fix

tests/integ/modin/crosstab/test_crosstab.py

@@ -53,7 +53,7 @@ def test_basic_crosstab_with_numpy_arrays_different_lengths(self, dropna, a, b,
     def test_basic_crosstab_with_series_objs_full_overlap(self, dropna, a, b, c):
         # In this case, all indexes are identical - hence "full" overlap.
         query_count = 2
-        join_count = 5 if dropna else 10
+        join_count = 4 if dropna else 5
 
         def eval_func(lib):
             if lib is pd:
@@ -80,7 +80,7 @@ def test_basic_crosstab_with_series_objs_some_overlap(self, dropna, a, b, c):
         # of the Series objects. This test case passes because we pass in arrays that
         # are the length of the intersection rather than the length of each of the Series.
         query_count = 2
-        join_count = 5 if dropna else 10
+        join_count = 4 if dropna else 5
         b = native_pd.Series(
             b,
             index=list(range(len(a))),
@@ -206,7 +206,7 @@ def test_basic_crosstab_with_df_and_series_objs_pandas_errors_columns(
         self, dropna, a, b, c
     ):
         query_count = 4
-        join_count = 1 if dropna else 3
+        join_count = 1 if dropna else 2
         a = native_pd.Series(
             a,
             dtype=object,
@@ -252,7 +252,7 @@ def test_basic_crosstab_with_df_and_series_objs_pandas_errors_index(
         self, dropna, a, b, c
     ):
         query_count = 6
-        join_count = 5 if dropna else 17
+        join_count = 5 if dropna else 11
         a = native_pd.Series(
             a,
             dtype=object,

tests/integ/modin/frame/test_cache_result.py

@@ -160,7 +160,7 @@ def test_cache_result_post_pivot(self, inplace, simple_test_data):
         native_df = perform_chained_operations(
             native_df.pivot_table(**pivot_kwargs), native_pd
         )
-        with SqlCounter(query_count=1, join_count=10, union_count=9):
+        with SqlCounter(query_count=1, join_count=1, union_count=9):
             snow_df = perform_chained_operations(snow_df, pd)
             assert_snowpark_pandas_equals_to_pandas_without_dtypecheck(
                 snow_df, native_df

tests/integ/modin/frame/test_describe.py

@@ -73,7 +73,7 @@ def test_describe_obj_only(data, expected_union_count):
 
 
 @pytest.mark.parametrize(
-    "dtype, expected_union_count", [(int, 7), (float, 7), (object, 9)]
+    "dtype, expected_union_count", [(int, 7), (float, 7), (object, 5)]
 )
 def test_describe_empty_rows(dtype, expected_union_count):
     with SqlCounter(query_count=1, union_count=expected_union_count):
@@ -181,7 +181,7 @@ def test_describe_include_exclude_obj_only(include, exclude, expected_exception)
     }
     with SqlCounter(
         query_count=1 if expected_exception is None else 0,
-        union_count=9 if expected_exception is None else 0,
+        union_count=5 if expected_exception is None else 0,
     ):
         eval_snowpark_pandas_result(
             *create_test_dfs(data),

tests/integ/modin/frame/test_loc.py

@@ -1144,7 +1144,7 @@ def loc_set_helper(df):
 
     query_count, join_count = 1, 2
     if not all(isinstance(rk_val, bool) for rk_val in row_key):
-        join_count += 2
+        join_count += 1
     if isinstance(col_key, native_pd.Series):
         query_count += 1
     with SqlCounter(query_count=query_count, join_count=join_count):
@@ -4219,9 +4219,9 @@ def test_df_loc_set_series_value(key, convert_key_to_series, row_loc):
     key_sorted = key == list("ABC")
     if row_loc is not None:
         if convert_key_to_series:
-            join_count = 9
-        else:
             join_count = 6
+        else:
+            join_count = 4
     else:
         if convert_key_to_series:
             join_count = 3
@@ -4278,7 +4278,7 @@ def test_df_loc_set_series_value_slice_key(key, row_loc):
     snow_df = pd.DataFrame(native_df)
     query_count = 2
     if row_loc is not None:
-        join_count = 6
+        join_count = 4
     else:
         join_count = 1
 

tests/integ/modin/pivot/test_pivot_table_dropna.py

@@ -85,7 +85,7 @@ def test_pivot_table_multiple_pivot_values_dropna_null_data(
         )
 
 
-@sql_count_checker(query_count=1, join_count=11)
+@sql_count_checker(query_count=1, join_count=5)
 def test_pivot_table_multiple_index_single_pivot_values_dropna_null_data(
     df_data_with_nulls_2,
 ):
@@ -120,7 +120,7 @@ def test_pivot_table_single_all_aggfuncs_dropna_and_null_data(
         )
 
 
-@sql_count_checker(query_count=1, join_count=7)
+@sql_count_checker(query_count=1, join_count=4)
 def test_pivot_table_single_nuance_aggfuncs_dropna_and_null_data(
     df_data_with_nulls_2,
 ):

tests/integ/modin/pivot/test_pivot_table_margins.py

@@ -191,7 +191,7 @@ def test_pivot_table_multiple_pivot_values_null_data_with_margins_nan_blocked(
         )
 
 
-@sql_count_checker(query_count=1, join_count=12, union_count=1)
+@sql_count_checker(query_count=1, join_count=6, union_count=1)
 def test_pivot_table_mixed_index_types_with_margins(
     df_data,
 ):
@@ -352,21 +352,23 @@ def test_single_value_single_aggfunc(
             named_columns=named_columns,
         )
 
-    @sql_count_checker(query_count=1, join_count=1, union_count=2)
     def test_multiple_value_single_aggfunc(
         self, columns, named_columns, df_data_more_pivot_values
     ):
-        pivot_table_test_helper(
-            df_data_more_pivot_values,
-            {
-                "columns": columns,
-                "values": ["D", "E"],
-                "aggfunc": "sum",
-                "dropna": True,
-                "margins": True,
-            },
-            named_columns=named_columns,
-        )
+        with SqlCounter(
+            query_count=1, join_count=1, union_count=2 if len(columns) > 1 else 1
+        ):
+            pivot_table_test_helper(
+                df_data_more_pivot_values,
+                {
+                    "columns": columns,
+                    "values": ["D", "E"],
+                    "aggfunc": "sum",
+                    "dropna": True,
+                    "margins": True,
+                },
+                named_columns=named_columns,
+            )
 
     @sql_count_checker(query_count=1, join_count=3)
     def test_single_value_multiple_aggfunc(

tests/integ/modin/types/test_timedelta_indexing.py

@@ -466,7 +466,7 @@ def test_index_get_timedelta(key, join_count):
     [
         [2, "iat", 1, 1],
         [native_pd.Timedelta("1 days 1 hour"), "at", 2, 4],
-        [[2, 1], "iloc", 1, 4],
+        [[2, 1], "iloc", 1, 3],
         [
             [
                 native_pd.Timedelta("1 days 1 hour"),
@@ -510,7 +510,7 @@ def test_series_with_timedelta_index(key, api, query_count, join_count):
     [
         [2, "iat", 1, 1],
         [native_pd.Timedelta("1 days 1 hour"), "at", 2, 4],
-        [[2, 1], "iloc", 1, 4],
+        [[2, 1], "iloc", 1, 3],
         [
             [
                 native_pd.Timedelta("1 days 1 hour"),