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rapidsai / cudf

cuDF - GPU DataFrame Library
https://docs.rapids.ai/api/cudf/stable/
Apache License 2.0
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[BUG] sort_values on categorical column fails in dask_cudf #11795

Open eriknw opened 1 year ago

eriknw commented 1 year ago

Describe the bug ddf.sort_values(col) does not work with a dask_cudf DataFrame when col is categorical.

Steps/Code to reproduce bug

import cudf
import dask_cudf
df = cudf.DataFrame({"a": list("caba"), "b": list(range(4))})
df["a"] = df["a"].astype("category")
ddf = dask_cudf.from_cudf(df, npartitions=2)
df.sort_values("a")  # <-- works as expected
ddf.sort_values("a")  # raises
Traceback ```python-traceback --------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In [7], line 1 ----> 1 ddf.sort_values("a") File ~/miniconda3/envs/cugraph_dev15/lib/python3.9/contextlib.py:79, in ContextDecorator.__call__..inner(*args, **kwds) 76 @wraps(func) 77 def inner(*args, **kwds): 78 with self._recreate_cm(): ---> 79 return func(*args, **kwds) File ~/miniconda3/envs/cugraph_dev15/lib/python3.9/site-packages/dask_cudf/core.py:256, in DataFrame.sort_values(self, by, ignore_index, max_branch, divisions, set_divisions, ascending, na_position, sort_function, sort_function_kwargs, **kwargs) 251 if kwargs: 252 raise ValueError( 253 f"Unsupported input arguments passed : {list(kwargs.keys())}" 254 ) --> 256 df = sorting.sort_values( 257 self, 258 by, 259 max_branch=max_branch, 260 divisions=divisions, 261 set_divisions=set_divisions, 262 ignore_index=ignore_index, 263 ascending=ascending, 264 na_position=na_position, 265 sort_function=sort_function, 266 sort_function_kwargs=sort_function_kwargs, 267 ) 269 if ignore_index: 270 return df.reset_index(drop=True) File ~/miniconda3/envs/cugraph_dev15/lib/python3.9/contextlib.py:79, in ContextDecorator.__call__..inner(*args, **kwds) 76 @wraps(func) 77 def inner(*args, **kwds): 78 with self._recreate_cm(): ---> 79 return func(*args, **kwds) File ~/miniconda3/envs/cugraph_dev15/lib/python3.9/site-packages/dask_cudf/sorting.py:266, in sort_values(df, by, max_branch, divisions, set_divisions, ignore_index, ascending, na_position, sort_function, sort_function_kwargs) 264 # Step 1 - Calculate new divisions (if necessary) 265 if divisions is None: --> 266 divisions = quantile_divisions(df, by, npartitions) 268 # Step 2 - Perform repartitioning shuffle 269 meta = df._meta._constructor_sliced([0]) File ~/miniconda3/envs/cugraph_dev15/lib/python3.9/contextlib.py:79, in ContextDecorator.__call__..inner(*args, **kwds) 76 @wraps(func) 77 def inner(*args, **kwds): 78 with self._recreate_cm(): ---> 79 return func(*args, **kwds) File ~/miniconda3/envs/cugraph_dev15/lib/python3.9/site-packages/dask_cudf/sorting.py:213, in quantile_divisions(df, by, npartitions) 211 dtype = df[col].dtype 212 if dtype != "object": --> 213 divisions[col] = divisions[col].astype("int64") 214 divisions[col].iloc[-1] += 1 215 divisions[col] = divisions[col].astype(dtype) File ~/miniconda3/envs/cugraph_dev15/lib/python3.9/contextlib.py:79, in ContextDecorator.__call__..inner(*args, **kwds) 76 @wraps(func) 77 def inner(*args, **kwds): 78 with self._recreate_cm(): ---> 79 return func(*args, **kwds) File ~/miniconda3/envs/cugraph_dev15/lib/python3.9/site-packages/cudf/core/series.py:1857, in Series.astype(self, dtype, copy, errors, **kwargs) 1855 else: 1856 dtype = {self.name: dtype} -> 1857 return super().astype(dtype, copy, errors, **kwargs) File ~/miniconda3/envs/cugraph_dev15/lib/python3.9/site-packages/cudf/core/indexed_frame.py:3264, in IndexedFrame.astype(self, dtype, copy, errors, **kwargs) 3262 except Exception as e: 3263 if errors == "raise": -> 3264 raise e 3265 return self 3267 return self._from_data(data, index=self._index) File ~/miniconda3/envs/cugraph_dev15/lib/python3.9/site-packages/cudf/core/indexed_frame.py:3261, in IndexedFrame.astype(self, dtype, copy, errors, **kwargs) 3258 raise ValueError("invalid error value specified") 3260 try: -> 3261 data = super().astype(dtype, copy, **kwargs) 3262 except Exception as e: 3263 if errors == "raise": File ~/miniconda3/envs/cugraph_dev15/lib/python3.9/contextlib.py:79, in ContextDecorator.__call__..inner(*args, **kwds) 76 @wraps(func) 77 def inner(*args, **kwds): 78 with self._recreate_cm(): ---> 79 return func(*args, **kwds) File ~/miniconda3/envs/cugraph_dev15/lib/python3.9/site-packages/cudf/core/frame.py:328, in Frame.astype(self, dtype, copy, **kwargs) 326 dt = dtype.get(col_name, col.dtype) 327 if not is_dtype_equal(dt, col.dtype): --> 328 result[col_name] = col.astype(dt, copy=copy, **kwargs) 329 else: 330 result[col_name] = col.copy() if copy else col File ~/miniconda3/envs/cugraph_dev15/lib/python3.9/site-packages/cudf/core/column/column.py:857, in ColumnBase.astype(self, dtype, **kwargs) 851 dtype = ( 852 pandas_dtypes_alias_to_cudf_alias.get(dtype, dtype) 853 if isinstance(dtype, str) 854 else pandas_dtypes_to_np_dtypes.get(dtype, dtype) 855 ) 856 if _is_non_decimal_numeric_dtype(dtype): --> 857 return self.as_numerical_column(dtype, **kwargs) 858 elif is_categorical_dtype(dtype): 859 return self.as_categorical_column(dtype, **kwargs) File ~/miniconda3/envs/cugraph_dev15/lib/python3.9/site-packages/cudf/core/column/categorical.py:1236, in CategoricalColumn.as_numerical_column(self, dtype, **kwargs) 1235 def as_numerical_column(self, dtype: Dtype, **kwargs) -> NumericalColumn: -> 1236 return self._get_decategorized_column().as_numerical_column(dtype) File ~/miniconda3/envs/cugraph_dev15/lib/python3.9/site-packages/cudf/core/column/string.py:5312, in StringColumn.as_numerical_column(self, dtype, **kwargs) 5310 if out_dtype.kind in {"i", "u"}: 5311 if not libstrings.is_integer(string_col).all(): -> 5312 raise ValueError( 5313 "Could not convert strings to integer " 5314 "type due to presence of non-integer values." 5315 ) 5316 elif out_dtype.kind == "f": 5317 if not libstrings.is_float(string_col).all(): ValueError: Could not convert strings to integer type due to presence of non-integer values. ```

Expected behavior I expect it to work--that is, match the result of cudf and dask.dataframe.

Environment overview (please complete the following information)

Environment details

Click here to see environment details

     **git***
     commit 82b9922cc1635f6f0923f633a17a7c12f93ebdbe (HEAD -> pg_set_index_and_categorical, eriknw/pg_set_index_and_categorical)
     Author: Erik Welch 
     Date:   Tue Sep 27 11:28:04 2022 -0700

     workaround dask_cudf issue with `sort_values` on categorical column
     **git submodules***

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     |                               |                      |                  N/A |
     +-------------------------------+----------------------+----------------------+

     +-----------------------------------------------------------------------------+
     | Processes:                                                                  |
     |  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
     |        ID   ID                                                   Usage      |
     |=============================================================================|
     |  No running processes found                                                 |
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     ***CMake***
     /home/nfs/erwelch/miniconda3/envs/cugraph_dev15/bin/cmake
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     /home/nfs/erwelch/miniconda3/envs/cugraph_dev15/bin/python
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     ***conda packages***
     /home/nfs/erwelch/miniconda3/condabin/conda
     # packages in environment at /home/nfs/erwelch/miniconda3/envs/cugraph_dev15:
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Additional context Encountered in ProperterGraph in cugraph.

vyasr commented 4 months ago

This works now, but with the caveat that categorical column must be explicitly marked as ordered

In [1]: import cudf
   ...: import dask_cudf
   ...: df = cudf.DataFrame({"a": list("caba"), "b": list(range(4))})
   ...: df["a"] = df["a"].astype("category").cat.as_ordered()  # Without ordering the dask version fails.
   ...: ddf = dask_cudf.from_cudf(df, npartitions=2)
   ...: print(df.sort_values("a"))
   ...: print(ddf.sort_values("a").compute())
   a  b
1  a  1
3  a  3
2  b  2
0  c  0
   a  b
1  a  1
3  a  3
2  b  2
0  c  0

@rjzamora any idea why dask_cudf behaves differently from cudf w.r.t. the ordering?

rjzamora commented 4 months ago

Good catch @vyasr - The dask behavior was actually "fixed" recently in dask-expr (https://github.com/dask/dask-expr/pull/1058), but I just realized that the pd.CategoricalDtype check will need to be updated to work for cudf (my mistake for missing that when I reviewed).

Even with dask-expr fixed, however, your snippet will not work for dask_cudf, because there seems to be a bug in cudf:

import cudf as lib  # Works for pandas, but not for cudf

df = lib.DataFrame({"a": list("caba"), "b": list(range(4))})
df["a"] = df["a"].astype("category")
df = df.iloc[:2]
df["a"].cat.as_ordered()
...
ValueError: Length of values (4) does not match length of index (2)

EDIT: I submitted https://github.com/rapidsai/cudf/issues/15778 to track this.

rjzamora commented 4 months ago

Update: Latest version of dask-expr:main + dask:main now results in an ugly segfault when sorting on a categorical column. After https://github.com/rapidsai/cudf/pull/15788, the user will get a clear error until the upstream divisions logic is "generalized" to work with cudf.

vyasr commented 4 months ago

The chain has gotten a bit long here, let me summarize to make sure I have everything right. #15780 will fix #15778. Once that is merged, will this issue also be fixed in the dask-expr case, or is there still work to be done to generalize dask-expr to work correctly for cudf because https://github.com/dask/dask-expr/pull/1058 wasn't complete? And in either case, do we still expect this to fail for users of the legacy dask API (which I guess isn't too important if we're going to be forced to migrate to dask-expr anyway)?

rjzamora commented 4 months ago

Summary:

I certainly want to fix categorical sorting for 24.06 if possible, but my current expectation is that we will need to raise an error and tell the user to disable query planning. If I can find a work-around in the next day or so, then we can remove the error. Otherwise, the proper/upstream fix will only apply to 24.08.