# Buggy code
def _map(df, other):
    # Set `as_index` to True to track the metadata of the grouping object
    # It is used to make sure that between phases we are constructing the
    # right index and placing columns in the correct order.
    groupby_args["as_index"] = True
    other = other.squeeze(axis=axis ^ 1)
    if isinstance(other, pandas.DataFrame):
        df = pandas.concat([df] + [other[[o for o in other if o not in df]]], axis=1)
        other = list(other.columns)
    result = map_func(df.groupby(by=other, axis=axis, **groupby_args), **map_args)
    if (
        not isinstance(result.index, pandas.MultiIndex)
        and result.index.name is not None
        and result.index.name in result.columns
    ):
        result.index.name = "{}{}".format("_modin_groupby_", result.index.name)
    return result


# Traceback (ray.exceptions.RayTaskError)
Traceback (most recent call last):
File "groupby_test16.py", line 29, in <module>
df1 = gb.prod()
File "/localdisk/gashiman/modin/modin/pandas/groupby.py", line 333, in prod
return self._groupby_reduce(callable, None)
File "/localdisk/gashiman/modin/modin/pandas/groupby.py", line 582, in _groupby_reduce
query_compiler=groupby_qc.groupby_reduce(
File "/localdisk/gashiman/modin/modin/backends/pandas/query_compiler.py", line 1298, in groupby_reduce
new_modin_frame = qc._modin_frame.groupby_reduce(
File "/localdisk/gashiman/modin/modin/engines/base/frame/data.py", line 1259, in groupby_reduce
new_index = self._frame_mgr_cls.get_indices(
File "/localdisk/gashiman/modin/modin/engines/ray/pandas_on_ray/frame/partition_manager.py", line 87, in get_indices
new_idx = ray.get(new_idx)
File "/nfs/site/home/gashiman/.local/lib/python3.8/site-packages/ray/worker.py", line 1515, in get
raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(ValueError): ray::modin.engines.ray.pandas_on_ray.frame.partition.deploy_ray_func() (pid=2588931, ip=10.241.129.19)
File "python/ray/_raylet.pyx", line 427, in ray._raylet.execute_task
File "python/ray/_raylet.pyx", line 449, in ray._raylet.execute_task
ray.exceptions.RayTaskError: ray::modin.engines.ray.pandas_on_ray.frame.axis_partition.deploy_ray_func() (pid=2588931, ip=10.241.129.19)
File "python/ray/_raylet.pyx", line 427, in ray._raylet.execute_task
File "python/ray/_raylet.pyx", line 449, in ray._raylet.execute_task
ray.exceptions.RayTaskError: ray::modin.engines.ray.pandas_on_ray.frame.partition_manager.func() (pid=2588931, ip=10.241.129.19)
File "python/ray/_raylet.pyx", line 463, in ray._raylet.execute_task
File "/localdisk/gashiman/modin/modin/engines/ray/pandas_on_ray/frame/partition_manager.py", line 44, in func
return apply_func(df, other)
File "/localdisk/gashiman/modin/modin/backends/pandas/query_compiler.py", line 1248, in _map
result = map_func(
File "/localdisk/gashiman/modin/modin/pandas/groupby.py", line 332, in callable
return df.prod(**kwargs)
File "/nfs/site/home/gashiman/.local/lib/python3.8/site-packages/pandas/core/groupby/groupby.py", line 1371, in f
return self._cython_agg_general(alias, alt=npfunc, **kwargs)
File "/nfs/site/home/gashiman/.local/lib/python3.8/site-packages/pandas/core/groupby/generic.py", line 993, in _cython_agg_general
agg_blocks, agg_items = self._cython_agg_blocks(
File "/nfs/site/home/gashiman/.local/lib/python3.8/site-packages/pandas/core/groupby/generic.py", line 1022, in _cython_agg_blocks
result, _ = self.grouper.aggregate(
File "/nfs/site/home/gashiman/.local/lib/python3.8/site-packages/pandas/core/groupby/ops.py", line 586, in aggregate
return self._cython_operation(
File "/nfs/site/home/gashiman/.local/lib/python3.8/site-packages/pandas/core/groupby/ops.py", line 529, in _cython_operation
result = self._aggregate(
File "/nfs/site/home/gashiman/.local/lib/python3.8/site-packages/pandas/core/groupby/ops.py", line 608, in _aggregate
agg_func(result, counts, values, comp_ids, min_count)
File "pandas/_libs/groupby.pyx", line 511, in pandas._libs.groupby._group_prod
File "stringsource", line 658, in View.MemoryView.memoryview_cwrapper
File "stringsource", line 349, in View.MemoryView.memoryview.__cinit__
ValueError: buffer source array is read-only

# Fixed code
def _map(df, other):
    def compute_map(df, other):
        # Set `as_index` to True to track the metadata of the grouping object
        # It is used to make sure that between phases we are constructing the
        # right index and placing columns in the correct order.
        groupby_args["as_index"] = True
        other = other.squeeze(axis=axis ^ 1)
        if isinstance(other, pandas.DataFrame):
            df = pandas.concat(
                [df] + [other[[o for o in other if o not in df]]], axis=1
            )
            other = list(other.columns)
        result = map_func(df.groupby(by=other, axis=axis, **groupby_args), **map_args)
        # The _modin_groupby_ prefix indicates that this is the first partition,
        # and since we may need to insert the grouping data in the reduce phase
        if (
            not isinstance(result.index, pandas.MultiIndex)
            and result.index.name is not None
            and result.index.name in result.columns
        ):
            result.index.name = "{}{}".format("_modin_groupby_", result.index.name)
        return result

    try:
        return compute_map(df, other)
    # This will happen with Arrow buffer read-only errors. We don't want to copy
    # all the time, so this will try to fast-path the code first.
    except ValueError:
        return compute_map(df.copy(), other.copy())