def test_var_dist1(self):
        def test_impl(A, B):
            df = pd.DataFrame({'A': A, 'B': B})
            df2 = df.groupby('A', as_index=False)['B'].sum()
            # TODO: fix handling of df setitem to force match of array dists
            # probably with a new node that is appended to the end of basic block
            # df2['C'] = np.full(len(df2.B), 3, np.int8)
            # TODO: full_like for Series
            df2['C'] = np.full_like(df2.B.values, 3, np.int8)
            return df2

        A = np.array([1, 1, 2, 3])
        B = np.array([3, 4, 5, 6])
        hpat_func = self.jit(locals={'A:input': 'distributed',
                                     'B:input': 'distributed', 'df2:return': 'distributed'})(test_impl)
        start, end = get_start_end(len(A))
        df2 = hpat_func(A[start:end], B[start:end])
        # TODO:
        # pd.testing.assert_frame_equal(
        #     hpat_func(A[start:end], B[start:end]), test_impl(A, B))