different"
+        raise AssertionError(msg)
+
+
+def assertSparkDFEquality(
+    left: PySparkDataFrame, right: PySparkDataFrame,
+):
+    def assert_rows_equality(rows1, rows2):
+        if rows1 != rows2:
+            msg = "Dataframes are different"
+            raise AssertionError(msg)

Review Comment:
   Yes, we should use PySpark specific errors instead of Python built-in exception if the exception can be raised from user space.
   
   In this case, we can use `PySparkAssertionError` instead of `AssertionError` with proper error class. e.g.
   ```python
   ...
   from pyspark.errors import PySparkAssertionError
   ...
       def assert_rows_equality(rows1, rows2):
           if rows1 != rows2:
               raise PySparkAssertionError(
                   error_class="DIFFERENT_DATAFRAME",
               )
   ```
   
   New error class can be added to https://github.com/apache/spark/blob/master/python/pyspark/errors/error_classes.py.



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