[PySpark] Add schema evolution config to PySpark DeltaMergeBuilder (delta-io#2778)

#### Which Delta project/connector is this regarding?
<!--
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request title
For example: [Spark] Title of my pull request
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- [ ] Spark
- [ ] Standalone
- [ ] Flink
- [ ] Kernel
- [X] PySpark

## Description

This PR continues from delta-io#2737 to
add a `withSchemaEvolution()` method for `DeltaMergeBuilder` in PySpark.


## How was this patch tested?

New unit tests.

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

Yes, this PR allows the user to turn on schema evolution for MERGE in
PySpark by calling the `table.merge(...).withSchemaEvolution()` method.

Author: xupefei

python/delta/tables.py

@@ -1013,6 +1013,19 @@ def whenNotMatchedBySourceDelete(
         new_jbuilder = self.__getNotMatchedBySourceBuilder(condition).delete()
         return DeltaMergeBuilder(self._spark, new_jbuilder)
 
+    @since(3.2)  # type: ignore[arg-type]
+    def withSchemaEvolution(self) -> "DeltaMergeBuilder":
+        """
+        Enable schema evolution for the merge operation. This allows the target table schema to
+        be automatically updated based on the schema of the source DataFrame.
+
+        See :py:class:`~delta.tables.DeltaMergeBuilder` for complete usage details.
+
+        :return: this builder
+        """
+        new_jbuilder = self._jbuilder.withSchemaEvolution()
+        return DeltaMergeBuilder(self._spark, new_jbuilder)
+
     @since(0.4)  # type: ignore[arg-type]
     def execute(self) -> None:
         """

python/delta/tests/test_deltatable.py

@@ -335,6 +335,20 @@ def reset_table() -> None:
             .execute()
         self.__checkAnswer(dt.toDF(), ([('a', -1), ('b', 2), ('c', 3), ('d', 4), ('e', -5)]))
 
+        # Schema evolution
+        reset_table()
+        dt.alias("t") \
+            .merge(source.toDF("key", "extra").alias("s"), expr("t.key = s.key")) \
+            .whenMatchedUpdate(set={"extra": "-1"}) \
+            .whenNotMatchedInsertAll() \
+            .withSchemaEvolution() \
+            .execute()
+        self.__checkAnswer(
+            DeltaTable.forPath(self.spark, self.tempFile).toDF(),  # reload the table
+            ([('a', 1, -1), ('b', 2, -1), ('c', 3, None), ('d', 4, None), ('e', None, -5),
+              ('f', None, -6)]),
+            ["key", "value", "extra"])
+
         # ============== Test bad args ==============
         # ---- bad args in merge()
         with self.assertRaisesRegex(TypeError, "must be DataFrame"):