xfail some low shuffle merge tests with cdf on databricks

Author: jihoonson

integration_tests/src/main/python/delta_lake_low_shuffle_merge_test.py

@@ -93,7 +93,7 @@ def test_delta_merge_not_match_insert_only(spark_tmp_path, spark_tmp_table_facto
                                           (range(5), range(5)),  # full delete of target
                                           (range(10), range(20, 30))  # no-op delete
                                           ], ids=idfn)
-@pytest.mark.parametrize("use_cdf", [True, False], ids=idfn)
+@pytest.mark.parametrize("use_cdf", [pytest.param(True, marks=pytest.mark.xfail(reason="https://github.com/NVIDIA/spark-rapids/issues/13552")), False], ids=idfn)
 @pytest.mark.parametrize("partition_columns", [None, ["a"], ["b"], ["a", "b"]], ids=idfn)
 @pytest.mark.parametrize("num_slices", num_slices_to_test, ids=idfn)
 def test_delta_merge_match_delete_only(spark_tmp_path, spark_tmp_table_factory, table_ranges,
@@ -111,7 +111,7 @@ def test_delta_merge_match_delete_only(spark_tmp_path, spark_tmp_table_factory,
                          (not is_databricks_runtime() and spark_version().startswith("3.4"))),
                     reason="Delta Lake Low Shuffle Merge only supports Databricks 13.3 or OSS "
                            "delta 2.4")
-@pytest.mark.parametrize("use_cdf", [True, False], ids=idfn)
+@pytest.mark.parametrize("use_cdf", [pytest.param(True, marks=pytest.mark.xfail(reason="https://github.com/NVIDIA/spark-rapids/issues/13552")), False], ids=idfn)
 @pytest.mark.parametrize("num_slices", num_slices_to_test, ids=idfn)
 def test_delta_merge_standard_upsert(spark_tmp_path, spark_tmp_table_factory, use_cdf, num_slices):
     do_test_delta_merge_standard_upsert(spark_tmp_path, spark_tmp_table_factory, use_cdf, False,
@@ -126,7 +126,7 @@ def test_delta_merge_standard_upsert(spark_tmp_path, spark_tmp_table_factory, us
                          (not is_databricks_runtime() and spark_version().startswith("3.4"))),
                     reason="Delta Lake Low Shuffle Merge only supports Databricks 13.3 or OSS "
                            "delta 2.4")
-@pytest.mark.parametrize("use_cdf", [True, False], ids=idfn)
+@pytest.mark.parametrize("use_cdf", [pytest.param(True, marks=pytest.mark.xfail(reason="https://github.com/NVIDIA/spark-rapids/issues/13552")), False], ids=idfn)
 @pytest.mark.parametrize("merge_sql", [
     "MERGE INTO {dest_table} d USING {src_table} s ON d.a == s.a" \
     " WHEN MATCHED AND s.b > 'q' THEN UPDATE SET d.a = s.a / 2, d.b = s.b" \
@@ -173,7 +173,7 @@ def test_delta_merge_upsert_with_unmatchable_match_condition(spark_tmp_path, spa
                          (not is_databricks_runtime() and spark_version().startswith("3.4"))),
                     reason="Delta Lake Low Shuffle Merge only supports Databricks 13.3 or OSS "
                            "delta 2.4")
-@pytest.mark.parametrize("use_cdf", [True, False], ids=idfn)
+@pytest.mark.parametrize("use_cdf", [pytest.param(True, marks=pytest.mark.xfail(reason="https://github.com/NVIDIA/spark-rapids/issues/13552")), False], ids=idfn)
 def test_delta_merge_update_with_aggregation(spark_tmp_path, spark_tmp_table_factory, use_cdf):
     do_test_delta_merge_update_with_aggregation(spark_tmp_path, spark_tmp_table_factory, use_cdf, False,
                                                 delta_merge_enabled_conf)