FIX-#2169: avoid unnecessary index access in groupby

modin/backends/base/query_compiler.py

@@ -1621,49 +1621,63 @@ def has_multiindex(self, axis=0):
         assert axis == 1
         return isinstance(self.columns, pandas.MultiIndex)
 
-    def get_index_name(self):
+    def get_index_name(self, axis=0):
         """
-        Get index name.
+        Get index name of specified axis.
+
+        Parameters
+        ----------
+        axis: int (default 0),
+            Axis to return index name on.
 
         Returns
         -------
         hashable
             Index name, None for MultiIndex.
         """
-        return self.index.name
+        return self.get_axis(axis).name
 
-    def set_index_name(self, name):
+    def set_index_name(self, name, axis=0):
         """
-        Set index name.
+        Set index name for the specified axis.
 
         Parameters
         ----------
-        name: hashable
+        name: hashable,
             New index name.
+        axis: int (default 0),
+            Axis to set name along.
         """
-        self.index.name = name
+        self.get_axis(axis).name = name
 
-    def get_index_names(self):
+    def get_index_names(self, axis=0):
         """
-        Get index names.
+        Get index names of specified axis.
+
+        Parameters
+        ----------
+        axis: int (default 0),
+            Axis to return index names on.
 
         Returns
         -------
         list
             Index names.
         """
-        return self.index.names
+        return self.get_axis(axis).names
 
-    def set_index_names(self, names):
+    def set_index_names(self, names, axis=0):
         """
-        Set index names.
+        Set index names for the specified axis.
 
         Parameters
         ----------
-        names: list
+        names: list,
             New index names.
+        axis: int (default 0),
+            Axis to set names along.
         """
-        self.index.names = names
+        self.get_axis(axis).names = names
 
     # DateTime methods
 

modin/backends/pandas/query_compiler.py

@@ -2969,22 +2969,3 @@ def cat_codes(self):
         return self.default_to_pandas(lambda df: df[df.columns[0]].cat.codes)
 
     # END Cat operations
-
-    def has_multiindex(self, axis=0):
-        """
-        Check if specified axis is indexed by MultiIndex.
-
-        Parameters
-        ----------
-        axis : 0 or 1, default 0
-            The axis to check (0 - index, 1 - columns).
-
-        Returns
-        -------
-        bool
-            True if index at specified axis is MultiIndex and False otherwise.
-        """
-        if axis == 0:
-            return isinstance(self.index, pandas.MultiIndex)
-        assert axis == 1
-        return isinstance(self.columns, pandas.MultiIndex)

modin/experimental/backends/omnisci/query_compiler.py

@@ -633,17 +633,23 @@ def has_multiindex(self, axis=0):
         assert axis == 1
         return isinstance(self.columns, pandas.MultiIndex)
 
-    def get_index_name(self):
-        return self._modin_frame.get_index_name()
+    def get_index_name(self, axis=0):
+        return self.columns.name if axis else self._modin_frame.get_index_name()
 
-    def set_index_name(self, name):
-        self._modin_frame = self._modin_frame.set_index_name(name)
+    def set_index_name(self, name, axis=0):
+        if axis == 0:
+            self._modin_frame = self._modin_frame.set_index_name(name)
+        else:
+            self.columns.name = name
 
-    def get_index_names(self):
-        return self._modin_frame.get_index_names()
+    def get_index_names(self, axis=0):
+        return self.columns.names if axis else self._modin_frame.get_index_names()
 
-    def set_index_names(self, names):
-        self._modin_frame = self._modin_frame.set_index_names(names)
+    def set_index_names(self, names=None, axis=0):
+        if axis == 0:
+            self._modin_frame = self._modin_frame.set_index_names(names)
+        else:
+            self.columns.names = names
 
     def free(self):
         return

modin/experimental/engines/omnisci_on_ray/test/test_dataframe.py

@@ -54,10 +54,17 @@ def run_and_compare(
     **kwargs
 ):
     def run_modin(
-        fn, data, data2, force_lazy, force_arrow_execute, allow_subqueries, **kwargs
+        fn,
+        data,
+        data2,
+        force_lazy,
+        force_arrow_execute,
+        allow_subqueries,
+        constructor_kwargs,
+        **kwargs
     ):
-        kwargs["df1"] = pd.DataFrame(data)
-        kwargs["df2"] = pd.DataFrame(data2)
+        kwargs["df1"] = pd.DataFrame(data, **constructor_kwargs)
+        kwargs["df2"] = pd.DataFrame(data2, **constructor_kwargs)
         kwargs["df"] = kwargs["df1"]
 
         if force_lazy:
@@ -76,9 +83,10 @@ def run_modin(
 
         return exp_res
 
+    constructor_kwargs = kwargs.pop("constructor_kwargs", {})
     try:
-        kwargs["df1"] = pandas.DataFrame(data)
-        kwargs["df2"] = pandas.DataFrame(data2)
+        kwargs["df1"] = pandas.DataFrame(data, **constructor_kwargs)
+        kwargs["df2"] = pandas.DataFrame(data2, **constructor_kwargs)
         kwargs["df"] = kwargs["df1"]
         ref_res = fn(lib=pandas, **kwargs)
     except Exception as e:
@@ -90,6 +98,7 @@ def run_modin(
                 force_lazy=force_lazy,
                 force_arrow_execute=force_arrow_execute,
                 allow_subqueries=allow_subqueries,
+                constructor_kwargs=constructor_kwargs,
                 **kwargs
             )
             _ = exp_res.index
@@ -101,6 +110,7 @@ def run_modin(
             force_lazy=force_lazy,
             force_arrow_execute=force_arrow_execute,
             allow_subqueries=allow_subqueries,
+            constructor_kwargs=constructor_kwargs,
             **kwargs
         )
         df_equals(ref_res, exp_res)
@@ -634,6 +644,15 @@ def groupby_mean(df, cols, as_index, **kwargs):
 
         run_and_compare(groupby_mean, data=self.data, cols=cols, as_index=as_index)
 
+    def test_groupby_lazy_multiindex(self):
+        index = generate_multiindex(len(self.data["a"]))
+
+        def groupby(df, *args, **kwargs):
+            df = df + 1
+            return df.groupby("a").agg({"b": "size"})
+
+        run_and_compare(groupby, data=self.data, constructor_kwargs={"index": index})
+
     taxi_data = {
         "a": [1, 1, 2, 2],
         "b": [11, 21, 12, 11],

modin/pandas/dataframe.py

@@ -368,12 +368,9 @@ def groupby(
         elif isinstance(by, str):
             drop = by in self.columns
             idx_name = by
-            if (
-                self._query_compiler.has_multiindex(axis=axis)
-                and by in self.axes[axis].names
-                or hasattr(self.axes[axis], "name")
-                and self.axes[axis].name == by
-            ):
+            if self._query_compiler.has_multiindex(
+                axis=axis
+            ) and by in self._query_compiler.get_index_names(axis):
                 # In this case we pass the string value of the name through to the
                 # partitions. This is more efficient than broadcasting the values.
                 pass
@@ -419,8 +416,7 @@ def groupby(
                 if mismatch and all(
                     isinstance(obj, str)
                     and (
-                        obj in self
-                        or (hasattr(self.index, "names") and obj in self.index.names)
+                        obj in self or obj in self._query_compiler.get_index_names(axis)
                     )
                     for obj in by
                 ):

modin/pandas/groupby.py

@@ -224,14 +224,15 @@ def _shift(periods, freq, axis, fill_value, is_set_nan_rows=True):
             )
             result.index = pandas.MultiIndex.from_arrays(
                 new_idx_lvl_arrays,
-                names=[col_name for col_name in self._by.columns] + [result.index.name],
+                names=[col_name for col_name in self._by.columns]
+                + [result._query_compiler.get_index_name()],
             )
             result = result.dropna(subset=self._by.columns).sort_index()
         else:
             result = self._apply_agg_function(
                 lambda df: df.shift(periods, freq, axis, fill_value)
             )
-            result.index.name = None
+            result._query_compiler.set_index_name(None)
         return result
 
     def nth(self, n, dropna=None):
@@ -240,7 +241,7 @@ def nth(self, n, dropna=None):
     def cumsum(self, axis=0, *args, **kwargs):
         result = self._apply_agg_function(lambda df: df.cumsum(axis, *args, **kwargs))
         # pandas does not name the index on cumsum
-        result.index.name = None
+        result._query_compiler.set_index_name(None)
         return result
 
     @property
@@ -258,7 +259,7 @@ def filter(self, func, dropna=True, *args, **kwargs):
     def cummax(self, axis=0, **kwargs):
         result = self._apply_agg_function(lambda df: df.cummax(axis, **kwargs))
         # pandas does not name the index on cummax
-        result.index.name = None
+        result._query_compiler.set_index_name(None)
         return result
 
     def apply(self, func, *args, **kwargs):
@@ -340,7 +341,7 @@ def __getitem__(self, key):
     def cummin(self, axis=0, **kwargs):
         result = self._apply_agg_function(lambda df: df.cummin(axis=axis, **kwargs))
         # pandas does not name the index on cummin
-        result.index.name = None
+        result._query_compiler.set_index_name(None)
         return result
 
     def bfill(self, limit=None):
@@ -438,7 +439,7 @@ def mad(self, **kwargs):
     def rank(self, **kwargs):
         result = self._apply_agg_function(lambda df: df.rank(**kwargs))
         # pandas does not name the index on rank
-        result.index.name = None
+        result._query_compiler.set_index_name(None)
         return result
 
     @property
@@ -597,7 +598,7 @@ def head(self, n=5):
     def cumprod(self, axis=0, *args, **kwargs):
         result = self._apply_agg_function(lambda df: df.cumprod(axis, *args, **kwargs))
         # pandas does not name the index on cumprod
-        result.index.name = None
+        result._query_compiler.set_index_name(None)
         return result
 
     def __iter__(self):
@@ -611,7 +612,7 @@ def transform(self, func, *args, **kwargs):
             lambda df: df.transform(func, *args, **kwargs)
         )
         # pandas does not name the index on transform
-        result.index.name = None
+        result._query_compiler.set_index_name(None)
         return result
 
     def corr(self, **kwargs):
@@ -620,7 +621,7 @@ def corr(self, **kwargs):
     def fillna(self, **kwargs):
         result = self._apply_agg_function(lambda df: df.fillna(**kwargs))
         # pandas does not name the index on fillna
-        result.index.name = None
+        result._query_compiler.set_index_name(None)
         return result
 
     def count(self, **kwargs):
@@ -641,7 +642,7 @@ def pipe(self, func, *args, **kwargs):
     def cumcount(self, ascending=True):
         result = self._default_to_pandas(lambda df: df.cumcount(ascending=ascending))
         # pandas does not name the index on cumcount
-        result.index.name = None
+        result._query_compiler.set_index_name(None)
         return result
 
     def tail(self, n=5):